id	sid	tid	token	lemma	pos
hjic-96	1	1	hungarian	hungarian	ADJ
hjic-96	1	2	journal	journal	NOUN
hjic-96	1	3	of	of	ADP
hjic-96	1	4	industrial	industrial	ADJ
hjic-96	1	5	chemistry	chemistry	NOUN
hjic-96	1	6	veszprém	veszprém	NOUN
hjic-96	1	7	vol	vol	NOUN
hjic-96	1	8	.	.	PUNCT
hjic-96	2	1	33(1	33(1	NUM
hjic-96	2	2	-	-	SYM
hjic-96	2	3	2	2	NUM
hjic-96	2	4	)	)	PUNCT
hjic-96	2	5	.	.	PUNCT
hjic-96	3	1	pp	pp	ADJ
hjic-96	3	2	.	.	PUNCT
hjic-96	4	1	57	57	NUM
hjic-96	4	2	-	-	SYM
hjic-96	4	3	67	67	NUM
hjic-96	4	4	.	.	PUNCT
hjic-96	5	1	(	(	PUNCT
hjic-96	5	2	2005	2005	NUM
hjic-96	5	3	)	)	PUNCT
hjic-96	5	4	fuzzy	fuzzy	ADJ
hjic-96	5	5	association	association	NOUN
hjic-96	5	6	rule	rule	NOUN
hjic-96	5	7	mining	mining	NOUN
hjic-96	5	8	for	for	ADP
hjic-96	5	9	data	datum	NOUN
hjic-96	5	10	driven	drive	VERB
hjic-96	5	11	analysis	analysis	NOUN
hjic-96	5	12	of	of	ADP
hjic-96	5	13	dynamical	dynamical	ADJ
hjic-96	5	14	systems	system	NOUN
hjic-96	5	15	f.p	f.p	PROPN
hjic-96	5	16	.	.	PROPN
hjic-96	5	17	pach	pach	PROPN
hjic-96	5	18	,	,	PUNCT
hjic-96	5	19	f.	f.	PROPN
hjic-96	5	20	szeifert	szeifert	PROPN
hjic-96	5	21	,	,	PUNCT
hjic-96	5	22	s.	s.	PROPN
hjic-96	5	23	nemeth	nemeth	PROPN
hjic-96	5	24	,	,	PUNCT
hjic-96	5	25	p.	p.	PROPN
hjic-96	5	26	arva	arva	PROPN
hjic-96	5	27	and	and	CCONJ
hjic-96	5	28	j.	j.	PROPN
hjic-96	5	29	abonyi	abonyi	PROPN
hjic-96	5	30	*	*	PROPN
hjic-96	5	31	department	department	PROPN
hjic-96	5	32	of	of	ADP
hjic-96	5	33	process	process	NOUN
hjic-96	5	34	engeneering	engeneere	VERB
hjic-96	5	35	,	,	PUNCT
hjic-96	5	36	university	university	NOUN
hjic-96	5	37	of	of	ADP
hjic-96	5	38	veszprém	veszprém	NOUN
hjic-96	5	39	,	,	PUNCT
hjic-96	5	40	veszprém	veszprém	NOUN
hjic-96	5	41	,	,	PUNCT
hjic-96	5	42	egyetem	egyetem	PROPN
hjic-96	5	43	u.	u.	PROPN
hjic-96	5	44	10	10	NUM
hjic-96	5	45	,	,	PUNCT
hjic-96	5	46	h-8200	h-8200	PROPN
hjic-96	5	47	,	,	PUNCT
hjic-96	5	48	hungary	hungary	NOUN
hjic-96	5	49	,	,	PUNCT
hjic-96	5	50	www.fmt.vein.hu/softcomp	www.fmt.vein.hu/softcomp	PROPN
hjic-96	5	51	,	,	PUNCT
hjic-96	5	52	abonyij@fmt.vein.hu	abonyij@fmt.vein.hu	PROPN
hjic-96	5	53	in	in	ADP
hjic-96	5	54	system	system	NOUN
hjic-96	5	55	identification	identification	NOUN
hjic-96	5	56	a	a	DET
hjic-96	5	57	key	key	ADJ
hjic-96	5	58	step	step	NOUN
hjic-96	5	59	is	be	AUX
hjic-96	5	60	to	to	PART
hjic-96	5	61	find	find	VERB
hjic-96	5	62	a	a	DET
hjic-96	5	63	suitable	suitable	ADJ
hjic-96	5	64	model	model	NOUN
hjic-96	5	65	structure	structure	NOUN
hjic-96	5	66	.	.	PUNCT
hjic-96	6	1	the	the	DET
hjic-96	6	2	utilizations	utilization	NOUN
hjic-96	6	3	of	of	ADP
hjic-96	6	4	prior	prior	ADJ
hjic-96	6	5	knowledge	knowledge	NOUN
hjic-96	6	6	and	and	CCONJ
hjic-96	6	7	physical	physical	ADJ
hjic-96	6	8	insight	insight	NOUN
hjic-96	6	9	about	about	ADP
hjic-96	6	10	the	the	DET
hjic-96	6	11	system	system	NOUN
hjic-96	6	12	are	be	AUX
hjic-96	6	13	very	very	ADV
hjic-96	6	14	important	important	ADJ
hjic-96	6	15	when	when	SCONJ
hjic-96	6	16	selecting	select	VERB
hjic-96	6	17	the	the	DET
hjic-96	6	18	model	model	NOUN
hjic-96	6	19	structure	structure	NOUN
hjic-96	6	20	.	.	PUNCT
hjic-96	7	1	in	in	ADP
hjic-96	7	2	nonlinear	nonlinear	ADJ
hjic-96	7	3	black	black	ADJ
hjic-96	7	4	-	-	PUNCT
hjic-96	7	5	box	box	NOUN
hjic-96	7	6	modeling	modeling	NOUN
hjic-96	7	7	no	no	DET
hjic-96	7	8	physical	physical	ADJ
hjic-96	7	9	insight	insight	NOUN
hjic-96	7	10	is	be	AUX
hjic-96	7	11	available	available	ADJ
hjic-96	7	12	we	we	PRON
hjic-96	7	13	have	have	VERB
hjic-96	7	14	“	"	PUNCT
hjic-96	7	15	only	only	ADV
hjic-96	7	16	”	"	PUNCT
hjic-96	7	17	observed	observe	VERB
hjic-96	7	18	inputs	input	NOUN
hjic-96	7	19	and	and	CCONJ
hjic-96	7	20	outputs	output	NOUN
hjic-96	7	21	from	from	ADP
hjic-96	7	22	the	the	DET
hjic-96	7	23	dynamical	dynamical	ADJ
hjic-96	7	24	system	system	NOUN
hjic-96	7	25	.	.	PUNCT
hjic-96	8	1	association	association	NOUN
hjic-96	8	2	rule	rule	NOUN
hjic-96	8	3	mining	mining	NOUN
hjic-96	8	4	is	be	AUX
hjic-96	8	5	one	one	NUM
hjic-96	8	6	of	of	ADP
hjic-96	8	7	the	the	DET
hjic-96	8	8	widely	widely	ADV
hjic-96	8	9	used	use	VERB
hjic-96	8	10	data	data	NOUN
hjic-96	8	11	mining	mining	NOUN
hjic-96	8	12	tools	tool	NOUN
hjic-96	8	13	.	.	PUNCT
hjic-96	9	1	it	it	PRON
hjic-96	9	2	finds	find	VERB
hjic-96	9	3	interesting	interesting	ADJ
hjic-96	9	4	association	association	NOUN
hjic-96	9	5	or	or	CCONJ
hjic-96	9	6	correlation	correlation	NOUN
hjic-96	9	7	relationships	relationship	NOUN
hjic-96	9	8	among	among	ADP
hjic-96	9	9	a	a	DET
hjic-96	9	10	large	large	ADJ
hjic-96	9	11	data	datum	NOUN
hjic-96	9	12	set	set	VERB
hjic-96	9	13	.	.	PUNCT
hjic-96	10	1	the	the	DET
hjic-96	10	2	aim	aim	NOUN
hjic-96	10	3	of	of	ADP
hjic-96	10	4	this	this	DET
hjic-96	10	5	paper	paper	NOUN
hjic-96	10	6	is	be	AUX
hjic-96	10	7	to	to	PART
hjic-96	10	8	demonstrate	demonstrate	VERB
hjic-96	10	9	that	that	SCONJ
hjic-96	10	10	this	this	DET
hjic-96	10	11	data	data	NOUN
hjic-96	10	12	mining	mining	NOUN
hjic-96	10	13	tool	tool	NOUN
hjic-96	10	14	can	can	AUX
hjic-96	10	15	be	be	AUX
hjic-96	10	16	effectively	effectively	ADV
hjic-96	10	17	applied	apply	VERB
hjic-96	10	18	for	for	ADP
hjic-96	10	19	the	the	DET
hjic-96	10	20	datadriven	datadriven	ADJ
hjic-96	10	21	modeling	modeling	NOUN
hjic-96	10	22	and	and	CCONJ
hjic-96	10	23	analysis	analysis	NOUN
hjic-96	10	24	of	of	ADP
hjic-96	10	25	dynamical	dynamical	ADJ
hjic-96	10	26	systems	system	NOUN
hjic-96	10	27	.	.	PUNCT
hjic-96	11	1	the	the	DET
hjic-96	11	2	detected	detect	VERB
hjic-96	11	3	association	association	NOUN
hjic-96	11	4	rules	rule	NOUN
hjic-96	11	5	can	can	AUX
hjic-96	11	6	be	be	AUX
hjic-96	11	7	interpreted	interpret	VERB
hjic-96	11	8	as	as	ADP
hjic-96	11	9	simple	simple	ADJ
hjic-96	11	10	local	local	ADJ
hjic-96	11	11	input	input	NOUN
hjic-96	11	12	-	-	PUNCT
hjic-96	11	13	output	output	NOUN
hjic-96	11	14	models	model	NOUN
hjic-96	11	15	of	of	ADP
hjic-96	11	16	the	the	DET
hjic-96	11	17	modeled	model	VERB
hjic-96	11	18	process	process	NOUN
hjic-96	11	19	.	.	PUNCT
hjic-96	12	1	hence	hence	ADV
hjic-96	12	2	,	,	PUNCT
hjic-96	12	3	the	the	DET
hjic-96	12	4	analysis	analysis	NOUN
hjic-96	12	5	of	of	ADP
hjic-96	12	6	the	the	DET
hjic-96	12	7	mined	mine	VERB
hjic-96	12	8	association	association	NOUN
hjic-96	12	9	rules	rule	NOUN
hjic-96	12	10	(	(	PUNCT
hjic-96	12	11	models	model	NOUN
hjic-96	12	12	)	)	PUNCT
hjic-96	12	13	can	can	AUX
hjic-96	12	14	provide	provide	VERB
hjic-96	12	15	useful	useful	ADJ
hjic-96	12	16	information	information	NOUN
hjic-96	12	17	about	about	ADP
hjic-96	12	18	the	the	DET
hjic-96	12	19	structure	structure	NOUN
hjic-96	12	20	and	and	CCONJ
hjic-96	12	21	the	the	DET
hjic-96	12	22	order	order	NOUN
hjic-96	12	23	of	of	ADP
hjic-96	12	24	the	the	DET
hjic-96	12	25	model	model	NOUN
hjic-96	12	26	that	that	PRON
hjic-96	12	27	can	can	AUX
hjic-96	12	28	adequately	adequately	ADV
hjic-96	12	29	describe	describe	VERB
hjic-96	12	30	the	the	DET
hjic-96	12	31	dynamical	dynamical	ADJ
hjic-96	12	32	behavior	behavior	NOUN
hjic-96	12	33	of	of	ADP
hjic-96	12	34	the	the	DET
hjic-96	12	35	process	process	NOUN
hjic-96	12	36	.	.	PUNCT
hjic-96	13	1	in	in	ADP
hjic-96	13	2	this	this	DET
hjic-96	13	3	paper	paper	NOUN
hjic-96	13	4	a	a	DET
hjic-96	13	5	fuzzy	fuzzy	ADJ
hjic-96	13	6	association	association	NOUN
hjic-96	13	7	rule	rule	NOUN
hjic-96	13	8	mining	mining	NOUN
hjic-96	13	9	algorithm	algorithm	NOUN
hjic-96	13	10	is	be	AUX
hjic-96	13	11	introduced	introduce	VERB
hjic-96	13	12	and	and	CCONJ
hjic-96	13	13	a	a	DET
hjic-96	13	14	rule	rule	NOUN
hjic-96	13	15	-	-	PUNCT
hjic-96	13	16	base	base	NOUN
hjic-96	13	17	simplification	simplification	NOUN
hjic-96	13	18	algorithm	algorithm	NOUN
hjic-96	13	19	is	be	AUX
hjic-96	13	20	presented	present	VERB
hjic-96	13	21	for	for	ADP
hjic-96	13	22	the	the	DET
hjic-96	13	23	generation	generation	NOUN
hjic-96	13	24	of	of	ADP
hjic-96	13	25	a	a	DET
hjic-96	13	26	set	set	NOUN
hjic-96	13	27	of	of	ADP
hjic-96	13	28	“	"	PUNCT
hjic-96	13	29	rule	rule	NOUN
hjic-96	13	30	-	-	PUNCT
hjic-96	13	31	based	base	VERB
hjic-96	13	32	models	model	NOUN
hjic-96	13	33	”	"	PUNCT
hjic-96	13	34	that	that	PRON
hjic-96	13	35	can	can	AUX
hjic-96	13	36	be	be	AUX
hjic-96	13	37	directly	directly	ADV
hjic-96	13	38	used	use	VERB
hjic-96	13	39	as	as	ADP
hjic-96	13	40	a	a	DET
hjic-96	13	41	qualitative	qualitative	ADJ
hjic-96	13	42	model	model	NOUN
hjic-96	13	43	of	of	ADP
hjic-96	13	44	the	the	DET
hjic-96	13	45	system	system	NOUN
hjic-96	13	46	.	.	PUNCT
hjic-96	14	1	the	the	DET
hjic-96	14	2	general	general	ADJ
hjic-96	14	3	applicability	applicability	NOUN
hjic-96	14	4	of	of	ADP
hjic-96	14	5	the	the	DET
hjic-96	14	6	developed	develop	VERB
hjic-96	14	7	tool	tool	NOUN
hjic-96	14	8	is	be	AUX
hjic-96	14	9	illustrated	illustrate	VERB
hjic-96	14	10	by	by	ADP
hjic-96	14	11	the	the	DET
hjic-96	14	12	analysis	analysis	NOUN
hjic-96	14	13	of	of	ADP
hjic-96	14	14	the	the	DET
hjic-96	14	15	input	input	NOUN
hjic-96	14	16	-	-	PUNCT
hjic-96	14	17	output	output	NOUN
hjic-96	14	18	data	datum	NOUN
hjic-96	14	19	of	of	ADP
hjic-96	14	20	a	a	DET
hjic-96	14	21	continuously	continuously	ADV
hjic-96	14	22	stirred	stir	VERB
hjic-96	14	23	styrene	styrene	ADJ
hjic-96	14	24	polymerization	polymerization	NOUN
hjic-96	14	25	reactor	reactor	NOUN
hjic-96	14	26	.	.	PUNCT
hjic-96	15	1	the	the	DET
hjic-96	15	2	detected	detect	VERB
hjic-96	15	3	association	association	NOUN
hjic-96	15	4	rules	rule	NOUN
hjic-96	15	5	is	be	AUX
hjic-96	15	6	used	use	VERB
hjic-96	15	7	for	for	ADP
hjic-96	15	8	the	the	DET
hjic-96	15	9	selection	selection	NOUN
hjic-96	15	10	of	of	ADP
hjic-96	15	11	the	the	DET
hjic-96	15	12	structure	structure	NOUN
hjic-96	15	13	of	of	ADP
hjic-96	15	14	a	a	DET
hjic-96	15	15	linear	linear	NOUN
hjic-96	15	16	and	and	CCONJ
hjic-96	15	17	nonlinear	nonlinear	ADJ
hjic-96	15	18	(	(	PUNCT
hjic-96	15	19	neural	neural	ADJ
hjic-96	15	20	network	network	NOUN
hjic-96	15	21	)	)	PUNCT
hjic-96	15	22	models	model	NOUN
hjic-96	15	23	for	for	ADP
hjic-96	15	24	this	this	DET
hjic-96	15	25	process	process	NOUN
hjic-96	15	26	and	and	CCONJ
hjic-96	15	27	determine	determine	VERB
hjic-96	15	28	the	the	DET
hjic-96	15	29	most	most	ADV
hjic-96	15	30	relevant	relevant	ADJ
hjic-96	15	31	process	process	NOUN
hjic-96	15	32	variables	variable	NOUN
hjic-96	15	33	.	.	PUNCT
hjic-96	16	1	keywords	keyword	NOUN
hjic-96	16	2	:	:	PUNCT
hjic-96	16	3	process	process	NOUN
hjic-96	16	4	modeling	modeling	NOUN
hjic-96	16	5	,	,	PUNCT
hjic-96	16	6	model	model	NOUN
hjic-96	16	7	structure	structure	NOUN
hjic-96	16	8	selection	selection	NOUN
hjic-96	16	9	,	,	PUNCT
hjic-96	16	10	association	association	NOUN
hjic-96	16	11	rules	rule	NOUN
hjic-96	16	12	,	,	PUNCT
hjic-96	16	13	rule	rule	NOUN
hjic-96	16	14	base	base	NOUN
hjic-96	16	15	systems	system	NOUN
hjic-96	16	16	,	,	PUNCT
hjic-96	16	17	polymerization	polymerization	NOUN
hjic-96	16	18	introduction	introduction	NOUN
hjic-96	16	19	in	in	ADP
hjic-96	16	20	process	process	NOUN
hjic-96	16	21	modeling	model	VERB
hjic-96	16	22	the	the	DET
hjic-96	16	23	a	a	DET
hjic-96	16	24	priori	priori	ADJ
hjic-96	16	25	knowledge	knowledge	NOUN
hjic-96	16	26	,	,	PUNCT
hjic-96	16	27	experimental	experimental	ADJ
hjic-96	16	28	data	datum	NOUN
hjic-96	16	29	and	and	CCONJ
hjic-96	16	30	experiments	experiment	NOUN
hjic-96	16	31	are	be	AUX
hjic-96	16	32	crucial	crucial	ADJ
hjic-96	16	33	.	.	PUNCT
hjic-96	17	1	the	the	DET
hjic-96	17	2	process	process	NOUN
hjic-96	17	3	of	of	ADP
hjic-96	17	4	modeling	modeling	NOUN
hjic-96	17	5	from	from	ADP
hjic-96	17	6	experimental	experimental	ADJ
hjic-96	17	7	data	datum	NOUN
hjic-96	17	8	is	be	AUX
hjic-96	17	9	known	know	VERB
hjic-96	17	10	as	as	ADP
hjic-96	17	11	system	system	NOUN
hjic-96	17	12	identification	identification	NOUN
hjic-96	17	13	by	by	ADP
hjic-96	17	14	ljung	ljung	ADJ
hjic-96	17	15	[	[	X
hjic-96	17	16	1	1	NUM
hjic-96	17	17	]	]	PUNCT
hjic-96	17	18	.	.	PUNCT
hjic-96	18	1	the	the	DET
hjic-96	18	2	main	main	ADJ
hjic-96	18	3	steps	step	NOUN
hjic-96	18	4	of	of	ADP
hjic-96	18	5	the	the	DET
hjic-96	18	6	system	system	NOUN
hjic-96	18	7	identification	identification	NOUN
hjic-96	18	8	process	process	NOUN
hjic-96	18	9	are	be	AUX
hjic-96	18	10	summarized	summarize	VERB
hjic-96	18	11	well	well	ADV
hjic-96	18	12	by	by	ADP
hjic-96	18	13	petrick	petrick	NOUN
hjic-96	18	14	and	and	CCONJ
hjic-96	18	15	wigdorowitz	wigdorowitz	NOUN
hjic-96	18	16	[	[	X
hjic-96	18	17	2	2	NUM
hjic-96	18	18	]	]	SYM
hjic-96	18	19	:	:	PUNCT
hjic-96	18	20	1	1	X
hjic-96	18	21	.	.	X
hjic-96	18	22	design	design	VERB
hjic-96	18	23	an	an	DET
hjic-96	18	24	experiment	experiment	NOUN
hjic-96	18	25	to	to	PART
hjic-96	18	26	obtain	obtain	VERB
hjic-96	18	27	the	the	DET
hjic-96	18	28	physical	physical	ADJ
hjic-96	18	29	process	process	NOUN
hjic-96	18	30	input	input	NOUN
hjic-96	18	31	/	/	SYM
hjic-96	18	32	output	output	NOUN
hjic-96	18	33	experimental	experimental	ADJ
hjic-96	18	34	data	datum	NOUN
hjic-96	18	35	sets	set	NOUN
hjic-96	18	36	pertinent	pertinent	ADJ
hjic-96	18	37	to	to	ADP
hjic-96	18	38	the	the	DET
hjic-96	18	39	model	model	NOUN
hjic-96	18	40	application	application	NOUN
hjic-96	18	41	.	.	PUNCT
hjic-96	19	1	2	2	X
hjic-96	19	2	.	.	X
hjic-96	19	3	examine	examine	VERB
hjic-96	19	4	the	the	DET
hjic-96	19	5	measured	measure	VERB
hjic-96	19	6	data	datum	NOUN
hjic-96	19	7	.	.	PUNCT
hjic-96	20	1	remove	remove	VERB
hjic-96	20	2	trends	trend	NOUN
hjic-96	20	3	and	and	CCONJ
hjic-96	20	4	outliers	outlier	NOUN
hjic-96	20	5	.	.	PUNCT
hjic-96	21	1	apply	apply	VERB
hjic-96	21	2	filtering	filter	VERB
hjic-96	21	3	to	to	PART
hjic-96	21	4	remove	remove	VERB
hjic-96	21	5	measurement	measurement	NOUN
hjic-96	21	6	and	and	CCONJ
hjic-96	21	7	process	process	NOUN
hjic-96	21	8	noise	noise	NOUN
hjic-96	21	9	.	.	PUNCT
hjic-96	22	1	3	3	X
hjic-96	22	2	.	.	X
hjic-96	22	3	construct	construct	VERB
hjic-96	22	4	a	a	DET
hjic-96	22	5	set	set	NOUN
hjic-96	22	6	of	of	ADP
hjic-96	22	7	candidate	candidate	NOUN
hjic-96	22	8	models	model	NOUN
hjic-96	22	9	based	base	VERB
hjic-96	22	10	on	on	ADP
hjic-96	22	11	information	information	NOUN
hjic-96	22	12	from	from	ADP
hjic-96	22	13	the	the	DET
hjic-96	22	14	experimental	experimental	ADJ
hjic-96	22	15	data	data	NOUN
hjic-96	22	16	sets	set	NOUN
hjic-96	22	17	.	.	PUNCT
hjic-96	23	1	this	this	DET
hjic-96	23	2	step	step	NOUN
hjic-96	23	3	is	be	AUX
hjic-96	23	4	the	the	DET
hjic-96	23	5	model	model	NOUN
hjic-96	23	6	structure	structure	NOUN
hjic-96	23	7	identification	identification	NOUN
hjic-96	23	8	.	.	PUNCT
hjic-96	24	1	4	4	X
hjic-96	24	2	.	.	X
hjic-96	24	3	select	select	VERB
hjic-96	24	4	a	a	DET
hjic-96	24	5	particular	particular	ADJ
hjic-96	24	6	model	model	NOUN
hjic-96	24	7	from	from	ADP
hjic-96	24	8	the	the	DET
hjic-96	24	9	set	set	NOUN
hjic-96	24	10	of	of	ADP
hjic-96	24	11	candidate	candidate	NOUN
hjic-96	24	12	models	model	NOUN
hjic-96	24	13	in	in	ADP
hjic-96	24	14	step	step	NOUN
hjic-96	24	15	3	3	NUM
hjic-96	24	16	and	and	CCONJ
hjic-96	24	17	estimate	estimate	VERB
hjic-96	24	18	the	the	DET
hjic-96	24	19	model	model	NOUN
hjic-96	24	20	parameter	parameter	NOUN
hjic-96	24	21	values	value	NOUN
hjic-96	24	22	using	use	VERB
hjic-96	24	23	the	the	DET
hjic-96	24	24	experimental	experimental	ADJ
hjic-96	24	25	data	data	NOUN
hjic-96	24	26	sets	set	NOUN
hjic-96	24	27	.	.	PUNCT
hjic-96	25	1	5	5	X
hjic-96	25	2	.	.	X
hjic-96	25	3	evaluate	evaluate	VERB
hjic-96	25	4	how	how	SCONJ
hjic-96	25	5	good	good	ADJ
hjic-96	25	6	the	the	DET
hjic-96	25	7	model	model	NOUN
hjic-96	25	8	is	be	AUX
hjic-96	25	9	,	,	PUNCT
hjic-96	25	10	using	use	VERB
hjic-96	25	11	an	an	DET
hjic-96	25	12	objective	objective	ADJ
hjic-96	25	13	function	function	NOUN
hjic-96	25	14	.	.	PUNCT
hjic-96	26	1	if	if	SCONJ
hjic-96	26	2	the	the	DET
hjic-96	26	3	model	model	NOUN
hjic-96	26	4	is	be	AUX
hjic-96	26	5	not	not	PART
hjic-96	26	6	satisfactory	satisfactory	ADJ
hjic-96	26	7	then	then	ADV
hjic-96	26	8	repeat	repeat	VERB
hjic-96	26	9	step	step	NOUN
hjic-96	26	10	4	4	NUM
hjic-96	26	11	until	until	SCONJ
hjic-96	26	12	all	all	DET
hjic-96	26	13	the	the	DET
hjic-96	26	14	candidate	candidate	NOUN
hjic-96	26	15	models	model	NOUN
hjic-96	26	16	have	have	AUX
hjic-96	26	17	been	be	AUX
hjic-96	26	18	evaluated	evaluate	VERB
hjic-96	26	19	.	.	PUNCT
hjic-96	27	1	6	6	X
hjic-96	27	2	.	.	X
hjic-96	27	3	if	if	SCONJ
hjic-96	27	4	a	a	DET
hjic-96	27	5	satisfactory	satisfactory	ADJ
hjic-96	27	6	model	model	NOUN
hjic-96	27	7	is	be	AUX
hjic-96	27	8	still	still	ADV
hjic-96	27	9	not	not	PART
hjic-96	27	10	obtained	obtain	VERB
hjic-96	27	11	in	in	ADP
hjic-96	27	12	step	step	NOUN
hjic-96	27	13	5	5	NUM
hjic-96	27	14	then	then	ADV
hjic-96	27	15	repeat	repeat	VERB
hjic-96	27	16	the	the	DET
hjic-96	27	17	procedure	procedure	NOUN
hjic-96	27	18	either	either	CCONJ
hjic-96	27	19	from	from	ADP
hjic-96	27	20	step	step	NOUN
hjic-96	27	21	1	1	NUM
hjic-96	27	22	or	or	CCONJ
hjic-96	27	23	step	step	NOUN
hjic-96	27	24	3	3	NUM
hjic-96	27	25	,	,	PUNCT
hjic-96	27	26	depending	depend	VERB
hjic-96	27	27	on	on	ADP
hjic-96	27	28	the	the	DET
hjic-96	27	29	problem	problem	NOUN
hjic-96	27	30	.	.	PUNCT
hjic-96	28	1	a	a	DET
hjic-96	28	2	key	key	ADJ
hjic-96	28	3	step	step	NOUN
hjic-96	28	4	(	(	PUNCT
hjic-96	28	5	step	step	NOUN
hjic-96	28	6	3	3	NUM
hjic-96	28	7	)	)	PUNCT
hjic-96	28	8	is	be	AUX
hjic-96	28	9	to	to	PART
hjic-96	28	10	find	find	VERB
hjic-96	28	11	a	a	DET
hjic-96	28	12	suitable	suitable	ADJ
hjic-96	28	13	model	model	NOUN
hjic-96	28	14	structure	structure	NOUN
hjic-96	28	15	which	which	PRON
hjic-96	28	16	is	be	AUX
hjic-96	28	17	capable	capable	ADJ
hjic-96	28	18	of	of	ADP
hjic-96	28	19	representing	represent	VERB
hjic-96	28	20	the	the	DET
hjic-96	28	21	dynamical	dynamical	ADJ
hjic-96	28	22	behavior	behavior	NOUN
hjic-96	28	23	of	of	ADP
hjic-96	28	24	the	the	DET
hjic-96	28	25	system	system	NOUN
hjic-96	28	26	.	.	PUNCT
hjic-96	29	1	therefore	therefore	ADV
hjic-96	29	2	effective	effective	ADJ
hjic-96	29	3	methods	method	NOUN
hjic-96	29	4	for	for	ADP
hjic-96	29	5	structure	structure	NOUN
hjic-96	29	6	selection	selection	NOUN
hjic-96	29	7	are	be	AUX
hjic-96	29	8	necessary	necessary	ADJ
hjic-96	29	9	.	.	PUNCT
hjic-96	30	1	consider	consider	VERB
hjic-96	30	2	the	the	DET
hjic-96	30	3	main	main	ADJ
hjic-96	30	4	aspects	aspect	NOUN
hjic-96	30	5	influencing	influence	VERB
hjic-96	30	6	the	the	DET
hjic-96	30	7	choice	choice	NOUN
hjic-96	30	8	of	of	ADP
hjic-96	30	9	a	a	DET
hjic-96	30	10	model	model	NOUN
hjic-96	30	11	structure	structure	NOUN
hjic-96	30	12	:	:	PUNCT
hjic-96	30	13	what	what	DET
hjic-96	30	14	type	type	NOUN
hjic-96	30	15	of	of	ADP
hjic-96	30	16	model	model	NOUN
hjic-96	30	17	is	be	AUX
hjic-96	30	18	needed	need	VERB
hjic-96	30	19	,	,	PUNCT
hjic-96	30	20	nonlinear	nonlinear	ADJ
hjic-96	30	21	or	or	CCONJ
hjic-96	30	22	linear	linear	ADJ
hjic-96	30	23	,	,	PUNCT
hjic-96	30	24	static	static	ADJ
hjic-96	30	25	or	or	CCONJ
hjic-96	30	26	dynamic	dynamic	ADJ
hjic-96	30	27	,	,	PUNCT
hjic-96	30	28	distributed	distribute	VERB
hjic-96	30	29	or	or	CCONJ
hjic-96	30	30	lamped	lampe	VERB
hjic-96	30	31	?	?	PUNCT
hjic-96	31	1	*	*	PUNCT
hjic-96	31	2	correspondence	correspondence	NOUN
hjic-96	31	3	concerning	concern	VERB
hjic-96	31	4	this	this	DET
hjic-96	31	5	article	article	NOUN
hjic-96	31	6	should	should	AUX
hjic-96	31	7	be	be	AUX
hjic-96	31	8	addressed	address	VERB
hjic-96	31	9	to	to	ADP
hjic-96	31	10	j.	j.	PROPN
hjic-96	31	11	abonyi	abonyi	PROPN
hjic-96	31	12	(	(	PUNCT
hjic-96	31	13	abonyij@fmt.vein.hu	abonyij@fmt.vein.hu	PROPN
hjic-96	31	14	)	)	PUNCT
hjic-96	31	15	58	58	NUM
hjic-96	32	1	how	how	SCONJ
hjic-96	32	2	large	large	ADJ
hjic-96	32	3	must	must	AUX
hjic-96	32	4	the	the	DET
hjic-96	32	5	model	model	NOUN
hjic-96	32	6	set	set	NOUN
hjic-96	32	7	be	be	AUX
hjic-96	32	8	?	?	PUNCT
hjic-96	33	1	this	this	DET
hjic-96	33	2	question	question	NOUN
hjic-96	33	3	includes	include	VERB
hjic-96	33	4	the	the	DET
hjic-96	33	5	issue	issue	NOUN
hjic-96	33	6	of	of	ADP
hjic-96	33	7	expected	expect	VERB
hjic-96	33	8	model	model	NOUN
hjic-96	33	9	orders	order	NOUN
hjic-96	33	10	and	and	CCONJ
hjic-96	33	11	types	type	NOUN
hjic-96	33	12	of	of	ADP
hjic-96	33	13	nonlinearities	nonlinearitie	NOUN
hjic-96	33	14	.	.	PUNCT
hjic-96	34	1	how	how	SCONJ
hjic-96	34	2	must	must	AUX
hjic-96	34	3	the	the	DET
hjic-96	34	4	model	model	NOUN
hjic-96	34	5	be	be	AUX
hjic-96	34	6	parameterized	parameterize	VERB
hjic-96	34	7	?	?	PUNCT
hjic-96	35	1	this	this	PRON
hjic-96	35	2	involves	involve	VERB
hjic-96	35	3	selecting	select	VERB
hjic-96	35	4	a	a	DET
hjic-96	35	5	criterion	criterion	NOUN
hjic-96	35	6	to	to	PART
hjic-96	35	7	enable	enable	VERB
hjic-96	35	8	measuring	measure	VERB
hjic-96	35	9	the	the	DET
hjic-96	35	10	closeness	closeness	NOUN
hjic-96	35	11	of	of	ADP
hjic-96	35	12	the	the	DET
hjic-96	35	13	model	model	ADJ
hjic-96	35	14	dynamic	dynamic	ADJ
hjic-96	35	15	behavior	behavior	NOUN
hjic-96	35	16	to	to	ADP
hjic-96	35	17	the	the	DET
hjic-96	35	18	physical	physical	ADJ
hjic-96	35	19	process	process	NOUN
hjic-96	35	20	dynamic	dynamic	ADJ
hjic-96	35	21	behavior	behavior	NOUN
hjic-96	35	22	as	as	SCONJ
hjic-96	35	23	model	model	NOUN
hjic-96	35	24	parameters	parameter	NOUN
hjic-96	35	25	are	be	AUX
hjic-96	35	26	varied	varied	ADJ
hjic-96	35	27	.	.	PUNCT
hjic-96	36	1	large	large	ADJ
hjic-96	36	2	number	number	NOUN
hjic-96	36	3	of	of	ADP
hjic-96	36	4	model	model	NOUN
hjic-96	36	5	structure	structure	NOUN
hjic-96	36	6	selection	selection	NOUN
hjic-96	36	7	methods	method	NOUN
hjic-96	36	8	has	have	AUX
hjic-96	36	9	been	be	AUX
hjic-96	36	10	introduced	introduce	VERB
hjic-96	36	11	.	.	PUNCT
hjic-96	37	1	for	for	ADP
hjic-96	37	2	linear	linear	NOUN
hjic-96	37	3	models	model	NOUN
hjic-96	37	4	,	,	PUNCT
hjic-96	37	5	for	for	ADP
hjic-96	37	6	example	example	NOUN
hjic-96	37	7	correlation	correlation	NOUN
hjic-96	37	8	analysis	analysis	NOUN
hjic-96	37	9	and	and	CCONJ
hjic-96	37	10	multivariate	multivariate	NOUN
hjic-96	37	11	structure	structure	NOUN
hjic-96	37	12	selection	selection	NOUN
hjic-96	37	13	techniques	technique	NOUN
hjic-96	37	14	[	[	X
hjic-96	37	15	3	3	NUM
hjic-96	37	16	]	]	PUNCT
hjic-96	37	17	such	such	ADJ
hjic-96	37	18	as	as	ADP
hjic-96	37	19	principal	principal	ADJ
hjic-96	37	20	component	component	NOUN
hjic-96	37	21	analysis	analysis	NOUN
hjic-96	37	22	(	(	PUNCT
hjic-96	37	23	pca	pca	NOUN
hjic-96	37	24	)	)	PUNCT
hjic-96	37	25	are	be	AUX
hjic-96	37	26	proposed	propose	VERB
hjic-96	37	27	.	.	PUNCT
hjic-96	38	1	several	several	ADJ
hjic-96	38	2	information	information	NOUN
hjic-96	38	3	-	-	PUNCT
hjic-96	38	4	theoretical	theoretical	ADJ
hjic-96	38	5	criteria	criterion	NOUN
hjic-96	38	6	have	have	AUX
hjic-96	38	7	been	be	AUX
hjic-96	38	8	also	also	ADV
hjic-96	38	9	proposed	propose	VERB
hjic-96	38	10	for	for	ADP
hjic-96	38	11	the	the	DET
hjic-96	38	12	structure	structure	NOUN
hjic-96	38	13	selection	selection	NOUN
hjic-96	38	14	of	of	ADP
hjic-96	38	15	linear	linear	PROPN
hjic-96	38	16	dynamic	dynamic	ADJ
hjic-96	38	17	input	input	NOUN
hjic-96	38	18	-	-	PUNCT
hjic-96	38	19	output	output	NOUN
hjic-96	38	20	models	model	NOUN
hjic-96	38	21	.	.	PUNCT
hjic-96	39	1	these	these	DET
hjic-96	39	2	methods	method	NOUN
hjic-96	39	3	are	be	AUX
hjic-96	39	4	based	base	VERB
hjic-96	39	5	on	on	ADP
hjic-96	39	6	the	the	DET
hjic-96	39	7	minimization	minimization	NOUN
hjic-96	39	8	of	of	ADP
hjic-96	39	9	a	a	DET
hjic-96	39	10	criterion	criterion	NOUN
hjic-96	39	11	function	function	NOUN
hjic-96	39	12	which	which	PRON
hjic-96	39	13	involves	involve	VERB
hjic-96	39	14	the	the	DET
hjic-96	39	15	estimation	estimation	NOUN
hjic-96	39	16	of	of	ADP
hjic-96	39	17	the	the	DET
hjic-96	39	18	one	one	NUM
hjic-96	39	19	-	-	PUNCT
hjic-96	39	20	step	step	NOUN
hjic-96	39	21	-	-	PUNCT
hjic-96	39	22	prediction	prediction	NOUN
hjic-96	39	23	error	error	NOUN
hjic-96	39	24	plus	plus	CCONJ
hjic-96	39	25	some	some	DET
hjic-96	39	26	penalty	penalty	NOUN
hjic-96	39	27	function	function	NOUN
hjic-96	39	28	.	.	PUNCT
hjic-96	40	1	the	the	DET
hjic-96	40	2	classical	classical	ADJ
hjic-96	40	3	criteria	criterion	NOUN
hjic-96	40	4	are	be	AUX
hjic-96	40	5	the	the	DET
hjic-96	40	6	final	final	ADJ
hjic-96	40	7	prediction	prediction	NOUN
hjic-96	40	8	error	error	NOUN
hjic-96	40	9	(	(	PUNCT
hjic-96	40	10	fpe	fpe	PROPN
hjic-96	40	11	)	)	PUNCT
hjic-96	40	12	,	,	PUNCT
hjic-96	40	13	the	the	DET
hjic-96	40	14	akaike	akaike	ADJ
hjic-96	40	15	information	information	NOUN
hjic-96	40	16	criterion	criterion	NOUN
hjic-96	40	17	(	(	PUNCT
hjic-96	40	18	aic	aic	PROPN
hjic-96	40	19	)	)	PUNCT
hjic-96	41	1	[	[	X
hjic-96	41	2	4	4	NUM
hjic-96	41	3	]	]	PUNCT
hjic-96	41	4	,	,	PUNCT
hjic-96	41	5	the	the	DET
hjic-96	41	6	minimum	minimum	ADJ
hjic-96	41	7	description	description	NOUN
hjic-96	41	8	length	length	NOUN
hjic-96	41	9	(	(	PUNCT
hjic-96	41	10	mdl	mdl	NOUN
hjic-96	41	11	)	)	PUNCT
hjic-96	41	12	criterion	criterion	NOUN
hjic-96	42	1	[	[	X
hjic-96	42	2	5	5	NUM
hjic-96	42	3	]	]	PUNCT
hjic-96	42	4	,	,	PUNCT
hjic-96	42	5	the	the	DET
hjic-96	42	6	schwarz	schwarz	PROPN
hjic-96	42	7	criterion	criterion	NOUN
hjic-96	42	8	(	(	PUNCT
hjic-96	42	9	bic	bic	PROPN
hjic-96	42	10	)	)	PUNCT
hjic-96	43	1	[	[	X
hjic-96	43	2	6	6	NUM
hjic-96	43	3	]	]	PUNCT
hjic-96	43	4	and	and	CCONJ
hjic-96	43	5	the	the	DET
hjic-96	43	6	hannan	hannan	PROPN
hjic-96	43	7	-	-	PUNCT
hjic-96	43	8	quinn	quinn	PROPN
hjic-96	43	9	criteria	criterion	NOUN
hjic-96	43	10	(	(	PUNCT
hjic-96	43	11	hic	hic	ADJ
hjic-96	43	12	)	)	PUNCT
hjic-96	44	1	[	[	X
hjic-96	44	2	7	7	NUM
hjic-96	44	3	]	]	PUNCT
hjic-96	44	4	.	.	PUNCT
hjic-96	45	1	they	they	PRON
hjic-96	45	2	only	only	ADV
hjic-96	45	3	differ	differ	VERB
hjic-96	45	4	on	on	ADP
hjic-96	45	5	the	the	DET
hjic-96	45	6	employed	employ	VERB
hjic-96	45	7	penalty	penalty	NOUN
hjic-96	45	8	function	function	NOUN
hjic-96	45	9	,	,	PUNCT
hjic-96	45	10	but	but	CCONJ
hjic-96	45	11	in	in	ADP
hjic-96	45	12	[	[	X
hjic-96	45	13	8	8	NUM
hjic-96	45	14	]	]	X
hjic-96	45	15	a	a	DET
hjic-96	45	16	new	new	ADJ
hjic-96	45	17	criterion	criterion	NOUN
hjic-96	45	18	function	function	NOUN
hjic-96	45	19	is	be	AUX
hjic-96	45	20	introduced	introduce	VERB
hjic-96	45	21	based	base	VERB
hjic-96	45	22	on	on	ADP
hjic-96	45	23	the	the	DET
hjic-96	45	24	decomposition	decomposition	NOUN
hjic-96	45	25	of	of	ADP
hjic-96	45	26	the	the	DET
hjic-96	45	27	variance	variance	NOUN
hjic-96	45	28	of	of	ADP
hjic-96	45	29	the	the	DET
hjic-96	45	30	innovations	innovation	NOUN
hjic-96	45	31	of	of	ADP
hjic-96	45	32	the	the	DET
hjic-96	45	33	model	model	NOUN
hjic-96	45	34	in	in	ADP
hjic-96	45	35	terms	term	NOUN
hjic-96	45	36	of	of	ADP
hjic-96	45	37	their	their	PRON
hjic-96	45	38	frequency	frequency	NOUN
hjic-96	45	39	components	component	NOUN
hjic-96	45	40	.	.	PUNCT
hjic-96	46	1	the	the	DET
hjic-96	46	2	information	information	NOUN
hjic-96	46	3	criteria	criterion	NOUN
hjic-96	46	4	have	have	AUX
hjic-96	46	5	been	be	AUX
hjic-96	46	6	used	use	VERB
hjic-96	46	7	in	in	ADP
hjic-96	46	8	a	a	DET
hjic-96	46	9	context	context	NOUN
hjic-96	46	10	of	of	ADP
hjic-96	46	11	regression	regression	NOUN
hjic-96	46	12	models	model	NOUN
hjic-96	46	13	[	[	X
hjic-96	46	14	9	9	NUM
hjic-96	46	15	,	,	PUNCT
hjic-96	46	16	10	10	NUM
hjic-96	46	17	]	]	PUNCT
hjic-96	46	18	,	,	PUNCT
hjic-96	46	19	in	in	ADP
hjic-96	46	20	distributed	distribute	VERB
hjic-96	46	21	lag	lag	NOUN
hjic-96	46	22	regression	regression	NOUN
hjic-96	46	23	models	model	NOUN
hjic-96	46	24	[	[	X
hjic-96	46	25	11	11	NUM
hjic-96	46	26	]	]	PUNCT
hjic-96	46	27	,	,	PUNCT
hjic-96	46	28	or	or	CCONJ
hjic-96	46	29	in	in	ADP
hjic-96	46	30	selection	selection	NOUN
hjic-96	46	31	of	of	ADP
hjic-96	46	32	the	the	DET
hjic-96	46	33	order	order	NOUN
hjic-96	46	34	an	an	DET
hjic-96	46	35	autoregressive	autoregressive	ADJ
hjic-96	46	36	and	and	CCONJ
hjic-96	46	37	autoregressive	autoregressive	ADJ
hjic-96	46	38	moving	move	VERB
hjic-96	46	39	average	average	ADJ
hjic-96	46	40	model	model	NOUN
hjic-96	46	41	[	[	X
hjic-96	46	42	12	12	NUM
hjic-96	46	43	,	,	PUNCT
hjic-96	46	44	13	13	NUM
hjic-96	46	45	,	,	PUNCT
hjic-96	46	46	14	14	NUM
hjic-96	46	47	]	]	PUNCT
hjic-96	46	48	.	.	PUNCT
hjic-96	47	1	in	in	ADP
hjic-96	47	2	paper	paper	NOUN
hjic-96	47	3	[	[	X
hjic-96	47	4	15	15	NUM
hjic-96	47	5	]	]	X
hjic-96	47	6	the	the	DET
hjic-96	47	7	effects	effect	NOUN
hjic-96	47	8	of	of	ADP
hjic-96	47	9	the	the	DET
hjic-96	47	10	model	model	NOUN
hjic-96	47	11	selection	selection	NOUN
hjic-96	47	12	problem	problem	NOUN
hjic-96	47	13	,	,	PUNCT
hjic-96	47	14	and	and	CCONJ
hjic-96	47	15	in	in	ADP
hjic-96	47	16	paper	paper	NOUN
hjic-96	47	17	[	[	X
hjic-96	47	18	16	16	NUM
hjic-96	47	19	]	]	PUNCT
hjic-96	47	20	the	the	DET
hjic-96	47	21	variable	variable	ADJ
hjic-96	47	22	selection	selection	NOUN
hjic-96	47	23	problem	problem	NOUN
hjic-96	47	24	are	be	AUX
hjic-96	47	25	studied	study	VERB
hjic-96	47	26	.	.	PUNCT
hjic-96	48	1	determining	determine	VERB
hjic-96	48	2	the	the	DET
hjic-96	48	3	structure	structure	NOUN
hjic-96	48	4	of	of	ADP
hjic-96	48	5	linear	linear	PROPN
hjic-96	48	6	systems	system	NOUN
hjic-96	48	7	is	be	AUX
hjic-96	48	8	a	a	DET
hjic-96	48	9	rather	rather	ADV
hjic-96	48	10	straightforward	straightforward	ADJ
hjic-96	48	11	task	task	NOUN
hjic-96	48	12	with	with	ADP
hjic-96	48	13	these	these	DET
hjic-96	48	14	tools	tool	NOUN
hjic-96	48	15	,	,	PUNCT
hjic-96	48	16	but	but	CCONJ
hjic-96	48	17	for	for	ADP
hjic-96	48	18	nonlinear	nonlinear	ADJ
hjic-96	48	19	systems	system	NOUN
hjic-96	48	20	other	other	ADJ
hjic-96	48	21	structure	structure	NOUN
hjic-96	48	22	selection	selection	NOUN
hjic-96	48	23	methods	method	NOUN
hjic-96	48	24	are	be	AUX
hjic-96	48	25	need	need	NOUN
hjic-96	48	26	.	.	PUNCT
hjic-96	49	1	aguirre	aguirre	PROPN
hjic-96	49	2	and	and	CCONJ
hjic-96	49	3	billings	billing	NOUN
hjic-96	49	4	[	[	X
hjic-96	49	5	17	17	NUM
hjic-96	49	6	]	]	PUNCT
hjic-96	49	7	defined	define	VERB
hjic-96	49	8	the	the	DET
hjic-96	49	9	concepts	concept	NOUN
hjic-96	49	10	of	of	ADP
hjic-96	49	11	term	term	NOUN
hjic-96	49	12	clusters	cluster	NOUN
hjic-96	49	13	and	and	CCONJ
hjic-96	49	14	cluster	cluster	NOUN
hjic-96	49	15	coefficients	coefficient	NOUN
hjic-96	49	16	and	and	CCONJ
hjic-96	49	17	used	use	VERB
hjic-96	49	18	in	in	ADP
hjic-96	49	19	the	the	DET
hjic-96	49	20	context	context	NOUN
hjic-96	49	21	of	of	ADP
hjic-96	49	22	system	system	NOUN
hjic-96	49	23	identification	identification	NOUN
hjic-96	49	24	.	.	PUNCT
hjic-96	50	1	this	this	DET
hjic-96	50	2	approach	approach	NOUN
hjic-96	50	3	is	be	AUX
hjic-96	50	4	used	use	VERB
hjic-96	50	5	for	for	ADP
hjic-96	50	6	the	the	DET
hjic-96	50	7	structure	structure	NOUN
hjic-96	50	8	selection	selection	NOUN
hjic-96	50	9	of	of	ADP
hjic-96	50	10	polynomial	polynomial	ADJ
hjic-96	50	11	models	model	NOUN
hjic-96	50	12	in	in	ADP
hjic-96	50	13	the	the	DET
hjic-96	50	14	paper	paper	NOUN
hjic-96	50	15	of	of	ADP
hjic-96	50	16	aguirre	aguirre	PROPN
hjic-96	50	17	and	and	CCONJ
hjic-96	50	18	mendes	mende	NOUN
hjic-96	50	19	[	[	X
hjic-96	50	20	18	18	NUM
hjic-96	50	21	]	]	PUNCT
hjic-96	50	22	.	.	PUNCT
hjic-96	51	1	in	in	ADP
hjic-96	51	2	[	[	X
hjic-96	51	3	19	19	NUM
hjic-96	51	4	]	]	X
hjic-96	51	5	an	an	DET
hjic-96	51	6	alternative	alternative	ADJ
hjic-96	51	7	solution	solution	NOUN
hjic-96	51	8	is	be	AUX
hjic-96	51	9	introduced	introduce	VERB
hjic-96	51	10	by	by	ADP
hjic-96	51	11	initially	initially	ADV
hjic-96	51	12	conducting	conduct	VERB
hjic-96	51	13	a	a	DET
hjic-96	51	14	forward	forward	ADJ
hjic-96	51	15	search	search	NOUN
hjic-96	51	16	through	through	ADP
hjic-96	51	17	the	the	DET
hjic-96	51	18	many	many	ADJ
hjic-96	51	19	possible	possible	ADJ
hjic-96	51	20	candidate	candidate	NOUN
hjic-96	51	21	model	model	NOUN
hjic-96	51	22	terms	term	NOUN
hjic-96	51	23	before	before	ADP
hjic-96	51	24	performing	perform	VERB
hjic-96	51	25	an	an	DET
hjic-96	51	26	exhaustive	exhaustive	ADJ
hjic-96	51	27	all	all	PRON
hjic-96	51	28	-	-	PUNCT
hjic-96	51	29	subset	subset	VERB
hjic-96	51	30	model	model	NOUN
hjic-96	51	31	selection	selection	NOUN
hjic-96	51	32	on	on	ADP
hjic-96	51	33	the	the	DET
hjic-96	51	34	resulting	result	VERB
hjic-96	51	35	model	model	NOUN
hjic-96	51	36	.	.	PUNCT
hjic-96	52	1	a	a	DET
hjic-96	52	2	backward	backward	ADJ
hjic-96	52	3	search	search	NOUN
hjic-96	52	4	approach	approach	NOUN
hjic-96	52	5	based	base	VERB
hjic-96	52	6	on	on	ADP
hjic-96	52	7	orthogonal	orthogonal	ADJ
hjic-96	52	8	parameter	parameter	NOUN
hjic-96	52	9	estimation	estimation	NOUN
hjic-96	52	10	is	be	AUX
hjic-96	52	11	also	also	ADV
hjic-96	52	12	applied	apply	VERB
hjic-96	52	13	to	to	ADP
hjic-96	52	14	structure	structure	NOUN
hjic-96	52	15	selection	selection	NOUN
hjic-96	52	16	[	[	X
hjic-96	52	17	20	20	NUM
hjic-96	52	18	,	,	PUNCT
hjic-96	52	19	21	21	NUM
hjic-96	52	20	]	]	PUNCT
hjic-96	52	21	.	.	PUNCT
hjic-96	53	1	the	the	DET
hjic-96	53	2	paper	paper	NOUN
hjic-96	54	1	[	[	X
hjic-96	54	2	22	22	NUM
hjic-96	54	3	]	]	PUNCT
hjic-96	54	4	discusses	discuss	VERB
hjic-96	54	5	several	several	ADJ
hjic-96	54	6	model	model	NOUN
hjic-96	54	7	structures	structure	NOUN
hjic-96	54	8	selection	selection	NOUN
hjic-96	54	9	methods	method	NOUN
hjic-96	54	10	and	and	CCONJ
hjic-96	54	11	nonlinear	nonlinear	ADJ
hjic-96	54	12	input	input	NOUN
hjic-96	54	13	-	-	PUNCT
hjic-96	54	14	output	output	NOUN
hjic-96	54	15	models	model	NOUN
hjic-96	54	16	that	that	PRON
hjic-96	54	17	are	be	AUX
hjic-96	54	18	suitable	suitable	ADJ
hjic-96	54	19	for	for	ADP
hjic-96	54	20	implementation	implementation	NOUN
hjic-96	54	21	of	of	ADP
hjic-96	54	22	feed	feed	NOUN
hjic-96	54	23	-	-	PUNCT
hjic-96	54	24	forward	forward	NOUN
hjic-96	54	25	neural	neural	ADJ
hjic-96	54	26	networks	network	NOUN
hjic-96	54	27	.	.	PUNCT
hjic-96	55	1	a	a	DET
hjic-96	55	2	systematic	systematic	ADJ
hjic-96	55	3	method	method	NOUN
hjic-96	55	4	for	for	ADP
hjic-96	55	5	the	the	DET
hjic-96	55	6	selection	selection	NOUN
hjic-96	55	7	of	of	ADP
hjic-96	55	8	model	model	NOUN
hjic-96	55	9	order	order	NOUN
hjic-96	55	10	and	and	CCONJ
hjic-96	55	11	time	time	NOUN
hjic-96	55	12	delay	delay	NOUN
hjic-96	55	13	is	be	AUX
hjic-96	55	14	presented	present	VERB
hjic-96	55	15	in	in	ADP
hjic-96	55	16	[	[	X
hjic-96	55	17	23	23	NUM
hjic-96	55	18	]	]	PUNCT
hjic-96	55	19	.	.	PUNCT
hjic-96	56	1	the	the	DET
hjic-96	56	2	method	method	NOUN
hjic-96	56	3	is	be	AUX
hjic-96	56	4	applied	apply	VERB
hjic-96	56	5	to	to	ADP
hjic-96	56	6	the	the	DET
hjic-96	56	7	neural	neural	ADJ
hjic-96	56	8	network	network	NOUN
hjic-96	56	9	modeling	modeling	NOUN
hjic-96	56	10	of	of	ADP
hjic-96	56	11	a	a	DET
hjic-96	56	12	multivariable	multivariable	ADJ
hjic-96	56	13	chemical	chemical	NOUN
hjic-96	56	14	process	process	NOUN
hjic-96	56	15	rig	rig	VERB
hjic-96	56	16	.	.	PUNCT
hjic-96	57	1	a	a	DET
hjic-96	57	2	deterministic	deterministic	ADJ
hjic-96	57	3	suitability	suitability	NOUN
hjic-96	57	4	measure	measure	NOUN
hjic-96	57	5	is	be	AUX
hjic-96	57	6	introduced	introduce	VERB
hjic-96	57	7	in	in	ADP
hjic-96	57	8	[	[	X
hjic-96	57	9	24	24	NUM
hjic-96	57	10	]	]	PUNCT
hjic-96	57	11	that	that	PRON
hjic-96	57	12	quantifies	quantify	VERB
hjic-96	57	13	the	the	DET
hjic-96	57	14	capably	capably	ADV
hjic-96	57	15	of	of	ADP
hjic-96	57	16	a	a	DET
hjic-96	57	17	particular	particular	ADJ
hjic-96	57	18	model	model	NOUN
hjic-96	57	19	class	class	NOUN
hjic-96	57	20	to	to	PART
hjic-96	57	21	capture	capture	VERB
hjic-96	57	22	the	the	DET
hjic-96	57	23	control	control	NOUN
hjic-96	57	24	relevant	relevant	ADJ
hjic-96	57	25	i	i	PROPN
hjic-96	57	26	/	/	SYM
hjic-96	57	27	o	o	NOUN
hjic-96	57	28	-	-	NOUN
hjic-96	57	29	behavior	behavior	NOUN
hjic-96	57	30	of	of	ADP
hjic-96	57	31	a	a	DET
hjic-96	57	32	nonlinear	nonlinear	ADJ
hjic-96	57	33	system	system	NOUN
hjic-96	57	34	.	.	PUNCT
hjic-96	58	1	this	this	DET
hjic-96	58	2	suitability	suitability	NOUN
hjic-96	58	3	measure	measure	NOUN
hjic-96	58	4	can	can	AUX
hjic-96	58	5	be	be	AUX
hjic-96	58	6	used	use	VERB
hjic-96	58	7	for	for	ADP
hjic-96	58	8	the	the	DET
hjic-96	58	9	purpose	purpose	NOUN
hjic-96	58	10	of	of	ADP
hjic-96	58	11	model	model	NOUN
hjic-96	58	12	structure	structure	NOUN
hjic-96	58	13	selection	selection	NOUN
hjic-96	58	14	prior	prior	ADV
hjic-96	58	15	to	to	ADP
hjic-96	58	16	the	the	DET
hjic-96	58	17	actual	actual	ADJ
hjic-96	58	18	parameter	parameter	NOUN
hjic-96	58	19	identification	identification	NOUN
hjic-96	58	20	.	.	PUNCT
hjic-96	59	1	the	the	DET
hjic-96	59	2	fast	fast	ADJ
hjic-96	59	3	bootstrap	bootstrap	NOUN
hjic-96	59	4	(	(	PUNCT
hjic-96	59	5	fb	fb	INTJ
hjic-96	59	6	)	)	PUNCT
hjic-96	59	7	methodology	methodology	NOUN
hjic-96	59	8	to	to	PART
hjic-96	59	9	select	select	VERB
hjic-96	59	10	the	the	DET
hjic-96	59	11	best	good	ADJ
hjic-96	59	12	model	model	NOUN
hjic-96	59	13	structure	structure	NOUN
hjic-96	59	14	is	be	AUX
hjic-96	59	15	presented	present	VERB
hjic-96	59	16	in	in	ADP
hjic-96	59	17	[	[	X
hjic-96	59	18	25	25	NUM
hjic-96	59	19	]	]	PUNCT
hjic-96	59	20	.	.	PUNCT
hjic-96	60	1	the	the	DET
hjic-96	60	2	methodology	methodology	NOUN
hjic-96	60	3	is	be	AUX
hjic-96	60	4	applied	apply	VERB
hjic-96	60	5	to	to	ADP
hjic-96	60	6	a	a	DET
hjic-96	60	7	regression	regression	NOUN
hjic-96	60	8	task	task	NOUN
hjic-96	60	9	.	.	PUNCT
hjic-96	61	1	in	in	ADP
hjic-96	61	2	[	[	X
hjic-96	61	3	26	26	NUM
hjic-96	61	4	]	]	PUNCT
hjic-96	61	5	a	a	DET
hjic-96	61	6	methodology	methodology	NOUN
hjic-96	61	7	for	for	ADP
hjic-96	61	8	model	model	NOUN
hjic-96	61	9	structure	structure	NOUN
hjic-96	61	10	selection	selection	NOUN
hjic-96	61	11	based	base	VERB
hjic-96	61	12	on	on	ADP
hjic-96	61	13	a	a	DET
hjic-96	61	14	genetic	genetic	ADJ
hjic-96	61	15	algorithm	algorithm	NOUN
hjic-96	61	16	was	be	AUX
hjic-96	61	17	introduced	introduce	VERB
hjic-96	61	18	and	and	CCONJ
hjic-96	61	19	applied	apply	VERB
hjic-96	61	20	to	to	ADP
hjic-96	61	21	nonlinear	nonlinear	ADJ
hjic-96	61	22	discrete	discrete	ADJ
hjic-96	61	23	-	-	PUNCT
hjic-96	61	24	time	time	NOUN
hjic-96	61	25	dynamic	dynamic	ADJ
hjic-96	61	26	systems	system	NOUN
hjic-96	61	27	.	.	PUNCT
hjic-96	62	1	a	a	DET
hjic-96	62	2	modified	modify	VERB
hjic-96	62	3	genetic	genetic	ADJ
hjic-96	62	4	programming	programming	NOUN
hjic-96	62	5	approach	approach	NOUN
hjic-96	62	6	for	for	ADP
hjic-96	62	7	model	model	NOUN
hjic-96	62	8	structure	structure	NOUN
hjic-96	62	9	selection	selection	NOUN
hjic-96	62	10	is	be	AUX
hjic-96	62	11	introduced	introduce	VERB
hjic-96	62	12	in	in	ADP
hjic-96	62	13	[	[	X
hjic-96	62	14	27	27	NUM
hjic-96	62	15	]	]	PUNCT
hjic-96	62	16	.	.	PUNCT
hjic-96	63	1	it	it	PRON
hjic-96	63	2	is	be	AUX
hjic-96	63	3	combined	combine	VERB
hjic-96	63	4	with	with	ADP
hjic-96	63	5	a	a	DET
hjic-96	63	6	classical	classical	ADJ
hjic-96	63	7	technique	technique	NOUN
hjic-96	63	8	for	for	ADP
hjic-96	63	9	parameter	parameter	NOUN
hjic-96	63	10	estimation	estimation	NOUN
hjic-96	63	11	.	.	PUNCT
hjic-96	64	1	hong	hong	PROPN
hjic-96	64	2	and	and	CCONJ
hjic-96	64	3	harris	harris	PROPN
hjic-96	65	1	[	[	X
hjic-96	65	2	28	28	NUM
hjic-96	65	3	]	]	PUNCT
hjic-96	65	4	introduced	introduce	VERB
hjic-96	65	5	a	a	DET
hjic-96	65	6	learning	learning	NOUN
hjic-96	65	7	algorithm	algorithm	NOUN
hjic-96	65	8	for	for	ADP
hjic-96	65	9	model	model	NOUN
hjic-96	65	10	subset	subset	NOUN
hjic-96	65	11	selection	selection	NOUN
hjic-96	65	12	which	which	PRON
hjic-96	65	13	based	base	VERB
hjic-96	65	14	on	on	ADP
hjic-96	65	15	a	a	DET
hjic-96	65	16	new	new	ADJ
hjic-96	65	17	composite	composite	ADJ
hjic-96	65	18	cost	cost	NOUN
hjic-96	65	19	function	function	NOUN
hjic-96	65	20	that	that	PRON
hjic-96	65	21	simultaneously	simultaneously	ADV
hjic-96	65	22	optimizes	optimize	VERB
hjic-96	65	23	the	the	DET
hjic-96	65	24	model	model	NOUN
hjic-96	65	25	approximation	approximation	NOUN
hjic-96	65	26	ability	ability	NOUN
hjic-96	65	27	and	and	CCONJ
hjic-96	65	28	model	model	NOUN
hjic-96	65	29	adequacy	adequacy	NOUN
hjic-96	65	30	.	.	PUNCT
hjic-96	66	1	in	in	ADP
hjic-96	66	2	[	[	X
hjic-96	66	3	29	29	NUM
hjic-96	66	4	]	]	X
hjic-96	66	5	a	a	DET
hjic-96	66	6	cost	cost	NOUN
hjic-96	66	7	functional	functional	NOUN
hjic-96	66	8	is	be	AUX
hjic-96	66	9	evaluated	evaluate	VERB
hjic-96	66	10	for	for	ADP
hjic-96	66	11	each	each	DET
hjic-96	66	12	identified	identify	VERB
hjic-96	66	13	model	model	NOUN
hjic-96	66	14	and	and	CCONJ
hjic-96	66	15	the	the	DET
hjic-96	66	16	model	model	NOUN
hjic-96	66	17	with	with	ADP
hjic-96	66	18	minimum	minimum	ADJ
hjic-96	66	19	cost	cost	NOUN
hjic-96	66	20	is	be	AUX
hjic-96	66	21	preferred	prefer	VERB
hjic-96	66	22	.	.	PUNCT
hjic-96	67	1	suboptimal	suboptimal	ADJ
hjic-96	67	2	search	search	NOUN
hjic-96	67	3	strategies	strategy	NOUN
hjic-96	67	4	are	be	AUX
hjic-96	67	5	adopted	adopt	VERB
hjic-96	67	6	,	,	PUNCT
hjic-96	67	7	forward	forward	ADV
hjic-96	67	8	and	and	CCONJ
hjic-96	67	9	stepwise	stepwise	ADJ
hjic-96	67	10	strategies	strategy	NOUN
hjic-96	67	11	are	be	AUX
hjic-96	67	12	considered	consider	VERB
hjic-96	67	13	.	.	PUNCT
hjic-96	68	1	we	we	PRON
hjic-96	68	2	introduce	introduce	VERB
hjic-96	68	3	in	in	ADP
hjic-96	68	4	this	this	DET
hjic-96	68	5	paper	paper	NOUN
hjic-96	68	6	a	a	DET
hjic-96	68	7	new	new	ADJ
hjic-96	68	8	data	data	NOUN
hjic-96	68	9	-	-	PUNCT
hjic-96	68	10	driven	drive	VERB
hjic-96	68	11	structure	structure	NOUN
hjic-96	68	12	selection	selection	NOUN
hjic-96	68	13	method	method	NOUN
hjic-96	68	14	.	.	PUNCT
hjic-96	69	1	the	the	DET
hjic-96	69	2	new	new	ADJ
hjic-96	69	3	method	method	NOUN
hjic-96	69	4	is	be	AUX
hjic-96	69	5	based	base	VERB
hjic-96	69	6	on	on	ADP
hjic-96	69	7	fuzzy	fuzzy	ADJ
hjic-96	69	8	association	association	NOUN
hjic-96	69	9	rule	rule	NOUN
hjic-96	69	10	mining	mining	NOUN
hjic-96	69	11	and	and	CCONJ
hjic-96	69	12	it	it	PRON
hjic-96	69	13	is	be	AUX
hjic-96	69	14	called	call	VERB
hjic-96	69	15	mossfarm	mossfarm	NOUN
hjic-96	69	16	(	(	PUNCT
hjic-96	69	17	model	model	NOUN
hjic-96	69	18	structure	structure	NOUN
hjic-96	69	19	selection	selection	NOUN
hjic-96	69	20	by	by	ADP
hjic-96	69	21	fuzzy	fuzzy	ADJ
hjic-96	69	22	association	association	NOUN
hjic-96	69	23	rule	rule	NOUN
hjic-96	69	24	mining	mining	NOUN
hjic-96	69	25	)	)	PUNCT
hjic-96	69	26	.	.	PUNCT
hjic-96	70	1	association	association	NOUN
hjic-96	70	2	rule	rule	NOUN
hjic-96	70	3	mining	mining	NOUN
hjic-96	70	4	finds	find	VERB
hjic-96	70	5	interesting	interesting	ADJ
hjic-96	70	6	association	association	NOUN
hjic-96	70	7	or	or	CCONJ
hjic-96	70	8	correlation	correlation	NOUN
hjic-96	70	9	relationships	relationship	NOUN
hjic-96	70	10	among	among	ADP
hjic-96	70	11	a	a	DET
hjic-96	70	12	large	large	ADJ
hjic-96	70	13	data	datum	NOUN
hjic-96	70	14	set	set	VERB
hjic-96	70	15	.	.	PUNCT
hjic-96	71	1	the	the	DET
hjic-96	71	2	problem	problem	NOUN
hjic-96	71	3	of	of	ADP
hjic-96	71	4	mining	mining	NOUN
hjic-96	71	5	association	association	NOUN
hjic-96	71	6	rules	rule	NOUN
hjic-96	71	7	was	be	AUX
hjic-96	71	8	introduced	introduce	VERB
hjic-96	71	9	over	over	ADP
hjic-96	71	10	supermarket	supermarket	NOUN
hjic-96	71	11	basket	basket	NOUN
hjic-96	71	12	data	datum	NOUN
hjic-96	71	13	in	in	ADP
hjic-96	71	14	[	[	X
hjic-96	71	15	30	30	NUM
hjic-96	71	16	]	]	PUNCT
hjic-96	71	17	.	.	PUNCT
hjic-96	72	1	it	it	PRON
hjic-96	72	2	helps	help	VERB
hjic-96	72	3	to	to	PART
hjic-96	72	4	learn	learn	VERB
hjic-96	72	5	more	more	ADJ
hjic-96	72	6	about	about	ADP
hjic-96	72	7	the	the	DET
hjic-96	72	8	buying	buying	NOUN
hjic-96	72	9	habits	habit	NOUN
hjic-96	72	10	of	of	ADP
hjic-96	72	11	the	the	DET
hjic-96	72	12	customer	customer	NOUN
hjic-96	72	13	.	.	PUNCT
hjic-96	73	1	it	it	PRON
hjic-96	73	2	gets	get	VERB
hjic-96	73	3	information	information	NOUN
hjic-96	73	4	and	and	CCONJ
hjic-96	73	5	answers	answer	NOUN
hjic-96	73	6	for	for	ADP
hjic-96	73	7	the	the	DET
hjic-96	73	8	market	market	NOUN
hjic-96	73	9	questions	question	NOUN
hjic-96	73	10	.	.	PUNCT
hjic-96	74	1	but	but	CCONJ
hjic-96	74	2	the	the	DET
hjic-96	74	3	market	market	NOUN
hjic-96	74	4	basket	basket	NOUN
hjic-96	74	5	analysis	analysis	NOUN
hjic-96	74	6	is	be	AUX
hjic-96	74	7	just	just	ADV
hjic-96	74	8	one	one	NUM
hjic-96	74	9	application	application	NOUN
hjic-96	74	10	of	of	ADP
hjic-96	74	11	association	association	NOUN
hjic-96	74	12	rule	rule	NOUN
hjic-96	74	13	mining	mining	NOUN
hjic-96	74	14	this	this	DET
hjic-96	74	15	paper	paper	NOUN
hjic-96	74	16	presents	present	VERB
hjic-96	74	17	a	a	DET
hjic-96	74	18	new	new	ADJ
hjic-96	74	19	application	application	NOUN
hjic-96	74	20	area	area	NOUN
hjic-96	74	21	,	,	PUNCT
hjic-96	74	22	the	the	DET
hjic-96	74	23	model	model	NOUN
hjic-96	74	24	structure	structure	NOUN
hjic-96	74	25	selection	selection	NOUN
hjic-96	74	26	.	.	PUNCT
hjic-96	75	1	this	this	DET
hjic-96	75	2	paper	paper	NOUN
hjic-96	75	3	is	be	AUX
hjic-96	75	4	organized	organize	VERB
hjic-96	75	5	as	as	SCONJ
hjic-96	75	6	follows	follow	VERB
hjic-96	75	7	.	.	PUNCT
hjic-96	76	1	the	the	DET
hjic-96	76	2	first	first	ADJ
hjic-96	76	3	section	section	NOUN
hjic-96	76	4	introduces	introduce	VERB
hjic-96	76	5	the	the	DET
hjic-96	76	6	system	system	NOUN
hjic-96	76	7	identification	identification	NOUN
hjic-96	76	8	problem	problem	NOUN
hjic-96	76	9	in	in	ADP
hjic-96	76	10	nonlinear	nonlinear	ADJ
hjic-96	76	11	black	black	PROPN
hjic-96	76	12	box	box	PROPN
hjic-96	76	13	modeling	modeling	NOUN
hjic-96	76	14	.	.	PUNCT
hjic-96	77	1	association	association	NOUN
hjic-96	77	2	rule	rule	NOUN
hjic-96	77	3	mining	mining	NOUN
hjic-96	77	4	theory	theory	NOUN
hjic-96	77	5	is	be	AUX
hjic-96	77	6	presented	present	VERB
hjic-96	77	7	in	in	ADP
hjic-96	77	8	the	the	DET
hjic-96	77	9	second	second	ADJ
hjic-96	77	10	section	section	NOUN
hjic-96	77	11	.	.	PUNCT
hjic-96	78	1	in	in	ADP
hjic-96	78	2	third	third	ADJ
hjic-96	78	3	section	section	NOUN
hjic-96	78	4	the	the	DET
hjic-96	78	5	fuzzy	fuzzy	ADJ
hjic-96	78	6	association	association	NOUN
hjic-96	78	7	rule	rule	NOUN
hjic-96	78	8	mining	mining	NOUN
hjic-96	78	9	is	be	AUX
hjic-96	78	10	detailed	detail	VERB
hjic-96	78	11	.	.	PUNCT
hjic-96	79	1	our	our	PRON
hjic-96	79	2	new	new	ADJ
hjic-96	79	3	method	method	NOUN
hjic-96	79	4	based	base	VERB
hjic-96	79	5	on	on	ADP
hjic-96	79	6	fuzzy	fuzzy	ADJ
hjic-96	79	7	association	association	NOUN
hjic-96	79	8	rule	rule	NOUN
hjic-96	79	9	mining	mining	NOUN
hjic-96	79	10	is	be	AUX
hjic-96	79	11	introduced	introduce	VERB
hjic-96	79	12	in	in	ADP
hjic-96	79	13	the	the	DET
hjic-96	79	14	fourth	fourth	ADJ
hjic-96	79	15	section	section	NOUN
hjic-96	79	16	.	.	PUNCT
hjic-96	80	1	the	the	DET
hjic-96	80	2	last	last	ADJ
hjic-96	80	3	fifth	fifth	ADJ
hjic-96	80	4	section	section	NOUN
hjic-96	80	5	illustrates	illustrate	VERB
hjic-96	80	6	how	how	SCONJ
hjic-96	80	7	the	the	DET
hjic-96	80	8	mossfarm	mossfarm	NOUN
hjic-96	80	9	method	method	NOUN
hjic-96	80	10	select	select	VERB
hjic-96	80	11	the	the	DET
hjic-96	80	12	most	most	ADV
hjic-96	80	13	important	important	ADJ
hjic-96	80	14	model	model	NOUN
hjic-96	80	15	structures	structure	NOUN
hjic-96	80	16	of	of	ADP
hjic-96	80	17	a	a	DET
hjic-96	80	18	linear	linear	NOUN
hjic-96	80	19	(	(	PUNCT
hjic-96	80	20	least	least	ADJ
hjic-96	80	21	square	square	ADJ
hjic-96	80	22	method	method	NOUN
hjic-96	80	23	)	)	PUNCT
hjic-96	80	24	and	and	CCONJ
hjic-96	80	25	a	a	DET
hjic-96	80	26	non	non	ADJ
hjic-96	80	27	-	-	ADJ
hjic-96	80	28	linear	linear	ADJ
hjic-96	80	29	(	(	PUNCT
hjic-96	80	30	neural	neural	ADJ
hjic-96	80	31	network	network	NOUN
hjic-96	80	32	)	)	PUNCT
hjic-96	80	33	model	model	NOUN
hjic-96	80	34	of	of	ADP
hjic-96	80	35	a	a	DET
hjic-96	80	36	styrene	styrene	ADJ
hjic-96	80	37	polymerization	polymerization	NOUN
hjic-96	80	38	cstr	cstr	NOUN
hjic-96	80	39	.	.	PUNCT
hjic-96	81	1	system	system	NOUN
hjic-96	81	2	identification	identification	NOUN
hjic-96	81	3	in	in	ADP
hjic-96	81	4	nonlinear	nonlinear	ADJ
hjic-96	81	5	black	black	PROPN
hjic-96	81	6	box	box	PROPN
hjic-96	81	7	modeling	modeling	NOUN
hjic-96	81	8	to	to	PART
hjic-96	81	9	be	be	AUX
hjic-96	81	10	successful	successful	ADJ
hjic-96	81	11	the	the	DET
hjic-96	81	12	entire	entire	ADJ
hjic-96	81	13	modeling	modeling	NOUN
hjic-96	81	14	process	process	NOUN
hjic-96	81	15	should	should	AUX
hjic-96	81	16	be	be	AUX
hjic-96	81	17	given	give	VERB
hjic-96	81	18	as	as	ADV
hjic-96	81	19	much	much	ADJ
hjic-96	81	20	information	information	NOUN
hjic-96	81	21	about	about	ADP
hjic-96	81	22	the	the	DET
hjic-96	81	23	system	system	NOUN
hjic-96	81	24	as	as	SCONJ
hjic-96	81	25	is	be	AUX
hjic-96	81	26	practical	practical	ADJ
hjic-96	81	27	.	.	PUNCT
hjic-96	82	1	the	the	DET
hjic-96	82	2	utilization	utilization	NOUN
hjic-96	82	3	of	of	ADP
hjic-96	82	4	prior	prior	ADJ
hjic-96	82	5	knowledge	knowledge	NOUN
hjic-96	82	6	and	and	CCONJ
hjic-96	82	7	physical	physical	ADJ
hjic-96	82	8	insight	insight	NOUN
hjic-96	82	9	about	about	ADP
hjic-96	82	10	the	the	DET
hjic-96	82	11	system	system	NOUN
hjic-96	82	12	are	be	AUX
hjic-96	82	13	very	very	ADV
hjic-96	82	14	important	important	ADJ
hjic-96	82	15	,	,	PUNCT
hjic-96	82	16	but	but	CCONJ
hjic-96	82	17	in	in	ADP
hjic-96	82	18	nonlinear	nonlinear	ADJ
hjic-96	82	19	black	black	ADJ
hjic-96	82	20	-	-	PUNCT
hjic-96	82	21	box	box	NOUN
hjic-96	82	22	situation	situation	NOUN
hjic-96	82	23	no	no	DET
hjic-96	82	24	physical	physical	ADJ
hjic-96	82	25	insight	insight	NOUN
hjic-96	82	26	is	be	AUX
hjic-96	82	27	available	available	ADJ
hjic-96	82	28	,	,	PUNCT
hjic-96	82	29	we	we	PRON
hjic-96	82	30	have	have	VERB
hjic-96	82	31	“	"	PUNCT
hjic-96	82	32	only	only	ADV
hjic-96	82	33	”	"	PUNCT
hjic-96	82	34	observed	observe	VERB
hjic-96	82	35	inputs	input	NOUN
hjic-96	82	36	and	and	CCONJ
hjic-96	82	37	outputs	output	NOUN
hjic-96	82	38	from	from	ADP
hjic-96	82	39	the	the	DET
hjic-96	82	40	system	system	NOUN
hjic-96	82	41	.	.	PUNCT
hjic-96	83	1	this	this	DET
hjic-96	83	2	paper	paper	NOUN
hjic-96	83	3	concentrates	concentrate	VERB
hjic-96	83	4	on	on	ADP
hjic-96	83	5	structure	structure	NOUN
hjic-96	83	6	selection	selection	NOUN
hjic-96	83	7	task	task	NOUN
hjic-96	83	8	in	in	ADP
hjic-96	83	9	case	case	NOUN
hjic-96	83	10	of	of	ADP
hjic-96	83	11	the	the	DET
hjic-96	83	12	black	black	ADJ
hjic-96	83	13	-	-	PUNCT
hjic-96	83	14	box	box	NOUN
hjic-96	83	15	modeling	modeling	NOUN
hjic-96	83	16	.	.	PUNCT
hjic-96	84	1	59	59	NUM
hjic-96	84	2	in	in	ADP
hjic-96	84	3	a	a	DET
hjic-96	84	4	system	system	NOUN
hjic-96	84	5	identification	identification	NOUN
hjic-96	84	6	problem	problem	NOUN
hjic-96	84	7	in	in	ADP
hjic-96	84	8	case	case	NOUN
hjic-96	84	9	of	of	ADP
hjic-96	84	10	black	black	NOUN
hjic-96	84	11	-	-	PUNCT
hjic-96	84	12	box	box	NOUN
hjic-96	84	13	modeling	modeling	NOUN
hjic-96	84	14	[	[	X
hjic-96	84	15	31	31	NUM
hjic-96	84	16	]	]	PUNCT
hjic-96	84	17	we	we	PRON
hjic-96	84	18	have	have	VERB
hjic-96	84	19	only	only	ADV
hjic-96	84	20	input	input	NOUN
hjic-96	84	21	,	,	PUNCT
hjic-96	84	22	and	and	CCONJ
hjic-96	84	23	output	output	NOUN
hjic-96	84	24	,	,	PUNCT
hjic-96	84	25	data	datum	NOUN
hjic-96	84	26	from	from	ADP
hjic-96	84	27	the	the	DET
hjic-96	84	28	process	process	NOUN
hjic-96	84	29	(	(	PUNCT
hjic-96	84	30	system	system	NOUN
hjic-96	84	31	)	)	PUNCT
hjic-96	84	32	,	,	PUNCT
hjic-96	84	33	ku	ku	PROPN
hjic-96	84	34	ky	ky	PROPN
hjic-96	84	35	(	(	PUNCT
hjic-96	84	36	1	1	NUM
hjic-96	84	37	)	)	PUNCT
hjic-96	84	38	[	[	PUNCT
hjic-96	84	39	kk	kk	X
hjic-96	84	40	uuu	uuu	PROPN
hjic-96	84	41	,	,	PUNCT
hjic-96	84	42	,	,	PUNCT
hjic-96	84	43	21	21	NUM
hjic-96	84	44	k	k	X
hjic-96	84	45	=	=	NOUN
hjic-96	84	46	u	u	X
hjic-96	84	47	]	]	X
hjic-96	84	48	(	(	PUNCT
hjic-96	84	49	2	2	NUM
hjic-96	84	50	)	)	PUNCT
hjic-96	84	51	[	[	PUNCT
hjic-96	84	52	]	]	X
hjic-96	84	53	kk	kk	X
hjic-96	84	54	yyy	yyy	PROPN
hjic-96	84	55	,	,	PUNCT
hjic-96	84	56	,	,	PUNCT
hjic-96	84	57	21	21	NUM
hjic-96	84	58	k	k	X
hjic-96	84	59	=	=	X
hjic-96	84	60	y	y	X
hjic-96	84	61	we	we	PRON
hjic-96	84	62	are	be	AUX
hjic-96	84	63	looking	look	VERB
hjic-96	84	64	for	for	ADP
hjic-96	84	65	a	a	DET
hjic-96	84	66	relationship	relationship	NOUN
hjic-96	84	67	between	between	ADP
hjic-96	84	68	past	past	ADJ
hjic-96	84	69	observations	observation	NOUN
hjic-96	84	70	and	and	CCONJ
hjic-96	84	71	future	future	ADJ
hjic-96	84	72	outputs	output	NOUN
hjic-96	84	73	,	,	PUNCT
hjic-96	84	74	]	]	PUNCT
hjic-96	84	75	,	,	PUNCT
hjic-96	84	76	[	[	PUNCT
hjic-96	84	77	11	11	NUM
hjic-96	84	78	−−	−−	PROPN
hjic-96	84	79	kk	kk	PROPN
hjic-96	84	80	yu	yu	PROPN
hjic-96	84	81	,	,	PUNCT
hjic-96	84	82	(	(	PUNCT
hjic-96	84	83	3	3	X
hjic-96	84	84	)	)	PUNCT
hjic-96	84	85	kkkk	kkkk	PROPN
hjic-96	84	86	efy	efy	ADJ
hjic-96	84	87	+	+	NOUN
hjic-96	84	88	=	=	NOUN
hjic-96	84	89	−−	−−	NOUN
hjic-96	84	90	)	)	PUNCT
hjic-96	84	91	,	,	PUNCT
hjic-96	84	92	(	(	PUNCT
hjic-96	84	93	11	11	NUM
hjic-96	84	94	yu	yu	NOUN
hjic-96	84	95	where	where	SCONJ
hjic-96	84	96	represents	represent	VERB
hjic-96	84	97	an	an	DET
hjic-96	84	98	error	error	NOUN
hjic-96	84	99	value	value	NOUN
hjic-96	84	100	,	,	PUNCT
hjic-96	84	101	because	because	SCONJ
hjic-96	84	102	will	will	AUX
hjic-96	84	103	not	not	PART
hjic-96	84	104	be	be	AUX
hjic-96	84	105	an	an	DET
hjic-96	84	106	exact	exact	ADJ
hjic-96	84	107	function	function	NOUN
hjic-96	84	108	of	of	ADP
hjic-96	84	109	past	past	ADJ
hjic-96	84	110	data	datum	NOUN
hjic-96	84	111	.	.	PUNCT
hjic-96	85	1	however	however	ADV
hjic-96	85	2	,	,	PUNCT
hjic-96	85	3	a	a	DET
hjic-96	85	4	goal	goal	NOUN
hjic-96	85	5	must	must	AUX
hjic-96	85	6	be	be	AUX
hjic-96	85	7	that	that	PRON
hjic-96	85	8	is	be	AUX
hjic-96	85	9	small	small	ADJ
hjic-96	85	10	,	,	PUNCT
hjic-96	85	11	so	so	SCONJ
hjic-96	85	12	that	that	SCONJ
hjic-96	85	13	we	we	PRON
hjic-96	85	14	may	may	AUX
hjic-96	85	15	think	think	VERB
hjic-96	85	16	of	of	ADP
hjic-96	85	17	function	function	NOUN
hjic-96	85	18	as	as	ADP
hjic-96	85	19	a	a	DET
hjic-96	85	20	good	good	ADJ
hjic-96	85	21	prediction	prediction	NOUN
hjic-96	85	22	of	of	ADP
hjic-96	85	23	.	.	PUNCT
hjic-96	86	1	ke	ke	PROPN
hjic-96	86	2	ky	ky	PROPN
hjic-96	86	3	ke	ke	PROPN
hjic-96	86	4	(	(	PUNCT
hjic-96	86	5	.)f	.)f	PROPN
hjic-96	86	6	ky	ky	PROPN
hjic-96	86	7	eq	eq	PROPN
hjic-96	86	8	.	.	PROPN
hjic-96	86	9	3	3	NUM
hjic-96	86	10	models	model	NOUN
hjic-96	86	11	general	general	ADJ
hjic-96	86	12	discrete	discrete	ADJ
hjic-96	86	13	time	time	NOUN
hjic-96	86	14	dynamic	dynamic	ADJ
hjic-96	86	15	systems	system	NOUN
hjic-96	86	16	,	,	PUNCT
hjic-96	86	17	but	but	CCONJ
hjic-96	86	18	nonlinear	nonlinear	ADJ
hjic-96	86	19	static	static	ADJ
hjic-96	86	20	processes	process	NOUN
hjic-96	86	21	can	can	AUX
hjic-96	86	22	be	be	AUX
hjic-96	86	23	also	also	ADV
hjic-96	86	24	represented	represent	VERB
hjic-96	86	25	by	by	ADP
hjic-96	86	26	the	the	DET
hjic-96	86	27	following	follow	VERB
hjic-96	86	28	regression	regression	NOUN
hjic-96	86	29	model	model	NOUN
hjic-96	86	30	:	:	PUNCT
hjic-96	86	31	(	(	PUNCT
hjic-96	86	32	4	4	NUM
hjic-96	86	33	)	)	PUNCT
hjic-96	86	34	)	)	PUNCT
hjic-96	87	1	(	(	PUNCT
hjic-96	87	2	kk	kk	PROPN
hjic-96	87	3	fy	fy	PROPN
hjic-96	87	4	x=	x=	PROPN
hjic-96	88	1	the	the	PRON
hjic-96	88	2	is	be	AUX
hjic-96	88	3	a	a	DET
hjic-96	88	4	non	non	ADJ
hjic-96	88	5	-	-	ADJ
hjic-96	88	6	linear	linear	ADJ
hjic-96	88	7	function	function	NOUN
hjic-96	88	8	,	,	PUNCT
hjic-96	88	9	represents	represent	VERB
hjic-96	88	10	its	its	PRON
hjic-96	88	11	input	input	NOUN
hjic-96	88	12	vector	vector	NOUN
hjic-96	88	13	and	and	CCONJ
hjic-96	88	14	denotes	denote	NOUN
hjic-96	88	15	the	the	DET
hjic-96	88	16	k	k	PROPN
hjic-96	88	17	-	-	PUNCT
hjic-96	88	18	th	th	VERB
hjic-96	88	19	input	input	NOUN
hjic-96	88	20	-	-	PUNCT
hjic-96	88	21	output	output	NOUN
hjic-96	88	22	data	datum	NOUN
hjic-96	88	23	.	.	PUNCT
hjic-96	89	1	the	the	DET
hjic-96	89	2	model	model	NOUN
hjic-96	89	3	regression	regression	NOUN
hjic-96	89	4	vector	vector	NOUN
hjic-96	89	5	in	in	ADP
hjic-96	89	6	a	a	DET
hjic-96	89	7	narx	narx	NOUN
hjic-96	89	8	(	(	PUNCT
hjic-96	89	9	non	non	ADJ
hjic-96	89	10	-	-	ADJ
hjic-96	89	11	linear	linear	ADJ
hjic-96	89	12	auto	auto	NOUN
hjic-96	89	13	-	-	PUNCT
hjic-96	89	14	regressive	regressive	ADJ
hjic-96	89	15	models	model	NOUN
hjic-96	89	16	with	with	ADP
hjic-96	89	17	exegoneus	exegoneus	NOUN
hjic-96	89	18	inputs	input	NOUN
hjic-96	89	19	)	)	PUNCT
hjic-96	89	20	model	model	NOUN
hjic-96	89	21	contains	contain	VERB
hjic-96	89	22	the	the	DET
hjic-96	89	23	past	past	ADJ
hjic-96	89	24	values	value	NOUN
hjic-96	89	25	of	of	ADP
hjic-96	89	26	the	the	DET
hjic-96	89	27	process	process	NOUN
hjic-96	89	28	outputs	output	NOUN
hjic-96	89	29	and	and	CCONJ
hjic-96	89	30	the	the	DET
hjic-96	89	31	process	process	NOUN
hjic-96	89	32	inputs	input	VERB
hjic-96	89	33	as	as	ADP
hjic-96	89	34	regressors	regressor	NOUN
hjic-96	89	35	:	:	PUNCT
hjic-96	89	36	(	(	PUNCT
hjic-96	89	37	.)f	.)f	X
hjic-96	89	38	kx	kx	PROPN
hjic-96	89	39	nk	nk	PROPN
hjic-96	89	40	,	,	PUNCT
hjic-96	89	41	,	,	PUNCT
hjic-96	89	42	1k=	1k=	NUM
hjic-96	89	43	kx	kx	PROPN
hjic-96	89	44	ky	ky	PROPN
hjic-96	89	45	ku	ku	PROPN
hjic-96	89	46	t	t	PROPN
hjic-96	89	47	nkkkmkkkk	nkkkmkkkk	ADV
hjic-96	89	48	uuuyyy	uuuyyy	PROPN
hjic-96	89	49	]	]	X
hjic-96	89	50	,	,	PUNCT
hjic-96	89	51	,	,	PUNCT
hjic-96	89	52	,	,	PUNCT
hjic-96	89	53	,	,	PUNCT
hjic-96	89	54	[	[	PUNCT
hjic-96	89	55	,	,	PUNCT
hjic-96	89	56	2,12,1	2,12,1	NUM
hjic-96	89	57	−−−−−−=	−−−−−−=	PROPN
hjic-96	89	58	kkx	kkx	PROPN
hjic-96	89	59	(	(	PUNCT
hjic-96	89	60	5	5	NUM
hjic-96	89	61	)	)	PUNCT
hjic-96	89	62	the	the	DET
hjic-96	89	63	m	m	NOUN
hjic-96	89	64	determines	determine	VERB
hjic-96	89	65	the	the	DET
hjic-96	89	66	number	number	NOUN
hjic-96	89	67	of	of	ADP
hjic-96	89	68	past	past	ADJ
hjic-96	89	69	outputs	output	NOUN
hjic-96	89	70	and	and	CCONJ
hjic-96	89	71	n	n	PRON
hjic-96	89	72	represents	represent	VERB
hjic-96	89	73	the	the	DET
hjic-96	89	74	past	past	ADJ
hjic-96	89	75	inputs	input	NOUN
hjic-96	89	76	(	(	PUNCT
hjic-96	89	77	model	model	NOUN
hjic-96	89	78	order	order	NOUN
hjic-96	89	79	)	)	PUNCT
hjic-96	89	80	.	.	PUNCT
hjic-96	90	1	while	while	SCONJ
hjic-96	90	2	the	the	DET
hjic-96	90	3	output	output	NOUN
hjic-96	90	4	of	of	ADP
hjic-96	90	5	the	the	DET
hjic-96	90	6	regression	regression	NOUN
hjic-96	90	7	model	model	NOUN
hjic-96	90	8	,	,	PUNCT
hjic-96	90	9	is	be	AUX
hjic-96	90	10	the	the	DET
hjic-96	90	11	one	one	NUM
hjic-96	90	12	-	-	PUNCT
hjic-96	90	13	step	step	NOUN
hjic-96	90	14	-	-	PUNCT
hjic-96	90	15	ahead	ahead	NOUN
hjic-96	90	16	prediction	prediction	NOUN
hjic-96	90	17	of	of	ADP
hjic-96	90	18	the	the	DET
hjic-96	90	19	process	process	NOUN
hjic-96	90	20	.	.	PUNCT
hjic-96	91	1	this	this	DET
hjic-96	91	2	siso	siso	NOUN
hjic-96	91	3	form	form	NOUN
hjic-96	91	4	of	of	ADP
hjic-96	91	5	the	the	DET
hjic-96	91	6	narx	narx	NOUN
hjic-96	91	7	models	model	NOUN
hjic-96	91	8	could	could	AUX
hjic-96	91	9	be	be	AUX
hjic-96	91	10	extended	extend	VERB
hjic-96	91	11	to	to	ADP
hjic-96	91	12	the	the	DET
hjic-96	91	13	mimo	mimo	PROPN
hjic-96	91	14	case	case	NOUN
hjic-96	91	15	.	.	PUNCT
hjic-96	92	1	ky	ky	PROPN
hjic-96	92	2	association	association	PROPN
hjic-96	92	3	rule	rule	NOUN
hjic-96	92	4	mining	mine	VERB
hjic-96	92	5	one	one	NUM
hjic-96	92	6	of	of	ADP
hjic-96	92	7	the	the	DET
hjic-96	92	8	widely	widely	ADV
hjic-96	92	9	used	use	VERB
hjic-96	92	10	research	research	NOUN
hjic-96	92	11	tasks	task	NOUN
hjic-96	92	12	in	in	ADP
hjic-96	92	13	data	datum	NOUN
hjic-96	92	14	mining	mining	NOUN
hjic-96	92	15	is	be	AUX
hjic-96	92	16	the	the	DET
hjic-96	92	17	discovery	discovery	NOUN
hjic-96	92	18	of	of	ADP
hjic-96	92	19	frequent	frequent	ADJ
hjic-96	92	20	item	item	NOUN
hjic-96	92	21	sets	set	NOUN
hjic-96	92	22	and	and	CCONJ
hjic-96	92	23	association	association	NOUN
hjic-96	92	24	rules	rule	NOUN
hjic-96	92	25	.	.	PUNCT
hjic-96	93	1	the	the	DET
hjic-96	93	2	problem	problem	NOUN
hjic-96	93	3	originates	originate	VERB
hjic-96	93	4	in	in	ADP
hjic-96	93	5	market	market	NOUN
hjic-96	93	6	basket	basket	NOUN
hjic-96	93	7	analysis	analysis	NOUN
hjic-96	93	8	which	which	PRON
hjic-96	93	9	aims	aim	VERB
hjic-96	93	10	at	at	ADP
hjic-96	93	11	understanding	understand	VERB
hjic-96	93	12	the	the	DET
hjic-96	93	13	behavior	behavior	NOUN
hjic-96	93	14	of	of	ADP
hjic-96	93	15	retail	retail	ADJ
hjic-96	93	16	customers	customer	NOUN
hjic-96	93	17	,	,	PUNCT
hjic-96	93	18	or	or	CCONJ
hjic-96	93	19	in	in	ADP
hjic-96	93	20	other	other	ADJ
hjic-96	93	21	words	word	NOUN
hjic-96	93	22	,	,	PUNCT
hjic-96	93	23	finding	find	VERB
hjic-96	93	24	associations	association	NOUN
hjic-96	93	25	among	among	ADP
hjic-96	93	26	the	the	DET
hjic-96	93	27	items	item	NOUN
hjic-96	93	28	purchased	purchase	VERB
hjic-96	93	29	together	together	ADV
hjic-96	93	30	.	.	PUNCT
hjic-96	94	1	a	a	DET
hjic-96	94	2	famous	famous	ADJ
hjic-96	94	3	example	example	NOUN
hjic-96	94	4	of	of	ADP
hjic-96	94	5	an	an	DET
hjic-96	94	6	association	association	NOUN
hjic-96	94	7	rule	rule	NOUN
hjic-96	94	8	in	in	ADP
hjic-96	94	9	such	such	DET
hjic-96	94	10	a	a	DET
hjic-96	94	11	database	database	NOUN
hjic-96	94	12	is	be	AUX
hjic-96	94	13	“	"	PUNCT
hjic-96	94	14	diapers	diaper	NOUN
hjic-96	94	15	=	=	NOUN
hjic-96	94	16	>	>	X
hjic-96	94	17	beer	beer	NOUN
hjic-96	94	18	”	"	PUNCT
hjic-96	94	19	,	,	PUNCT
hjic-96	94	20	i.e.	i.e.	X
hjic-96	94	21	young	young	ADJ
hjic-96	94	22	fathers	father	NOUN
hjic-96	94	23	being	be	AUX
hjic-96	94	24	sent	send	VERB
hjic-96	94	25	off	off	ADP
hjic-96	94	26	to	to	ADP
hjic-96	94	27	the	the	DET
hjic-96	94	28	store	store	NOUN
hjic-96	94	29	to	to	PART
hjic-96	94	30	buy	buy	VERB
hjic-96	94	31	diapers	diaper	NOUN
hjic-96	94	32	,	,	PUNCT
hjic-96	94	33	reward	reward	VERB
hjic-96	94	34	themselves	themselves	PRON
hjic-96	94	35	for	for	ADP
hjic-96	94	36	their	their	PRON
hjic-96	94	37	trouble	trouble	NOUN
hjic-96	94	38	.	.	PUNCT
hjic-96	95	1	because	because	SCONJ
hjic-96	95	2	of	of	ADP
hjic-96	95	3	the	the	DET
hjic-96	95	4	practical	practical	ADJ
hjic-96	95	5	usefulness	usefulness	NOUN
hjic-96	95	6	of	of	ADP
hjic-96	95	7	association	association	NOUN
hjic-96	95	8	rule	rule	NOUN
hjic-96	95	9	discovery	discovery	NOUN
hjic-96	95	10	,	,	PUNCT
hjic-96	95	11	this	this	DET
hjic-96	95	12	approach	approach	NOUN
hjic-96	95	13	can	can	AUX
hjic-96	95	14	be	be	AUX
hjic-96	95	15	applied	apply	VERB
hjic-96	95	16	in	in	ADP
hjic-96	95	17	various	various	ADJ
hjic-96	95	18	research	research	NOUN
hjic-96	95	19	areas	area	NOUN
hjic-96	95	20	.	.	PUNCT
hjic-96	96	1	how	how	SCONJ
hjic-96	96	2	can	can	AUX
hjic-96	96	3	we	we	PRON
hjic-96	96	4	search	search	VERB
hjic-96	96	5	association	association	NOUN
hjic-96	96	6	rules	rule	NOUN
hjic-96	96	7	?	?	PUNCT
hjic-96	97	1	the	the	DET
hjic-96	97	2	association	association	NOUN
hjic-96	97	3	rule	rule	NOUN
hjic-96	97	4	mining	mining	NOUN
hjic-96	97	5	is	be	AUX
hjic-96	97	6	based	base	VERB
hjic-96	97	7	on	on	ADP
hjic-96	97	8	frequent	frequent	ADJ
hjic-96	97	9	item	item	NOUN
hjic-96	97	10	set	set	VERB
hjic-96	97	11	searching	search	VERB
hjic-96	97	12	.	.	PUNCT
hjic-96	98	1	an	an	DET
hjic-96	98	2	item	item	NOUN
hjic-96	98	3	could	could	AUX
hjic-96	98	4	be	be	AUX
hjic-96	98	5	for	for	ADP
hjic-96	98	6	example	example	NOUN
hjic-96	98	7	one	one	NUM
hjic-96	98	8	product	product	NOUN
hjic-96	98	9	in	in	ADP
hjic-96	98	10	the	the	DET
hjic-96	98	11	supermarket	supermarket	NOUN
hjic-96	98	12	example	example	NOUN
hjic-96	98	13	,	,	PUNCT
hjic-96	98	14	e.g.	e.g.	ADV
hjic-96	98	15	{	{	PUNCT
hjic-96	98	16	beer	beer	NOUN
hjic-96	98	17	}	}	PUNCT
hjic-96	98	18	,	,	PUNCT
hjic-96	98	19	and	and	CCONJ
hjic-96	98	20	an	an	DET
hjic-96	98	21	item	item	NOUN
hjic-96	98	22	set	set	VERB
hjic-96	98	23	is	be	AUX
hjic-96	98	24	a	a	DET
hjic-96	98	25	set	set	NOUN
hjic-96	98	26	of	of	ADP
hjic-96	98	27	items	item	NOUN
hjic-96	98	28	(	(	PUNCT
hjic-96	98	29	products	product	NOUN
hjic-96	98	30	)	)	PUNCT
hjic-96	98	31	,	,	PUNCT
hjic-96	98	32	e.g.	e.g.	ADV
hjic-96	98	33	{	{	PUNCT
hjic-96	98	34	milk	milk	NOUN
hjic-96	98	35	,	,	PUNCT
hjic-96	98	36	beer	beer	NOUN
hjic-96	98	37	,	,	PUNCT
hjic-96	98	38	diapers	diaper	NOUN
hjic-96	98	39	}	}	PUNCT
hjic-96	98	40	.	.	PUNCT
hjic-96	99	1	the	the	DET
hjic-96	99	2	occurrences	occurrence	NOUN
hjic-96	99	3	of	of	ADP
hjic-96	99	4	an	an	DET
hjic-96	99	5	item	item	NOUN
hjic-96	99	6	(	(	PUNCT
hjic-96	99	7	item	item	NOUN
hjic-96	99	8	sets	set	NOUN
hjic-96	99	9	)	)	PUNCT
hjic-96	99	10	in	in	ADP
hjic-96	99	11	a	a	DET
hjic-96	99	12	data	data	NOUN
hjic-96	99	13	set	set	VERB
hjic-96	99	14	are	be	AUX
hjic-96	99	15	called	call	VERB
hjic-96	99	16	support	support	NOUN
hjic-96	99	17	.	.	PUNCT
hjic-96	100	1	the	the	DET
hjic-96	100	2	support	support	NOUN
hjic-96	100	3	value	value	NOUN
hjic-96	100	4	of	of	ADP
hjic-96	100	5	an	an	DET
hjic-96	100	6	item	item	NOUN
hjic-96	100	7	(	(	PUNCT
hjic-96	100	8	item	item	NOUN
hjic-96	100	9	set	set	NOUN
hjic-96	100	10	)	)	PUNCT
hjic-96	100	11	could	could	AUX
hjic-96	100	12	be	be	AUX
hjic-96	100	13	seen	see	VERB
hjic-96	100	14	as	as	ADP
hjic-96	100	15	a	a	DET
hjic-96	100	16	probability	probability	NOUN
hjic-96	100	17	value	value	NOUN
hjic-96	100	18	.	.	PUNCT
hjic-96	101	1	the	the	DET
hjic-96	101	2	support	support	NOUN
hjic-96	101	3	gives	give	VERB
hjic-96	101	4	in	in	ADP
hjic-96	101	5	how	how	SCONJ
hjic-96	101	6	many	many	ADJ
hjic-96	101	7	percent	percent	NOUN
hjic-96	101	8	of	of	ADP
hjic-96	101	9	the	the	DET
hjic-96	101	10	transactions	transaction	NOUN
hjic-96	101	11	is	be	AUX
hjic-96	101	12	the	the	DET
hjic-96	101	13	item	item	NOUN
hjic-96	101	14	(	(	PUNCT
hjic-96	101	15	are	be	AUX
hjic-96	101	16	the	the	DET
hjic-96	101	17	items	item	NOUN
hjic-96	101	18	of	of	ADP
hjic-96	101	19	an	an	DET
hjic-96	101	20	item	item	NOUN
hjic-96	101	21	set	set	VERB
hjic-96	101	22	together	together	ADV
hjic-96	101	23	)	)	PUNCT
hjic-96	101	24	?	?	PUNCT
hjic-96	102	1	be	be	AUX
hjic-96	102	2	the	the	DET
hjic-96	102	3	x	x	SYM
hjic-96	102	4	an	an	DET
hjic-96	102	5	item	item	NOUN
hjic-96	102	6	set	set	NOUN
hjic-96	102	7	,	,	PUNCT
hjic-96	102	8	the	the	DET
hjic-96	102	9	support	support	NOUN
hjic-96	102	10	value	value	NOUN
hjic-96	102	11	of	of	ADP
hjic-96	102	12	x	x	PUNCT
hjic-96	102	13	is	be	AUX
hjic-96	102	14	calculated	calculate	VERB
hjic-96	102	15	as	as	SCONJ
hjic-96	102	16	follows	follow	VERB
hjic-96	102	17	:	:	PUNCT
hjic-96	102	18	nstransactio	nstransactio	NOUN
hjic-96	102	19	of	of	ADP
hjic-96	102	20	with	with	ADP
hjic-96	102	21	nstransactio	nstransactio	NOUN
hjic-96	102	22	of	of	ADP
hjic-96	102	23	#	#	NOUN
hjic-96	102	24	#	#	NOUN
hjic-96	102	25	)	)	PUNCT
hjic-96	102	26	(	(	PUNCT
hjic-96	102	27	)	)	PUNCT
hjic-96	102	28	supp	supp	PROPN
hjic-96	102	29	(	(	PUNCT
hjic-96	102	30	xxpx	xxpx	PROPN
hjic-96	102	31	=	=	SYM
hjic-96	102	32	=	=	SYM
hjic-96	102	33	(	(	PUNCT
hjic-96	102	34	6	6	NUM
hjic-96	102	35	)	)	PUNCT
hjic-96	102	36	an	an	DET
hjic-96	102	37	item	item	NOUN
hjic-96	102	38	x	x	X
hjic-96	102	39	(	(	PUNCT
hjic-96	102	40	or	or	CCONJ
hjic-96	102	41	the	the	DET
hjic-96	102	42	item	item	NOUN
hjic-96	102	43	set	set	VERB
hjic-96	102	44	x	x	X
hjic-96	102	45	)	)	PUNCT
hjic-96	102	46	is	be	AUX
hjic-96	102	47	called	call	VERB
hjic-96	102	48	frequent	frequent	ADJ
hjic-96	102	49	item	item	NOUN
hjic-96	102	50	(	(	PUNCT
hjic-96	102	51	item	item	NOUN
hjic-96	102	52	set	set	NOUN
hjic-96	102	53	)	)	PUNCT
hjic-96	102	54	if	if	SCONJ
hjic-96	102	55	its	its	PRON
hjic-96	102	56	support	support	NOUN
hjic-96	102	57	is	be	AUX
hjic-96	102	58	higher	high	ADJ
hjic-96	102	59	than	than	ADP
hjic-96	102	60	a	a	DET
hjic-96	102	61	given	give	VERB
hjic-96	102	62	(	(	PUNCT
hjic-96	102	63	user	user	NOUN
hjic-96	102	64	defined	define	VERB
hjic-96	102	65	)	)	PUNCT
hjic-96	102	66	threshold	threshold	NOUN
hjic-96	102	67	,	,	PUNCT
hjic-96	102	68	namely	namely	ADV
hjic-96	102	69	the	the	DET
hjic-96	102	70	minimal	minimal	ADJ
hjic-96	102	71	support	support	NOUN
hjic-96	102	72	(	(	PUNCT
hjic-96	102	73	σ	σ	NOUN
hjic-96	102	74	)	)	PUNCT
hjic-96	102	75	.	.	PUNCT
hjic-96	103	1	see	see	VERB
hjic-96	103	2	table	table	NOUN
hjic-96	103	3	1	1	NUM
hjic-96	103	4	which	which	PRON
hjic-96	103	5	includes	include	VERB
hjic-96	103	6	an	an	DET
hjic-96	103	7	example	example	NOUN
hjic-96	103	8	supermarket	supermarket	NOUN
hjic-96	103	9	transaction	transaction	NOUN
hjic-96	103	10	data	datum	NOUN
hjic-96	103	11	set	set	VERB
hjic-96	103	12	,	,	PUNCT
hjic-96	103	13	where	where	SCONJ
hjic-96	103	14	each	each	DET
hjic-96	103	15	row	row	NOUN
hjic-96	103	16	represents	represent	VERB
hjic-96	103	17	a	a	DET
hjic-96	103	18	transaction	transaction	NOUN
hjic-96	103	19	.	.	PUNCT
hjic-96	104	1	the	the	DET
hjic-96	104	2	first	first	ADJ
hjic-96	104	3	column	column	NOUN
hjic-96	104	4	contains	contain	VERB
hjic-96	104	5	the	the	DET
hjic-96	104	6	transaction	transaction	NOUN
hjic-96	104	7	number	number	NOUN
hjic-96	104	8	(	(	PUNCT
hjic-96	104	9	tid	tid	NOUN
hjic-96	104	10	transaction	transaction	NOUN
hjic-96	104	11	identifier	identifier	NOUN
hjic-96	104	12	)	)	PUNCT
hjic-96	104	13	and	and	CCONJ
hjic-96	104	14	in	in	ADP
hjic-96	104	15	the	the	DET
hjic-96	104	16	second	second	ADJ
hjic-96	104	17	column	column	NOUN
hjic-96	104	18	the	the	DET
hjic-96	104	19	purchased	purchase	VERB
hjic-96	104	20	products	product	NOUN
hjic-96	104	21	are	be	AUX
hjic-96	104	22	listed	list	VERB
hjic-96	104	23	in	in	ADP
hjic-96	104	24	the	the	DET
hjic-96	104	25	transaction	transaction	NOUN
hjic-96	104	26	.	.	PUNCT
hjic-96	105	1	table	table	NOUN
hjic-96	105	2	1	1	NUM
hjic-96	105	3	example	example	NOUN
hjic-96	105	4	transaction	transaction	NOUN
hjic-96	105	5	data	datum	NOUN
hjic-96	105	6	set	set	VERB
hjic-96	105	7	tid	tid	NOUN
hjic-96	105	8	items	item	NOUN
hjic-96	105	9	1	1	NUM
hjic-96	105	10	bread	bread	NOUN
hjic-96	105	11	,	,	PUNCT
hjic-96	105	12	milk	milk	NOUN
hjic-96	105	13	2	2	NUM
hjic-96	105	14	beer	beer	NOUN
hjic-96	105	15	,	,	PUNCT
hjic-96	105	16	bread	bread	NOUN
hjic-96	105	17	,	,	PUNCT
hjic-96	105	18	diaper	diaper	NOUN
hjic-96	105	19	,	,	PUNCT
hjic-96	105	20	eggs	egg	NOUN
hjic-96	105	21	3	3	NUM
hjic-96	105	22	beer	beer	NOUN
hjic-96	105	23	,	,	PUNCT
hjic-96	105	24	coke	coke	PROPN
hjic-96	105	25	,	,	PUNCT
hjic-96	105	26	diaper	diaper	NOUN
hjic-96	105	27	,	,	PUNCT
hjic-96	105	28	milk	milk	NOUN
hjic-96	105	29	4	4	NUM
hjic-96	105	30	beer	beer	NOUN
hjic-96	105	31	,	,	PUNCT
hjic-96	105	32	bread	bread	NOUN
hjic-96	105	33	,	,	PUNCT
hjic-96	105	34	diaper	diaper	NOUN
hjic-96	105	35	,	,	PUNCT
hjic-96	105	36	milk	milk	VERB
hjic-96	105	37	the	the	DET
hjic-96	105	38	frequent	frequent	ADJ
hjic-96	105	39	item	item	NOUN
hjic-96	105	40	set	set	VERB
hjic-96	105	41	searching	search	VERB
hjic-96	105	42	is	be	AUX
hjic-96	105	43	a	a	DET
hjic-96	105	44	very	very	ADV
hjic-96	105	45	easy	easy	ADJ
hjic-96	105	46	task	task	NOUN
hjic-96	105	47	for	for	SCONJ
hjic-96	105	48	this	this	DET
hjic-96	105	49	example	example	NOUN
hjic-96	105	50	data	datum	NOUN
hjic-96	105	51	set	set	VERB
hjic-96	105	52	,	,	PUNCT
hjic-96	105	53	because	because	SCONJ
hjic-96	105	54	the	the	DET
hjic-96	105	55	number	number	NOUN
hjic-96	105	56	of	of	ADP
hjic-96	105	57	transactions	transaction	NOUN
hjic-96	105	58	is	be	AUX
hjic-96	105	59	only	only	ADV
hjic-96	105	60	four	four	NUM
hjic-96	105	61	.	.	PUNCT
hjic-96	106	1	if	if	SCONJ
hjic-96	106	2	the	the	DET
hjic-96	106	3	minimum	minimum	ADJ
hjic-96	106	4	support	support	NOUN
hjic-96	106	5	is	be	AUX
hjic-96	106	6	equal	equal	ADJ
hjic-96	106	7	to	to	ADP
hjic-96	106	8	50	50	NUM
hjic-96	106	9	percent	percent	NOUN
hjic-96	106	10	(	(	PUNCT
hjic-96	106	11	σ	σ	NOUN
hjic-96	106	12	=	=	SYM
hjic-96	106	13	two	two	NUM
hjic-96	106	14	occurrences	occurrence	NOUN
hjic-96	106	15	)	)	PUNCT
hjic-96	106	16	,	,	PUNCT
hjic-96	106	17	we	we	PRON
hjic-96	106	18	can	can	AUX
hjic-96	106	19	search	search	VERB
hjic-96	106	20	all	all	DET
hjic-96	106	21	the	the	DET
hjic-96	106	22	frequent	frequent	ADJ
hjic-96	106	23	items	item	NOUN
hjic-96	106	24	and	and	CCONJ
hjic-96	106	25	item	item	NOUN
hjic-96	106	26	sets	set	NOUN
hjic-96	106	27	,	,	PUNCT
hjic-96	106	28	e.g.	e.g.	ADV
hjic-96	106	29	a	a	DET
hjic-96	106	30	frequent	frequent	ADJ
hjic-96	106	31	item	item	NOUN
hjic-96	106	32	is	be	AUX
hjic-96	106	33	the	the	DET
hjic-96	106	34	{	{	PUNCT
hjic-96	106	35	milk	milk	NOUN
hjic-96	106	36	}	}	PUNCT
hjic-96	106	37	(	(	PUNCT
hjic-96	106	38	with	with	ADP
hjic-96	106	39	75	75	NUM
hjic-96	106	40	%	%	NOUN
hjic-96	106	41	support	support	NOUN
hjic-96	106	42	)	)	PUNCT
hjic-96	106	43	,	,	PUNCT
hjic-96	106	44	or	or	CCONJ
hjic-96	106	45	a	a	DET
hjic-96	106	46	frequent	frequent	ADJ
hjic-96	106	47	item	item	NOUN
hjic-96	106	48	set	set	VERB
hjic-96	106	49	is	be	AUX
hjic-96	106	50	the	the	DET
hjic-96	106	51	{	{	PUNCT
hjic-96	106	52	diaper	diaper	NOUN
hjic-96	106	53	,	,	PUNCT
hjic-96	106	54	beer	beer	NOUN
hjic-96	106	55	}	}	PUNCT
hjic-96	106	56	(	(	PUNCT
hjic-96	106	57	with	with	ADP
hjic-96	106	58	75	75	NUM
hjic-96	106	59	%	%	NOUN
hjic-96	106	60	support	support	NOUN
hjic-96	106	61	)	)	PUNCT
hjic-96	106	62	.	.	PUNCT
hjic-96	107	1	but	but	CCONJ
hjic-96	107	2	if	if	SCONJ
hjic-96	107	3	we	we	PRON
hjic-96	107	4	have	have	VERB
hjic-96	107	5	a	a	DET
hjic-96	107	6	large	large	ADJ
hjic-96	107	7	data	datum	NOUN
hjic-96	107	8	set	set	NOUN
hjic-96	107	9	(	(	PUNCT
hjic-96	107	10	database	database	NOUN
hjic-96	107	11	)	)	PUNCT
hjic-96	107	12	with	with	ADP
hjic-96	107	13	many	many	ADJ
hjic-96	107	14	transactions	transaction	NOUN
hjic-96	107	15	and	and	CCONJ
hjic-96	107	16	several	several	ADJ
hjic-96	107	17	items	item	NOUN
hjic-96	107	18	the	the	DET
hjic-96	107	19	frequent	frequent	ADJ
hjic-96	107	20	item	item	NOUN
hjic-96	107	21	set	set	VERB
hjic-96	107	22	searching	search	VERB
hjic-96	107	23	demands	demand	NOUN
hjic-96	107	24	to	to	PART
hjic-96	107	25	use	use	VERB
hjic-96	107	26	an	an	DET
hjic-96	107	27	efficient	efficient	ADJ
hjic-96	107	28	algorithm	algorithm	NOUN
hjic-96	107	29	.	.	PUNCT
hjic-96	108	1	a	a	DET
hjic-96	108	2	widely	widely	ADV
hjic-96	108	3	used	use	VERB
hjic-96	108	4	frequent	frequent	ADJ
hjic-96	108	5	item	item	NOUN
hjic-96	108	6	set	set	VERB
hjic-96	108	7	searching	search	VERB
hjic-96	108	8	algorithm	algorithm	NOUN
hjic-96	108	9	is	be	AUX
hjic-96	108	10	the	the	DET
hjic-96	108	11	apriori	apriori	ADJ
hjic-96	108	12	algorithm	algorithm	NOUN
hjic-96	108	13	(	(	PUNCT
hjic-96	108	14	was	be	AUX
hjic-96	108	15	introduced	introduce	VERB
hjic-96	108	16	in	in	ADP
hjic-96	108	17	[	[	X
hjic-96	108	18	30	30	NUM
hjic-96	108	19	]	]	NUM
hjic-96	108	20	)	)	PUNCT
hjic-96	108	21	.	.	PUNCT
hjic-96	109	1	the	the	DET
hjic-96	109	2	name	name	NOUN
hjic-96	109	3	of	of	ADP
hjic-96	109	4	algorithm	algorithm	NOUN
hjic-96	109	5	is	be	AUX
hjic-96	109	6	based	base	VERB
hjic-96	109	7	on	on	ADP
hjic-96	109	8	the	the	DET
hjic-96	109	9	fact	fact	NOUN
hjic-96	109	10	that	that	SCONJ
hjic-96	109	11	the	the	DET
hjic-96	109	12	apriori	apriori	NOUN
hjic-96	109	13	uses	use	VERB
hjic-96	109	14	prior	prior	ADJ
hjic-96	109	15	knowledge	knowledge	NOUN
hjic-96	109	16	of	of	ADP
hjic-96	109	17	frequent	frequent	ADJ
hjic-96	109	18	item	item	NOUN
hjic-96	109	19	sets	set	NOUN
hjic-96	109	20	already	already	ADV
hjic-96	109	21	determined	determine	VERB
hjic-96	109	22	.	.	PUNCT
hjic-96	110	1	it	it	PRON
hjic-96	110	2	is	be	AUX
hjic-96	110	3	an	an	DET
hjic-96	110	4	iterative	iterative	NOUN
hjic-96	110	5	,	,	PUNCT
hjic-96	110	6	breadth	breadth	NOUN
hjic-96	110	7	-	-	PUNCT
hjic-96	110	8	first	first	ADJ
hjic-96	110	9	search	search	NOUN
hjic-96	110	10	algorithm	algorithm	NOUN
hjic-96	110	11	,	,	PUNCT
hjic-96	110	12	based	base	VERB
hjic-96	110	13	on	on	ADP
hjic-96	110	14	generating	generate	VERB
hjic-96	110	15	stepwise	stepwise	NOUN
hjic-96	110	16	longer	long	ADJ
hjic-96	110	17	candidate	candidate	NOUN
hjic-96	110	18	item	item	NOUN
hjic-96	110	19	sets	set	NOUN
hjic-96	110	20	,	,	PUNCT
hjic-96	110	21	and	and	CCONJ
hjic-96	110	22	clever	clever	ADJ
hjic-96	110	23	pruning	pruning	NOUN
hjic-96	110	24	of	of	ADP
hjic-96	110	25	non	non	ADJ
hjic-96	110	26	-	-	ADJ
hjic-96	110	27	frequent	frequent	ADJ
hjic-96	110	28	item	item	NOUN
hjic-96	110	29	sets	set	NOUN
hjic-96	110	30	.	.	PUNCT
hjic-96	111	1	pruning	prune	VERB
hjic-96	111	2	takes	take	VERB
hjic-96	111	3	advantage	advantage	NOUN
hjic-96	111	4	of	of	ADP
hjic-96	111	5	the	the	DET
hjic-96	111	6	so	so	ADV
hjic-96	111	7	-	-	PUNCT
hjic-96	111	8	called	call	VERB
hjic-96	111	9	apriori	apriori	X
hjic-96	111	10	(	(	PUNCT
hjic-96	111	11	or	or	CCONJ
hjic-96	111	12	upward	upward	ADJ
hjic-96	111	13	closure	closure	NOUN
hjic-96	111	14	)	)	PUNCT
hjic-96	111	15	property	property	NOUN
hjic-96	111	16	of	of	ADP
hjic-96	111	17	frequent	frequent	ADJ
hjic-96	111	18	item	item	NOUN
hjic-96	111	19	sets	set	NOUN
hjic-96	111	20	:	:	PUNCT
hjic-96	111	21	all	all	DET
hjic-96	111	22	subsets	subset	NOUN
hjic-96	111	23	of	of	ADP
hjic-96	111	24	a	a	DET
hjic-96	111	25	frequent	frequent	ADJ
hjic-96	111	26	item	item	NOUN
hjic-96	111	27	set	set	NOUN
hjic-96	111	28	must	must	AUX
hjic-96	111	29	also	also	ADV
hjic-96	111	30	be	be	AUX
hjic-96	111	31	frequent	frequent	ADJ
hjic-96	111	32	.	.	PUNCT
hjic-96	112	1	each	each	DET
hjic-96	112	2	candidate	candidate	NOUN
hjic-96	112	3	generation	generation	NOUN
hjic-96	112	4	step	step	NOUN
hjic-96	112	5	is	be	AUX
hjic-96	112	6	followed	follow	VERB
hjic-96	112	7	by	by	ADP
hjic-96	112	8	a	a	DET
hjic-96	112	9	counting	counting	NOUN
hjic-96	112	10	step	step	NOUN
hjic-96	112	11	where	where	SCONJ
hjic-96	112	12	the	the	DET
hjic-96	112	13	supports	support	NOUN
hjic-96	112	14	of	of	ADP
hjic-96	112	15	candidates	candidate	NOUN
hjic-96	112	16	are	be	AUX
hjic-96	112	17	checked	check	VERB
hjic-96	112	18	and	and	CCONJ
hjic-96	112	19	non	non	ADJ
hjic-96	112	20	-	-	ADJ
hjic-96	112	21	frequent	frequent	ADJ
hjic-96	112	22	ones	one	NOUN
hjic-96	112	23	deleted	delete	VERB
hjic-96	112	24	.	.	PUNCT
hjic-96	113	1	generation	generation	NOUN
hjic-96	113	2	and	and	CCONJ
hjic-96	113	3	counting	counting	NOUN
hjic-96	113	4	alternate	alternate	NOUN
hjic-96	113	5	,	,	PUNCT
hjic-96	113	6	until	until	SCONJ
hjic-96	113	7	at	at	ADP
hjic-96	113	8	some	some	DET
hjic-96	113	9	step	step	NOUN
hjic-96	113	10	all	all	DET
hjic-96	113	11	generated	generate	VERB
hjic-96	113	12	candidates	candidate	NOUN
hjic-96	113	13	turn	turn	VERB
hjic-96	113	14	out	out	ADP
hjic-96	113	15	to	to	PART
hjic-96	113	16	be	be	AUX
hjic-96	113	17	non	non	ADJ
hjic-96	113	18	-	-	ADJ
hjic-96	113	19	frequent	frequent	ADJ
hjic-96	113	20	.	.	PUNCT
hjic-96	114	1	if	if	SCONJ
hjic-96	114	2	we	we	PRON
hjic-96	114	3	searched	search	VERB
hjic-96	114	4	all	all	DET
hjic-96	114	5	the	the	DET
hjic-96	114	6	frequent	frequent	ADJ
hjic-96	114	7	item	item	NOUN
hjic-96	114	8	sets	set	NOUN
hjic-96	114	9	by	by	ADP
hjic-96	114	10	the	the	DET
hjic-96	114	11	apriori	apriori	ADJ
hjic-96	114	12	algorithm	algorithm	NOUN
hjic-96	114	13	,	,	PUNCT
hjic-96	114	14	we	we	PRON
hjic-96	114	15	can	can	AUX
hjic-96	114	16	generate	generate	VERB
hjic-96	114	17	association	association	NOUN
hjic-96	114	18	rules	rule	NOUN
hjic-96	114	19	from	from	ADP
hjic-96	114	20	them	they	PRON
hjic-96	114	21	.	.	PUNCT
hjic-96	115	1	an	an	DET
hjic-96	115	2	association	association	NOUN
hjic-96	115	3	rule	rule	NOUN
hjic-96	115	4	has	have	VERB
hjic-96	115	5	two	two	NUM
hjic-96	115	6	parts	part	NOUN
hjic-96	115	7	:	:	PUNCT
hjic-96	115	8	the	the	DET
hjic-96	115	9	rule	rule	NOUN
hjic-96	115	10	antecedent	antecedent	NOUN
hjic-96	115	11	60	60	NUM
hjic-96	115	12	(	(	PUNCT
hjic-96	115	13	denoted	denote	VERB
hjic-96	115	14	by	by	ADP
hjic-96	115	15	x	x	NOUN
hjic-96	115	16	)	)	PUNCT
hjic-96	115	17	and	and	CCONJ
hjic-96	115	18	the	the	DET
hjic-96	115	19	rule	rule	NOUN
hjic-96	115	20	consequent	consequent	NOUN
hjic-96	115	21	(	(	PUNCT
hjic-96	115	22	denoted	denote	VERB
hjic-96	115	23	by	by	ADP
hjic-96	115	24	y	y	PROPN
hjic-96	115	25	)	)	PUNCT
hjic-96	115	26	,	,	PUNCT
hjic-96	115	27	and	and	CCONJ
hjic-96	115	28	both	both	PRON
hjic-96	115	29	of	of	ADP
hjic-96	115	30	them	they	PRON
hjic-96	115	31	contain	contain	VERB
hjic-96	115	32	items	item	NOUN
hjic-96	115	33	.	.	PUNCT
hjic-96	116	1	therefore	therefore	ADV
hjic-96	116	2	an	an	DET
hjic-96	116	3	association	association	NOUN
hjic-96	116	4	rule	rule	NOUN
hjic-96	116	5	is	be	AUX
hjic-96	116	6	represented	represent	VERB
hjic-96	116	7	by	by	ADP
hjic-96	116	8	the	the	DET
hjic-96	116	9	form	form	NOUN
hjic-96	116	10	x	x	PUNCT
hjic-96	116	11	=	=	X
hjic-96	116	12	>	>	X
hjic-96	116	13	y.	y.	NOUN
hjic-96	116	14	from	from	ADP
hjic-96	116	15	a	a	DET
hjic-96	116	16	frequent	frequent	ADJ
hjic-96	116	17	item	item	NOUN
hjic-96	116	18	set	set	NOUN
hjic-96	116	19	we	we	PRON
hjic-96	116	20	can	can	AUX
hjic-96	116	21	generate	generate	VERB
hjic-96	116	22	all	all	DET
hjic-96	116	23	the	the	DET
hjic-96	116	24	possible	possible	ADJ
hjic-96	116	25	rules	rule	NOUN
hjic-96	116	26	.	.	PUNCT
hjic-96	117	1	each	each	DET
hjic-96	117	2	item	item	NOUN
hjic-96	117	3	and	and	CCONJ
hjic-96	117	4	sub	sub	NOUN
hjic-96	117	5	item	item	NOUN
hjic-96	117	6	set	set	NOUN
hjic-96	117	7	could	could	AUX
hjic-96	117	8	be	be	AUX
hjic-96	117	9	placed	place	VERB
hjic-96	117	10	in	in	ADP
hjic-96	117	11	both	both	DET
hjic-96	117	12	parts	part	NOUN
hjic-96	117	13	of	of	ADP
hjic-96	117	14	a	a	DET
hjic-96	117	15	rule	rule	NOUN
hjic-96	117	16	.	.	PUNCT
hjic-96	118	1	in	in	ADP
hjic-96	118	2	the	the	DET
hjic-96	118	3	previous	previous	ADJ
hjic-96	118	4	example	example	NOUN
hjic-96	118	5	,	,	PUNCT
hjic-96	118	6	we	we	PRON
hjic-96	118	7	can	can	AUX
hjic-96	118	8	generate	generate	VERB
hjic-96	118	9	six	six	NUM
hjic-96	118	10	rules	rule	NOUN
hjic-96	118	11	from	from	ADP
hjic-96	118	12	the	the	DET
hjic-96	118	13	frequent	frequent	ADJ
hjic-96	118	14	item	item	NOUN
hjic-96	118	15	sets	set	NOUN
hjic-96	118	16	{	{	PUNCT
hjic-96	118	17	beer	beer	NOUN
hjic-96	118	18	,	,	PUNCT
hjic-96	118	19	bread	bread	NOUN
hjic-96	118	20	,	,	PUNCT
hjic-96	118	21	diaper	diaper	NOUN
hjic-96	118	22	}	}	PUNCT
hjic-96	118	23	(	(	PUNCT
hjic-96	118	24	see	see	VERB
hjic-96	118	25	the	the	DET
hjic-96	118	26	possible	possible	ADJ
hjic-96	118	27	rules	rule	NOUN
hjic-96	118	28	in	in	ADP
hjic-96	118	29	figure	figure	NOUN
hjic-96	118	30	1	1	NUM
hjic-96	118	31	)	)	PUNCT
hjic-96	118	32	.	.	PUNCT
hjic-96	119	1	fig.1	fig.1	ADJ
hjic-96	119	2	example	example	NOUN
hjic-96	119	3	for	for	ADP
hjic-96	119	4	association	association	NOUN
hjic-96	119	5	rule	rule	NOUN
hjic-96	119	6	generating	generate	VERB
hjic-96	119	7	it	it	PRON
hjic-96	119	8	is	be	AUX
hjic-96	119	9	very	very	ADV
hjic-96	119	10	important	important	ADJ
hjic-96	119	11	to	to	PART
hjic-96	119	12	know	know	VERB
hjic-96	119	13	which	which	DET
hjic-96	119	14	association	association	NOUN
hjic-96	119	15	rules	rule	NOUN
hjic-96	119	16	are	be	AUX
hjic-96	119	17	well	well	ADV
hjic-96	119	18	usable	usable	ADJ
hjic-96	119	19	,	,	PUNCT
hjic-96	119	20	namely	namely	ADV
hjic-96	119	21	which	which	PRON
hjic-96	119	22	gives	give	VERB
hjic-96	119	23	the	the	DET
hjic-96	119	24	most	most	ADJ
hjic-96	119	25	information	information	NOUN
hjic-96	119	26	about	about	ADP
hjic-96	119	27	the	the	DET
hjic-96	119	28	data	datum	NOUN
hjic-96	119	29	.	.	PUNCT
hjic-96	120	1	two	two	NUM
hjic-96	120	2	basic	basic	ADJ
hjic-96	120	3	measures	measure	NOUN
hjic-96	120	4	are	be	AUX
hjic-96	120	5	used	use	VERB
hjic-96	120	6	to	to	PART
hjic-96	120	7	calculate	calculate	VERB
hjic-96	120	8	how	how	SCONJ
hjic-96	120	9	“	"	PUNCT
hjic-96	120	10	important	important	ADJ
hjic-96	120	11	”	"	PUNCT
hjic-96	120	12	an	an	DET
hjic-96	120	13	association	association	NOUN
hjic-96	120	14	rule	rule	NOUN
hjic-96	120	15	.	.	PUNCT
hjic-96	121	1	first	first	ADJ
hjic-96	121	2	one	one	NUM
hjic-96	121	3	is	be	AUX
hjic-96	121	4	the	the	DET
hjic-96	121	5	previously	previously	ADV
hjic-96	121	6	defined	define	VERB
hjic-96	121	7	support	support	NOUN
hjic-96	121	8	measure	measure	NOUN
hjic-96	121	9	.	.	PUNCT
hjic-96	122	1	the	the	DET
hjic-96	122	2	support	support	NOUN
hjic-96	122	3	of	of	ADP
hjic-96	122	4	an	an	DET
hjic-96	122	5	association	association	NOUN
hjic-96	122	6	rule	rule	NOUN
hjic-96	122	7	is	be	AUX
hjic-96	122	8	the	the	DET
hjic-96	122	9	support	support	NOUN
hjic-96	122	10	of	of	ADP
hjic-96	122	11	the	the	DET
hjic-96	122	12	set	set	NOUN
hjic-96	122	13	of	of	ADP
hjic-96	122	14	its	its	PRON
hjic-96	122	15	items	item	NOUN
hjic-96	122	16	.	.	PUNCT
hjic-96	123	1	for	for	ADP
hjic-96	123	2	example	example	NOUN
hjic-96	123	3	,	,	PUNCT
hjic-96	123	4	the	the	DET
hjic-96	123	5	support	support	NOUN
hjic-96	123	6	of	of	ADP
hjic-96	123	7	the	the	DET
hjic-96	123	8	rule	rule	NOUN
hjic-96	123	9	“	"	PUNCT
hjic-96	123	10	{	{	PUNCT
hjic-96	123	11	bread	bread	NOUN
hjic-96	123	12	,	,	PUNCT
hjic-96	123	13	diaper	diaper	NOUN
hjic-96	123	14	}	}	PUNCT
hjic-96	123	15	=	=	NOUN
hjic-96	123	16	>	>	X
hjic-96	123	17	{	{	PUNCT
hjic-96	123	18	beer	beer	NOUN
hjic-96	123	19	}	}	PUNCT
hjic-96	123	20	”	"	PUNCT
hjic-96	123	21	is	be	AUX
hjic-96	123	22	equal	equal	ADJ
hjic-96	123	23	to	to	ADP
hjic-96	123	24	the	the	DET
hjic-96	123	25	support	support	NOUN
hjic-96	123	26	of	of	ADP
hjic-96	123	27	the	the	DET
hjic-96	123	28	item	item	NOUN
hjic-96	123	29	set	set	NOUN
hjic-96	123	30	{	{	PUNCT
hjic-96	123	31	beer	beer	NOUN
hjic-96	123	32	,	,	PUNCT
hjic-96	123	33	bread	bread	NOUN
hjic-96	123	34	,	,	PUNCT
hjic-96	123	35	diaper	diaper	NOUN
hjic-96	123	36	}	}	PUNCT
hjic-96	123	37	.	.	PUNCT
hjic-96	124	1	the	the	DET
hjic-96	124	2	second	second	ADJ
hjic-96	124	3	one	one	NOUN
hjic-96	124	4	,	,	PUNCT
hjic-96	124	5	the	the	DET
hjic-96	124	6	confidence	confidence	NOUN
hjic-96	124	7	measure	measure	NOUN
hjic-96	124	8	of	of	ADP
hjic-96	124	9	a	a	DET
hjic-96	124	10	rule	rule	NOUN
hjic-96	124	11	is	be	AUX
hjic-96	124	12	calculated	calculate	VERB
hjic-96	124	13	as	as	SCONJ
hjic-96	124	14	follows	follow	VERB
hjic-96	124	15	:	:	PUNCT
hjic-96	124	16	)	)	PUNCT
hjic-96	124	17	supp	supp	PROPN
hjic-96	124	18	(	(	PUNCT
hjic-96	124	19	)	)	PUNCT
hjic-96	124	20	supp	supp	PROPN
hjic-96	124	21	(	(	PUNCT
hjic-96	124	22	)	)	PUNCT
hjic-96	124	23	(	(	PUNCT
hjic-96	124	24	x	x	NUM
hjic-96	124	25	yxyxconf	yxyxconf	NOUN
hjic-96	124	26	∪	∪	ADV
hjic-96	124	27	=	=	SYM
hjic-96	124	28	=	=	NOUN
hjic-96	124	29	>	>	X
hjic-96	124	30	(	(	PUNCT
hjic-96	124	31	7	7	NUM
hjic-96	124	32	)	)	PUNCT
hjic-96	124	33	because	because	SCONJ
hjic-96	124	34	the	the	DET
hjic-96	124	35	confidence	confidence	NOUN
hjic-96	124	36	measure	measure	NOUN
hjic-96	124	37	is	be	AUX
hjic-96	124	38	a	a	DET
hjic-96	124	39	conditional	conditional	ADJ
hjic-96	124	40	probability	probability	NOUN
hjic-96	124	41	(	(	PUNCT
hjic-96	124	42	the	the	DET
hjic-96	124	43	quotient	quotient	NOUN
hjic-96	124	44	of	of	ADP
hjic-96	124	45	the	the	DET
hjic-96	124	46	rule	rule	NOUN
hjic-96	124	47	and	and	CCONJ
hjic-96	124	48	antecedent	antecedent	NOUN
hjic-96	124	49	supports	support	VERB
hjic-96	124	50	)	)	PUNCT
hjic-96	124	51	it	it	PRON
hjic-96	124	52	serves	serve	VERB
hjic-96	124	53	information	information	NOUN
hjic-96	124	54	about	about	ADP
hjic-96	124	55	the	the	DET
hjic-96	124	56	relationship	relationship	NOUN
hjic-96	124	57	of	of	ADP
hjic-96	124	58	the	the	DET
hjic-96	124	59	antecedent	antecedent	NOUN
hjic-96	124	60	and	and	CCONJ
hjic-96	124	61	consequent	consequent	ADJ
hjic-96	124	62	parts	part	NOUN
hjic-96	124	63	of	of	ADP
hjic-96	124	64	a	a	DET
hjic-96	124	65	rule	rule	NOUN
hjic-96	124	66	.	.	PUNCT
hjic-96	125	1	a	a	DET
hjic-96	125	2	rule	rule	NOUN
hjic-96	125	3	x	x	PUNCT
hjic-96	125	4	=	=	X
hjic-96	125	5	>	>	X
hjic-96	125	6	y	y	PROPN
hjic-96	125	7	is	be	AUX
hjic-96	125	8	called	call	VERB
hjic-96	125	9	important	important	ADJ
hjic-96	125	10	,	,	PUNCT
hjic-96	125	11	or	or	CCONJ
hjic-96	125	12	strong	strong	ADJ
hjic-96	125	13	rule	rule	NOUN
hjic-96	125	14	if	if	SCONJ
hjic-96	125	15	its	its	PRON
hjic-96	125	16	support	support	NOUN
hjic-96	125	17	and	and	CCONJ
hjic-96	125	18	confidence	confidence	NOUN
hjic-96	125	19	are	be	AUX
hjic-96	125	20	higher	high	ADJ
hjic-96	125	21	than	than	ADP
hjic-96	125	22	the	the	DET
hjic-96	125	23	minimum	minimum	ADJ
hjic-96	125	24	support	support	NOUN
hjic-96	125	25	(	(	PUNCT
hjic-96	125	26	σ	σ	NOUN
hjic-96	125	27	)	)	PUNCT
hjic-96	125	28	and	and	CCONJ
hjic-96	125	29	the	the	DET
hjic-96	125	30	minimum	minimum	ADJ
hjic-96	125	31	confidence	confidence	NOUN
hjic-96	125	32	thresholds	threshold	NOUN
hjic-96	125	33	(	(	PUNCT
hjic-96	125	34	γ	γ	PROPN
hjic-96	125	35	)	)	PUNCT
hjic-96	125	36	.	.	PUNCT
hjic-96	126	1	the	the	DET
hjic-96	126	2	confidence	confidence	NOUN
hjic-96	126	3	is	be	AUX
hjic-96	126	4	a	a	DET
hjic-96	126	5	basic	basic	ADJ
hjic-96	126	6	rule	rule	NOUN
hjic-96	126	7	interestingness	interestingness	PROPN
hjic-96	126	8	measure	measure	NOUN
hjic-96	126	9	,	,	PUNCT
hjic-96	126	10	but	but	CCONJ
hjic-96	126	11	many	many	ADJ
hjic-96	126	12	other	other	ADJ
hjic-96	126	13	measures	measure	NOUN
hjic-96	126	14	are	be	AUX
hjic-96	126	15	also	also	ADV
hjic-96	126	16	can	can	AUX
hjic-96	126	17	be	be	AUX
hjic-96	126	18	used	use	VERB
hjic-96	126	19	to	to	PART
hjic-96	126	20	determine	determine	VERB
hjic-96	126	21	the	the	DET
hjic-96	126	22	importance	importance	NOUN
hjic-96	126	23	and	and	CCONJ
hjic-96	126	24	ordering	order	VERB
hjic-96	126	25	the	the	DET
hjic-96	126	26	mined	mine	VERB
hjic-96	126	27	rules	rule	NOUN
hjic-96	126	28	(	(	PUNCT
hjic-96	126	29	e.g.	e.g.	ADV
hjic-96	126	30	ri	ri	ADJ
hjic-96	126	31	–	–	PUNCT
hjic-96	126	32	rule	rule	NOUN
hjic-96	126	33	interesting	interesting	ADJ
hjic-96	126	34	,	,	PUNCT
hjic-96	126	35	lift	lift	NOUN
hjic-96	126	36	,	,	PUNCT
hjic-96	126	37	correlation	correlation	NOUN
hjic-96	126	38	,	,	PUNCT
hjic-96	126	39	jaccard	jaccard	PROPN
hjic-96	126	40	,	,	PUNCT
hjic-96	126	41	piatetskyshapiro	piatetskyshapiro	ADV
hjic-96	126	42	,	,	PUNCT
hjic-96	126	43	etc	etc	X
hjic-96	126	44	.	.	X
hjic-96	126	45	measures	measure	NOUN
hjic-96	126	46	)	)	PUNCT
hjic-96	126	47	.	.	PUNCT
hjic-96	127	1	the	the	DET
hjic-96	127	2	number	number	NOUN
hjic-96	127	3	of	of	ADP
hjic-96	127	4	the	the	DET
hjic-96	127	5	possible	possible	ADJ
hjic-96	127	6	association	association	NOUN
hjic-96	127	7	rules	rule	NOUN
hjic-96	127	8	is	be	AUX
hjic-96	127	9	very	very	ADV
hjic-96	127	10	high	high	ADJ
hjic-96	127	11	in	in	ADP
hjic-96	127	12	case	case	NOUN
hjic-96	127	13	of	of	ADP
hjic-96	127	14	an	an	DET
hjic-96	127	15	item	item	NOUN
hjic-96	127	16	set	set	VERB
hjic-96	127	17	with	with	ADP
hjic-96	127	18	many	many	ADJ
hjic-96	127	19	elements	element	NOUN
hjic-96	127	20	(	(	PUNCT
hjic-96	127	21	e.g.	e.g.	ADV
hjic-96	127	22	if	if	SCONJ
hjic-96	127	23	ten	ten	NUM
hjic-96	127	24	items	item	NOUN
hjic-96	127	25	are	be	AUX
hjic-96	127	26	in	in	ADP
hjic-96	127	27	an	an	DET
hjic-96	127	28	item	item	NOUN
hjic-96	127	29	set	set	NOUN
hjic-96	127	30	,	,	PUNCT
hjic-96	127	31	the	the	DET
hjic-96	127	32	number	number	NOUN
hjic-96	127	33	of	of	ADP
hjic-96	127	34	possible	possible	ADJ
hjic-96	127	35	rules	rule	NOUN
hjic-96	127	36	is	be	AUX
hjic-96	127	37	)	)	PUNCT
hjic-96	127	38	.	.	PUNCT
hjic-96	128	1	therefore	therefore	ADV
hjic-96	128	2	it	it	PRON
hjic-96	128	3	is	be	AUX
hjic-96	128	4	well	well	ADV
hjic-96	128	5	worth	worth	ADJ
hjic-96	128	6	using	use	VERB
hjic-96	128	7	the	the	DET
hjic-96	128	8	antimonotonic	antimonotonic	ADJ
hjic-96	128	9	feature	feature	NOUN
hjic-96	128	10	.	.	PUNCT
hjic-96	129	1	for	for	ADP
hjic-96	129	2	generating	generating	NOUN
hjic-96	129	3	of	of	ADP
hjic-96	129	4	the	the	DET
hjic-96	129	5	(	(	PUNCT
hjic-96	129	6	n-1)-large	n-1)-large	NUM
hjic-96	129	7	rules	rule	NOUN
hjic-96	129	8	we	we	PRON
hjic-96	129	9	can	can	AUX
hjic-96	129	10	use	use	VERB
hjic-96	129	11	in	in	ADP
hjic-96	129	12	the	the	DET
hjic-96	129	13	previous	previous	ADJ
hjic-96	129	14	step	step	NOUN
hjic-96	129	15	selected	select	VERB
hjic-96	129	16	frequent	frequent	ADJ
hjic-96	129	17	(	(	PUNCT
hjic-96	129	18	n)-large	n)-large	NUM
hjic-96	129	19	rule	rule	NOUN
hjic-96	129	20	.	.	PUNCT
hjic-96	130	1	for	for	ADP
hjic-96	130	2	example	example	NOUN
hjic-96	130	3	be	be	AUX
hjic-96	130	4	the	the	DET
hjic-96	130	5	z	z	NOUN
hjic-96	130	6	a	a	DET
hjic-96	130	7	frequent	frequent	ADJ
hjic-96	130	8	item	item	NOUN
hjic-96	130	9	set	set	NOUN
hjic-96	130	10	.	.	PUNCT
hjic-96	131	1	the	the	DET
hjic-96	131	2	following	follow	VERB
hjic-96	131	3	two	two	NUM
hjic-96	131	4	association	association	NOUN
hjic-96	131	5	rules	rule	NOUN
hjic-96	131	6	are	be	AUX
hjic-96	131	7	generated	generate	VERB
hjic-96	131	8	from	from	ADP
hjic-96	131	9	z	z	PROPN
hjic-96	131	10	:	:	PUNCT
hjic-96	131	11	1	1	NUM
hjic-96	131	12	)	)	PUNCT
hjic-96	131	13	x	x	PUNCT
hjic-96	132	1	=	=	NOUN
hjic-96	132	2	>	>	X
hjic-96	132	3	z	z	NOUN
hjic-96	132	4	\	\	NOUN
hjic-96	132	5	x	x	PUNCT
hjic-96	132	6	and	and	CCONJ
hjic-96	132	7	2	2	NUM
hjic-96	132	8	)	)	PUNCT
hjic-96	132	9	x	x	PUNCT
hjic-96	133	1	=	=	NOUN
hjic-96	133	2	>	>	X
hjic-96	133	3	z	z	NOUN
hjic-96	133	4	\	\	PUNCT
hjic-96	134	1	x	x	X
hjic-96	134	2	,	,	PUNCT
hjic-96	134	3	where	where	SCONJ
hjic-96	134	4	.	.	PUNCT
hjic-96	135	1	if	if	SCONJ
hjic-96	135	2	the	the	DET
hjic-96	135	3	first	first	ADJ
hjic-96	135	4	rule	rule	NOUN
hjic-96	135	5	does	do	AUX
hjic-96	135	6	not	not	PART
hjic-96	135	7	fulfil	fulfil	VERB
hjic-96	135	8	the	the	DET
hjic-96	135	9	support	support	NOUN
hjic-96	135	10	criteria	criterion	NOUN
hjic-96	135	11	,	,	PUNCT
hjic-96	135	12	the	the	DET
hjic-96	135	13	second	second	ADJ
hjic-96	135	14	rule	rule	NOUN
hjic-96	135	15	is	be	AUX
hjic-96	135	16	also	also	ADV
hjic-96	135	17	can	can	AUX
hjic-96	135	18	not	not	PART
hjic-96	135	19	to	to	PART
hjic-96	135	20	be	be	AUX
hjic-96	135	21	frequent	frequent	ADJ
hjic-96	135	22	.	.	PUNCT
hjic-96	136	1	2210	2210	NUM
hjic-96	137	1	−	−	PUNCT
hjic-96	137	2	xx∈	xx∈	PROPN
hjic-96	137	3	the	the	DET
hjic-96	137	4	importance	importance	NOUN
hjic-96	137	5	of	of	ADP
hjic-96	137	6	an	an	DET
hjic-96	137	7	association	association	NOUN
hjic-96	137	8	rule	rule	NOUN
hjic-96	137	9	can	can	AUX
hjic-96	137	10	be	be	AUX
hjic-96	137	11	determined	determine	VERB
hjic-96	137	12	not	not	PART
hjic-96	137	13	only	only	ADV
hjic-96	137	14	by	by	ADP
hjic-96	137	15	objective	objective	ADJ
hjic-96	137	16	way	way	NOUN
hjic-96	137	17	.	.	PUNCT
hjic-96	138	1	the	the	DET
hjic-96	138	2	determination	determination	NOUN
hjic-96	138	3	can	can	AUX
hjic-96	138	4	be	be	AUX
hjic-96	138	5	also	also	ADV
hjic-96	138	6	subjective	subjective	ADJ
hjic-96	138	7	.	.	PUNCT
hjic-96	139	1	the	the	DET
hjic-96	139	2	users	user	NOUN
hjic-96	139	3	can	can	AUX
hjic-96	139	4	add	add	VERB
hjic-96	139	5	the	the	DET
hjic-96	139	6	“	"	PUNCT
hjic-96	139	7	right	right	ADJ
hjic-96	139	8	”	"	PUNCT
hjic-96	139	9	form	form	NOUN
hjic-96	139	10	of	of	ADP
hjic-96	139	11	the	the	DET
hjic-96	139	12	rules	rule	NOUN
hjic-96	139	13	.	.	PUNCT
hjic-96	140	1	suppose	suppose	VERB
hjic-96	140	2	that	that	SCONJ
hjic-96	140	3	a	a	DET
hjic-96	140	4	user	user	NOUN
hjic-96	140	5	wants	want	VERB
hjic-96	140	6	to	to	PART
hjic-96	140	7	search	search	VERB
hjic-96	140	8	only	only	ADV
hjic-96	140	9	rules	rule	NOUN
hjic-96	140	10	with	with	ADP
hjic-96	140	11	a	a	DET
hjic-96	140	12	distinguished	distinguished	ADJ
hjic-96	140	13	item	item	NOUN
hjic-96	140	14	in	in	ADP
hjic-96	140	15	consequent	consequent	ADJ
hjic-96	140	16	part	part	NOUN
hjic-96	140	17	.	.	PUNCT
hjic-96	141	1	for	for	ADP
hjic-96	141	2	example	example	NOUN
hjic-96	141	3	be	be	AUX
hjic-96	141	4	this	this	DET
hjic-96	141	5	item	item	NOUN
hjic-96	141	6	a	a	DET
hjic-96	141	7	productfamily	productfamily	ADV
hjic-96	141	8	,	,	PUNCT
hjic-96	141	9	books	book	NOUN
hjic-96	141	10	.	.	PUNCT
hjic-96	142	1	in	in	ADP
hjic-96	142	2	this	this	DET
hjic-96	142	3	case	case	NOUN
hjic-96	142	4	,	,	PUNCT
hjic-96	142	5	only	only	ADV
hjic-96	142	6	the	the	DET
hjic-96	142	7	rules	rule	NOUN
hjic-96	142	8	where	where	SCONJ
hjic-96	142	9	a	a	DET
hjic-96	142	10	book	book	NOUN
hjic-96	142	11	is	be	AUX
hjic-96	142	12	placed	place	VERB
hjic-96	142	13	in	in	ADP
hjic-96	142	14	the	the	DET
hjic-96	142	15	consequent	consequent	ADJ
hjic-96	142	16	part	part	NOUN
hjic-96	142	17	will	will	AUX
hjic-96	142	18	be	be	AUX
hjic-96	142	19	strong	strong	ADJ
hjic-96	142	20	rules	rule	NOUN
hjic-96	142	21	.	.	PUNCT
hjic-96	143	1	to	to	PART
hjic-96	143	2	increase	increase	VERB
hjic-96	143	3	the	the	DET
hjic-96	143	4	usability	usability	NOUN
hjic-96	143	5	of	of	ADP
hjic-96	143	6	the	the	DET
hjic-96	143	7	association	association	NOUN
hjic-96	143	8	rule	rule	NOUN
hjic-96	143	9	,	,	PUNCT
hjic-96	143	10	fuzzy	fuzzy	ADJ
hjic-96	143	11	association	association	NOUN
hjic-96	143	12	rules	rule	NOUN
hjic-96	143	13	are	be	AUX
hjic-96	143	14	proposed	propose	VERB
hjic-96	143	15	.	.	PUNCT
hjic-96	144	1	in	in	ADP
hjic-96	144	2	the	the	DET
hjic-96	144	3	next	next	ADJ
hjic-96	144	4	section	section	NOUN
hjic-96	144	5	,	,	PUNCT
hjic-96	144	6	the	the	DET
hjic-96	144	7	basic	basic	ADJ
hjic-96	144	8	definitions	definition	NOUN
hjic-96	144	9	of	of	ADP
hjic-96	144	10	fuzzy	fuzzy	ADJ
hjic-96	144	11	association	association	NOUN
hjic-96	144	12	rule	rule	NOUN
hjic-96	144	13	theory	theory	NOUN
hjic-96	144	14	are	be	AUX
hjic-96	144	15	presented	present	VERB
hjic-96	144	16	.	.	PUNCT
hjic-96	145	1	fuzzy	fuzzy	ADJ
hjic-96	145	2	association	association	NOUN
hjic-96	145	3	rule	rule	NOUN
hjic-96	145	4	mining	mine	VERB
hjic-96	145	5	the	the	DET
hjic-96	145	6	fuzzy	fuzzy	ADJ
hjic-96	145	7	association	association	NOUN
hjic-96	145	8	rules	rule	NOUN
hjic-96	145	9	can	can	AUX
hjic-96	145	10	be	be	AUX
hjic-96	145	11	discovered	discover	VERB
hjic-96	145	12	in	in	ADP
hjic-96	145	13	also	also	ADV
hjic-96	145	14	two	two	NUM
hjic-96	145	15	steps	step	NOUN
hjic-96	145	16	as	as	SCONJ
hjic-96	145	17	we	we	PRON
hjic-96	145	18	showed	show	VERB
hjic-96	145	19	in	in	ADP
hjic-96	145	20	crisp	crisp	ADJ
hjic-96	145	21	case	case	NOUN
hjic-96	145	22	:	:	PUNCT
hjic-96	145	23	1	1	X
hjic-96	145	24	)	)	PUNCT
hjic-96	145	25	mining	mining	NOUN
hjic-96	145	26	frequent	frequent	ADJ
hjic-96	145	27	item	item	NOUN
hjic-96	145	28	sets	set	NOUN
hjic-96	145	29	,	,	PUNCT
hjic-96	145	30	and	and	CCONJ
hjic-96	145	31	2	2	X
hjic-96	145	32	)	)	PUNCT
hjic-96	145	33	generating	generate	VERB
hjic-96	145	34	fuzzy	fuzzy	ADJ
hjic-96	145	35	association	association	NOUN
hjic-96	145	36	rules	rule	NOUN
hjic-96	145	37	from	from	ADP
hjic-96	145	38	the	the	DET
hjic-96	145	39	discovered	discover	VERB
hjic-96	145	40	set	set	NOUN
hjic-96	145	41	of	of	ADP
hjic-96	145	42	frequent	frequent	ADJ
hjic-96	145	43	item	item	NOUN
hjic-96	145	44	sets	set	NOUN
hjic-96	145	45	.	.	PUNCT
hjic-96	146	1	a	a	DET
hjic-96	146	2	dataset	dataset	NOUN
hjic-96	146	3	(	(	PUNCT
hjic-96	146	4	database	database	NOUN
hjic-96	146	5	)	)	PUNCT
hjic-96	146	6	includes	include	VERB
hjic-96	146	7	records	record	NOUN
hjic-96	146	8	(	(	PUNCT
hjic-96	146	9	data	datum	NOUN
hjic-96	146	10	rows	row	NOUN
hjic-96	146	11	)	)	PUNCT
hjic-96	146	12	via	via	ADP
hjic-96	146	13	the	the	DET
hjic-96	146	14	data	data	NOUN
hjic-96	146	15	fields	field	NOUN
hjic-96	146	16	(	(	PUNCT
hjic-96	146	17	columns	column	NOUN
hjic-96	146	18	)	)	PUNCT
hjic-96	146	19	.	.	PUNCT
hjic-96	147	1	the	the	DET
hjic-96	147	2	fields	field	NOUN
hjic-96	147	3	are	be	AUX
hjic-96	147	4	frequent	frequent	ADJ
hjic-96	147	5	called	call	VERB
hjic-96	147	6	as	as	ADP
hjic-96	147	7	attributes	attribute	NOUN
hjic-96	147	8	.	.	PUNCT
hjic-96	148	1	because	because	SCONJ
hjic-96	148	2	in	in	ADP
hjic-96	148	3	fuzzy	fuzzy	ADJ
hjic-96	148	4	association	association	NOUN
hjic-96	148	5	rule	rule	NOUN
hjic-96	148	6	theory	theory	NOUN
hjic-96	148	7	the	the	DET
hjic-96	148	8	items	item	NOUN
hjic-96	148	9	are	be	AUX
hjic-96	148	10	fuzzy	fuzzy	ADJ
hjic-96	148	11	sets	set	NOUN
hjic-96	148	12	,	,	PUNCT
hjic-96	148	13	a	a	DET
hjic-96	148	14	partition	partition	NOUN
hjic-96	148	15	method	method	NOUN
hjic-96	148	16	is	be	AUX
hjic-96	148	17	necessary	necessary	ADJ
hjic-96	148	18	which	which	PRON
hjic-96	148	19	transforms	transform	VERB
hjic-96	148	20	the	the	DET
hjic-96	148	21	crisp	crisp	ADJ
hjic-96	148	22	data	datum	NOUN
hjic-96	148	23	set	set	VERB
hjic-96	148	24	into	into	ADP
hjic-96	148	25	fuzzy	fuzzy	ADJ
hjic-96	148	26	data	datum	NOUN
hjic-96	148	27	set	set	VERB
hjic-96	148	28	for	for	ADP
hjic-96	148	29	all	all	DET
hjic-96	148	30	attributes	attribute	NOUN
hjic-96	148	31	.	.	PUNCT
hjic-96	149	1	for	for	ADP
hjic-96	149	2	the	the	DET
hjic-96	149	3	numerical	numerical	ADJ
hjic-96	149	4	attributes	attribute	NOUN
hjic-96	149	5	(	(	PUNCT
hjic-96	149	6	as	as	ADP
hjic-96	149	7	for	for	ADP
hjic-96	149	8	example	example	NOUN
hjic-96	149	9	the	the	DET
hjic-96	149	10	temperature	temperature	NOUN
hjic-96	149	11	,	,	PUNCT
hjic-96	149	12	pressure	pressure	NOUN
hjic-96	149	13	,	,	PUNCT
hjic-96	149	14	etc	etc	X
hjic-96	149	15	.	.	X
hjic-96	149	16	)	)	PUNCT
hjic-96	149	17	of	of	ADP
hjic-96	149	18	the	the	DET
hjic-96	149	19	data	datum	NOUN
hjic-96	149	20	set	set	VERB
hjic-96	149	21	,	,	PUNCT
hjic-96	149	22	fuzzy	fuzzy	ADJ
hjic-96	149	23	sets	set	NOUN
hjic-96	149	24	can	can	AUX
hjic-96	149	25	be	be	AUX
hjic-96	149	26	defined	define	VERB
hjic-96	149	27	with	with	ADP
hjic-96	149	28	gaussian	gaussian	ADJ
hjic-96	149	29	,	,	PUNCT
hjic-96	149	30	sigmoid	sigmoid	NOUN
hjic-96	149	31	,	,	PUNCT
hjic-96	149	32	or	or	CCONJ
hjic-96	149	33	piecewise	piecewise	NOUN
hjic-96	149	34	linear	linear	ADJ
hjic-96	149	35	fuzzy	fuzzy	ADJ
hjic-96	149	36	dichotomies	dichotomy	NOUN
hjic-96	149	37	.	.	PUNCT
hjic-96	150	1	therefore	therefore	ADV
hjic-96	150	2	triangular	triangular	NOUN
hjic-96	150	3	,	,	PUNCT
hjic-96	150	4	trapezoidal	trapezoidal	ADJ
hjic-96	150	5	type	type	NOUN
hjic-96	150	6	of	of	ADP
hjic-96	150	7	fuzzy	fuzzy	ADJ
hjic-96	150	8	sets	set	NOUN
hjic-96	150	9	(	(	PUNCT
hjic-96	150	10	intervals	interval	NOUN
hjic-96	150	11	)	)	PUNCT
hjic-96	150	12	can	can	AUX
hjic-96	150	13	be	be	AUX
hjic-96	150	14	used	use	VERB
hjic-96	150	15	for	for	ADP
hjic-96	150	16	data	data	NOUN
hjic-96	150	17	partition	partition	NOUN
hjic-96	150	18	.	.	PUNCT
hjic-96	151	1	see	see	VERB
hjic-96	151	2	the	the	DET
hjic-96	151	3	figure	figure	NOUN
hjic-96	151	4	2	2	NUM
hjic-96	151	5	for	for	ADP
hjic-96	151	6	an	an	DET
hjic-96	151	7	example	example	NOUN
hjic-96	151	8	,	,	PUNCT
hjic-96	151	9	where	where	SCONJ
hjic-96	151	10	the	the	DET
hjic-96	151	11	attributes	attribute	NOUN
hjic-96	151	12	and	and	CCONJ
hjic-96	151	13	are	be	AUX
hjic-96	151	14	partitioned	partition	VERB
hjic-96	151	15	by	by	ADP
hjic-96	151	16	two	two	NUM
hjic-96	151	17	-	-	PUNCT
hjic-96	151	18	two	two	NUM
hjic-96	151	19	trapezoidal	trapezoidal	ADJ
hjic-96	151	20	fuzzy	fuzzy	ADJ
hjic-96	151	21	sets	set	NOUN
hjic-96	151	22	.	.	PUNCT
hjic-96	152	1	1z	1z	NOUN
hjic-96	152	2	2z	2z	NUM
hjic-96	152	3	fig.2	fig.2	VERB
hjic-96	152	4	a	a	DET
hjic-96	152	5	fuzzy	fuzzy	ADJ
hjic-96	152	6	partition	partition	NOUN
hjic-96	152	7	of	of	ADP
hjic-96	152	8	data	datum	NOUN
hjic-96	152	9	space	space	NOUN
hjic-96	152	10	(	(	PUNCT
hjic-96	152	11	,	,	PUNCT
hjic-96	152	12	)	)	PUNCT
hjic-96	152	13	1z	1z	NOUN
hjic-96	152	14	2z	2z	NOUN
hjic-96	152	15	let	let	AUX
hjic-96	152	16	be	be	AUX
hjic-96	152	17	a	a	DET
hjic-96	152	18	transformed	transform	VERB
hjic-96	152	19	(	(	PUNCT
hjic-96	152	20	partitioned	partition	VERB
hjic-96	152	21	)	)	PUNCT
hjic-96	152	22	fuzzy	fuzzy	ADJ
hjic-96	152	23	dataset	dataset	NOUN
hjic-96	152	24	of	of	ADP
hjic-96	152	25	n	n	DET
hjic-96	152	26	tuples	tuple	NOUN
hjic-96	152	27	(	(	PUNCT
hjic-96	152	28	data	datum	NOUN
hjic-96	152	29	records	record	NOUN
hjic-96	152	30	~	~	PUNCT
hjic-96	152	31	data	data	NOUN
hjic-96	152	32	points	point	NOUN
hjic-96	152	33	)	)	PUNCT
hjic-96	152	34	with	with	ADP
hjic-96	152	35	a	a	DET
hjic-96	152	36	set	set	NOUN
hjic-96	152	37	of	of	ADP
hjic-96	152	38	attributes	attribute	NOUN
hjic-96	152	39	}	}	PUNCT
hjic-96	152	40	,	,	PUNCT
hjic-96	152	41	,	,	PUNCT
hjic-96	152	42	,	,	PUNCT
hjic-96	152	43	{	{	PUNCT
hjic-96	152	44	21	21	NUM
hjic-96	152	45	ntttd	ntttd	NOUN
hjic-96	152	46	k=	k=	PUNCT
hjic-96	152	47	}	}	PUNCT
hjic-96	152	48	,	,	PUNCT
hjic-96	152	49	,	,	PUNCT
hjic-96	152	50	,	,	PUNCT
hjic-96	152	51	{	{	PUNCT
hjic-96	152	52	21	21	NUM
hjic-96	152	53	qzzzζ	qzzzζ	NOUN
hjic-96	152	54	k=	k=	PUNCT
hjic-96	152	55	and	and	CCONJ
hjic-96	152	56	let	let	VERB
hjic-96	152	57	be	be	AUX
hjic-96	152	58	an	an	DET
hjic-96	152	59	arbitrary	arbitrary	ADJ
hjic-96	152	60	fuzzy	fuzzy	ADJ
hjic-96	152	61	interval	interval	NOUN
hjic-96	152	62	(	(	PUNCT
hjic-96	152	63	fuzzy	fuzzy	ADJ
hjic-96	152	64	set	set	NOUN
hjic-96	152	65	)	)	PUNCT
hjic-96	152	66	associated	associate	VERB
hjic-96	152	67	with	with	ADP
hjic-96	152	68	attribute	attribute	NOUN
hjic-96	152	69	in	in	ADP
hjic-96	152	70	z	z	PROPN
hjic-96	152	71	where	where	SCONJ
hjic-96	152	72	q	q	PROPN
hjic-96	152	73	denotes	denote	VERB
hjic-96	152	74	the	the	DET
hjic-96	152	75	number	number	NOUN
hjic-96	152	76	of	of	ADP
hjic-96	152	77	attributes	attribute	NOUN
hjic-96	152	78	.	.	PUNCT
hjic-96	153	1	from	from	ADP
hjic-96	153	2	this	this	DET
hjic-96	153	3	point	point	NOUN
hjic-96	153	4	,	,	PUNCT
hjic-96	153	5	we	we	PRON
hjic-96	153	6	use	use	VERB
hjic-96	153	7	the	the	DET
hjic-96	153	8	notation	notation	PROPN
hjic-96	153	9	jic	jic	PROPN
hjic-96	153	10	,	,	PUNCT
hjic-96	153	11	iz	iz	INTJ
hjic-96	153	12	jii	jii	PROPN
hjic-96	153	13	cz	cz	VERB
hjic-96	153	14	,	,	PUNCT
hjic-96	153	15	:	:	PUNCT
hjic-96	153	16	for	for	ADP
hjic-96	153	17	an	an	DET
hjic-96	153	18	attribute	attribute	NOUN
hjic-96	153	19	-	-	PUNCT
hjic-96	153	20	fuzzy	fuzzy	ADJ
hjic-96	153	21	interval	interval	NOUN
hjic-96	153	22	pair	pair	NOUN
hjic-96	153	23	,	,	PUNCT
hjic-96	153	24	or	or	CCONJ
hjic-96	153	25	simply	simply	ADV
hjic-96	153	26	61	61	NUM
hjic-96	153	27	fuzzy	fuzzy	ADJ
hjic-96	153	28	item	item	NOUN
hjic-96	153	29	.	.	PUNCT
hjic-96	154	1	an	an	DET
hjic-96	154	2	example	example	NOUN
hjic-96	154	3	could	could	AUX
hjic-96	154	4	be	be	AUX
hjic-96	154	5	youngage	youngage	NOUN
hjic-96	154	6	:	:	PUNCT
hjic-96	154	7	.	.	PUNCT
hjic-96	155	1	for	for	ADP
hjic-96	155	2	fuzzy	fuzzy	ADJ
hjic-96	155	3	item	item	NOUN
hjic-96	155	4	sets	set	NOUN
hjic-96	155	5	,	,	PUNCT
hjic-96	155	6	we	we	PRON
hjic-96	155	7	use	use	VERB
hjic-96	155	8	expressions	expression	NOUN
hjic-96	155	9	like	like	ADP
hjic-96	155	10	cz	cz	NOUN
hjic-96	155	11	:	:	PUNCT
hjic-96	155	12	to	to	PART
hjic-96	155	13	denote	denote	VERB
hjic-96	155	14	an	an	DET
hjic-96	155	15	ordered	ordered	ADJ
hjic-96	155	16	set	set	NOUN
hjic-96	155	17	of	of	ADP
hjic-96	155	18	attributes	attribute	NOUN
hjic-96	155	19	(	(	PUNCT
hjic-96	155	20	ζ⊆z	ζ⊆z	PROPN
hjic-96	155	21	ζ	ζ	NOUN
hjic-96	155	22	denotes	denote	NOUN
hjic-96	155	23	the	the	DET
hjic-96	155	24	set	set	NOUN
hjic-96	155	25	of	of	ADP
hjic-96	155	26	the	the	DET
hjic-96	155	27	all	all	DET
hjic-96	155	28	possible	possible	ADJ
hjic-96	155	29	attributes	attribute	NOUN
hjic-96	155	30	)	)	PUNCT
hjic-96	155	31	and	and	CCONJ
hjic-96	155	32	a	a	DET
hjic-96	155	33	corresponding	corresponding	ADJ
hjic-96	155	34	set	set	NOUN
hjic-96	155	35	of	of	ADP
hjic-96	155	36	some	some	DET
hjic-96	155	37	fuzzy	fuzzy	ADJ
hjic-96	155	38	intervals	interval	NOUN
hjic-96	155	39	,	,	PUNCT
hjic-96	155	40	one	one	NUM
hjic-96	155	41	per	per	ADP
hjic-96	155	42	attribute	attribute	NOUN
hjic-96	155	43	,	,	PUNCT
hjic-96	155	44	i.e	i.e	PROPN
hjic-96	155	45	c	c	X
hjic-96	155	46	]	]	PUNCT
hjic-96	155	47	:	:	PUNCT
hjic-96	155	48	:	:	PUNCT
hjic-96	155	49	:	:	PUNCT
hjic-96	155	50	[:	[:	X
hjic-96	155	51	,	,	PUNCT
hjic-96	155	52	,	,	PUNCT
hjic-96	155	53	,	,	PUNCT
hjic-96	155	54	2211	2211	NUM
hjic-96	155	55	jiijiijii	jiijiijii	NOUN
hjic-96	155	56	qq	qq	X
hjic-96	155	57	czczczcz	czczczcz	ADJ
hjic-96	155	58	∪∪∪=	∪∪∪=	X
hjic-96	155	59	k	k	X
hjic-96	155	60	.	.	PUNCT
hjic-96	156	1	in	in	ADP
hjic-96	156	2	the	the	DET
hjic-96	156	3	literature	literature	NOUN
hjic-96	156	4	,	,	PUNCT
hjic-96	156	5	the	the	DET
hjic-96	156	6	fuzzy	fuzzy	ADJ
hjic-96	156	7	support	support	NOUN
hjic-96	156	8	value	value	NOUN
hjic-96	156	9	has	have	AUX
hjic-96	156	10	been	be	AUX
hjic-96	156	11	defined	define	VERB
hjic-96	156	12	in	in	ADP
hjic-96	156	13	different	different	ADJ
hjic-96	156	14	ways	way	NOUN
hjic-96	156	15	.	.	PUNCT
hjic-96	157	1	some	some	DET
hjic-96	157	2	researchers	researcher	NOUN
hjic-96	157	3	suggest	suggest	VERB
hjic-96	157	4	the	the	DET
hjic-96	157	5	minimum	minimum	ADJ
hjic-96	157	6	operator	operator	NOUN
hjic-96	157	7	as	as	ADP
hjic-96	157	8	in	in	ADP
hjic-96	157	9	fuzzy	fuzzy	ADJ
hjic-96	157	10	intersection	intersection	NOUN
hjic-96	157	11	,	,	PUNCT
hjic-96	157	12	others	other	NOUN
hjic-96	157	13	prefer	prefer	VERB
hjic-96	157	14	the	the	DET
hjic-96	157	15	product	product	NOUN
hjic-96	157	16	operator	operator	NOUN
hjic-96	157	17	.	.	PUNCT
hjic-96	158	1	they	they	PRON
hjic-96	158	2	can	can	AUX
hjic-96	158	3	be	be	AUX
hjic-96	158	4	defined	define	VERB
hjic-96	158	5	formally	formally	ADV
hjic-96	158	6	as	as	SCONJ
hjic-96	158	7	follows	follow	VERB
hjic-96	158	8	:	:	PUNCT
hjic-96	158	9	value	value	NOUN
hjic-96	158	10	for	for	ADP
hjic-96	158	11	attribute	attribute	NOUN
hjic-96	158	12	,	,	PUNCT
hjic-96	158	13	then	then	ADV
hjic-96	158	14	the	the	DET
hjic-96	158	15	fuzzy	fuzzy	ADJ
hjic-96	158	16	support	support	NOUN
hjic-96	158	17	of	of	ADP
hjic-96	158	18	)	)	PUNCT
hjic-96	158	19	(	(	PUNCT
hjic-96	158	20	ik	ik	PROPN
hjic-96	158	21	zt	zt	PROPN
hjic-96	158	22	iz	iz	ADJ
hjic-96	158	23	2	2	NUM
hjic-96	158	24	:	:	PUNCT
hjic-96	158	25	cz	cz	NOUN
hjic-96	158	26	with	with	ADP
hjic-96	158	27	respect	respect	NOUN
hjic-96	158	28	to	to	ADP
hjic-96	158	29	d	d	NOUN
hjic-96	158	30	is	be	AUX
hjic-96	158	31	defined	define	VERB
hjic-96	158	32	as	as	SCONJ
hjic-96	158	33	n	n	PRON
hjic-96	158	34	zt	zt	PROPN
hjic-96	158	35	czfs	czf	VERB
hjic-96	158	36	n	n	PROPN
hjic-96	158	37	k	k	PROPN
hjic-96	158	38	ikczcz	ikczcz	NOUN
hjic-96	158	39	jii	jii	PROPN
hjic-96	158	40	∑	∑	PUNCT
hjic-96	158	41	λ	λ	X
hjic-96	158	42	=	=	PUNCT
hjic-96	159	1	=	=	PUNCT
hjic-96	159	2	∈1	∈1	ADJ
hjic-96	159	3	:	:	PUNCT
hjic-96	159	4	:	:	PUNCT
hjic-96	159	5	)	)	PUNCT
hjic-96	159	6	(	(	PUNCT
hjic-96	159	7	)	)	PUNCT
hjic-96	159	8	:(	:(	PUNCT
hjic-96	159	9	,	,	PUNCT
hjic-96	159	10	(	(	PUNCT
hjic-96	159	11	8)	8)	NUM
hjic-96	159	12	where	where	SCONJ
hjic-96	159	13	the	the	PRON
hjic-96	159	14	is	be	AUX
hjic-96	159	15	an	an	DET
hjic-96	159	16	operator	operator	NOUN
hjic-96	159	17	set	set	VERB
hjic-96	159	18	.	.	PUNCT
hjic-96	160	1	in	in	ADP
hjic-96	160	2	this	this	DET
hjic-96	160	3	paper	paper	NOUN
hjic-96	160	4	we	we	PRON
hjic-96	160	5	prefer	prefer	VERB
hjic-96	160	6	the	the	DET
hjic-96	160	7	product	product	NOUN
hjic-96	160	8	form	form	NOUN
hjic-96	160	9	.	.	PUNCT
hjic-96	161	1	a	a	DET
hjic-96	161	2	fuzzy	fuzzy	ADJ
hjic-96	161	3	support	support	NOUN
hjic-96	161	4	reflects	reflect	VERB
hjic-96	161	5	how	how	SCONJ
hjic-96	161	6	the	the	DET
hjic-96	161	7	record	record	NOUN
hjic-96	161	8	of	of	ADP
hjic-96	161	9	the	the	DET
hjic-96	161	10	identification	identification	NOUN
hjic-96	161	11	data	datum	NOUN
hjic-96	161	12	set	set	VERB
hjic-96	161	13	support	support	VERB
hjic-96	161	14	the	the	DET
hjic-96	161	15	item	item	NOUN
hjic-96	161	16	set	set	NOUN
hjic-96	161	17	.	.	PUNCT
hjic-96	162	1	a	a	DET
hjic-96	162	2	fuzzy	fuzzy	ADJ
hjic-96	162	3	item	item	NOUN
hjic-96	162	4	set	set	NOUN
hjic-96	162	5	}	}	PUNCT
hjic-96	162	6	,	,	PUNCT
hjic-96	162	7	{	{	PUNCT
hjic-96	162	8	min	min	NOUN
hjic-96	162	9	,	,	PUNCT
hjic-96	162	10	kπ	kπ	PROPN
hjic-96	162	11	=	=	NOUN
hjic-96	162	12	λ	λ	NOUN
hjic-96	162	13	cz	cz	NOUN
hjic-96	162	14	:	:	PUNCT
hjic-96	162	15	is	be	AUX
hjic-96	162	16	called	call	VERB
hjic-96	162	17	frequent	frequent	ADJ
hjic-96	162	18	if	if	SCONJ
hjic-96	162	19	its	its	PRON
hjic-96	162	20	fuzzy	fuzzy	ADJ
hjic-96	162	21	support	support	NOUN
hjic-96	162	22	value	value	NOUN
hjic-96	162	23	is	be	AUX
hjic-96	162	24	higher	high	ADJ
hjic-96	162	25	than	than	ADP
hjic-96	162	26	or	or	CCONJ
hjic-96	162	27	equal	equal	ADJ
hjic-96	162	28	to	to	ADP
hjic-96	162	29	a	a	DET
hjic-96	162	30	user	user	NOUN
hjic-96	162	31	-	-	PUNCT
hjic-96	162	32	defined	define	VERB
hjic-96	162	33	minimum	minimum	NOUN
hjic-96	162	34	support	support	NOUN
hjic-96	162	35	(	(	PUNCT
hjic-96	162	36	σ	σ	NOUN
hjic-96	162	37	)	)	PUNCT
hjic-96	162	38	.	.	PUNCT
hjic-96	163	1	the	the	DET
hjic-96	163	2	following	follow	VERB
hjic-96	163	3	example	example	NOUN
hjic-96	163	4	illustrates	illustrate	VERB
hjic-96	163	5	the	the	DET
hjic-96	163	6	calculation	calculation	NOUN
hjic-96	163	7	of	of	ADP
hjic-96	163	8	the	the	DET
hjic-96	163	9	fuzzy	fuzzy	ADJ
hjic-96	163	10	support	support	NOUN
hjic-96	163	11	value	value	NOUN
hjic-96	163	12	.	.	PUNCT
hjic-96	164	1	let	let	VERB
hjic-96	164	2	]	]	X
hjic-96	164	3	high	high	ADJ
hjic-96	164	4	:	:	PUNCT
hjic-96	164	5	income	income	NOUN
hjic-96	164	6	medium	medium	NOUN
hjic-96	164	7	:	:	PUNCT
hjic-96	164	8	balance	balance	NOUN
hjic-96	164	9	[:	[:	X
hjic-96	164	10	u	u	NOUN
hjic-96	164	11	=	=	NOUN
hjic-96	164	12	ax	ax	NOUN
hjic-96	164	13	be	be	VERB
hjic-96	164	14	a	a	DET
hjic-96	164	15	fuzzy	fuzzy	ADJ
hjic-96	164	16	item	item	NOUN
hjic-96	164	17	set	set	VERB
hjic-96	164	18	and	and	CCONJ
hjic-96	164	19	the	the	DET
hjic-96	164	20	example	example	NOUN
hjic-96	164	21	dataset	dataset	NOUN
hjic-96	164	22	is	be	AUX
hjic-96	164	23	shown	show	VERB
hjic-96	164	24	in	in	ADP
hjic-96	164	25	table	table	NOUN
hjic-96	164	26	2	2	NUM
hjic-96	164	27	.	.	PUNCT
hjic-96	164	28	table	table	NOUN
hjic-96	164	29	2	2	NUM
hjic-96	164	30	example	example	NOUN
hjic-96	164	31	database	database	NOUN
hjic-96	164	32	containing	contain	VERB
hjic-96	164	33	memberships	membership	NOUN
hjic-96	164	34	the	the	DET
hjic-96	164	35	fuzzy	fuzzy	ADJ
hjic-96	164	36	support	support	NOUN
hjic-96	164	37	of	of	ADP
hjic-96	164	38	ax	ax	NOUN
hjic-96	164	39	:	:	PUNCT
hjic-96	164	40	is	be	AUX
hjic-96	164	41	calculated	calculate	VERB
hjic-96	164	42	as	as	SCONJ
hjic-96	164	43	follows	follow	VERB
hjic-96	164	44	:	:	PUNCT
hjic-96	164	45	0.3367=	0.3367=	NOUN
hjic-96	164	46	⋅+⋅+⋅	⋅+⋅+⋅	ADJ
hjic-96	164	47	=	=	SYM
hjic-96	164	48	3	3	NUM
hjic-96	164	49	7.07.04.08.04.05.0	7.07.04.08.04.05.0	NUM
hjic-96	164	50	):	):	PUNCT
hjic-96	164	51	(	(	PUNCT
hjic-96	164	52	axfs	axfs	NOUN
hjic-96	164	53	since	since	SCONJ
hjic-96	164	54	the	the	DET
hjic-96	164	55	rules	rule	NOUN
hjic-96	164	56	are	be	AUX
hjic-96	164	57	generated	generate	VERB
hjic-96	164	58	from	from	ADP
hjic-96	164	59	the	the	DET
hjic-96	164	60	frequent	frequent	ADJ
hjic-96	164	61	item	item	NOUN
hjic-96	164	62	sets	set	NOUN
hjic-96	164	63	,	,	PUNCT
hjic-96	164	64	the	the	DET
hjic-96	164	65	generation	generation	NOUN
hjic-96	164	66	of	of	ADP
hjic-96	164	67	fuzzy	fuzzy	ADJ
hjic-96	164	68	association	association	NOUN
hjic-96	164	69	rules	rule	NOUN
hjic-96	164	70	becomes	become	VERB
hjic-96	164	71	relatively	relatively	ADV
hjic-96	164	72	straightforward	straightforward	ADJ
hjic-96	164	73	.	.	PUNCT
hjic-96	165	1	more	more	ADV
hjic-96	165	2	precisely	precisely	ADV
hjic-96	165	3	,	,	PUNCT
hjic-96	165	4	each	each	DET
hjic-96	165	5	frequent	frequent	ADJ
hjic-96	165	6	item	item	NOUN
hjic-96	165	7	set	set	VERB
hjic-96	165	8	cz	cz	NOUN
hjic-96	165	9	:	:	PUNCT
hjic-96	165	10	is	be	AUX
hjic-96	165	11	divided	divide	VERB
hjic-96	165	12	into	into	ADP
hjic-96	165	13	the	the	DET
hjic-96	165	14	consequent	consequent	NOUN
hjic-96	165	15	by	by	ADP
hjic-96	165	16	:	:	PUNCT
hjic-96	165	17	and	and	CCONJ
hjic-96	165	18	antecedent	antecedent	NOUN
hjic-96	165	19	ax	ax	NOUN
hjic-96	165	20	:	:	PUNCT
hjic-96	165	21	,	,	PUNCT
hjic-96	165	22	where	where	SCONJ
hjic-96	165	23	and	and	CCONJ
hjic-96	165	24	.	.	PUNCT
hjic-96	166	1	with	with	ADP
hjic-96	166	2	the	the	DET
hjic-96	166	3	use	use	NOUN
hjic-96	166	4	of	of	ADP
hjic-96	166	5	this	this	DET
hjic-96	166	6	notation	notation	NOUN
hjic-96	166	7	a	a	DET
hjic-96	166	8	fuzzy	fuzzy	ADJ
hjic-96	166	9	association	association	NOUN
hjic-96	166	10	rule	rule	NOUN
hjic-96	166	11	can	can	AUX
hjic-96	166	12	be	be	AUX
hjic-96	166	13	represented	represent	VERB
hjic-96	166	14	in	in	ADP
hjic-96	166	15	the	the	DET
hjic-96	166	16	form	form	NOUN
hjic-96	166	17	of	of	ADP
hjic-96	166	18	caxzyzx	caxzyzx	PROPN
hjic-96	166	19	⊂−=⊂	⊂−=⊂	PRON
hjic-96	166	20	,	,	PUNCT
hjic-96	166	21	,	,	PUNCT
hjic-96	166	22	acb	acb	PROPN
hjic-96	166	23	−=	−=	VERB
hjic-96	166	24	if	if	SCONJ
hjic-96	166	25	x	x	PRON
hjic-96	166	26	is	be	AUX
hjic-96	166	27	a	a	PRON
hjic-96	166	28	,	,	PUNCT
hjic-96	166	29	then	then	ADV
hjic-96	166	30	y	y	PROPN
hjic-96	166	31	is	be	AUX
hjic-96	166	32	b	b	NOUN
hjic-96	166	33	,	,	PUNCT
hjic-96	166	34	(	(	PUNCT
hjic-96	166	35	9	9	NUM
hjic-96	166	36	)	)	PUNCT
hjic-96	166	37	or	or	CCONJ
hjic-96	166	38	in	in	ADP
hjic-96	166	39	more	more	ADJ
hjic-96	166	40	compact	compact	ADJ
hjic-96	166	41	form	form	NOUN
hjic-96	166	42	,	,	PUNCT
hjic-96	166	43	byax	byax	VERB
hjic-96	166	44	:	:	PUNCT
hjic-96	166	45	:	:	PUNCT
hjic-96	166	46	⇒	⇒	NOUN
hjic-96	166	47	.	.	PUNCT
hjic-96	167	1	(	(	PUNCT
hjic-96	167	2	10	10	NUM
hjic-96	167	3	)	)	PUNCT
hjic-96	167	4	a	a	DET
hjic-96	167	5	fuzzy	fuzzy	ADJ
hjic-96	167	6	association	association	NOUN
hjic-96	167	7	rule	rule	NOUN
hjic-96	167	8	is	be	AUX
hjic-96	167	9	considered	consider	VERB
hjic-96	167	10	strong	strong	ADJ
hjic-96	167	11	if	if	SCONJ
hjic-96	167	12	its	its	PRON
hjic-96	167	13	support	support	NOUN
hjic-96	167	14	and	and	CCONJ
hjic-96	167	15	confidence	confidence	NOUN
hjic-96	167	16	exceeds	exceed	VERB
hjic-96	167	17	the	the	DET
hjic-96	167	18	given	give	VERB
hjic-96	167	19	minimum	minimum	ADJ
hjic-96	167	20	support	support	NOUN
hjic-96	167	21	(	(	PUNCT
hjic-96	167	22	σ	σ	NOUN
hjic-96	167	23	)	)	PUNCT
hjic-96	167	24	and	and	CCONJ
hjic-96	167	25	minimum	minimum	NOUN
hjic-96	167	26	confidence	confidence	NOUN
hjic-96	167	27	(	(	PUNCT
hjic-96	167	28	γ	γ	PROPN
hjic-96	167	29	)	)	PUNCT
hjic-96	167	30	.	.	PUNCT
hjic-96	168	1	since	since	SCONJ
hjic-96	168	2	the	the	DET
hjic-96	168	3	rules	rule	NOUN
hjic-96	168	4	are	be	AUX
hjic-96	168	5	generated	generate	VERB
hjic-96	168	6	from	from	ADP
hjic-96	168	7	frequent	frequent	ADJ
hjic-96	168	8	item	item	NOUN
hjic-96	168	9	sets	set	NOUN
hjic-96	168	10	,	,	PUNCT
hjic-96	168	11	they	they	PRON
hjic-96	168	12	satisfy	satisfy	VERB
hjic-96	168	13	the	the	DET
hjic-96	168	14	minimum	minimum	ADJ
hjic-96	168	15	support	support	NOUN
hjic-96	168	16	automatically	automatically	ADV
hjic-96	168	17	.	.	PUNCT
hjic-96	169	1	the	the	DET
hjic-96	169	2	fuzzy	fuzzy	ADJ
hjic-96	169	3	confidence	confidence	NOUN
hjic-96	169	4	of	of	ADP
hjic-96	169	5	a	a	DET
hjic-96	169	6	fuzzy	fuzzy	ADJ
hjic-96	169	7	association	association	NOUN
hjic-96	169	8	rule	rule	NOUN
hjic-96	169	9	byax	byax	NOUN
hjic-96	169	10	:	:	PUNCT
hjic-96	169	11	:	:	PUNCT
hjic-96	169	12	⇒	⇒	NOUN
hjic-96	169	13	is	be	AUX
hjic-96	169	14	defined	define	VERB
hjic-96	169	15	as	as	ADP
hjic-96	169	16	)	)	PUNCT
hjic-96	169	17	:(	:(	PUNCT
hjic-96	169	18	):	):	PUNCT
hjic-96	169	19	:	:	PUNCT
hjic-96	169	20	(	(	PUNCT
hjic-96	169	21	)	)	PUNCT
hjic-96	169	22	:	:	PUNCT
hjic-96	169	23	:(	:(	PUNCT
hjic-96	169	24	axfs	axfs	NOUN
hjic-96	169	25	byaxfs	byaxfs	NOUN
hjic-96	169	26	byaxfc	byaxfc	AUX
hjic-96	169	27	⇒	⇒	VERB
hjic-96	169	28	=	=	PRON
hjic-96	169	29	⇒	⇒	NOUN
hjic-96	169	30	(	(	PUNCT
hjic-96	169	31	11	11	NUM
hjic-96	169	32	)	)	PUNCT
hjic-96	169	33	and	and	CCONJ
hjic-96	169	34	it	it	PRON
hjic-96	169	35	is	be	AUX
hjic-96	169	36	a	a	DET
hjic-96	169	37	conditional	conditional	ADJ
hjic-96	169	38	probability	probability	NOUN
hjic-96	169	39	of	of	ADP
hjic-96	169	40	the	the	DET
hjic-96	169	41	parts	part	NOUN
hjic-96	169	42	of	of	ADP
hjic-96	169	43	the	the	DET
hjic-96	169	44	rule	rule	NOUN
hjic-96	169	45	:	:	PUNCT
hjic-96	169	46	(	(	PUNCT
hjic-96	169	47	)	)	PUNCT
hjic-96	169	48	axbyp	axbyp	VERB
hjic-96	169	49	:|	:|	X
hjic-96	169	50	:	:	PUNCT
hjic-96	169	51	.	.	PUNCT
hjic-96	170	1	fuzzy	fuzzy	ADJ
hjic-96	170	2	association	association	NOUN
hjic-96	170	3	rules	rule	NOUN
hjic-96	170	4	mined	mine	VERB
hjic-96	170	5	using	use	VERB
hjic-96	170	6	the	the	DET
hjic-96	170	7	above	above	ADJ
hjic-96	170	8	fuzzy	fuzzy	ADJ
hjic-96	170	9	support	support	NOUN
hjic-96	170	10	-	-	PUNCT
hjic-96	170	11	confidence	confidence	NOUN
hjic-96	170	12	framework	framework	NOUN
hjic-96	170	13	are	be	AUX
hjic-96	170	14	useful	useful	ADJ
hjic-96	170	15	for	for	ADP
hjic-96	170	16	many	many	ADJ
hjic-96	170	17	applications	application	NOUN
hjic-96	170	18	.	.	PUNCT
hjic-96	171	1	however	however	ADV
hjic-96	171	2	,	,	PUNCT
hjic-96	171	3	a	a	DET
hjic-96	171	4	rule	rule	NOUN
hjic-96	171	5	might	might	AUX
hjic-96	171	6	be	be	AUX
hjic-96	171	7	identified	identify	VERB
hjic-96	171	8	as	as	ADP
hjic-96	171	9	interesting	interesting	ADJ
hjic-96	171	10	when	when	SCONJ
hjic-96	171	11	,	,	PUNCT
hjic-96	171	12	in	in	ADP
hjic-96	171	13	fact	fact	NOUN
hjic-96	171	14	,	,	PUNCT
hjic-96	171	15	the	the	DET
hjic-96	171	16	occurrence	occurrence	NOUN
hjic-96	171	17	ax	ax	NOUN
hjic-96	171	18	:	:	PUNCT
hjic-96	171	19	does	do	AUX
hjic-96	171	20	not	not	PART
hjic-96	171	21	imply	imply	VERB
hjic-96	171	22	the	the	DET
hjic-96	171	23	occurrence	occurrence	NOUN
hjic-96	171	24	of	of	ADP
hjic-96	171	25	by	by	ADP
hjic-96	171	26	:	:	PUNCT
hjic-96	171	27	.	.	PUNCT
hjic-96	172	1	the	the	DET
hjic-96	172	2	occurrence	occurrence	NOUN
hjic-96	172	3	of	of	ADP
hjic-96	172	4	a	a	DET
hjic-96	172	5	fuzzy	fuzzy	ADJ
hjic-96	172	6	item	item	NOUN
hjic-96	172	7	set	set	NOUN
hjic-96	172	8	ax	ax	NOUN
hjic-96	172	9	:	:	PUNCT
hjic-96	172	10	is	be	AUX
hjic-96	172	11	independent	independent	ADJ
hjic-96	172	12	of	of	ADP
hjic-96	172	13	the	the	DET
hjic-96	172	14	item	item	NOUN
hjic-96	172	15	set	set	VERB
hjic-96	172	16	by	by	ADP
hjic-96	172	17	:	:	PUNCT
hjic-96	172	18	if	if	SCONJ
hjic-96	172	19	b	b	X
hjic-96	172	20	)	)	PUNCT
hjic-96	172	21	,	,	PUNCT
hjic-96	172	22	:	:	PUNCT
hjic-96	172	23	fs(y	fs(y	PROPN
hjic-96	172	24	a	a	X
hjic-96	172	25	)	)	PUNCT
hjic-96	172	26	:	:	PUNCT
hjic-96	172	27	fs(x	fs(x	PUNCT
hjic-96	172	28	c	c	NOUN
hjic-96	172	29	)	)	PUNCT
hjic-96	172	30	:	:	PUNCT
hjic-96	172	31	fs(z	fs(z	X
hjic-96	172	32	⋅=	⋅=	PROPN
hjic-96	172	33	otherwise	otherwise	ADV
hjic-96	172	34	item	item	NOUN
hjic-96	172	35	sets	set	VERB
hjic-96	172	36	ax	ax	NOUN
hjic-96	172	37	:	:	PUNCT
hjic-96	172	38	and	and	CCONJ
hjic-96	172	39	by	by	ADP
hjic-96	172	40	:	:	PUNCT
hjic-96	172	41	are	be	AUX
hjic-96	172	42	dependent	dependent	ADJ
hjic-96	172	43	and	and	CCONJ
hjic-96	172	44	correlated	correlate	VERB
hjic-96	172	45	as	as	ADP
hjic-96	172	46	events	event	NOUN
hjic-96	172	47	.	.	PUNCT
hjic-96	173	1	the	the	DET
hjic-96	173	2	correlation	correlation	NOUN
hjic-96	173	3	between	between	ADP
hjic-96	173	4	the	the	DET
hjic-96	173	5	occurrence	occurrence	NOUN
hjic-96	173	6	of	of	ADP
hjic-96	173	7	ax	ax	NOUN
hjic-96	173	8	:	:	PUNCT
hjic-96	173	9	and	and	CCONJ
hjic-96	173	10	by	by	ADP
hjic-96	173	11	:	:	PUNCT
hjic-96	173	12	can	can	AUX
hjic-96	173	13	be	be	AUX
hjic-96	173	14	measured	measure	VERB
hjic-96	173	15	by	by	ADP
hjic-96	173	16	computing	compute	VERB
hjic-96	173	17	the	the	DET
hjic-96	173	18	interestingness	interestingness	NOUN
hjic-96	173	19	of	of	ADP
hjic-96	173	20	a	a	DET
hjic-96	173	21	given	give	VERB
hjic-96	173	22	rule	rule	NOUN
hjic-96	173	23	:	:	PUNCT
hjic-96	173	24	(	(	PUNCT
hjic-96	173	25	)	)	PUNCT
hjic-96	173	26	)	)	PUNCT
hjic-96	174	1	:()	:()	PUNCT
hjic-96	174	2	:	:	PUNCT
hjic-96	174	3	(	(	PUNCT
hjic-96	174	4	)	)	PUNCT
hjic-96	174	5	:	:	PUNCT
hjic-96	174	6	(:	(:	VERB
hjic-96	174	7	,	,	PUNCT
hjic-96	174	8	:	:	PUNCT
hjic-96	174	9	byfsaxfs	byfsaxfs	PROPN
hjic-96	174	10	czfsbyaxfcorr	czfsbyaxfcorr	NOUN
hjic-96	174	11	⋅	⋅	PROPN
hjic-96	174	12	=	=	SYM
hjic-96	174	13	(	(	PUNCT
hjic-96	174	14	12	12	NUM
hjic-96	174	15	)	)	PUNCT
hjic-96	174	16	balance	balance	NOUN
hjic-96	174	17	:	:	PUNCT
hjic-96	174	18	med	med	PROPN
hjic-96	174	19	.	.	PUNCT
hjic-96	175	1	credit	credit	NOUN
hjic-96	175	2	:	:	PUNCT
hjic-96	175	3	high	high	ADJ
hjic-96	175	4	income	income	NOUN
hjic-96	175	5	:	:	PUNCT
hjic-96	175	6	high	high	ADJ
hjic-96	175	7	0.5	0.5	NUM
hjic-96	175	8	0.6	0.6	NUM
hjic-96	175	9	0.4	0.4	NUM
hjic-96	175	10	0.8	0.8	NUM
hjic-96	175	11	0.9	0.9	NUM
hjic-96	175	12	0.4	0.4	NUM
hjic-96	175	13	0.7	0.7	NUM
hjic-96	175	14	0.8	0.8	NUM
hjic-96	175	15	0.7	0.7	NUM
hjic-96	175	16	if	if	SCONJ
hjic-96	175	17	the	the	DET
hjic-96	175	18	resulting	result	VERB
hjic-96	175	19	value	value	NOUN
hjic-96	175	20	of	of	ADP
hjic-96	175	21	eq	eq	PROPN
hjic-96	175	22	.	.	PROPN
hjic-96	175	23	12	12	NUM
hjic-96	175	24	is	be	AUX
hjic-96	175	25	less	less	ADJ
hjic-96	175	26	than	than	ADP
hjic-96	175	27	one	one	NUM
hjic-96	175	28	,	,	PUNCT
hjic-96	175	29	the	the	DET
hjic-96	175	30	occurrence	occurrence	NOUN
hjic-96	175	31	of	of	ADP
hjic-96	175	32	ax	ax	NOUN
hjic-96	175	33	:	:	PUNCT
hjic-96	175	34	is	be	AUX
hjic-96	175	35	negatively	negatively	ADV
hjic-96	175	36	correlated	correlate	VERB
hjic-96	175	37	with	with	ADP
hjic-96	175	38	the	the	DET
hjic-96	175	39	occurrence	occurrence	NOUN
hjic-96	175	40	of	of	ADP
hjic-96	175	41	by	by	ADP
hjic-96	175	42	:	:	PUNCT
hjic-96	175	43	.	.	PUNCT
hjic-96	176	1	if	if	SCONJ
hjic-96	176	2	the	the	DET
hjic-96	176	3	resulting	result	VERB
hjic-96	176	4	value	value	NOUN
hjic-96	176	5	is	be	AUX
hjic-96	176	6	greater	great	ADJ
hjic-96	176	7	than	than	ADP
hjic-96	176	8	one	one	NUM
hjic-96	176	9	,	,	PUNCT
hjic-96	176	10	ax	ax	NOUN
hjic-96	176	11	:	:	PUNCT
hjic-96	176	12	and	and	CCONJ
hjic-96	176	13	by	by	ADP
hjic-96	176	14	:	:	PUNCT
hjic-96	176	15	are	be	AUX
hjic-96	176	16	positively	positively	ADV
hjic-96	176	17	correlated	correlate	VERB
hjic-96	176	18	.	.	PUNCT
hjic-96	177	1	it	it	PRON
hjic-96	177	2	means	mean	VERB
hjic-96	177	3	the	the	DET
hjic-96	177	4	occurrence	occurrence	NOUN
hjic-96	177	5	of	of	ADP
hjic-96	177	6	one	one	NUM
hjic-96	177	7	implies	imply	VERB
hjic-96	177	8	the	the	DET
hjic-96	177	9	other	other	ADJ
hjic-96	177	10	.	.	PUNCT
hjic-96	178	1	if	if	SCONJ
hjic-96	178	2	the	the	DET
hjic-96	178	3	resulting	result	VERB
hjic-96	178	4	value	value	NOUN
hjic-96	178	5	is	be	AUX
hjic-96	178	6	near	near	ADJ
hjic-96	178	7	to	to	ADP
hjic-96	178	8	one	one	NUM
hjic-96	178	9	,	,	PUNCT
hjic-96	178	10	then	then	ADV
hjic-96	178	11	ax	ax	VERB
hjic-96	178	12	:	:	PUNCT
hjic-96	178	13	and	and	CCONJ
hjic-96	178	14	by	by	ADP
hjic-96	178	15	:	:	PUNCT
hjic-96	178	16	are	be	AUX
hjic-96	178	17	independent	independent	ADJ
hjic-96	178	18	and	and	CCONJ
hjic-96	178	19	there	there	PRON
hjic-96	178	20	is	be	VERB
hjic-96	178	21	no	no	DET
hjic-96	178	22	correlation	correlation	NOUN
hjic-96	178	23	between	between	ADP
hjic-96	178	24	them	they	PRON
hjic-96	178	25	.	.	PUNCT
hjic-96	179	1	after	after	ADP
hjic-96	179	2	the	the	DET
hjic-96	179	3	review	review	NOUN
hjic-96	179	4	of	of	ADP
hjic-96	179	5	basics	basic	NOUN
hjic-96	179	6	of	of	ADP
hjic-96	179	7	association	association	NOUN
hjic-96	179	8	rule	rule	NOUN
hjic-96	179	9	mining	mining	NOUN
hjic-96	179	10	,	,	PUNCT
hjic-96	179	11	the	the	DET
hjic-96	179	12	next	next	ADJ
hjic-96	179	13	section	section	NOUN
hjic-96	179	14	presents	present	VERB
hjic-96	179	15	how	how	SCONJ
hjic-96	179	16	use	use	VERB
hjic-96	179	17	the	the	DET
hjic-96	179	18	fuzzy	fuzzy	ADJ
hjic-96	179	19	association	association	NOUN
hjic-96	179	20	rules	rule	NOUN
hjic-96	179	21	for	for	ADP
hjic-96	179	22	model	model	NOUN
hjic-96	179	23	structure	structure	NOUN
hjic-96	179	24	selection	selection	NOUN
hjic-96	179	25	.	.	PUNCT
hjic-96	180	1	mossfarm	mossfarm	VERB
hjic-96	180	2	model	model	NOUN
hjic-96	180	3	structure	structure	NOUN
hjic-96	180	4	selection	selection	NOUN
hjic-96	180	5	by	by	ADP
hjic-96	180	6	fuzzy	fuzzy	ADJ
hjic-96	180	7	association	association	NOUN
hjic-96	180	8	rule	rule	NOUN
hjic-96	180	9	mining	mining	NOUN
hjic-96	180	10	since	since	SCONJ
hjic-96	180	11	in	in	ADP
hjic-96	180	12	the	the	DET
hjic-96	180	13	previous	previous	ADJ
hjic-96	180	14	section	section	NOUN
hjic-96	180	15	all	all	PRON
hjic-96	180	16	of	of	ADP
hjic-96	180	17	the	the	DET
hjic-96	180	18	necessary	necessary	ADJ
hjic-96	180	19	definitions	definition	NOUN
hjic-96	180	20	and	and	CCONJ
hjic-96	180	21	methods	method	NOUN
hjic-96	180	22	to	to	PART
hjic-96	180	23	mine	mine	VERB
hjic-96	180	24	fuzzy	fuzzy	ADJ
hjic-96	180	25	association	association	NOUN
hjic-96	180	26	rules	rule	NOUN
hjic-96	180	27	were	be	AUX
hjic-96	180	28	considered	consider	VERB
hjic-96	180	29	,	,	PUNCT
hjic-96	180	30	this	this	DET
hjic-96	180	31	section	section	NOUN
hjic-96	180	32	will	will	AUX
hjic-96	180	33	focus	focus	VERB
hjic-96	180	34	on	on	ADP
hjic-96	180	35	the	the	DET
hjic-96	180	36	main	main	ADJ
hjic-96	180	37	steps	step	NOUN
hjic-96	180	38	of	of	ADP
hjic-96	180	39	our	our	PRON
hjic-96	180	40	method	method	NOUN
hjic-96	180	41	that	that	PRON
hjic-96	180	42	are	be	AUX
hjic-96	180	43	needed	need	VERB
hjic-96	180	44	to	to	PART
hjic-96	180	45	solve	solve	VERB
hjic-96	180	46	the	the	DET
hjic-96	180	47	studied	studied	ADJ
hjic-96	180	48	model	model	NOUN
hjic-96	180	49	structure	structure	NOUN
hjic-96	180	50	(	(	PUNCT
hjic-96	180	51	order	order	NOUN
hjic-96	180	52	)	)	PUNCT
hjic-96	180	53	selection	selection	NOUN
hjic-96	180	54	problem	problem	NOUN
hjic-96	180	55	in	in	ADP
hjic-96	180	56	case	case	NOUN
hjic-96	180	57	of	of	ADP
hjic-96	180	58	narx	narx	PROPN
hjic-96	180	59	model	model	NOUN
hjic-96	180	60	.	.	PUNCT
hjic-96	181	1	62	62	NUM
hjic-96	181	2	suppose	suppose	VERB
hjic-96	181	3	that	that	SCONJ
hjic-96	181	4	we	we	PRON
hjic-96	181	5	have	have	AUX
hjic-96	181	6	only	only	ADV
hjic-96	181	7	measured	measure	VERB
hjic-96	181	8	input	input	NOUN
hjic-96	181	9	-	-	PUNCT
hjic-96	181	10	output	output	NOUN
hjic-96	181	11	data	datum	NOUN
hjic-96	181	12	from	from	ADP
hjic-96	181	13	a	a	DET
hjic-96	181	14	siso	siso	NOUN
hjic-96	181	15	process	process	NOUN
hjic-96	181	16	.	.	PUNCT
hjic-96	182	1	in	in	ADP
hjic-96	182	2	a	a	DET
hjic-96	182	3	narx	narx	NOUN
hjic-96	182	4	model	model	NOUN
hjic-96	182	5	of	of	ADP
hjic-96	182	6	the	the	DET
hjic-96	182	7	process	process	NOUN
hjic-96	182	8	,	,	PUNCT
hjic-96	182	9	from	from	ADP
hjic-96	182	10	this	this	DET
hjic-96	182	11	i	i	PROPN
hjic-96	182	12	/	/	SYM
hjic-96	182	13	o	o	NOUN
hjic-96	182	14	data	datum	NOUN
hjic-96	182	15	set	set	VERB
hjic-96	182	16	we	we	PRON
hjic-96	182	17	can	can	AUX
hjic-96	182	18	construct	construct	VERB
hjic-96	182	19	a	a	DET
hjic-96	182	20	regression	regression	NOUN
hjic-96	182	21	vector	vector	NOUN
hjic-96	182	22	from	from	ADP
hjic-96	182	23	each	each	DET
hjic-96	182	24	input	input	NOUN
hjic-96	182	25	-	-	PUNCT
hjic-96	182	26	output	output	NOUN
hjic-96	182	27	data	datum	NOUN
hjic-96	182	28	pairs	pair	NOUN
hjic-96	182	29	by	by	ADP
hjic-96	182	30	the	the	DET
hjic-96	182	31	following	following	ADJ
hjic-96	182	32	way	way	NOUN
hjic-96	182	33	,	,	PUNCT
hjic-96	182	34	similar	similar	ADJ
hjic-96	182	35	for	for	ADP
hjic-96	182	36	eq	eq	PROPN
hjic-96	182	37	.	.	PROPN
hjic-96	183	1	5	5	NUM
hjic-96	183	2	:	:	PUNCT
hjic-96	183	3	nk	nk	PROPN
hjic-96	183	4	,	,	PUNCT
hjic-96	183	5	,	,	PUNCT
hjic-96	183	6	1k=	1k=	NUM
hjic-96	183	7	t	t	NOUN
hjic-96	183	8	nkkkmkkkk	nkkkmkkkk	ADP
hjic-96	183	9	uuuyyy	uuuyyy	PROPN
hjic-96	183	10	]	]	X
hjic-96	183	11	,	,	PUNCT
hjic-96	183	12	,	,	PUNCT
hjic-96	183	13	,	,	PUNCT
hjic-96	183	14	,	,	PUNCT
hjic-96	183	15	[	[	PUNCT
hjic-96	183	16	,	,	PUNCT
hjic-96	183	17	2,12,1	2,12,1	NUM
hjic-96	183	18	−−−−−−=	−−−−−−=	PRON
hjic-96	183	19	kkx	kkx	PROPN
hjic-96	183	20	where	where	SCONJ
hjic-96	183	21	the	the	DET
hjic-96	183	22	past	past	ADJ
hjic-96	183	23	values	value	NOUN
hjic-96	183	24	of	of	ADP
hjic-96	183	25	the	the	DET
hjic-96	183	26	process	process	NOUN
hjic-96	183	27	outputs	output	NOUN
hjic-96	183	28	and	and	CCONJ
hjic-96	183	29	the	the	DET
hjic-96	183	30	process	process	NOUN
hjic-96	183	31	inputs	input	NOUN
hjic-96	183	32	are	be	AUX
hjic-96	183	33	the	the	DET
hjic-96	183	34	regressors	regressor	NOUN
hjic-96	183	35	.	.	PUNCT
hjic-96	184	1	the	the	DET
hjic-96	184	2	number	number	NOUN
hjic-96	184	3	of	of	ADP
hjic-96	184	4	past	past	ADJ
hjic-96	184	5	inputs	input	NOUN
hjic-96	184	6	(	(	PUNCT
hjic-96	184	7	n	n	CCONJ
hjic-96	184	8	)	)	PUNCT
hjic-96	184	9	and	and	CCONJ
hjic-96	184	10	past	past	ADP
hjic-96	184	11	outputs	output	NOUN
hjic-96	184	12	(	(	PUNCT
hjic-96	184	13	m	m	NOUN
hjic-96	184	14	)	)	PUNCT
hjic-96	184	15	are	be	AUX
hjic-96	184	16	often	often	ADV
hjic-96	184	17	referred	refer	VERB
hjic-96	184	18	to	to	ADP
hjic-96	184	19	as	as	ADP
hjic-96	184	20	model	model	NOUN
hjic-96	184	21	order	order	NOUN
hjic-96	184	22	.	.	PUNCT
hjic-96	185	1	ky	ky	PROPN
hjic-96	185	2	ku	ku	PROPN
hjic-96	185	3	the	the	DET
hjic-96	185	4	question	question	NOUN
hjic-96	185	5	is	be	AUX
hjic-96	185	6	how	how	SCONJ
hjic-96	185	7	to	to	PART
hjic-96	185	8	select	select	VERB
hjic-96	185	9	the	the	DET
hjic-96	185	10	right	right	ADJ
hjic-96	185	11	model	model	NOUN
hjic-96	185	12	order	order	NOUN
hjic-96	185	13	?	?	PUNCT
hjic-96	186	1	an	an	DET
hjic-96	186	2	answer	answer	NOUN
hjic-96	186	3	could	could	AUX
hjic-96	186	4	be	be	AUX
hjic-96	186	5	our	our	PRON
hjic-96	186	6	method	method	NOUN
hjic-96	186	7	,	,	PUNCT
hjic-96	186	8	the	the	DET
hjic-96	186	9	mossfarm	mossfarm	NOUN
hjic-96	186	10	.	.	PUNCT
hjic-96	187	1	the	the	DET
hjic-96	187	2	method	method	NOUN
hjic-96	187	3	consists	consist	VERB
hjic-96	187	4	of	of	ADP
hjic-96	187	5	the	the	DET
hjic-96	187	6	following	follow	VERB
hjic-96	187	7	five	five	NUM
hjic-96	187	8	steps	step	NOUN
hjic-96	187	9	:	:	PUNCT
hjic-96	187	10	1	1	NUM
hjic-96	187	11	)	)	PUNCT
hjic-96	187	12	generate	generate	VERB
hjic-96	187	13	a	a	DET
hjic-96	187	14	fuzzy	fuzzy	ADJ
hjic-96	187	15	database	database	NOUN
hjic-96	187	16	2	2	NUM
hjic-96	187	17	)	)	PUNCT
hjic-96	187	18	mine	mine	NOUN
hjic-96	187	19	frequent	frequent	ADJ
hjic-96	187	20	fuzzy	fuzzy	ADJ
hjic-96	187	21	item	item	NOUN
hjic-96	187	22	sets	set	VERB
hjic-96	187	23	3	3	NUM
hjic-96	187	24	)	)	PUNCT
hjic-96	187	25	generate	generate	VERB
hjic-96	187	26	fuzzy	fuzzy	ADJ
hjic-96	187	27	association	association	NOUN
hjic-96	187	28	rules	rule	NOUN
hjic-96	187	29	4	4	NUM
hjic-96	187	30	)	)	PUNCT
hjic-96	187	31	prune	prune	NOUN
hjic-96	187	32	the	the	DET
hjic-96	187	33	fuzzy	fuzzy	ADJ
hjic-96	187	34	rule	rule	NOUN
hjic-96	187	35	base	base	NOUN
hjic-96	187	36	5	5	NUM
hjic-96	187	37	)	)	PUNCT
hjic-96	187	38	aggregate	aggregate	VERB
hjic-96	187	39	the	the	DET
hjic-96	187	40	mined	mine	VERB
hjic-96	187	41	rules	rule	NOUN
hjic-96	187	42	,	,	PUNCT
hjic-96	187	43	select	select	VERB
hjic-96	187	44	the	the	DET
hjic-96	187	45	model	model	NOUN
hjic-96	187	46	structure	structure	NOUN
hjic-96	187	47	step	step	NOUN
hjic-96	187	48	1	1	NUM
hjic-96	187	49	)	)	PUNCT
hjic-96	187	50	observed	observed	ADJ
hjic-96	187	51	(	(	PUNCT
hjic-96	187	52	measured	measured	ADJ
hjic-96	187	53	)	)	PUNCT
hjic-96	187	54	input	input	NOUN
hjic-96	187	55	-	-	PUNCT
hjic-96	187	56	output	output	NOUN
hjic-96	187	57	data	datum	NOUN
hjic-96	187	58	are	be	AUX
hjic-96	187	59	general	general	ADJ
hjic-96	187	60	crisp	crisp	ADJ
hjic-96	187	61	values	value	NOUN
hjic-96	187	62	.	.	PUNCT
hjic-96	188	1	in	in	ADP
hjic-96	188	2	the	the	DET
hjic-96	188	3	first	first	ADJ
hjic-96	188	4	step	step	NOUN
hjic-96	188	5	the	the	DET
hjic-96	188	6	“	"	PUNCT
hjic-96	188	7	attributes	attribute	NOUN
hjic-96	188	8	”	"	PUNCT
hjic-96	188	9	(	(	PUNCT
hjic-96	188	10	regressors	regressor	NOUN
hjic-96	188	11	in	in	ADP
hjic-96	188	12	the	the	DET
hjic-96	188	13	regression	regression	NOUN
hjic-96	188	14	vector	vector	NOUN
hjic-96	188	15	)	)	PUNCT
hjic-96	188	16	need	need	VERB
hjic-96	188	17	to	to	PART
hjic-96	188	18	partition	partition	VERB
hjic-96	188	19	to	to	PART
hjic-96	188	20	get	get	VERB
hjic-96	188	21	fuzzy	fuzzy	ADJ
hjic-96	188	22	valued	value	VERB
hjic-96	188	23	data	datum	NOUN
hjic-96	188	24	set	set	VERB
hjic-96	188	25	.	.	PUNCT
hjic-96	189	1	the	the	DET
hjic-96	189	2	fuzzy	fuzzy	ADJ
hjic-96	189	3	gustafson	gustafson	PROPN
hjic-96	189	4	-	-	PUNCT
hjic-96	189	5	kessel	kessel	PROPN
hjic-96	189	6	(	(	PUNCT
hjic-96	189	7	gk	gk	PROPN
hjic-96	189	8	)	)	PUNCT
hjic-96	190	1	[	[	X
hjic-96	190	2	33	33	NUM
hjic-96	190	3	]	]	PUNCT
hjic-96	190	4	clustering	clustering	ADJ
hjic-96	190	5	algorithm	algorithm	NOUN
hjic-96	190	6	partitions	partition	VERB
hjic-96	190	7	the	the	DET
hjic-96	190	8	initial	initial	ADJ
hjic-96	190	9	data	datum	NOUN
hjic-96	190	10	on	on	ADP
hjic-96	190	11	every	every	DET
hjic-96	190	12	attribute	attribute	NOUN
hjic-96	190	13	(	(	PUNCT
hjic-96	190	14	dimension	dimension	NOUN
hjic-96	190	15	of	of	ADP
hjic-96	190	16	data	datum	NOUN
hjic-96	190	17	~	~	PUNCT
hjic-96	190	18	all	all	DET
hjic-96	190	19	the	the	DET
hjic-96	190	20	candidate	candidate	NOUN
hjic-96	190	21	regressors	regressor	NOUN
hjic-96	190	22	)	)	PUNCT
hjic-96	190	23	.	.	PUNCT
hjic-96	191	1	the	the	DET
hjic-96	191	2	resulted	resulted	ADJ
hjic-96	191	3	membership	membership	NOUN
hjic-96	191	4	functions	function	NOUN
hjic-96	191	5	are	be	AUX
hjic-96	191	6	transformed	transform	VERB
hjic-96	191	7	into	into	ADP
hjic-96	191	8	trapezoidal	trapezoidal	ADJ
hjic-96	191	9	membership	membership	NOUN
hjic-96	191	10	functions	function	NOUN
hjic-96	191	11	(	(	PUNCT
hjic-96	191	12	see	see	VERB
hjic-96	191	13	an	an	DET
hjic-96	191	14	example	example	NOUN
hjic-96	191	15	in	in	ADP
hjic-96	191	16	fig	fig	NOUN
hjic-96	191	17	.	.	PUNCT
hjic-96	192	1	4	4	NUM
hjic-96	192	2	where	where	SCONJ
hjic-96	192	3	on	on	ADP
hjic-96	192	4	two	two	NUM
hjic-96	192	5	attributes	attribute	NOUN
hjic-96	192	6	are	be	AUX
hjic-96	192	7	four	four	NUM
hjic-96	192	8	and	and	CCONJ
hjic-96	192	9	three	three	NUM
hjic-96	192	10	fuzzy	fuzzy	ADJ
hjic-96	192	11	sets	set	NOUN
hjic-96	192	12	,	,	PUNCT
hjic-96	192	13	respectively	respectively	ADV
hjic-96	192	14	)	)	PUNCT
hjic-96	192	15	.	.	PUNCT
hjic-96	193	1	0	0	NUM
hjic-96	193	2	0.5	0.5	NUM
hjic-96	193	3	1	1	NUM
hjic-96	193	4	0	0	NUM
hjic-96	193	5	0.5	0.5	NUM
hjic-96	193	6	1	1	NUM
hjic-96	193	7	0	0	NUM
hjic-96	193	8	0.5	0.5	NUM
hjic-96	193	9	1	1	NUM
hjic-96	193	10	0	0	NUM
hjic-96	193	11	0.5	0.5	NUM
hjic-96	193	12	1	1	NUM
hjic-96	193	13	0	0	NUM
hjic-96	193	14	1	1	NUM
hjic-96	193	15	1	1	NUM
hjic-96	193	16	fig.4	fig.4	PROPN
hjic-96	193	17	trapezoidal	trapezoidal	ADJ
hjic-96	193	18	membership	membership	NOUN
hjic-96	193	19	functions	function	NOUN
hjic-96	193	20	step	step	VERB
hjic-96	193	21	2	2	NUM
hjic-96	193	22	)	)	PUNCT
hjic-96	193	23	the	the	DET
hjic-96	193	24	resulted	result	VERB
hjic-96	193	25	fuzzy	fuzzy	ADJ
hjic-96	193	26	data	datum	NOUN
hjic-96	193	27	set	set	VERB
hjic-96	193	28	includes	include	VERB
hjic-96	193	29	the	the	DET
hjic-96	193	30	membership	membership	NOUN
hjic-96	193	31	function	function	NOUN
hjic-96	193	32	values	value	NOUN
hjic-96	193	33	of	of	ADP
hjic-96	193	34	each	each	DET
hjic-96	193	35	data	datum	NOUN
hjic-96	193	36	points	point	NOUN
hjic-96	193	37	on	on	ADP
hjic-96	193	38	each	each	DET
hjic-96	193	39	attributes	attribute	NOUN
hjic-96	193	40	,	,	PUNCT
hjic-96	193	41	and	and	CCONJ
hjic-96	193	42	the	the	DET
hjic-96	193	43	index	index	NOUN
hjic-96	193	44	of	of	ADP
hjic-96	193	45	fuzzy	fuzzy	ADJ
hjic-96	193	46	set	set	NOUN
hjic-96	193	47	which	which	PRON
hjic-96	193	48	give	give	VERB
hjic-96	193	49	the	the	DET
hjic-96	193	50	highest	high	ADJ
hjic-96	193	51	membership	membership	NOUN
hjic-96	193	52	value	value	NOUN
hjic-96	193	53	for	for	ADP
hjic-96	193	54	the	the	DET
hjic-96	193	55	data	data	NOUN
hjic-96	193	56	point	point	NOUN
hjic-96	193	57	in	in	ADP
hjic-96	193	58	a	a	DET
hjic-96	193	59	given	give	VERB
hjic-96	193	60	attribute	attribute	NOUN
hjic-96	193	61	.	.	PUNCT
hjic-96	194	1	these	these	DET
hjic-96	194	2	indices	index	NOUN
hjic-96	194	3	can	can	AUX
hjic-96	194	4	be	be	AUX
hjic-96	194	5	the	the	DET
hjic-96	194	6	items	item	NOUN
hjic-96	194	7	and	and	CCONJ
hjic-96	194	8	the	the	DET
hjic-96	194	9	set	set	NOUN
hjic-96	194	10	of	of	ADP
hjic-96	194	11	them	they	PRON
hjic-96	194	12	are	be	AUX
hjic-96	194	13	the	the	DET
hjic-96	194	14	item	item	NOUN
hjic-96	194	15	sets	set	NOUN
hjic-96	194	16	.	.	PUNCT
hjic-96	195	1	the	the	DET
hjic-96	195	2	frequent	frequent	ADJ
hjic-96	195	3	item	item	NOUN
hjic-96	195	4	set	set	VERB
hjic-96	195	5	searching	searching	NOUN
hjic-96	195	6	is	be	AUX
hjic-96	195	7	based	base	VERB
hjic-96	195	8	on	on	ADP
hjic-96	195	9	a	a	DET
hjic-96	195	10	fuzzy	fuzzy	ADJ
hjic-96	195	11	implementation	implementation	NOUN
hjic-96	195	12	of	of	ADP
hjic-96	195	13	the	the	DET
hjic-96	195	14	apriori	apriori	ADJ
hjic-96	195	15	algorithm	algorithm	NOUN
hjic-96	195	16	.	.	PUNCT
hjic-96	196	1	the	the	DET
hjic-96	196	2	fuzzy	fuzzy	ADJ
hjic-96	196	3	support	support	NOUN
hjic-96	196	4	values	value	NOUN
hjic-96	196	5	are	be	AUX
hjic-96	196	6	calculated	calculate	VERB
hjic-96	196	7	as	as	ADP
hjic-96	196	8	the	the	DET
hjic-96	196	9	eq	eq	NOUN
hjic-96	196	10	.	.	PROPN
hjic-96	196	11	8	8	NUM
hjic-96	196	12	shows	show	NOUN
hjic-96	196	13	.	.	PUNCT
hjic-96	197	1	step	step	NOUN
hjic-96	197	2	3	3	NUM
hjic-96	197	3	)	)	PUNCT
hjic-96	197	4	the	the	DET
hjic-96	197	5	mined	mine	VERB
hjic-96	197	6	frequent	frequent	ADJ
hjic-96	197	7	item	item	NOUN
hjic-96	197	8	sets	set	NOUN
hjic-96	197	9	are	be	AUX
hjic-96	197	10	the	the	DET
hjic-96	197	11	base	base	NOUN
hjic-96	197	12	of	of	ADP
hjic-96	197	13	fuzzy	fuzzy	ADJ
hjic-96	197	14	rule	rule	NOUN
hjic-96	197	15	generation	generation	NOUN
hjic-96	197	16	step	step	NOUN
hjic-96	197	17	.	.	PUNCT
hjic-96	198	1	every	every	DET
hjic-96	198	2	fuzzy	fuzzy	ADJ
hjic-96	198	3	rules	rule	NOUN
hjic-96	198	4	are	be	AUX
hjic-96	198	5	generated	generate	VERB
hjic-96	198	6	,	,	PUNCT
hjic-96	198	7	but	but	CCONJ
hjic-96	198	8	only	only	ADV
hjic-96	198	9	the	the	DET
hjic-96	198	10	rules	rule	NOUN
hjic-96	198	11	with	with	ADP
hjic-96	198	12	high	high	ADJ
hjic-96	198	13	support	support	NOUN
hjic-96	198	14	(	(	PUNCT
hjic-96	198	15	fs	fs	INTJ
hjic-96	198	16	>	>	X
hjic-96	198	17	σ	σ	PROPN
hjic-96	198	18	)	)	PUNCT
hjic-96	198	19	and	and	CCONJ
hjic-96	198	20	confidence	confidence	NOUN
hjic-96	198	21	(	(	PUNCT
hjic-96	198	22	fc	fc	INTJ
hjic-96	198	23	>	>	X
hjic-96	198	24	γ	γ	PROPN
hjic-96	198	25	)	)	PUNCT
hjic-96	198	26	values	value	NOUN
hjic-96	198	27	are	be	AUX
hjic-96	198	28	the	the	DET
hjic-96	198	29	relevant	relevant	ADJ
hjic-96	198	30	rules	rule	NOUN
hjic-96	198	31	.	.	PUNCT
hjic-96	199	1	the	the	DET
hjic-96	199	2	fuzzy	fuzzy	ADJ
hjic-96	199	3	support	support	NOUN
hjic-96	199	4	and	and	CCONJ
hjic-96	199	5	confidence	confidence	NOUN
hjic-96	199	6	values	value	NOUN
hjic-96	199	7	are	be	AUX
hjic-96	199	8	calculated	calculate	VERB
hjic-96	199	9	as	as	ADP
hjic-96	199	10	the	the	DET
hjic-96	199	11	eq	eq	NOUN
hjic-96	199	12	.	.	PROPN
hjic-96	199	13	8	8	NUM
hjic-96	199	14	and	and	CCONJ
hjic-96	199	15	11	11	NUM
hjic-96	199	16	show	show	NOUN
hjic-96	199	17	.	.	PUNCT
hjic-96	200	1	the	the	DET
hjic-96	200	2	interesting	interesting	ADJ
hjic-96	200	3	value	value	NOUN
hjic-96	200	4	of	of	ADP
hjic-96	200	5	the	the	DET
hjic-96	200	6	rules	rule	NOUN
hjic-96	200	7	are	be	AUX
hjic-96	200	8	determined	determine	VERB
hjic-96	200	9	by	by	ADP
hjic-96	200	10	the	the	DET
hjic-96	200	11	correlation	correlation	NOUN
hjic-96	200	12	factor	factor	NOUN
hjic-96	200	13	(	(	PUNCT
hjic-96	200	14	fcorr	fcorr	NOUN
hjic-96	200	15	,	,	PUNCT
hjic-96	200	16	calculated	calculate	VERB
hjic-96	200	17	by	by	ADP
hjic-96	200	18	eq.12	eq.12	NOUN
hjic-96	200	19	)	)	PUNCT
hjic-96	200	20	.	.	PUNCT
hjic-96	201	1	step	step	NOUN
hjic-96	201	2	4	4	NUM
hjic-96	201	3	)	)	PUNCT
hjic-96	201	4	the	the	DET
hjic-96	201	5	advantage	advantage	NOUN
hjic-96	201	6	of	of	ADP
hjic-96	201	7	the	the	DET
hjic-96	201	8	application	application	NOUN
hjic-96	201	9	of	of	ADP
hjic-96	201	10	the	the	DET
hjic-96	201	11	correlation	correlation	NOUN
hjic-96	201	12	measure	measure	NOUN
hjic-96	201	13	for	for	ADP
hjic-96	201	14	the	the	DET
hjic-96	201	15	analysis	analysis	NOUN
hjic-96	201	16	of	of	ADP
hjic-96	201	17	the	the	DET
hjic-96	201	18	quality	quality	NOUN
hjic-96	201	19	of	of	ADP
hjic-96	201	20	the	the	DET
hjic-96	201	21	rules	rule	NOUN
hjic-96	201	22	is	be	AUX
hjic-96	201	23	that	that	SCONJ
hjic-96	201	24	it	it	PRON
hjic-96	201	25	is	be	AUX
hjic-96	201	26	upward	upward	ADV
hjic-96	201	27	closed	closed	ADJ
hjic-96	201	28	.	.	PUNCT
hjic-96	202	1	based	base	VERB
hjic-96	202	2	on	on	ADP
hjic-96	202	3	this	this	PRON
hjic-96	202	4	,	,	PUNCT
hjic-96	202	5	a	a	DET
hjic-96	202	6	rule	rule	NOUN
hjic-96	202	7	based	base	VERB
hjic-96	202	8	pruning	prune	VERB
hjic-96	202	9	algorithm	algorithm	NOUN
hjic-96	202	10	has	have	AUX
hjic-96	202	11	been	be	AUX
hjic-96	202	12	developed	develop	VERB
hjic-96	202	13	that	that	PRON
hjic-96	202	14	removes	remove	VERB
hjic-96	202	15	the	the	DET
hjic-96	202	16	unnecessarily	unnecessarily	ADV
hjic-96	202	17	complex	complex	ADJ
hjic-96	202	18	rules	rule	NOUN
hjic-96	202	19	.	.	PUNCT
hjic-96	203	1	such	such	ADJ
hjic-96	203	2	rules	rule	NOUN
hjic-96	203	3	contain	contain	VERB
hjic-96	203	4	input	input	NOUN
hjic-96	203	5	variables	variable	NOUN
hjic-96	203	6	that	that	PRON
hjic-96	203	7	do	do	AUX
hjic-96	203	8	not	not	PART
hjic-96	203	9	significantly	significantly	ADV
hjic-96	203	10	improve	improve	VERB
hjic-96	203	11	the	the	DET
hjic-96	203	12	correlation	correlation	NOUN
hjic-96	203	13	of	of	ADP
hjic-96	203	14	rules	rule	NOUN
hjic-96	203	15	.	.	PUNCT
hjic-96	204	1	step	step	NOUN
hjic-96	204	2	5	5	NUM
hjic-96	204	3	)	)	PUNCT
hjic-96	204	4	we	we	PRON
hjic-96	204	5	have	have	VERB
hjic-96	204	6	to	to	PART
hjic-96	204	7	analyze	analyze	VERB
hjic-96	204	8	the	the	DET
hjic-96	204	9	mined	mine	VERB
hjic-96	204	10	association	association	NOUN
hjic-96	204	11	rules	rule	NOUN
hjic-96	204	12	to	to	PART
hjic-96	204	13	determine	determine	VERB
hjic-96	204	14	model	model	NOUN
hjic-96	204	15	structures	structure	NOUN
hjic-96	204	16	.	.	PUNCT
hjic-96	205	1	the	the	DET
hjic-96	205	2	rules	rule	NOUN
hjic-96	205	3	where	where	SCONJ
hjic-96	205	4	the	the	DET
hjic-96	205	5	first	first	ADJ
hjic-96	205	6	indices	index	NOUN
hjic-96	205	7	of	of	ADP
hjic-96	205	8	the	the	DET
hjic-96	205	9	fuzzy	fuzzy	ADJ
hjic-96	205	10	sets	set	NOUN
hjic-96	205	11	are	be	AUX
hjic-96	205	12	equal	equal	ADJ
hjic-96	205	13	in	in	ADP
hjic-96	205	14	the	the	DET
hjic-96	205	15	antecedent	antecedent	NOUN
hjic-96	205	16	parts	part	NOUN
hjic-96	205	17	,	,	PUNCT
hjic-96	205	18	give	give	VERB
hjic-96	205	19	identical	identical	ADJ
hjic-96	205	20	model	model	NOUN
hjic-96	205	21	structures	structure	NOUN
hjic-96	205	22	.	.	PUNCT
hjic-96	206	1	therefore	therefore	ADV
hjic-96	206	2	it	it	PRON
hjic-96	206	3	is	be	AUX
hjic-96	206	4	necessary	necessary	ADJ
hjic-96	206	5	to	to	PART
hjic-96	206	6	aggregate	aggregate	VERB
hjic-96	206	7	the	the	DET
hjic-96	206	8	support	support	NOUN
hjic-96	206	9	,	,	PUNCT
hjic-96	206	10	the	the	DET
hjic-96	206	11	confidence	confidence	NOUN
hjic-96	206	12	,	,	PUNCT
hjic-96	206	13	and	and	CCONJ
hjic-96	206	14	the	the	DET
hjic-96	206	15	correlation	correlation	NOUN
hjic-96	206	16	measures	measure	NOUN
hjic-96	206	17	of	of	ADP
hjic-96	206	18	these	these	DET
hjic-96	206	19	individual	individual	ADJ
hjic-96	206	20	rules	rule	NOUN
hjic-96	206	21	.	.	PUNCT
hjic-96	207	1	after	after	ADP
hjic-96	207	2	the	the	DET
hjic-96	207	3	aggregation	aggregation	NOUN
hjic-96	207	4	the	the	DET
hjic-96	207	5	given	give	VERB
hjic-96	207	6	model	model	NOUN
hjic-96	207	7	structures	structure	NOUN
hjic-96	207	8	must	must	AUX
hjic-96	207	9	be	be	AUX
hjic-96	207	10	ordered	order	VERB
hjic-96	207	11	by	by	ADP
hjic-96	207	12	the	the	DET
hjic-96	207	13	correlation	correlation	NOUN
hjic-96	207	14	(	(	PUNCT
hjic-96	207	15	calculated	calculate	VERB
hjic-96	207	16	by	by	ADP
hjic-96	207	17	eq	eq	PROPN
hjic-96	207	18	.	.	PROPN
hjic-96	207	19	12	12	NUM
hjic-96	207	20	)	)	PUNCT
hjic-96	207	21	measure	measure	NOUN
hjic-96	207	22	(	(	PUNCT
hjic-96	207	23	or	or	CCONJ
hjic-96	207	24	by	by	ADP
hjic-96	207	25	other	other	ADJ
hjic-96	207	26	rule	rule	NOUN
hjic-96	207	27	interesting	interesting	ADJ
hjic-96	207	28	measures	measure	NOUN
hjic-96	207	29	)	)	PUNCT
hjic-96	207	30	and	and	CCONJ
hjic-96	207	31	accordingly	accordingly	ADV
hjic-96	207	32	the	the	DET
hjic-96	207	33	first	first	ADJ
hjic-96	207	34	structures	structure	NOUN
hjic-96	207	35	will	will	AUX
hjic-96	207	36	be	be	AUX
hjic-96	207	37	the	the	DET
hjic-96	207	38	most	most	ADV
hjic-96	207	39	interesting	interesting	ADJ
hjic-96	207	40	structures	structure	NOUN
hjic-96	207	41	of	of	ADP
hjic-96	207	42	the	the	DET
hjic-96	207	43	models	model	NOUN
hjic-96	207	44	.	.	PUNCT
hjic-96	208	1	in	in	ADP
hjic-96	208	2	the	the	DET
hjic-96	208	3	next	next	ADJ
hjic-96	208	4	section	section	NOUN
hjic-96	208	5	an	an	DET
hjic-96	208	6	application	application	NOUN
hjic-96	208	7	study	study	NOUN
hjic-96	208	8	is	be	AUX
hjic-96	208	9	showed	show	VERB
hjic-96	208	10	to	to	PART
hjic-96	208	11	illustrate	illustrate	VERB
hjic-96	208	12	how	how	SCONJ
hjic-96	208	13	this	this	DET
hjic-96	208	14	method	method	NOUN
hjic-96	208	15	determines	determine	VERB
hjic-96	208	16	the	the	DET
hjic-96	208	17	structures	structure	NOUN
hjic-96	208	18	of	of	ADP
hjic-96	208	19	the	the	DET
hjic-96	208	20	models	model	NOUN
hjic-96	208	21	for	for	ADP
hjic-96	208	22	a	a	DET
hjic-96	208	23	dynamic	dynamic	ADJ
hjic-96	208	24	system	system	NOUN
hjic-96	208	25	and	and	CCONJ
hjic-96	208	26	selects	select	VERB
hjic-96	208	27	the	the	DET
hjic-96	208	28	most	most	ADV
hjic-96	208	29	relevant	relevant	ADJ
hjic-96	208	30	process	process	NOUN
hjic-96	208	31	variables	variable	NOUN
hjic-96	208	32	.	.	PUNCT
hjic-96	209	1	application	application	NOUN
hjic-96	209	2	study	study	NOUN
hjic-96	209	3	model	model	NOUN
hjic-96	209	4	of	of	ADP
hjic-96	209	5	styrene	styrene	ADJ
hjic-96	209	6	polymerization	polymerization	NOUN
hjic-96	209	7	cstr	cstr	NOUN
hjic-96	209	8	the	the	DET
hjic-96	209	9	data	data	NOUN
hjic-96	209	10	-	-	PUNCT
hjic-96	209	11	driven	drive	VERB
hjic-96	209	12	modeling	modeling	NOUN
hjic-96	209	13	of	of	ADP
hjic-96	209	14	styrene	styrene	ADJ
hjic-96	209	15	polymerization	polymerization	NOUN
hjic-96	209	16	in	in	ADP
hjic-96	209	17	a	a	DET
hjic-96	209	18	continuously	continuously	ADV
hjic-96	209	19	stirred	stir	VERB
hjic-96	209	20	tank	tank	NOUN
hjic-96	209	21	reactor	reactor	NOUN
hjic-96	209	22	is	be	AUX
hjic-96	209	23	considered	consider	VERB
hjic-96	209	24	as	as	ADP
hjic-96	209	25	a	a	DET
hjic-96	209	26	case	case	NOUN
hjic-96	209	27	study	study	NOUN
hjic-96	209	28	to	to	PART
hjic-96	209	29	demonstrate	demonstrate	VERB
hjic-96	209	30	the	the	DET
hjic-96	209	31	applicability	applicability	NOUN
hjic-96	209	32	of	of	ADP
hjic-96	209	33	the	the	DET
hjic-96	209	34	proposed	propose	VERB
hjic-96	209	35	method	method	NOUN
hjic-96	209	36	.	.	PUNCT
hjic-96	210	1	the	the	DET
hjic-96	210	2	schematic	schematic	ADJ
hjic-96	210	3	diagram	diagram	NOUN
hjic-96	210	4	of	of	ADP
hjic-96	210	5	the	the	DET
hjic-96	210	6	polymerization	polymerization	NOUN
hjic-96	210	7	process	process	NOUN
hjic-96	210	8	is	be	AUX
hjic-96	210	9	shown	show	VERB
hjic-96	210	10	in	in	ADP
hjic-96	210	11	fig	fig	NOUN
hjic-96	210	12	.	.	PUNCT
hjic-96	211	1	5	5	X
hjic-96	211	2	.	.	X
hjic-96	211	3	qm	qm	PROPN
hjic-96	211	4	cmf	cmf	PROPN
hjic-96	211	5	tf	tf	PROPN
hjic-96	211	6	qc	qc	PROPN
hjic-96	212	1	qt	qt	PROPN
hjic-96	212	2	ci	ci	PROPN
hjic-96	212	3	cmt	cmt	PROPN
hjic-96	212	4	tc	tc	PROPN
hjic-96	212	5	tc	tc	PROPN
hjic-96	212	6	ci	ci	PROPN
hjic-96	212	7	qs	qs	PROPN
hjic-96	212	8	qi	qi	PROPN
hjic-96	212	9	cif	cif	PROPN
hjic-96	213	1	tf	tf	INTJ
hjic-96	213	2	tf	tf	INTJ
hjic-96	213	3	cm	cm	PROPN
hjic-96	213	4	t	t	PROPN
hjic-96	213	5	tcf	tcf	PROPN
hjic-96	213	6	qm	qm	PROPN
hjic-96	213	7	cmf	cmf	PROPN
hjic-96	213	8	tf	tf	PROPN
hjic-96	213	9	qc	qc	PROPN
hjic-96	213	10	qt	qt	PROPN
hjic-96	213	11	ci	ci	PROPN
hjic-96	213	12	cmt	cmt	PROPN
hjic-96	213	13	tc	tc	PROPN
hjic-96	213	14	tc	tc	PROPN
hjic-96	213	15	ci	ci	PROPN
hjic-96	213	16	qs	qs	PROPN
hjic-96	213	17	qi	qi	PROPN
hjic-96	213	18	cif	cif	PROPN
hjic-96	214	1	tf	tf	INTJ
hjic-96	215	1	tf	tf	INTJ
hjic-96	215	2	cm	cm	NOUN
hjic-96	215	3	t	t	NOUN
hjic-96	215	4	tcf	tcf	PROPN
hjic-96	215	5	fig.5	fig.5	PROPN
hjic-96	215	6	scheme	scheme	NOUN
hjic-96	215	7	of	of	ADP
hjic-96	215	8	the	the	DET
hjic-96	215	9	styrene	styrene	ADJ
hjic-96	215	10	polymerization	polymerization	NOUN
hjic-96	215	11	cstr	cstr	NOUN
hjic-96	215	12	with	with	ADP
hjic-96	215	13	a	a	DET
hjic-96	215	14	cooling	cool	VERB
hjic-96	215	15	jacket	jacket	NOUN
hjic-96	215	16	on	on	ADP
hjic-96	215	17	figure	figure	NOUN
hjic-96	215	18	5	5	NUM
hjic-96	215	19	,	,	PUNCT
hjic-96	215	20	,	,	PUNCT
hjic-96	215	21	,	,	PUNCT
hjic-96	215	22	,	,	PUNCT
hjic-96	215	23	denote	denote	VERB
hjic-96	215	24	the	the	DET
hjic-96	215	25	monomer	monomer	NOUN
hjic-96	215	26	flowrate	flowrate	NOUN
hjic-96	215	27	,	,	PUNCT
hjic-96	215	28	the	the	DET
hjic-96	215	29	monomer	monomer	NOUN
hjic-96	215	30	feed	feed	NOUN
hjic-96	215	31	concentration	concentration	NOUN
hjic-96	215	32	,	,	PUNCT
hjic-96	215	33	the	the	DET
hjic-96	215	34	feed	feed	NOUN
hjic-96	215	35	mq	mq	PROPN
hjic-96	215	36	mfc	mfc	PROPN
hjic-96	215	37	ft	ft	PROPN
hjic-96	215	38	mc	mc	PROPN
hjic-96	215	39	63	63	NUM
hjic-96	215	40	temperature	temperature	NOUN
hjic-96	215	41	,	,	PUNCT
hjic-96	215	42	and	and	CCONJ
hjic-96	215	43	the	the	DET
hjic-96	215	44	monomer	monomer	NOUN
hjic-96	215	45	concentration	concentration	NOUN
hjic-96	215	46	,	,	PUNCT
hjic-96	215	47	respectively	respectively	ADV
hjic-96	215	48	.	.	PUNCT
hjic-96	216	1	the	the	DET
hjic-96	216	2	solvent	solvent	ADJ
hjic-96	216	3	flowrate	flowrate	NOUN
hjic-96	216	4	is	be	AUX
hjic-96	216	5	represented	represent	VERB
hjic-96	216	6	by	by	ADP
hjic-96	216	7	,	,	PUNCT
hjic-96	216	8	while	while	SCONJ
hjic-96	216	9	,	,	PUNCT
hjic-96	216	10	,	,	PUNCT
hjic-96	216	11	are	be	AUX
hjic-96	216	12	the	the	DET
hjic-96	216	13	initiator	initiator	NOUN
hjic-96	216	14	flowrate	flowrate	NOUN
hjic-96	216	15	,	,	PUNCT
hjic-96	216	16	the	the	DET
hjic-96	216	17	initiator	initiator	NOUN
hjic-96	216	18	feed	feed	NOUN
hjic-96	216	19	concentration	concentration	NOUN
hjic-96	216	20	,	,	PUNCT
hjic-96	216	21	and	and	CCONJ
hjic-96	216	22	the	the	DET
hjic-96	216	23	concentration	concentration	NOUN
hjic-96	216	24	of	of	ADP
hjic-96	216	25	the	the	DET
hjic-96	216	26	initiator	initiator	NOUN
hjic-96	216	27	in	in	ADP
hjic-96	216	28	the	the	DET
hjic-96	216	29	reactor	reactor	NOUN
hjic-96	216	30	,	,	PUNCT
hjic-96	216	31	respectively	respectively	ADV
hjic-96	216	32	.	.	PUNCT
hjic-96	216	33	,	,	PUNCT
hjic-96	216	34	and	and	CCONJ
hjic-96	216	35	are	be	AUX
hjic-96	216	36	the	the	DET
hjic-96	216	37	coolant	coolant	NOUN
hjic-96	216	38	feed	feed	NOUN
hjic-96	216	39	temperature	temperature	NOUN
hjic-96	216	40	,	,	PUNCT
hjic-96	216	41	the	the	DET
hjic-96	216	42	coolant	coolant	NOUN
hjic-96	216	43	flowrate	flowrate	ADJ
hjic-96	216	44	,	,	PUNCT
hjic-96	216	45	and	and	CCONJ
hjic-96	216	46	the	the	DET
hjic-96	216	47	coolant	coolant	NOUN
hjic-96	216	48	temperature	temperature	NOUN
hjic-96	216	49	.	.	PUNCT
hjic-96	217	1	the	the	DET
hjic-96	217	2	total	total	ADJ
hjic-96	217	3	flowrate	flowrate	NOUN
hjic-96	217	4	is	be	AUX
hjic-96	217	5	denoted	denote	VERB
hjic-96	217	6	by	by	ADP
hjic-96	217	7	and	and	CCONJ
hjic-96	217	8	t	t	PROPN
hjic-96	217	9	is	be	AUX
hjic-96	217	10	the	the	DET
hjic-96	217	11	reactor	reactor	NOUN
hjic-96	217	12	temperature	temperature	NOUN
hjic-96	217	13	.	.	PUNCT
hjic-96	218	1	the	the	DET
hjic-96	218	2	initiator	initiator	NOUN
hjic-96	218	3	is	be	AUX
hjic-96	218	4	azobisisobutyroitrile	azobisisobutyroitrile	ADJ
hjic-96	218	5	(	(	PUNCT
hjic-96	218	6	aibn	aibn	NOUN
hjic-96	218	7	)	)	PUNCT
hjic-96	218	8	dissolved	dissolve	VERB
hjic-96	218	9	in	in	ADP
hjic-96	218	10	benzene	benzene	NOUN
hjic-96	218	11	,	,	PUNCT
hjic-96	218	12	while	while	SCONJ
hjic-96	218	13	the	the	DET
hjic-96	218	14	monomer	monomer	NOUN
hjic-96	218	15	is	be	AUX
hjic-96	218	16	styrene	styrene	NOUN
hjic-96	218	17	and	and	CCONJ
hjic-96	218	18	the	the	DET
hjic-96	218	19	solvent	solvent	NOUN
hjic-96	218	20	is	be	AUX
hjic-96	218	21	benzene	benzene	ADJ
hjic-96	218	22	.	.	PUNCT
hjic-96	219	1	sq	sq	INTJ
hjic-96	219	2	iq	iq	PROPN
hjic-96	219	3	ifc	ifc	NOUN
hjic-96	219	4	ic	ic	PROPN
hjic-96	219	5	cft	cft	PROPN
hjic-96	220	1	cq	cq	INTJ
hjic-96	220	2	ct	ct	PROPN
hjic-96	220	3	tq	tq	INTJ
hjic-96	220	4	for	for	ADP
hjic-96	220	5	the	the	DET
hjic-96	220	6	simulation	simulation	NOUN
hjic-96	220	7	of	of	ADP
hjic-96	220	8	this	this	DET
hjic-96	220	9	system	system	NOUN
hjic-96	220	10	the	the	DET
hjic-96	220	11	model	model	NOUN
hjic-96	220	12	of	of	ADP
hjic-96	220	13	hidalgo	hidalgo	PROPN
hjic-96	220	14	and	and	CCONJ
hjic-96	220	15	brosilow	brosilow	VERB
hjic-96	220	16	[	[	PUNCT
hjic-96	220	17	33	33	NUM
hjic-96	220	18	]	]	PUNCT
hjic-96	220	19	is	be	AUX
hjic-96	220	20	applied	apply	VERB
hjic-96	220	21	:	:	PUNCT
hjic-96	220	22	i	i	PROPN
hjic-96	220	23	d	d	PROPN
hjic-96	220	24	ismiifii	ismiifii	VERB
hjic-96	220	25	ck	ck	PRON
hjic-96	220	26	v	v	NOUN
hjic-96	220	27	cqqcq	cqqcq	NOUN
hjic-96	220	28	dt	dt	X
hjic-96	220	29	dc	dc	PROPN
hjic-96	221	1	−	−	PROPN
hjic-96	222	1	+	+	NOUN
hjic-96	222	2	−	−	NOUN
hjic-96	222	3	=	=	SYM
hjic-96	222	4	)	)	PUNCT
hjic-96	222	5	(	(	PUNCT
hjic-96	222	6	q+	q+	X
hjic-96	222	7	(	(	PUNCT
hjic-96	222	8	13	13	NUM
hjic-96	222	9	)	)	PUNCT
hjic-96	222	10	gpmp	gpmp	PROPN
hjic-96	222	11	msmimfmm	msmimfmm	PROPN
hjic-96	222	12	cck	cck	PROPN
hjic-96	222	13	v	v	ADP
hjic-96	222	14	cqqqcq	cqqqcq	NOUN
hjic-96	222	15	dt	dt	X
hjic-96	222	16	dc	dc	PROPN
hjic-96	223	1	−	−	PROPN
hjic-96	224	1	+	+	PROPN
hjic-96	224	2	+	+	ADJ
hjic-96	224	3	−	−	NOUN
hjic-96	224	4	=	=	SYM
hjic-96	224	5	)	)	PUNCT
hjic-96	224	6	(	(	PUNCT
hjic-96	224	7	(	(	PUNCT
hjic-96	224	8	14	14	NUM
hjic-96	224	9	)	)	PUNCT
hjic-96	224	10	)	)	PUNCT
hjic-96	224	11	(	(	PUNCT
hjic-96	224	12	)	)	PUNCT
hjic-96	224	13	(	(	PUNCT
hjic-96	224	14	)	)	PUNCT
hjic-96	224	15	)	)	PUNCT
hjic-96	224	16	(	(	PUNCT
hjic-96	224	17	(	(	PUNCT
hjic-96	224	18	c	c	NOUN
hjic-96	224	19	p	p	NOUN
hjic-96	224	20	gpmp	gpmp	PROPN
hjic-96	224	21	p	p	PROPN
hjic-96	224	22	fsmi	fsmi	PROPN
hjic-96	224	23	tt	tt	PROPN
hjic-96	224	24	vc	vc	PROPN
hjic-96	224	25	au	au	PROPN
hjic-96	224	26	cck	cck	PROPN
hjic-96	224	27	c	c	PROPN
hjic-96	224	28	hr	hr	PROPN
hjic-96	224	29	v	v	PROPN
hjic-96	224	30	ttqqq	ttqqq	NOUN
hjic-96	224	31	dt	dt	X
hjic-96	224	32	dt	dt	PROPN
hjic-96	224	33	−−	−−	NOUN
hjic-96	224	34	−	−	PROPN
hjic-96	225	1	+	+	CCONJ
hjic-96	225	2	−++	−++	X
hjic-96	225	3	=	=	PUNCT
hjic-96	225	4	ρρ	ρρ	PROPN
hjic-96	225	5	(	(	PUNCT
hjic-96	225	6	15	15	NUM
hjic-96	225	7	)	)	PUNCT
hjic-96	225	8	)	)	PUNCT
hjic-96	225	9	(	(	PUNCT
hjic-96	225	10	)	)	PUNCT
hjic-96	225	11	(	(	PUNCT
hjic-96	225	12	c	c	NOUN
hjic-96	225	13	pc	pc	NOUN
hjic-96	225	14	ccfcc	ccfcc	NOUN
hjic-96	225	15	tt	tt	PROPN
hjic-96	225	16	vc	vc	PROPN
hjic-96	225	17	au	au	PROPN
hjic-96	225	18	v	v	PROPN
hjic-96	225	19	ttq	ttq	NOUN
hjic-96	225	20	dt	dt	X
hjic-96	225	21	dt	dt	NOUN
hjic-96	225	22	−+	−+	PROPN
hjic-96	225	23	−	−	PROPN
hjic-96	225	24	=	=	SYM
hjic-96	225	25	ρ	ρ	PROPN
hjic-96	225	26	(	(	PUNCT
hjic-96	225	27	16	16	NUM
hjic-96	225	28	)	)	PUNCT
hjic-96	225	29	⎥	⎥	PROPN
hjic-96	226	1	⎦	⎦	NOUN
hjic-96	226	2	⎤	⎤	ADJ
hjic-96	226	3	⎢	⎢	NOUN
hjic-96	226	4	⎣	⎣	PROPN
hjic-96	226	5	⎡	⎡	NOUN
hjic-96	226	6	=	=	SYM
hjic-96	226	7	t	t	PROPN
hjic-96	226	8	i	i	NOUN
hjic-96	226	9	d	d	PROPN
hjic-96	226	10	gp	gp	NOUN
hjic-96	227	1	k	k	PROPN
hjic-96	227	2	cfk	cfk	PROPN
hjic-96	227	3	c	c	PROPN
hjic-96	227	4	2	2	NUM
hjic-96	227	5	(	(	PUNCT
hjic-96	227	6	17	17	NUM
hjic-96	227	7	)	)	PUNCT
hjic-96	227	8	where	where	SCONJ
hjic-96	227	9	represents	represent	VERB
hjic-96	227	10	the	the	DET
hjic-96	227	11	concentration	concentration	NOUN
hjic-96	227	12	of	of	ADP
hjic-96	227	13	the	the	DET
hjic-96	227	14	growing	grow	VERB
hjic-96	227	15	polymer	polymer	NOUN
hjic-96	227	16	.	.	PUNCT
hjic-96	228	1	gpc	gpc	PROPN
hjic-96	228	2	the	the	DET
hjic-96	228	3	dimensionless	dimensionless	NOUN
hjic-96	228	4	model	model	NOUN
hjic-96	228	5	and	and	CCONJ
hjic-96	228	6	its	its	PRON
hjic-96	228	7	nominal	nominal	ADJ
hjic-96	228	8	parameter	parameter	NOUN
hjic-96	228	9	values	value	NOUN
hjic-96	228	10	are	be	AUX
hjic-96	228	11	detailed	detail	VERB
hjic-96	228	12	in	in	ADP
hjic-96	228	13	[	[	X
hjic-96	228	14	34	34	NUM
hjic-96	228	15	]	]	PUNCT
hjic-96	228	16	.	.	PUNCT
hjic-96	229	1	the	the	DET
hjic-96	229	2	dynamical	dynamical	ADJ
hjic-96	229	3	behavior	behavior	NOUN
hjic-96	229	4	of	of	ADP
hjic-96	229	5	this	this	DET
hjic-96	229	6	dimensionless	dimensionless	NOUN
hjic-96	229	7	model	model	NOUN
hjic-96	229	8	is	be	AUX
hjic-96	229	9	illustrated	illustrate	VERB
hjic-96	229	10	in	in	ADP
hjic-96	229	11	figure	figure	NOUN
hjic-96	229	12	6	6	NUM
hjic-96	229	13	,	,	PUNCT
hjic-96	229	14	where	where	SCONJ
hjic-96	229	15	the	the	DET
hjic-96	229	16	coolant	coolant	NOUN
hjic-96	229	17	flowrate	flowrate	NOUN
hjic-96	229	18	(	(	PUNCT
hjic-96	229	19	qc	qc	PROPN
hjic-96	229	20	)	)	PUNCT
hjic-96	229	21	is	be	AUX
hjic-96	229	22	considered	consider	VERB
hjic-96	229	23	as	as	ADP
hjic-96	229	24	an	an	DET
hjic-96	229	25	input	input	NOUN
hjic-96	229	26	variable	variable	NOUN
hjic-96	229	27	.	.	PUNCT
hjic-96	230	1	the	the	DET
hjic-96	230	2	steady	steady	ADJ
hjic-96	230	3	-	-	PUNCT
hjic-96	230	4	state	state	NOUN
hjic-96	230	5	input	input	NOUN
hjic-96	230	6	-	-	PUNCT
hjic-96	230	7	output	output	NOUN
hjic-96	230	8	relationship	relationship	NOUN
hjic-96	230	9	of	of	ADP
hjic-96	230	10	qc	qc	PROPN
hjic-96	230	11	and	and	CCONJ
hjic-96	230	12	the	the	DET
hjic-96	230	13	reactor	reactor	NOUN
hjic-96	230	14	temperature	temperature	NOUN
hjic-96	230	15	(	(	PUNCT
hjic-96	230	16	t	t	NOUN
hjic-96	230	17	)	)	PUNCT
hjic-96	230	18	confirms	confirm	VERB
hjic-96	230	19	the	the	DET
hjic-96	230	20	nonlinear	nonlinear	ADJ
hjic-96	230	21	behaviour	behaviour	NOUN
hjic-96	230	22	of	of	ADP
hjic-96	230	23	the	the	DET
hjic-96	230	24	model	model	NOUN
hjic-96	230	25	(	(	PUNCT
hjic-96	230	26	see	see	VERB
hjic-96	230	27	figure	figure	NOUN
hjic-96	230	28	7	7	NUM
hjic-96	230	29	)	)	PUNCT
hjic-96	230	30	.	.	PUNCT
hjic-96	231	1	suppose	suppose	VERB
hjic-96	231	2	we	we	PRON
hjic-96	231	3	have	have	VERB
hjic-96	231	4	only	only	ADV
hjic-96	231	5	input	input	NOUN
hjic-96	231	6	output	output	NOUN
hjic-96	231	7	simulated	simulate	VERB
hjic-96	231	8	data	datum	NOUN
hjic-96	231	9	taken	take	VERB
hjic-96	231	10	from	from	ADP
hjic-96	231	11	the	the	DET
hjic-96	231	12	above	above	PROPN
hjic-96	231	13	cstr	cstr	NOUN
hjic-96	231	14	model	model	NOUN
hjic-96	231	15	,	,	PUNCT
hjic-96	231	16	and	and	CCONJ
hjic-96	231	17	we	we	PRON
hjic-96	231	18	want	want	VERB
hjic-96	231	19	to	to	PART
hjic-96	231	20	identify	identify	VERB
hjic-96	231	21	a	a	DET
hjic-96	231	22	linear	linear	ADJ
hjic-96	231	23	arx	arx	PROPN
hjic-96	231	24	or	or	CCONJ
hjic-96	231	25	a	a	DET
hjic-96	231	26	neural	neural	ADJ
hjic-96	231	27	network	network	NOUN
hjic-96	231	28	based	base	VERB
hjic-96	231	29	narx	narx	PROPN
hjic-96	231	30	model	model	NOUN
hjic-96	231	31	with	with	ADP
hjic-96	231	32	some	some	DET
hjic-96	231	33	model	model	NOUN
hjic-96	231	34	structure	structure	NOUN
hjic-96	231	35	.	.	PUNCT
hjic-96	232	1	to	to	PART
hjic-96	232	2	determine	determine	VERB
hjic-96	232	3	(	(	PUNCT
hjic-96	232	4	select	select	ADJ
hjic-96	232	5	)	)	PUNCT
hjic-96	232	6	the	the	DET
hjic-96	232	7	structure	structure	NOUN
hjic-96	232	8	of	of	ADP
hjic-96	232	9	these	these	DET
hjic-96	232	10	models	model	NOUN
hjic-96	232	11	the	the	DET
hjic-96	232	12	proposed	propose	VERB
hjic-96	232	13	fuzzy	fuzzy	ADJ
hjic-96	232	14	association	association	NOUN
hjic-96	232	15	rule	rule	NOUN
hjic-96	232	16	based	base	VERB
hjic-96	232	17	method	method	NOUN
hjic-96	232	18	will	will	AUX
hjic-96	232	19	be	be	AUX
hjic-96	232	20	followed	follow	VERB
hjic-96	232	21	in	in	ADP
hjic-96	232	22	the	the	DET
hjic-96	232	23	next	next	ADJ
hjic-96	232	24	session	session	NOUN
hjic-96	232	25	.	.	PUNCT
hjic-96	233	1	0	0	NUM
hjic-96	233	2	50	50	NUM
hjic-96	233	3	100	100	NUM
hjic-96	233	4	150	150	NUM
hjic-96	233	5	200	200	NUM
hjic-96	233	6	250	250	NUM
hjic-96	233	7	300	300	NUM
hjic-96	233	8	0	0	NUM
hjic-96	233	9	0.005	0.005	NUM
hjic-96	233	10	0.01	0.01	NUM
hjic-96	233	11	c	c	NOUN
hjic-96	234	1	i	i	PRON
hjic-96	234	2	0	0	NUM
hjic-96	234	3	50	50	NUM
hjic-96	234	4	100	100	NUM
hjic-96	234	5	150	150	NUM
hjic-96	234	6	200	200	NUM
hjic-96	234	7	250	250	NUM
hjic-96	234	8	300	300	NUM
hjic-96	234	9	0	0	NUM
hjic-96	234	10	0.2	0.2	NUM
hjic-96	234	11	0.4	0.4	NUM
hjic-96	234	12	c	c	NOUN
hjic-96	234	13	m	m	VERB
hjic-96	234	14	0	0	NUM
hjic-96	234	15	50	50	NUM
hjic-96	234	16	100	100	NUM
hjic-96	234	17	150	150	NUM
hjic-96	234	18	200	200	NUM
hjic-96	234	19	250	250	NUM
hjic-96	234	20	300	300	NUM
hjic-96	234	21	0	0	NUM
hjic-96	234	22	1	1	NUM
hjic-96	234	23	2	2	NUM
hjic-96	234	24	3	3	NUM
hjic-96	234	25	tr	tr	NOUN
hjic-96	234	26	0	0	NUM
hjic-96	234	27	50	50	NUM
hjic-96	234	28	100	100	NUM
hjic-96	234	29	150	150	NUM
hjic-96	234	30	200	200	NUM
hjic-96	234	31	250	250	NUM
hjic-96	234	32	300	300	NUM
hjic-96	234	33	-1	-1	SYM
hjic-96	234	34	0	0	NUM
hjic-96	234	35	1	1	NUM
hjic-96	234	36	tc	tc	NOUN
hjic-96	234	37	0	0	NUM
hjic-96	234	38	50	50	NUM
hjic-96	234	39	100	100	NUM
hjic-96	234	40	150	150	NUM
hjic-96	234	41	200	200	NUM
hjic-96	234	42	250	250	NUM
hjic-96	234	43	300	300	NUM
hjic-96	234	44	0	0	NUM
hjic-96	234	45	5	5	NUM
hjic-96	234	46	q	q	NOUN
hjic-96	234	47	c	c	NOUN
hjic-96	234	48	time	time	NOUN
hjic-96	234	49	fig.6	fig.6	PROPN
hjic-96	234	50	dynamical	dynamical	ADJ
hjic-96	234	51	behavior	behavior	NOUN
hjic-96	234	52	of	of	ADP
hjic-96	234	53	the	the	DET
hjic-96	234	54	dimensionless	dimensionless	NOUN
hjic-96	234	55	model	model	NOUN
hjic-96	234	56	of	of	ADP
hjic-96	234	57	the	the	DET
hjic-96	234	58	styrene	styrene	ADJ
hjic-96	234	59	polymerization	polymerization	NOUN
hjic-96	234	60	reactor	reactor	NOUN
hjic-96	234	61	0.2	0.2	NUM
hjic-96	234	62	0.6	0.6	NUM
hjic-96	234	63	1	1	NUM
hjic-96	234	64	1.4	1.4	NUM
hjic-96	234	65	1.8	1.8	NUM
hjic-96	234	66	2.2	2.2	NUM
hjic-96	234	67	2.6	2.6	NUM
hjic-96	234	68	0	0	NUM
hjic-96	234	69	1	1	NUM
hjic-96	234	70	2	2	NUM
hjic-96	234	71	3	3	NUM
hjic-96	234	72	4	4	NUM
hjic-96	234	73	5	5	NUM
hjic-96	234	74	6	6	NUM
hjic-96	234	75	coolant	coolant	NOUN
hjic-96	234	76	flowrate	flowrate	NOUN
hjic-96	234	77	(	(	PUNCT
hjic-96	234	78	qc	qc	PROPN
hjic-96	234	79	)	)	PUNCT
hjic-96	234	80	re	re	VERB
hjic-96	234	81	ac	ac	VERB
hjic-96	234	82	to	to	ADP
hjic-96	234	83	r	r	PROPN
hjic-96	234	84	t	t	NOUN
hjic-96	234	85	em	em	PRON
hjic-96	235	1	p.	p.	NOUN
hjic-96	235	2	(	(	PUNCT
hjic-96	235	3	t	t	PROPN
hjic-96	235	4	)	)	PUNCT
hjic-96	235	5	fig.7	fig.7	ADV
hjic-96	235	6	steady	steady	ADJ
hjic-96	235	7	-	-	PUNCT
hjic-96	235	8	state	state	NOUN
hjic-96	235	9	input	input	NOUN
hjic-96	235	10	-	-	PUNCT
hjic-96	235	11	output	output	NOUN
hjic-96	235	12	relationship	relationship	NOUN
hjic-96	235	13	of	of	ADP
hjic-96	235	14	the	the	DET
hjic-96	235	15	coolant	coolant	NOUN
hjic-96	235	16	flowrate	flowrate	ADJ
hjic-96	235	17	and	and	CCONJ
hjic-96	235	18	the	the	DET
hjic-96	235	19	reactor	reactor	NOUN
hjic-96	235	20	temperature	temperature	NOUN
hjic-96	235	21	model	model	NOUN
hjic-96	235	22	structure	structure	NOUN
hjic-96	235	23	selection	selection	NOUN
hjic-96	235	24	by	by	ADP
hjic-96	235	25	mossfarm	mossfarm	NOUN
hjic-96	235	26	a	a	DET
hjic-96	235	27	siso	siso	NOUN
hjic-96	235	28	narx	narx	NOUN
hjic-96	235	29	model	model	NOUN
hjic-96	235	30	of	of	ADP
hjic-96	235	31	the	the	DET
hjic-96	235	32	previous	previous	ADJ
hjic-96	235	33	system	system	NOUN
hjic-96	235	34	is	be	AUX
hjic-96	235	35	considered	consider	VERB
hjic-96	235	36	where	where	SCONJ
hjic-96	235	37	the	the	DET
hjic-96	235	38	output	output	NOUN
hjic-96	235	39	of	of	ADP
hjic-96	235	40	model	model	NOUN
hjic-96	235	41	(	(	PUNCT
hjic-96	235	42	y	y	NOUN
hjic-96	235	43	)	)	PUNCT
hjic-96	235	44	is	be	AUX
hjic-96	235	45	the	the	DET
hjic-96	235	46	reactor	reactor	NOUN
hjic-96	235	47	temperature	temperature	NOUN
hjic-96	235	48	,	,	PUNCT
hjic-96	235	49	and	and	CCONJ
hjic-96	235	50	the	the	DET
hjic-96	235	51	input	input	NOUN
hjic-96	235	52	(	(	PUNCT
hjic-96	235	53	u	u	NOUN
hjic-96	235	54	)	)	PUNCT
hjic-96	235	55	is	be	AUX
hjic-96	235	56	the	the	DET
hjic-96	235	57	coolant	coolant	NOUN
hjic-96	235	58	flowrate	flowrate	ADJ
hjic-96	235	59	.	.	PUNCT
hjic-96	236	1	the	the	DET
hjic-96	236	2	maximal	maximal	ADJ
hjic-96	236	3	number	number	NOUN
hjic-96	236	4	of	of	ADP
hjic-96	236	5	lagged	lag	VERB
hjic-96	236	6	inputs	input	NOUN
hjic-96	236	7	and	and	CCONJ
hjic-96	236	8	outputs	output	NOUN
hjic-96	236	9	is	be	AUX
hjic-96	236	10	four	four	NUM
hjic-96	236	11	-	-	PUNCT
hjic-96	236	12	four	four	NUM
hjic-96	236	13	,	,	PUNCT
hjic-96	236	14	therefore	therefore	ADV
hjic-96	236	15	the	the	DET
hjic-96	236	16	more	more	ADV
hjic-96	236	17	complex	complex	ADJ
hjic-96	236	18	model	model	NOUN
hjic-96	236	19	is	be	AUX
hjic-96	236	20	:	:	PUNCT
hjic-96	236	21	]	]	X
hjic-96	236	22	)	)	PUNCT
hjic-96	236	23	,	,	PUNCT
hjic-96	236	24	,	,	PUNCT
hjic-96	236	25	,	,	PUNCT
hjic-96	236	26	(	(	PUNCT
hjic-96	236	27	[	[	PUNCT
hjic-96	236	28	4,,14,,11	4,,14,,11	NUM
hjic-96	236	29	−−−−+	−−−−+	NOUN
hjic-96	236	30	=	=	SYM
hjic-96	237	1	kkkkkkk	kkkkkkk	PROPN
hjic-96	237	2	uuuyyyfy	uuuyyyfy	VERB
hjic-96	237	3	kk	kk	X
hjic-96	237	4	(	(	PUNCT
hjic-96	237	5	18	18	NUM
hjic-96	237	6	)	)	PUNCT
hjic-96	237	7	if	if	SCONJ
hjic-96	237	8	the	the	DET
hjic-96	237	9	original	original	ADJ
hjic-96	237	10	(	(	PUNCT
hjic-96	237	11	the	the	DET
hjic-96	237	12	full	full	ADJ
hjic-96	237	13	,	,	PUNCT
hjic-96	237	14	see	see	VERB
hjic-96	237	15	eq	eq	ADP
hjic-96	237	16	.	.	PROPN
hjic-96	237	17	18	18	NUM
hjic-96	237	18	)	)	PUNCT
hjic-96	237	19	model	model	NOUN
hjic-96	237	20	structure	structure	NOUN
hjic-96	237	21	is	be	AUX
hjic-96	237	22	used	use	VERB
hjic-96	237	23	for	for	ADP
hjic-96	237	24	a	a	DET
hjic-96	237	25	linear	linear	NOUN
hjic-96	237	26	and	and	CCONJ
hjic-96	237	27	a	a	DET
hjic-96	237	28	neural	neural	ADJ
hjic-96	237	29	network	network	NOUN
hjic-96	237	30	(	(	PUNCT
hjic-96	237	31	nn	nn	NOUN
hjic-96	237	32	)	)	PUNCT
hjic-96	237	33	based	base	VERB
hjic-96	237	34	model	model	NOUN
hjic-96	237	35	,	,	PUNCT
hjic-96	237	36	the	the	DET
hjic-96	237	37	mean	mean	ADJ
hjic-96	237	38	square	square	ADJ
hjic-96	237	39	error	error	NOUN
hjic-96	237	40	(	(	PUNCT
hjic-96	237	41	mse	mse	NOUN
hjic-96	237	42	)	)	PUNCT
hjic-96	237	43	values	value	NOUN
hjic-96	237	44	are	be	AUX
hjic-96	237	45	0.00047	0.00047	NUM
hjic-96	237	46	and	and	CCONJ
hjic-96	237	47	0.00008	0.00008	NUM
hjic-96	237	48	,	,	PUNCT
hjic-96	237	49	respectively	respectively	ADV
hjic-96	237	50	.	.	PUNCT
hjic-96	238	1	in	in	ADP
hjic-96	238	2	the	the	DET
hjic-96	238	3	linear	linear	ADJ
hjic-96	238	4	model	model	NOUN
hjic-96	238	5	least	least	ADJ
hjic-96	238	6	square	square	ADJ
hjic-96	238	7	method	method	NOUN
hjic-96	238	8	is	be	AUX
hjic-96	238	9	used	use	VERB
hjic-96	238	10	.	.	PUNCT
hjic-96	239	1	at	at	ADP
hjic-96	239	2	the	the	DET
hjic-96	239	3	nn	nn	PROPN
hjic-96	239	4	model	model	NOUN
hjic-96	239	5	the	the	DET
hjic-96	239	6	number	number	NOUN
hjic-96	239	7	of	of	ADP
hjic-96	239	8	regressors	regressor	NOUN
hjic-96	239	9	in	in	ADP
hjic-96	239	10	the	the	DET
hjic-96	239	11	structure	structure	NOUN
hjic-96	239	12	is	be	AUX
hjic-96	239	13	used	use	VERB
hjic-96	239	14	for	for	ADP
hjic-96	239	15	set	set	VERB
hjic-96	239	16	the	the	DET
hjic-96	239	17	number	number	NOUN
hjic-96	239	18	of	of	ADP
hjic-96	239	19	neurons	neuron	NOUN
hjic-96	239	20	in	in	ADP
hjic-96	239	21	input	input	NOUN
hjic-96	239	22	,	,	PUNCT
hjic-96	239	23	hidden	hidden	ADJ
hjic-96	239	24	and	and	CCONJ
hjic-96	239	25	output	output	NOUN
hjic-96	239	26	layers	layer	NOUN
hjic-96	239	27	(	(	PUNCT
hjic-96	239	28	e.g.	e.g.	ADV
hjic-96	239	29	for	for	ADP
hjic-96	239	30	the	the	DET
hjic-96	239	31	structure	structure	NOUN
hjic-96	240	1	[	[	X
hjic-96	240	2	yk	yk	PROPN
hjic-96	240	3	,	,	PUNCT
hjic-96	240	4	yk-1	yk-1	NOUN
hjic-96	240	5	,	,	PUNCT
hjic-96	240	6	yk-2	yk-2	PROPN
hjic-96	240	7	,	,	PUNCT
hjic-96	240	8	yk-3	yk-3	PROPN
hjic-96	240	9	,	,	PUNCT
hjic-96	240	10	uk	uk	PROPN
hjic-96	240	11	]	]	X
hjic-96	240	12	input	input	NOUN
hjic-96	240	13	:	:	PUNCT
hjic-96	240	14	5	5	NUM
hjic-96	240	15	,	,	PUNCT
hjic-96	240	16	output	output	NOUN
hjic-96	240	17	:	:	PUNCT
hjic-96	240	18	1	1	NUM
hjic-96	240	19	,	,	PUNCT
hjic-96	240	20	hidden	hide	VERB
hjic-96	240	21	:	:	PUNCT
hjic-96	240	22	3	3	NUM
hjic-96	240	23	)	)	PUNCT
hjic-96	240	24	.	.	PUNCT
hjic-96	241	1	the	the	DET
hjic-96	241	2	applied	apply	VERB
hjic-96	241	3	learning	learning	NOUN
hjic-96	241	4	method	method	NOUN
hjic-96	241	5	was	be	AUX
hjic-96	241	6	the	the	DET
hjic-96	241	7	backpropagation	backpropagation	NOUN
hjic-96	241	8	method	method	NOUN
hjic-96	241	9	.	.	PUNCT
hjic-96	242	1	the	the	DET
hjic-96	242	2	structures	structure	NOUN
hjic-96	242	3	with	with	ADP
hjic-96	242	4	highest	high	ADJ
hjic-96	242	5	correlation	correlation	NOUN
hjic-96	242	6	factor	factor	NOUN
hjic-96	242	7	(	(	PUNCT
hjic-96	242	8	selected	select	VERB
hjic-96	242	9	by	by	ADP
hjic-96	242	10	mossfarm	mossfarm	NOUN
hjic-96	242	11	with	with	ADP
hjic-96	242	12	σ	σ	X
hjic-96	242	13	=	=	SYM
hjic-96	242	14	1	1	NUM
hjic-96	242	15	%	%	NOUN
hjic-96	242	16	,	,	PUNCT
hjic-96	242	17	γ	γ	NOUN
hjic-96	242	18	=	=	SYM
hjic-96	242	19	95	95	NUM
hjic-96	242	20	%	%	NOUN
hjic-96	242	21	)	)	PUNCT
hjic-96	242	22	are	be	AUX
hjic-96	242	23	listed	list	VERB
hjic-96	242	24	in	in	ADP
hjic-96	242	25	table	table	NOUN
hjic-96	242	26	3	3	NUM
hjic-96	242	27	.	.	NOUN
hjic-96	242	28	64	64	NUM
hjic-96	242	29	table	table	NOUN
hjic-96	242	30	3	3	NUM
hjic-96	242	31	the	the	DET
hjic-96	242	32	selected	select	VERB
hjic-96	242	33	model	model	NOUN
hjic-96	242	34	structures	structure	NOUN
hjic-96	242	35	#	#	NOUN
hjic-96	242	36	structure	structure	NOUN
hjic-96	242	37	fs	fs	ADP
hjic-96	242	38	fc	fc	PROPN
hjic-96	242	39	fcorr	fcorr	PROPN
hjic-96	242	40	1	1	PROPN
hjic-96	242	41	.	.	PUNCT
hjic-96	243	1	yk	yk	PROPN
hjic-96	243	2	,	,	PUNCT
hjic-96	243	3	yk-1	yk-1	ADV
hjic-96	243	4	,	,	PUNCT
hjic-96	243	5	yk-2	yk-2	PROPN
hjic-96	243	6	,	,	PUNCT
hjic-96	243	7	yk-3	yk-3	PROPN
hjic-96	243	8	,	,	PUNCT
hjic-96	243	9	uk	uk	PROPN
hjic-96	243	10	8.1	8.1	NUM
hjic-96	243	11	96.3	96.3	NUM
hjic-96	243	12	822	822	NUM
hjic-96	243	13	2	2	NUM
hjic-96	243	14	.	.	X
hjic-96	244	1	yk	yk	PROPN
hjic-96	244	2	,	,	PUNCT
hjic-96	244	3	yk-1	yk-1	ADP
hjic-96	244	4	,	,	PUNCT
hjic-96	244	5	yk-3	yk-3	PROPN
hjic-96	244	6	,	,	PUNCT
hjic-96	244	7	uk	uk	PROPN
hjic-96	244	8	8.2	8.2	NUM
hjic-96	244	9	95.9	95.9	NUM
hjic-96	244	10	819	819	NUM
hjic-96	244	11	3	3	NUM
hjic-96	244	12	.	.	PUNCT
hjic-96	245	1	yk	yk	PROPN
hjic-96	245	2	,	,	PUNCT
hjic-96	245	3	yk-2	yk-2	PROPN
hjic-96	245	4	,	,	PUNCT
hjic-96	245	5	yk-3	yk-3	PROPN
hjic-96	245	6	,	,	PUNCT
hjic-96	245	7	uk	uk	PROPN
hjic-96	245	8	8.2	8.2	NUM
hjic-96	245	9	95.7	95.7	NUM
hjic-96	245	10	817	817	NUM
hjic-96	245	11	4	4	NUM
hjic-96	245	12	.	.	PUNCT
hjic-96	246	1	yk	yk	PROPN
hjic-96	246	2	,	,	PUNCT
hjic-96	246	3	yk-1	yk-1	ADV
hjic-96	246	4	,	,	PUNCT
hjic-96	246	5	yk-2	yk-2	PROPN
hjic-96	246	6	,	,	PUNCT
hjic-96	246	7	yk-3	yk-3	NOUN
hjic-96	246	8	,	,	PUNCT
hjic-96	246	9	uk-1	uk-1	ADP
hjic-96	246	10	8.7	8.7	NUM
hjic-96	246	11	95.3	95.3	NUM
hjic-96	246	12	814	814	NUM
hjic-96	246	13	5	5	NUM
hjic-96	246	14	.	.	PUNCT
hjic-96	247	1	yk	yk	PROPN
hjic-96	247	2	,	,	PUNCT
hjic-96	247	3	yk-3	yk-3	PROPN
hjic-96	247	4	,	,	PUNCT
hjic-96	247	5	uk	uk	PROPN
hjic-96	247	6	,	,	PUNCT
hjic-96	247	7	uk-2	uk-2	PRON
hjic-96	247	8	,	,	PUNCT
hjic-96	247	9	uk-3	uk-3	VERB
hjic-96	247	10	8.3	8.3	NUM
hjic-96	247	11	95	95	NUM
hjic-96	247	12	811	811	NUM
hjic-96	247	13	table	table	NOUN
hjic-96	247	14	4	4	NUM
hjic-96	247	15	shows	show	VERB
hjic-96	247	16	the	the	DET
hjic-96	247	17	selected	select	VERB
hjic-96	247	18	model	model	NOUN
hjic-96	247	19	structures	structure	NOUN
hjic-96	247	20	for	for	ADP
hjic-96	247	21	several	several	ADJ
hjic-96	247	22	minimal	minimal	ADJ
hjic-96	247	23	support	support	NOUN
hjic-96	247	24	and	and	CCONJ
hjic-96	247	25	confidence	confidence	NOUN
hjic-96	247	26	conditions	condition	NOUN
hjic-96	247	27	.	.	PUNCT
hjic-96	248	1	the	the	DET
hjic-96	248	2	selected	select	VERB
hjic-96	248	3	model	model	NOUN
hjic-96	248	4	structures	structure	NOUN
hjic-96	248	5	(	(	PUNCT
hjic-96	248	6	e.g.	e.g.	ADV
hjic-96	248	7	in	in	ADP
hjic-96	248	8	table	table	NOUN
hjic-96	248	9	3	3	NUM
hjic-96	248	10	)	)	PUNCT
hjic-96	248	11	can	can	AUX
hjic-96	248	12	be	be	AUX
hjic-96	248	13	used	use	VERB
hjic-96	248	14	to	to	PART
hjic-96	248	15	identify	identify	VERB
hjic-96	248	16	the	the	DET
hjic-96	248	17	linear	linear	NOUN
hjic-96	248	18	and	and	CCONJ
hjic-96	248	19	the	the	DET
hjic-96	248	20	nn	nn	PROPN
hjic-96	248	21	model	model	PROPN
hjic-96	248	22	.	.	PUNCT
hjic-96	249	1	table	table	NOUN
hjic-96	249	2	4	4	NUM
hjic-96	249	3	the	the	DET
hjic-96	249	4	selected	select	VERB
hjic-96	249	5	model	model	NOUN
hjic-96	249	6	structures	structure	NOUN
hjic-96	249	7	for	for	ADP
hjic-96	249	8	several	several	ADJ
hjic-96	249	9	searching	searching	NOUN
hjic-96	249	10	condition	condition	NOUN
hjic-96	249	11	(	(	PUNCT
hjic-96	249	12	support	support	NOUN
hjic-96	249	13	,	,	PUNCT
hjic-96	249	14	confidence	confidence	NOUN
hjic-96	249	15	)	)	PUNCT
hjic-96	249	16	σ	σ	PROPN
hjic-96	249	17	γ	γ	X
hjic-96	249	18	best	good	ADJ
hjic-96	249	19	structure	structure	NOUN
hjic-96	249	20	1	1	NUM
hjic-96	249	21	95	95	NUM
hjic-96	249	22	yk	yk	PROPN
hjic-96	249	23	,	,	PUNCT
hjic-96	249	24	yk-1	yk-1	NOUN
hjic-96	249	25	,	,	PUNCT
hjic-96	249	26	yk-2	yk-2	PROPN
hjic-96	249	27	,	,	PUNCT
hjic-96	249	28	yk-3	yk-3	PROPN
hjic-96	249	29	,	,	PUNCT
hjic-96	249	30	uk	uk	PROPN
hjic-96	249	31	1	1	NUM
hjic-96	249	32	80	80	NUM
hjic-96	249	33	yk-3	yk-3	NOUN
hjic-96	249	34	,	,	PUNCT
hjic-96	249	35	uk	uk	PROPN
hjic-96	249	36	1	1	NUM
hjic-96	249	37	70	70	NUM
hjic-96	249	38	yk	yk	PROPN
hjic-96	249	39	,	,	PUNCT
hjic-96	249	40	yk-1	yk-1	ADP
hjic-96	249	41	,	,	PUNCT
hjic-96	249	42	yk-3	yk-3	NOUN
hjic-96	249	43	,	,	PUNCT
hjic-96	249	44	uk	uk	PROPN
hjic-96	249	45	,	,	PUNCT
hjic-96	249	46	uk-2	uk-2	X
hjic-96	249	47	1	1	NUM
hjic-96	249	48	60	60	NUM
hjic-96	249	49	yk	yk	PROPN
hjic-96	249	50	,	,	PUNCT
hjic-96	249	51	yk-1	yk-1	NOUN
hjic-96	249	52	,	,	PUNCT
hjic-96	249	53	yk-2	yk-2	PROPN
hjic-96	249	54	,	,	PUNCT
hjic-96	249	55	yk-3	yk-3	PROPN
hjic-96	249	56	,	,	PUNCT
hjic-96	249	57	uk	uk	PROPN
hjic-96	249	58	,	,	PUNCT
hjic-96	249	59	uk-1	uk-1	ADP
hjic-96	249	60	1	1	NUM
hjic-96	249	61	50	50	NUM
hjic-96	249	62	yk-1	yk-1	NOUN
hjic-96	249	63	,	,	PUNCT
hjic-96	249	64	yk-3	yk-3	NOUN
hjic-96	249	65	uk	uk	PROPN
hjic-96	249	66	,	,	PUNCT
hjic-96	249	67	uk-1	uk-1	NUM
hjic-96	249	68	,	,	PUNCT
hjic-96	249	69	uk-2	uk-2	X
hjic-96	249	70	,	,	PUNCT
hjic-96	249	71	uk-3	uk-3	PUNCT
hjic-96	249	72	5	5	NUM
hjic-96	249	73	50	50	NUM
hjic-96	249	74	yk	yk	PROPN
hjic-96	249	75	,	,	PUNCT
hjic-96	249	76	yk-3	yk-3	PROPN
hjic-96	249	77	,	,	PUNCT
hjic-96	249	78	uk	uk	PROPN
hjic-96	249	79	8	8	NUM
hjic-96	249	80	60	60	NUM
hjic-96	249	81	yk	yk	PROPN
hjic-96	249	82	,	,	PUNCT
hjic-96	249	83	yk-3	yk-3	PROPN
hjic-96	249	84	,	,	PUNCT
hjic-96	249	85	uk	uk	PROPN
hjic-96	249	86	3	3	NUM
hjic-96	249	87	70	70	NUM
hjic-96	249	88	yk	yk	PROPN
hjic-96	249	89	,	,	PUNCT
hjic-96	249	90	yk-3	yk-3	PROPN
hjic-96	249	91	,	,	PUNCT
hjic-96	249	92	uk	uk	PROPN
hjic-96	249	93	the	the	DET
hjic-96	249	94	results	result	NOUN
hjic-96	249	95	are	be	AUX
hjic-96	249	96	showed	show	VERB
hjic-96	249	97	in	in	ADP
hjic-96	249	98	figures	figure	NOUN
hjic-96	249	99	8	8	NUM
hjic-96	249	100	-	-	SYM
hjic-96	249	101	11	11	NUM
hjic-96	249	102	.	.	PUNCT
hjic-96	250	1	we	we	PRON
hjic-96	250	2	can	can	AUX
hjic-96	250	3	see	see	VERB
hjic-96	250	4	that	that	SCONJ
hjic-96	250	5	the	the	DET
hjic-96	250	6	nn	nn	PROPN
hjic-96	250	7	model	model	NOUN
hjic-96	250	8	gives	give	VERB
hjic-96	250	9	lower	low	ADJ
hjic-96	250	10	mse	mse	NOUN
hjic-96	250	11	values	value	NOUN
hjic-96	250	12	in	in	ADP
hjic-96	250	13	all	all	DET
hjic-96	250	14	cases	case	NOUN
hjic-96	250	15	.	.	PUNCT
hjic-96	251	1	the	the	DET
hjic-96	251	2	mse	mse	PROPN
hjic-96	251	3	values	value	NOUN
hjic-96	251	4	are	be	AUX
hjic-96	251	5	lower	low	ADJ
hjic-96	251	6	at	at	ADP
hjic-96	251	7	the	the	DET
hjic-96	251	8	using	using	NOUN
hjic-96	251	9	of	of	ADP
hjic-96	251	10	first	first	ADJ
hjic-96	251	11	structures	structure	NOUN
hjic-96	251	12	as	as	ADP
hjic-96	251	13	the	the	DET
hjic-96	251	14	other	other	ADJ
hjic-96	251	15	structures	structure	NOUN
hjic-96	251	16	in	in	ADP
hjic-96	251	17	both	both	DET
hjic-96	251	18	model	model	NOUN
hjic-96	251	19	(	(	PUNCT
hjic-96	251	20	linear	linear	PROPN
hjic-96	251	21	and	and	CCONJ
hjic-96	251	22	nn	nn	NUM
hjic-96	251	23	)	)	PUNCT
hjic-96	251	24	.	.	PUNCT
hjic-96	252	1	the	the	DET
hjic-96	252	2	resulted	resulted	ADJ
hjic-96	252	3	mse	mse	NOUN
hjic-96	252	4	values	value	NOUN
hjic-96	252	5	are	be	AUX
hjic-96	252	6	higher	high	ADJ
hjic-96	252	7	than	than	ADP
hjic-96	252	8	the	the	DET
hjic-96	252	9	original	original	ADJ
hjic-96	252	10	(	(	PUNCT
hjic-96	252	11	the	the	DET
hjic-96	252	12	full	full	ADJ
hjic-96	252	13	)	)	PUNCT
hjic-96	252	14	structures	structure	NOUN
hjic-96	252	15	,	,	PUNCT
hjic-96	252	16	but	but	CCONJ
hjic-96	252	17	the	the	DET
hjic-96	252	18	differences	difference	NOUN
hjic-96	252	19	are	be	AUX
hjic-96	252	20	not	not	PART
hjic-96	252	21	considerable	considerable	ADJ
hjic-96	252	22	and	and	CCONJ
hjic-96	252	23	these	these	DET
hjic-96	252	24	structures	structure	NOUN
hjic-96	252	25	are	be	AUX
hjic-96	252	26	smaller	small	ADJ
hjic-96	252	27	than	than	ADP
hjic-96	252	28	the	the	DET
hjic-96	252	29	original	original	ADJ
hjic-96	252	30	model	model	NOUN
hjic-96	252	31	structure	structure	NOUN
hjic-96	252	32	.	.	PUNCT
hjic-96	253	1	therefore	therefore	ADV
hjic-96	253	2	mossfarm	mossfarm	NOUN
hjic-96	253	3	can	can	AUX
hjic-96	253	4	be	be	AUX
hjic-96	253	5	an	an	DET
hjic-96	253	6	efficient	efficient	ADJ
hjic-96	253	7	method	method	NOUN
hjic-96	253	8	for	for	ADP
hjic-96	253	9	determining	determine	VERB
hjic-96	253	10	the	the	DET
hjic-96	253	11	model	model	NOUN
hjic-96	253	12	structure	structure	NOUN
hjic-96	253	13	for	for	ADP
hjic-96	253	14	inputoutput	inputoutput	NOUN
hjic-96	253	15	models	model	NOUN
hjic-96	253	16	.	.	PUNCT
hjic-96	254	1	0.00040	0.00040	NUM
hjic-96	254	2	0.00050	0.00050	NUM
hjic-96	254	3	0.00060	0.00060	NUM
hjic-96	254	4	0.00070	0.00070	NUM
hjic-96	254	5	0.00080	0.00080	NUM
hjic-96	254	6	0.00090	0.00090	NUM
hjic-96	254	7	1	1	NUM
hjic-96	254	8	2	2	NUM
hjic-96	254	9	3	3	NUM
hjic-96	254	10	4	4	NUM
hjic-96	254	11	5	5	NUM
hjic-96	254	12	structure	structure	NOUN
hjic-96	254	13	#	#	NOUN
hjic-96	254	14	m	m	PROPN
hjic-96	254	15	se	se	X
hjic-96	254	16	fig.8	fig.8	PROPN
hjic-96	254	17	the	the	DET
hjic-96	254	18	mse	mse	PROPN
hjic-96	254	19	values	value	NOUN
hjic-96	254	20	for	for	ADP
hjic-96	254	21	the	the	DET
hjic-96	254	22	linear	linear	ADJ
hjic-96	254	23	model	model	NOUN
hjic-96	254	24	with	with	ADP
hjic-96	254	25	the	the	DET
hjic-96	254	26	selected	select	VERB
hjic-96	254	27	model	model	NOUN
hjic-96	254	28	structures	structure	NOUN
hjic-96	254	29	0.00004	0.00004	NUM
hjic-96	254	30	0.00009	0.00009	NUM
hjic-96	254	31	0.00014	0.00014	NUM
hjic-96	254	32	0.00019	0.00019	NUM
hjic-96	255	1	0.00024	0.00024	NUM
hjic-96	255	2	0.00029	0.00029	NUM
hjic-96	255	3	1	1	NUM
hjic-96	255	4	2	2	NUM
hjic-96	255	5	3	3	NUM
hjic-96	255	6	4	4	NUM
hjic-96	255	7	5	5	NUM
hjic-96	255	8	structure	structure	NOUN
hjic-96	255	9	#	#	NOUN
hjic-96	255	10	m	m	PROPN
hjic-96	255	11	se	se	PROPN
hjic-96	255	12	fig.9	fig.9	ADP
hjic-96	255	13	the	the	DET
hjic-96	255	14	mse	mse	PROPN
hjic-96	255	15	values	value	NOUN
hjic-96	255	16	for	for	ADP
hjic-96	255	17	the	the	DET
hjic-96	255	18	nn	nn	PROPN
hjic-96	255	19	model	model	NOUN
hjic-96	255	20	with	with	ADP
hjic-96	255	21	the	the	DET
hjic-96	255	22	selected	select	VERB
hjic-96	255	23	model	model	NOUN
hjic-96	255	24	structures	structure	NOUN
hjic-96	256	1	0	0	NUM
hjic-96	256	2	0.1	0.1	NUM
hjic-96	256	3	0.2	0.2	NUM
hjic-96	256	4	0.3	0.3	NUM
hjic-96	256	5	0.4	0.4	NUM
hjic-96	256	6	0.5	0.5	NUM
hjic-96	256	7	0.6	0.6	NUM
hjic-96	256	8	0.7	0.7	NUM
hjic-96	256	9	0.8	0.8	NUM
hjic-96	256	10	0.9	0.9	NUM
hjic-96	256	11	1	1	NUM
hjic-96	256	12	-0.2	-0.2	NOUN
hjic-96	256	13	0	0	NUM
hjic-96	256	14	0.2	0.2	NUM
hjic-96	256	15	0.4	0.4	NUM
hjic-96	256	16	0.6	0.6	NUM
hjic-96	256	17	0.8	0.8	NUM
hjic-96	256	18	1	1	NUM
hjic-96	256	19	1.2	1.2	NUM
hjic-96	256	20	y(k	y(k	PROPN
hjic-96	256	21	)	)	PUNCT
hjic-96	256	22	data	datum	NOUN
hjic-96	256	23	ym	ym	INTJ
hjic-96	256	24	(	(	PUNCT
hjic-96	256	25	k	k	PROPN
hjic-96	256	26	)	)	PUNCT
hjic-96	256	27	li	li	PROPN
hjic-96	256	28	ne	ne	PROPN
hjic-96	256	29	ar	ar	PROPN
hjic-96	256	30	m	m	PROPN
hjic-96	256	31	od	od	PROPN
hjic-96	256	32	el	el	PROPN
hjic-96	256	33	fig	fig	PROPN
hjic-96	256	34	.10	.10	NUM
hjic-96	256	35	the	the	DET
hjic-96	256	36	linear	linear	ADJ
hjic-96	256	37	model	model	NOUN
hjic-96	256	38	output	output	NOUN
hjic-96	256	39	values	value	NOUN
hjic-96	256	40	ym(k	ym(k	PROPN
hjic-96	256	41	)	)	PUNCT
hjic-96	256	42	in	in	ADP
hjic-96	256	43	function	function	NOUN
hjic-96	256	44	of	of	ADP
hjic-96	256	45	the	the	DET
hjic-96	256	46	simulated	simulate	VERB
hjic-96	256	47	output	output	NOUN
hjic-96	256	48	values	value	NOUN
hjic-96	256	49	y(k	y(k	PROPN
hjic-96	256	50	)	)	PUNCT
hjic-96	256	51	65	65	NUM
hjic-96	256	52	0	0	NUM
hjic-96	256	53	0.1	0.1	NUM
hjic-96	256	54	0.2	0.2	NUM
hjic-96	256	55	0.3	0.3	NUM
hjic-96	256	56	0.4	0.4	NUM
hjic-96	256	57	0.5	0.5	NUM
hjic-96	256	58	0.6	0.6	NUM
hjic-96	256	59	0.7	0.7	NUM
hjic-96	256	60	0.8	0.8	NUM
hjic-96	256	61	0.9	0.9	NUM
hjic-96	256	62	1	1	NUM
hjic-96	256	63	0	0	NUM
hjic-96	256	64	0.1	0.1	NUM
hjic-96	256	65	0.2	0.2	NUM
hjic-96	256	66	0.3	0.3	NUM
hjic-96	256	67	0.4	0.4	NUM
hjic-96	256	68	0.5	0.5	NUM
hjic-96	256	69	0.6	0.6	NUM
hjic-96	256	70	0.7	0.7	NUM
hjic-96	256	71	0.8	0.8	NUM
hjic-96	256	72	0.9	0.9	NUM
hjic-96	256	73	1	1	NUM
hjic-96	256	74	y(k	y(k	PROPN
hjic-96	256	75	)	)	PUNCT
hjic-96	256	76	data	datum	NOUN
hjic-96	256	77	ym	ym	INTJ
hjic-96	257	1	(	(	PUNCT
hjic-96	257	2	k	k	PROPN
hjic-96	257	3	)	)	PUNCT
hjic-96	257	4	n	n	CCONJ
hjic-96	257	5	n	n	ADV
hjic-96	257	6	m	m	PROPN
hjic-96	257	7	od	od	PROPN
hjic-96	257	8	el	el	PROPN
hjic-96	257	9	fig.11	fig.11	PROPN
hjic-96	257	10	the	the	DET
hjic-96	257	11	nn	nn	PROPN
hjic-96	257	12	model	model	NOUN
hjic-96	257	13	output	output	NOUN
hjic-96	257	14	values	value	NOUN
hjic-96	257	15	ym(k	ym(k	PROPN
hjic-96	257	16	)	)	PUNCT
hjic-96	257	17	in	in	ADP
hjic-96	257	18	function	function	NOUN
hjic-96	257	19	of	of	ADP
hjic-96	257	20	the	the	DET
hjic-96	257	21	simulated	simulate	VERB
hjic-96	257	22	output	output	NOUN
hjic-96	257	23	values	value	NOUN
hjic-96	257	24	y(k	y(k	PROPN
hjic-96	257	25	)	)	PUNCT
hjic-96	257	26	table	table	NOUN
hjic-96	257	27	5	5	NUM
hjic-96	257	28	the	the	DET
hjic-96	257	29	effects	effect	NOUN
hjic-96	257	30	of	of	ADP
hjic-96	257	31	the	the	DET
hjic-96	257	32	rule	rule	NOUN
hjic-96	257	33	pruning	prune	VERB
hjic-96	257	34	step	step	NOUN
hjic-96	257	35	original	original	ADJ
hjic-96	257	36	r.	r.	PROPN
hjic-96	257	37	base	base	PROPN
hjic-96	257	38	pruned	prune	VERB
hjic-96	257	39	r.	r.	PROPN
hjic-96	257	40	base	base	PROPN
hjic-96	257	41	first	first	ADJ
hjic-96	257	42	structure	structure	NOUN
hjic-96	257	43	yk	yk	PROPN
hjic-96	257	44	,	,	PUNCT
hjic-96	257	45	uk	uk	PROPN
hjic-96	257	46	,	,	PUNCT
hjic-96	257	47	uk-1	uk-1	NUM
hjic-96	257	48	,	,	PUNCT
hjic-96	257	49	uk-2	uk-2	PROPN
hjic-96	257	50	,	,	PUNCT
hjic-96	257	51	uk-3	uk-3	PUNCT
hjic-96	257	52	yk	yk	PROPN
hjic-96	257	53	,	,	PUNCT
hjic-96	257	54	yk-3,uk	yk-3,uk	PROPN
hjic-96	257	55	rules	rule	VERB
hjic-96	257	56	714	714	NUM
hjic-96	257	57	27	27	NUM
hjic-96	257	58	conditions	condition	NOUN
hjic-96	257	59	3157	3157	NUM
hjic-96	257	60	77	77	NUM
hjic-96	257	61	mse	mse	NOUN
hjic-96	257	62	of	of	ADP
hjic-96	257	63	lin	lin	PROPN
hjic-96	257	64	.	.	PROPN
hjic-96	258	1	0.001	0.001	NUM
hjic-96	258	2	0.0008025	0.0008025	NUM
hjic-96	258	3	mse	mse	NOUN
hjic-96	258	4	of	of	ADP
hjic-96	258	5	lin	lin	PROPN
hjic-96	258	6	.	.	PUNCT
hjic-96	259	1	free	free	ADJ
hjic-96	259	2	0.0352	0.0352	NUM
hjic-96	259	3	0.0141	0.0141	NUM
hjic-96	259	4	mse	mse	NOUN
hjic-96	259	5	of	of	ADP
hjic-96	259	6	nn	nn	PROPN
hjic-96	259	7	0.00039197	0.00039197	NUM
hjic-96	259	8	0.00030913	0.00030913	NUM
hjic-96	259	9	mse	mse	NOUN
hjic-96	259	10	of	of	ADP
hjic-96	259	11	nn	nn	X
hjic-96	259	12	free	free	ADJ
hjic-96	259	13	0.03	0.03	NUM
hjic-96	259	14	0.0093	0.0093	NUM
hjic-96	259	15	table	table	NOUN
hjic-96	259	16	5	5	NUM
hjic-96	259	17	shows	show	VERB
hjic-96	259	18	the	the	DET
hjic-96	259	19	results	result	NOUN
hjic-96	259	20	of	of	ADP
hjic-96	259	21	the	the	DET
hjic-96	259	22	rule	rule	NOUN
hjic-96	259	23	base	base	NOUN
hjic-96	259	24	complexity	complexity	NOUN
hjic-96	259	25	analysis	analysis	NOUN
hjic-96	259	26	.	.	PUNCT
hjic-96	260	1	the	the	DET
hjic-96	260	2	searching	searching	NOUN
hjic-96	260	3	conditions	condition	NOUN
hjic-96	260	4	were	be	AUX
hjic-96	260	5	followings	following	NOUN
hjic-96	260	6	:	:	PUNCT
hjic-96	260	7	σ	σ	NOUN
hjic-96	260	8	=	=	SYM
hjic-96	260	9	3	3	NUM
hjic-96	260	10	%	%	NOUN
hjic-96	260	11	,	,	PUNCT
hjic-96	260	12	γ	γ	NOUN
hjic-96	260	13	=	=	SYM
hjic-96	260	14	90	90	NUM
hjic-96	260	15	%	%	NOUN
hjic-96	260	16	for	for	ADP
hjic-96	260	17	the	the	DET
hjic-96	260	18	original	original	ADJ
hjic-96	260	19	simulated	simulate	VERB
hjic-96	260	20	(	(	PUNCT
hjic-96	260	21	with	with	ADP
hjic-96	260	22	the	the	DET
hjic-96	260	23	regressor	regressor	NOUN
hjic-96	260	24	in	in	ADP
hjic-96	260	25	eq	eq	PROPN
hjic-96	260	26	.	.	PROPN
hjic-96	260	27	18	18	NUM
hjic-96	260	28	)	)	PUNCT
hjic-96	260	29	data	datum	NOUN
hjic-96	260	30	.	.	PUNCT
hjic-96	261	1	the	the	DET
hjic-96	261	2	rule	rule	NOUN
hjic-96	261	3	pruning	prune	VERB
hjic-96	261	4	step	step	NOUN
hjic-96	261	5	give	give	VERB
hjic-96	261	6	smaller	small	ADJ
hjic-96	261	7	,	,	PUNCT
hjic-96	261	8	but	but	CCONJ
hjic-96	261	9	well	well	ADV
hjic-96	261	10	usable	usable	ADJ
hjic-96	261	11	model	model	NOUN
hjic-96	261	12	structures	structure	NOUN
hjic-96	261	13	both	both	CCONJ
hjic-96	261	14	in	in	ADP
hjic-96	261	15	linear	linear	PROPN
hjic-96	261	16	and	and	CCONJ
hjic-96	261	17	nn	nn	NUM
hjic-96	261	18	models	model	NOUN
hjic-96	261	19	.	.	PUNCT
hjic-96	262	1	the	the	DET
hjic-96	262	2	pruned	prune	VERB
hjic-96	262	3	rule	rule	NOUN
hjic-96	262	4	base	base	NOUN
hjic-96	262	5	has	have	VERB
hjic-96	262	6	97.56	97.56	NUM
hjic-96	262	7	percent	percent	NOUN
hjic-96	262	8	less	less	ADJ
hjic-96	262	9	complexity	complexity	NOUN
hjic-96	262	10	than	than	ADP
hjic-96	262	11	the	the	DET
hjic-96	262	12	original	original	ADJ
hjic-96	262	13	rule	rule	NOUN
hjic-96	262	14	base	base	NOUN
hjic-96	262	15	and	and	CCONJ
hjic-96	262	16	lower	low	ADJ
hjic-96	262	17	mse	mse	NOUN
hjic-96	262	18	values	value	NOUN
hjic-96	262	19	.	.	PUNCT
hjic-96	263	1	if	if	SCONJ
hjic-96	263	2	the	the	DET
hjic-96	263	3	structures	structure	NOUN
hjic-96	263	4	are	be	AUX
hjic-96	263	5	ordered	order	VERB
hjic-96	263	6	by	by	ADP
hjic-96	263	7	the	the	DET
hjic-96	263	8	number	number	NOUN
hjic-96	263	9	of	of	ADP
hjic-96	263	10	aggregated	aggregate	VERB
hjic-96	263	11	rules	rule	NOUN
hjic-96	263	12	,	,	PUNCT
hjic-96	263	13	the	the	DET
hjic-96	263	14	first	first	ADJ
hjic-96	263	15	structures	structure	NOUN
hjic-96	263	16	are	be	AUX
hjic-96	263	17	the	the	DET
hjic-96	263	18	yk	yk	PROPN
hjic-96	263	19	,	,	PUNCT
hjic-96	263	20	yk-1	yk-1	ADV
hjic-96	263	21	,	,	PUNCT
hjic-96	263	22	yk-2	yk-2	NOUN
hjic-96	263	23	,	,	PUNCT
hjic-96	263	24	uk-1	uk-1	NUM
hjic-96	263	25	,	,	PUNCT
hjic-96	263	26	uk-2	uk-2	X
hjic-96	263	27	(	(	PUNCT
hjic-96	263	28	with	with	ADP
hjic-96	263	29	the	the	DET
hjic-96	263	30	original	original	ADJ
hjic-96	263	31	rule	rule	NOUN
hjic-96	263	32	base	base	NOUN
hjic-96	263	33	)	)	PUNCT
hjic-96	263	34	,	,	PUNCT
hjic-96	263	35	and	and	CCONJ
hjic-96	263	36	the	the	DET
hjic-96	263	37	yk	yk	PROPN
hjic-96	263	38	,	,	PUNCT
hjic-96	263	39	yk-3,uk	yk-3,uk	PROPN
hjic-96	263	40	(	(	PUNCT
hjic-96	263	41	with	with	ADP
hjic-96	263	42	pruned	prune	VERB
hjic-96	263	43	rule	rule	NOUN
hjic-96	263	44	base	base	NOUN
hjic-96	263	45	,	,	PUNCT
hjic-96	263	46	all	all	DET
hjic-96	263	47	other	other	ADJ
hjic-96	263	48	searching	searching	NOUN
hjic-96	263	49	parameters	parameter	NOUN
hjic-96	263	50	are	be	AUX
hjic-96	263	51	equal	equal	ADJ
hjic-96	263	52	as	as	SCONJ
hjic-96	263	53	was	be	AUX
hjic-96	263	54	in	in	ADP
hjic-96	263	55	case	case	NOUN
hjic-96	263	56	of	of	ADP
hjic-96	263	57	table	table	NOUN
hjic-96	263	58	5	5	NUM
hjic-96	263	59	)	)	PUNCT
hjic-96	263	60	.	.	PUNCT
hjic-96	264	1	for	for	ADP
hjic-96	264	2	the	the	DET
hjic-96	264	3	structure	structure	NOUN
hjic-96	264	4	yk	yk	PROPN
hjic-96	264	5	,	,	PUNCT
hjic-96	264	6	yk-1	yk-1	ADV
hjic-96	264	7	,	,	PUNCT
hjic-96	264	8	yk-2	yk-2	NOUN
hjic-96	264	9	,	,	PUNCT
hjic-96	264	10	uk-1	uk-1	PRON
hjic-96	264	11	,	,	PUNCT
hjic-96	264	12	uk-2	uk-2	PUNCT
hjic-96	264	13	the	the	DET
hjic-96	264	14	mse	mse	PROPN
hjic-96	264	15	values	value	NOUN
hjic-96	264	16	of	of	ADP
hjic-96	264	17	the	the	DET
hjic-96	264	18	linear	linear	NOUN
hjic-96	264	19	and	and	CCONJ
hjic-96	264	20	the	the	DET
hjic-96	264	21	nn	nn	PROPN
hjic-96	264	22	model	model	NOUN
hjic-96	264	23	in	in	ADP
hjic-96	264	24	the	the	DET
hjic-96	264	25	case	case	NOUN
hjic-96	264	26	of	of	ADP
hjic-96	264	27	free	free	ADJ
hjic-96	264	28	running	running	NOUN
hjic-96	264	29	are	be	AUX
hjic-96	264	30	0.0223	0.0223	NUM
hjic-96	264	31	,	,	PUNCT
hjic-96	264	32	0.0192	0.0192	NUM
hjic-96	264	33	respectively	respectively	ADV
hjic-96	264	34	(	(	PUNCT
hjic-96	264	35	the	the	DET
hjic-96	264	36	results	result	NOUN
hjic-96	264	37	are	be	AUX
hjic-96	264	38	depicted	depict	VERB
hjic-96	264	39	in	in	ADP
hjic-96	264	40	fig	fig	NOUN
hjic-96	264	41	.	.	PUNCT
hjic-96	265	1	12	12	NUM
hjic-96	265	2	and	and	CCONJ
hjic-96	265	3	fig	fig	NOUN
hjic-96	265	4	.	.	PUNCT
hjic-96	265	5	13	13	NUM
hjic-96	265	6	)	)	PUNCT
hjic-96	265	7	.	.	PUNCT
hjic-96	266	1	for	for	ADP
hjic-96	266	2	structure	structure	NOUN
hjic-96	266	3	yk	yk	PROPN
hjic-96	266	4	,	,	PUNCT
hjic-96	266	5	yk-3,uk	yk-3,uk	PROPN
hjic-96	266	6	lower	low	ADJ
hjic-96	266	7	mse	mse	PROPN
hjic-96	266	8	values	value	NOUN
hjic-96	266	9	are	be	AUX
hjic-96	266	10	resulted	result	VERB
hjic-96	266	11	:	:	PUNCT
hjic-96	266	12	0.0141	0.0141	NUM
hjic-96	266	13	at	at	ADP
hjic-96	266	14	free	free	ADJ
hjic-96	266	15	running	running	NOUN
hjic-96	266	16	of	of	ADP
hjic-96	266	17	linear	linear	ADJ
hjic-96	266	18	model	model	NOUN
hjic-96	266	19	and	and	CCONJ
hjic-96	266	20	0.0174	0.0174	NUM
hjic-96	266	21	at	at	ADP
hjic-96	266	22	free	free	ADJ
hjic-96	266	23	running	running	NOUN
hjic-96	266	24	of	of	ADP
hjic-96	266	25	nn	nn	PROPN
hjic-96	266	26	model	model	NOUN
hjic-96	266	27	.	.	PUNCT
hjic-96	267	1	0	0	NUM
hjic-96	268	1	200	200	NUM
hjic-96	268	2	400	400	NUM
hjic-96	268	3	600	600	NUM
hjic-96	268	4	800	800	NUM
hjic-96	268	5	1000	1000	NUM
hjic-96	268	6	1200	1200	NUM
hjic-96	268	7	0	0	NUM
hjic-96	268	8	0.1	0.1	NUM
hjic-96	268	9	0.2	0.2	NUM
hjic-96	268	10	0.3	0.3	NUM
hjic-96	268	11	0.4	0.4	NUM
hjic-96	268	12	0.5	0.5	NUM
hjic-96	268	13	0.6	0.6	NUM
hjic-96	268	14	0.7	0.7	NUM
hjic-96	268	15	0.8	0.8	NUM
hjic-96	268	16	0.9	0.9	NUM
hjic-96	268	17	1	1	NUM
hjic-96	268	18	linear	linear	ADJ
hjic-96	268	19	input	input	NOUN
hjic-96	268	20	-	-	PUNCT
hjic-96	268	21	output	output	NOUN
hjic-96	268	22	modell	modell	NOUN
hjic-96	268	23	(	(	PUNCT
hjic-96	268	24	free	free	ADJ
hjic-96	268	25	run	run	NOUN
hjic-96	268	26	)	)	PUNCT
hjic-96	268	27	y	y	NOUN
hjic-96	268	28	:	:	PUNCT
hjic-96	268	29	output	output	PROPN
hjic-96	268	30	ym	ym	NOUN
hjic-96	268	31	:	:	PUNCT
hjic-96	268	32	modell	modell	PROPN
hjic-96	268	33	output	output	NOUN
hjic-96	268	34	(	(	PUNCT
hjic-96	268	35	free	free	ADJ
hjic-96	268	36	run	run	NOUN
hjic-96	268	37	)	)	PUNCT
hjic-96	268	38	fig.12	fig.12	NOUN
hjic-96	268	39	results	result	NOUN
hjic-96	268	40	of	of	ADP
hjic-96	268	41	the	the	DET
hjic-96	268	42	free	free	ADJ
hjic-96	268	43	run	run	NOUN
hjic-96	268	44	of	of	ADP
hjic-96	268	45	linear	linear	PROPN
hjic-96	268	46	model	model	NOUN
hjic-96	268	47	for	for	ADP
hjic-96	268	48	yk	yk	PROPN
hjic-96	268	49	,	,	PUNCT
hjic-96	268	50	yk-1	yk-1	ADV
hjic-96	268	51	,	,	PUNCT
hjic-96	268	52	yk-2	yk-2	NOUN
hjic-96	268	53	,	,	PUNCT
hjic-96	268	54	uk-1	uk-1	NUM
hjic-96	268	55	,	,	PUNCT
hjic-96	268	56	uk-2	uk-2	PUNCT
hjic-96	268	57	structure	structure	NOUN
hjic-96	268	58	0	0	NUM
hjic-96	269	1	200	200	NUM
hjic-96	269	2	400	400	NUM
hjic-96	269	3	600	600	NUM
hjic-96	269	4	800	800	NUM
hjic-96	269	5	1000	1000	NUM
hjic-96	269	6	1200	1200	NUM
hjic-96	269	7	0	0	NUM
hjic-96	269	8	0.1	0.1	NUM
hjic-96	269	9	0.2	0.2	NUM
hjic-96	269	10	0.3	0.3	NUM
hjic-96	269	11	0.4	0.4	NUM
hjic-96	269	12	0.5	0.5	NUM
hjic-96	269	13	0.6	0.6	NUM
hjic-96	269	14	0.7	0.7	NUM
hjic-96	269	15	0.8	0.8	NUM
hjic-96	269	16	0.9	0.9	NUM
hjic-96	269	17	1	1	NUM
hjic-96	269	18	neural	neural	ADJ
hjic-96	269	19	network	network	NOUN
hjic-96	269	20	modell	modell	PROPN
hjic-96	269	21	(	(	PUNCT
hjic-96	269	22	free	free	ADJ
hjic-96	269	23	run	run	NOUN
hjic-96	269	24	)	)	PUNCT
hjic-96	269	25	y	y	NOUN
hjic-96	269	26	:	:	PUNCT
hjic-96	269	27	output	output	PROPN
hjic-96	269	28	ym	ym	NOUN
hjic-96	269	29	:	:	PUNCT
hjic-96	269	30	modell	modell	PROPN
hjic-96	269	31	output	output	NOUN
hjic-96	269	32	(	(	PUNCT
hjic-96	269	33	free	free	ADJ
hjic-96	269	34	run	run	NOUN
hjic-96	269	35	)	)	PUNCT
hjic-96	269	36	fig	fig	NOUN
hjic-96	269	37	.13	.13	NUM
hjic-96	269	38	results	result	NOUN
hjic-96	269	39	of	of	ADP
hjic-96	269	40	the	the	DET
hjic-96	269	41	free	free	ADJ
hjic-96	269	42	run	run	NOUN
hjic-96	269	43	of	of	ADP
hjic-96	269	44	neural	neural	ADJ
hjic-96	269	45	model	model	NOUN
hjic-96	269	46	yk	yk	PROPN
hjic-96	269	47	,	,	PUNCT
hjic-96	269	48	yk-1	yk-1	ADV
hjic-96	269	49	,	,	PUNCT
hjic-96	269	50	yk-2	yk-2	NOUN
hjic-96	269	51	,	,	PUNCT
hjic-96	269	52	uk-1	uk-1	NUM
hjic-96	269	53	,	,	PUNCT
hjic-96	269	54	uk-2	uk-2	PUNCT
hjic-96	269	55	structure	structure	NOUN
hjic-96	269	56	feature	feature	NOUN
hjic-96	269	57	(	(	PUNCT
hjic-96	269	58	variable	variable	ADJ
hjic-96	269	59	)	)	PUNCT
hjic-96	269	60	selection	selection	NOUN
hjic-96	269	61	by	by	ADP
hjic-96	269	62	mossfarm	mossfarm	NOUN
hjic-96	269	63	the	the	DET
hjic-96	269	64	proposed	propose	VERB
hjic-96	269	65	method	method	NOUN
hjic-96	269	66	also	also	ADV
hjic-96	269	67	can	can	AUX
hjic-96	269	68	be	be	AUX
hjic-96	269	69	used	use	VERB
hjic-96	269	70	for	for	ADP
hjic-96	269	71	select	select	VERB
hjic-96	269	72	the	the	DET
hjic-96	269	73	most	most	ADV
hjic-96	269	74	relevant	relevant	ADJ
hjic-96	269	75	variable	variable	NOUN
hjic-96	269	76	which	which	PRON
hjic-96	269	77	determine	determine	VERB
hjic-96	269	78	the	the	DET
hjic-96	269	79	output	output	NOUN
hjic-96	269	80	variable	variable	NOUN
hjic-96	269	81	.	.	PUNCT
hjic-96	270	1	the	the	DET
hjic-96	270	2	four	four	NUM
hjic-96	270	3	state	state	NOUN
hjic-96	270	4	dimensionless	dimensionless	NOUN
hjic-96	270	5	form	form	NOUN
hjic-96	270	6	of	of	ADP
hjic-96	270	7	the	the	DET
hjic-96	270	8	model	model	NOUN
hjic-96	270	9	hidalgo	hidalgo	PROPN
hjic-96	270	10	and	and	CCONJ
hjic-96	270	11	brosilow	brosilow	NOUN
hjic-96	270	12	could	could	AUX
hjic-96	270	13	be	be	AUX
hjic-96	270	14	extended	extend	VERB
hjic-96	270	15	with	with	ADP
hjic-96	270	16	the	the	DET
hjic-96	270	17	dimensionless	dimensionless	ADJ
hjic-96	270	18	moment	moment	NOUN
hjic-96	270	19	equations	equation	NOUN
hjic-96	270	20	.	.	PUNCT
hjic-96	271	1	a	a	DET
hjic-96	271	2	new	new	ADJ
hjic-96	271	3	dataset	dataset	NOUN
hjic-96	271	4	is	be	AUX
hjic-96	271	5	based	base	VERB
hjic-96	271	6	on	on	ADP
hjic-96	271	7	the	the	DET
hjic-96	271	8	simulation	simulation	NOUN
hjic-96	271	9	of	of	ADP
hjic-96	271	10	this	this	DET
hjic-96	271	11	extended	extended	ADJ
hjic-96	271	12	dimensionless	dimensionless	NOUN
hjic-96	271	13	model	model	NOUN
hjic-96	271	14	with	with	ADP
hjic-96	271	15	six	six	NUM
hjic-96	271	16	state	state	NOUN
hjic-96	271	17	variables	variable	NOUN
hjic-96	271	18	.	.	PUNCT
hjic-96	272	1	the	the	DET
hjic-96	272	2	dimensionless	dimensionless	ADJ
hjic-96	272	3	number	number	NOUN
hjic-96	272	4	-	-	PUNCT
hjic-96	272	5	average	average	NOUN
hjic-96	272	6	molecular	molecular	ADJ
hjic-96	272	7	weight	weight	NOUN
hjic-96	272	8	(	(	PUNCT
hjic-96	272	9	namw	namw	ADV
hjic-96	272	10	)	)	PUNCT
hjic-96	272	11	is	be	AUX
hjic-96	272	12	the	the	DET
hjic-96	272	13	ratio	ratio	NOUN
hjic-96	272	14	of	of	ADP
hjic-96	272	15	the	the	DET
hjic-96	272	16	last	last	ADJ
hjic-96	272	17	two	two	NUM
hjic-96	272	18	state	state	NOUN
hjic-96	272	19	variables	variable	NOUN
hjic-96	272	20	of	of	ADP
hjic-96	272	21	the	the	DET
hjic-96	272	22	model	model	NOUN
hjic-96	272	23	[	[	X
hjic-96	272	24	35	35	NUM
hjic-96	272	25	]	]	PUNCT
hjic-96	272	26	.	.	PUNCT
hjic-96	273	1	the	the	DET
hjic-96	273	2	relevant	relevant	ADJ
hjic-96	273	3	variables	variable	NOUN
hjic-96	273	4	which	which	PRON
hjic-96	273	5	determine	determine	VERB
hjic-96	273	6	the	the	DET
hjic-96	273	7	value	value	NOUN
hjic-96	273	8	of	of	ADP
hjic-96	273	9	the	the	DET
hjic-96	273	10	namw	namw	NOUN
hjic-96	273	11	are	be	AUX
hjic-96	273	12	selected	select	VERB
hjic-96	273	13	by	by	ADP
hjic-96	273	14	the	the	DET
hjic-96	273	15	mossfarm	mossfarm	NOUN
hjic-96	273	16	method	method	NOUN
hjic-96	273	17	.	.	PUNCT
hjic-96	274	1	the	the	DET
hjic-96	274	2	new	new	ADJ
hjic-96	274	3	initial	initial	ADJ
hjic-96	274	4	model	model	NOUN
hjic-96	274	5	structure	structure	NOUN
hjic-96	274	6	is	be	AUX
hjic-96	274	7	:	:	PUNCT
hjic-96	274	8	]	]	PUNCT
hjic-96	274	9	)	)	PUNCT
hjic-96	274	10	,	,	PUNCT
hjic-96	274	11	(	(	PUNCT
hjic-96	274	12	[	[	PUNCT
hjic-96	274	13	7,,211	7,,211	NUM
hjic-96	274	14	kkkk	kkkk	PROPN
hjic-96	274	15	xxxfy	xxxfy	PROPN
hjic-96	274	16	k=+	k=+	NOUN
hjic-96	274	17	(	(	PUNCT
hjic-96	274	18	19	19	NUM
hjic-96	274	19	)	)	PUNCT
hjic-96	274	20	where	where	SCONJ
hjic-96	274	21	the	the	DET
hjic-96	274	22	dimensionless	dimensionless	NOUN
hjic-96	274	23	variables	variable	NOUN
hjic-96	274	24	are	be	AUX
hjic-96	274	25	the	the	DET
hjic-96	274	26	following	follow	VERB
hjic-96	274	27	:	:	PUNCT
hjic-96	274	28	y	y	NOUN
hjic-96	274	29	:	:	PUNCT
hjic-96	274	30	model	model	PROPN
hjic-96	274	31	output	output	NOUN
hjic-96	274	32	namw	namw	ADV
hjic-96	274	33	,	,	PUNCT
hjic-96	274	34	x1	x1	PROPN
hjic-96	274	35	:	:	PUNCT
hjic-96	274	36	the	the	DET
hjic-96	274	37	initiator	initiator	NOUN
hjic-96	274	38	concentration	concentration	NOUN
hjic-96	274	39	,	,	PUNCT
hjic-96	274	40	x2	x2	PRON
hjic-96	274	41	:	:	PUNCT
hjic-96	274	42	monomer	monomer	NOUN
hjic-96	274	43	concentration	concentration	NOUN
hjic-96	274	44	,	,	PUNCT
hjic-96	274	45	x3	x3	ADJ
hjic-96	274	46	:	:	PUNCT
hjic-96	274	47	reactor	reactor	NOUN
hjic-96	274	48	temperature	temperature	NOUN
hjic-96	274	49	,	,	PUNCT
hjic-96	274	50	x4	x4	ADV
hjic-96	274	51	:	:	PUNCT
hjic-96	274	52	jacket	jacket	NOUN
hjic-96	274	53	temperature	temperature	NOUN
hjic-96	274	54	,	,	PUNCT
hjic-96	274	55	x5	x5	NOUN
hjic-96	274	56	:	:	PUNCT
hjic-96	274	57	the	the	DET
hjic-96	274	58	first	first	ADJ
hjic-96	274	59	variable	variable	NOUN
hjic-96	274	60	in	in	ADP
hjic-96	274	61	the	the	DET
hjic-96	274	62	moment	moment	NOUN
hjic-96	274	63	equations	equation	NOUN
hjic-96	274	64	,	,	PUNCT
hjic-96	274	65	x6	x6	PROPN
hjic-96	274	66	:	:	PUNCT
hjic-96	274	67	the	the	DET
hjic-96	274	68	second	second	ADJ
hjic-96	274	69	variable	variable	NOUN
hjic-96	274	70	in	in	ADP
hjic-96	274	71	the	the	DET
hjic-96	274	72	moment	moment	NOUN
hjic-96	274	73	equations	equation	NOUN
hjic-96	274	74	and	and	CCONJ
hjic-96	274	75	x7	x7	NOUN
hjic-96	274	76	:	:	PUNCT
hjic-96	274	77	cooling	cool	VERB
hjic-96	274	78	jacket	jacket	NOUN
hjic-96	274	79	flowrate	flowrate	ADJ
hjic-96	274	80	.	.	PUNCT
hjic-96	275	1	if	if	SCONJ
hjic-96	275	2	the	the	DET
hjic-96	275	3	searching	searching	NOUN
hjic-96	275	4	conditions	condition	NOUN
hjic-96	275	5	were	be	AUX
hjic-96	275	6	the	the	DET
hjic-96	275	7	followings	following	NOUN
hjic-96	275	8	:	:	PUNCT
hjic-96	275	9	number	number	NOUN
hjic-96	275	10	of	of	ADP
hjic-96	275	11	66	66	NUM
hjic-96	275	12	partitions	partition	NOUN
hjic-96	275	13	(	(	PUNCT
hjic-96	275	14	~	~	PUNCT
hjic-96	275	15	clusters	cluster	NOUN
hjic-96	275	16	)	)	PUNCT
hjic-96	275	17	for	for	ADP
hjic-96	275	18	the	the	DET
hjic-96	275	19	output	output	NOUN
hjic-96	275	20	variable	variable	NOUN
hjic-96	275	21	:	:	PUNCT
hjic-96	275	22	5	5	NUM
hjic-96	275	23	,	,	PUNCT
hjic-96	275	24	the	the	DET
hjic-96	275	25	number	number	NOUN
hjic-96	275	26	of	of	ADP
hjic-96	275	27	partitions	partition	NOUN
hjic-96	275	28	in	in	ADP
hjic-96	275	29	the	the	DET
hjic-96	275	30	regressor	regressor	NOUN
hjic-96	275	31	variables	variable	VERB
hjic-96	275	32	:	:	PUNCT
hjic-96	275	33	3	3	NUM
hjic-96	275	34	,	,	PUNCT
hjic-96	275	35	σ	σ	NOUN
hjic-96	275	36	=	=	SYM
hjic-96	275	37	10	10	NUM
hjic-96	275	38	%	%	NOUN
hjic-96	275	39	,	,	PUNCT
hjic-96	275	40	γ	γ	NOUN
hjic-96	275	41	=	=	SYM
hjic-96	275	42	50	50	NUM
hjic-96	275	43	%	%	NOUN
hjic-96	275	44	,	,	PUNCT
hjic-96	275	45	the	the	DET
hjic-96	275	46	mossfarm	mossfarm	NOUN
hjic-96	275	47	selects	select	VERB
hjic-96	275	48	the	the	DET
hjic-96	275	49	structure	structure	NOUN
hjic-96	275	50	x1k	x1k	PROPN
hjic-96	275	51	,	,	PUNCT
hjic-96	275	52	x3k	x3k	PROPN
hjic-96	275	53	(	(	PUNCT
hjic-96	275	54	“	"	PUNCT
hjic-96	275	55	aggregated	aggregate	VERB
hjic-96	275	56	”	"	PUNCT
hjic-96	275	57	from	from	ADP
hjic-96	275	58	one	one	NUM
hjic-96	275	59	rule	rule	NOUN
hjic-96	275	60	)	)	PUNCT
hjic-96	275	61	as	as	ADP
hjic-96	275	62	first	first	ADV
hjic-96	275	63	(	(	PUNCT
hjic-96	275	64	ordered	order	VERB
hjic-96	275	65	by	by	ADP
hjic-96	275	66	the	the	DET
hjic-96	275	67	correlation	correlation	NOUN
hjic-96	275	68	)	)	PUNCT
hjic-96	275	69	.	.	PUNCT
hjic-96	276	1	this	this	DET
hjic-96	276	2	result	result	NOUN
hjic-96	276	3	says	say	VERB
hjic-96	276	4	that	that	SCONJ
hjic-96	276	5	the	the	DET
hjic-96	276	6	initiator	initiator	NOUN
hjic-96	276	7	concentration	concentration	NOUN
hjic-96	276	8	and	and	CCONJ
hjic-96	276	9	the	the	DET
hjic-96	276	10	reactor	reactor	NOUN
hjic-96	276	11	temperature	temperature	NOUN
hjic-96	276	12	determine	determine	VERB
hjic-96	276	13	the	the	DET
hjic-96	276	14	number	number	NOUN
hjic-96	276	15	-	-	PUNCT
hjic-96	276	16	average	average	NOUN
hjic-96	276	17	molecular	molecular	ADJ
hjic-96	276	18	weight	weight	NOUN
hjic-96	276	19	.	.	PUNCT
hjic-96	277	1	if	if	SCONJ
hjic-96	277	2	the	the	DET
hjic-96	277	3	ordering	ordering	NOUN
hjic-96	277	4	is	be	AUX
hjic-96	277	5	based	base	VERB
hjic-96	277	6	on	on	ADP
hjic-96	277	7	the	the	DET
hjic-96	277	8	number	number	NOUN
hjic-96	277	9	of	of	ADP
hjic-96	277	10	aggregated	aggregate	VERB
hjic-96	277	11	rules	rule	NOUN
hjic-96	277	12	,	,	PUNCT
hjic-96	277	13	the	the	DET
hjic-96	277	14	first	first	ADJ
hjic-96	277	15	selected	select	VERB
hjic-96	277	16	structure	structure	NOUN
hjic-96	277	17	is	be	AUX
hjic-96	277	18	the	the	DET
hjic-96	277	19	x6k	x6k	PROPN
hjic-96	277	20	,	,	PUNCT
hjic-96	277	21	x7k	x7k	PROPN
hjic-96	277	22	.	.	PUNCT
hjic-96	278	1	(	(	PUNCT
hjic-96	278	2	aggregated	aggregate	VERB
hjic-96	278	3	from	from	ADP
hjic-96	278	4	two	two	NUM
hjic-96	278	5	rules	rule	NOUN
hjic-96	278	6	)	)	PUNCT
hjic-96	278	7	.	.	PUNCT
hjic-96	279	1	the	the	DET
hjic-96	279	2	results	result	NOUN
hjic-96	279	3	are	be	AUX
hjic-96	279	4	summarized	summarize	VERB
hjic-96	279	5	in	in	ADP
hjic-96	279	6	table	table	NOUN
hjic-96	279	7	6	6	NUM
hjic-96	279	8	.	.	PUNCT
hjic-96	279	9	table	table	NOUN
hjic-96	279	10	6	6	NUM
hjic-96	279	11	linear	linear	ADJ
hjic-96	279	12	and	and	CCONJ
hjic-96	279	13	nn	nn	NUM
hjic-96	279	14	model	model	NOUN
hjic-96	279	15	for	for	ADP
hjic-96	279	16	estimate	estimate	NOUN
hjic-96	279	17	number	number	NOUN
hjic-96	279	18	-	-	PUNCT
hjic-96	279	19	average	average	NOUN
hjic-96	279	20	molecular	molecular	ADJ
hjic-96	279	21	weight	weight	NOUN
hjic-96	279	22	ordering	ordering	NOUN
hjic-96	279	23	by	by	ADP
hjic-96	279	24	corralation	corralation	NOUN
hjic-96	279	25	ordering	ordering	NOUN
hjic-96	279	26	by	by	ADP
hjic-96	279	27	rule	rule	NOUN
hjic-96	279	28	number	number	NOUN
hjic-96	279	29	first	first	ADJ
hjic-96	279	30	structure	structure	NOUN
hjic-96	279	31	x1k	x1k	PROPN
hjic-96	279	32	,	,	PUNCT
hjic-96	279	33	x3k	x3k	NUM
hjic-96	279	34	x6k	x6k	PROPN
hjic-96	279	35	,	,	PUNCT
hjic-96	279	36	x7k	x7k	PROPN
hjic-96	279	37	mse	mse	PROPN
hjic-96	279	38	of	of	ADP
hjic-96	279	39	lin	lin	PROPN
hjic-96	279	40	.	.	PUNCT
hjic-96	280	1	0.0103	0.0103	NUM
hjic-96	280	2	0.0049	0.0049	NUM
hjic-96	280	3	mse	mse	NOUN
hjic-96	280	4	of	of	ADP
hjic-96	280	5	lin	lin	PROPN
hjic-96	280	6	.	.	PUNCT
hjic-96	281	1	free	free	PROPN
hjic-96	281	2	0.0106	0.0106	NUM
hjic-96	281	3	0.576	0.576	NUM
hjic-96	281	4	mse	mse	NOUN
hjic-96	281	5	of	of	ADP
hjic-96	281	6	nn	nn	PROPN
hjic-96	281	7	0.0001723	0.0001723	NUM
hjic-96	281	8	0.000416	0.000416	NUM
hjic-96	281	9	mse	mse	NOUN
hjic-96	281	10	of	of	ADP
hjic-96	281	11	nn	nn	X
hjic-96	281	12	free	free	ADJ
hjic-96	281	13	0.2080	0.2080	NUM
hjic-96	281	14	0.576	0.576	NUM
hjic-96	281	15	conclusions	conclusion	NOUN
hjic-96	281	16	this	this	DET
hjic-96	281	17	paper	paper	NOUN
hjic-96	281	18	showed	show	VERB
hjic-96	281	19	a	a	DET
hjic-96	281	20	new	new	ADJ
hjic-96	281	21	model	model	NOUN
hjic-96	281	22	-	-	PUNCT
hjic-96	281	23	free	free	ADJ
hjic-96	281	24	,	,	PUNCT
hjic-96	281	25	fuzzy	fuzzy	ADJ
hjic-96	281	26	association	association	NOUN
hjic-96	281	27	rule	rule	NOUN
hjic-96	281	28	mining	mining	NOUN
hjic-96	281	29	based	base	VERB
hjic-96	281	30	method	method	NOUN
hjic-96	281	31	for	for	ADP
hjic-96	281	32	model	model	NOUN
hjic-96	281	33	structure	structure	NOUN
hjic-96	281	34	selection	selection	NOUN
hjic-96	281	35	for	for	ADP
hjic-96	281	36	input	input	NOUN
hjic-96	281	37	-	-	PUNCT
hjic-96	281	38	output	output	NOUN
hjic-96	281	39	data	data	NOUN
hjic-96	281	40	-	-	PUNCT
hjic-96	281	41	driven	drive	VERB
hjic-96	281	42	models	model	NOUN
hjic-96	281	43	.	.	PUNCT
hjic-96	282	1	the	the	DET
hjic-96	282	2	results	result	NOUN
hjic-96	282	3	show	show	VERB
hjic-96	282	4	that	that	SCONJ
hjic-96	282	5	the	the	DET
hjic-96	282	6	developed	develop	VERB
hjic-96	282	7	tool	tool	NOUN
hjic-96	282	8	provides	provide	VERB
hjic-96	282	9	an	an	DET
hjic-96	282	10	efficient	efficient	ADJ
hjic-96	282	11	method	method	NOUN
hjic-96	282	12	for	for	ADP
hjic-96	282	13	determining	determine	VERB
hjic-96	282	14	the	the	DET
hjic-96	282	15	model	model	NOUN
hjic-96	282	16	structure	structure	NOUN
hjic-96	282	17	of	of	ADP
hjic-96	282	18	both	both	CCONJ
hjic-96	282	19	linear	linear	ADJ
hjic-96	282	20	and	and	CCONJ
hjic-96	282	21	neural	neural	ADJ
hjic-96	282	22	network	network	NOUN
hjic-96	282	23	based	base	VERB
hjic-96	282	24	input	input	NOUN
hjic-96	282	25	-	-	PUNCT
hjic-96	282	26	output	output	NOUN
hjic-96	282	27	models	model	NOUN
hjic-96	282	28	.	.	PUNCT
hjic-96	283	1	moreover	moreover	ADV
hjic-96	283	2	this	this	DET
hjic-96	283	3	method	method	NOUN
hjic-96	283	4	is	be	AUX
hjic-96	283	5	also	also	ADV
hjic-96	283	6	can	can	AUX
hjic-96	283	7	be	be	AUX
hjic-96	283	8	used	use	VERB
hjic-96	283	9	to	to	ADP
hjic-96	283	10	selection	selection	NOUN
hjic-96	283	11	of	of	ADP
hjic-96	283	12	the	the	DET
hjic-96	283	13	most	most	ADV
hjic-96	283	14	relevant	relevant	ADJ
hjic-96	283	15	process	process	NOUN
hjic-96	283	16	variables	variable	NOUN
hjic-96	283	17	(	(	PUNCT
hjic-96	283	18	feature	feature	NOUN
hjic-96	283	19	selection	selection	NOUN
hjic-96	283	20	problem	problem	NOUN
hjic-96	283	21	)	)	PUNCT
hjic-96	283	22	.	.	PUNCT
hjic-96	284	1	the	the	DET
hjic-96	284	2	proposed	propose	VERB
hjic-96	284	3	approach	approach	NOUN
hjic-96	284	4	has	have	AUX
hjic-96	284	5	been	be	AUX
hjic-96	284	6	implemented	implement	VERB
hjic-96	284	7	as	as	ADP
hjic-96	284	8	a	a	DET
hjic-96	284	9	matlab	matlab	PROPN
hjic-96	284	10	program	program	NOUN
hjic-96	284	11	called	call	VERB
hjic-96	284	12	mossfarm	mossfarm	NOUN
hjic-96	284	13	(	(	PUNCT
hjic-96	284	14	model	model	NOUN
hjic-96	284	15	structures	structure	NOUN
hjic-96	284	16	selection	selection	NOUN
hjic-96	284	17	by	by	ADP
hjic-96	284	18	association	association	NOUN
hjic-96	284	19	rules	rule	NOUN
hjic-96	284	20	mining	mining	NOUN
hjic-96	284	21	)	)	PUNCT
hjic-96	284	22	,	,	PUNCT
hjic-96	284	23	it	it	PRON
hjic-96	284	24	will	will	AUX
hjic-96	284	25	be	be	AUX
hjic-96	284	26	free	free	ADJ
hjic-96	284	27	available	available	ADJ
hjic-96	284	28	from	from	ADP
hjic-96	284	29	:	:	PUNCT
hjic-96	284	30	www.fmt.vein.hu/	www.fmt.vein.hu/	PROPN
hjic-96	284	31	softcomp	softcomp	PROPN
hjic-96	284	32	.	.	PUNCT
hjic-96	285	1	acknowledgement	acknowledgement	NOUN
hjic-96	285	2	this	this	DET
hjic-96	285	3	project	project	NOUN
hjic-96	285	4	has	have	AUX
hjic-96	285	5	been	be	AUX
hjic-96	285	6	financially	financially	ADV
hjic-96	285	7	supported	support	VERB
hjic-96	285	8	in	in	ADP
hjic-96	285	9	part	part	NOUN
hjic-96	285	10	by	by	ADP
hjic-96	285	11	the	the	DET
hjic-96	285	12	hungarian	hungarian	ADJ
hjic-96	285	13	national	national	PROPN
hjic-96	285	14	science	science	PROPN
hjic-96	285	15	foundation	foundation	PROPN
hjic-96	285	16	otka	otka	PROPN
hjic-96	285	17	(	(	PUNCT
hjic-96	285	18	no	no	INTJ
hjic-96	285	19	.	.	PUNCT
hjic-96	286	1	t037600	t037600	NOUN
hjic-96	286	2	,	,	PUNCT
hjic-96	286	3	no	no	INTJ
hjic-96	286	4	.	.	PUNCT
hjic-96	287	1	t049534	t049534	NUM
hjic-96	287	2	)	)	PUNCT
hjic-96	287	3	.	.	PUNCT
hjic-96	288	1	references	reference	NOUN
hjic-96	288	2	1	1	NUM
hjic-96	288	3	.	.	PUNCT
hjic-96	288	4	ljung	ljung	PROPN
hjic-96	288	5	l.	l.	PROPN
hjic-96	288	6	:	:	PUNCT
hjic-96	288	7	system	system	NOUN
hjic-96	288	8	identification	identification	NOUN
hjic-96	288	9	.	.	PUNCT
hjic-96	289	1	1987	1987	NUM
hjic-96	289	2	,	,	PUNCT
hjic-96	289	3	prentice	prentice	NOUN
hjic-96	289	4	hall	hall	NOUN
hjic-96	289	5	2	2	NUM
hjic-96	289	6	.	.	PUNCT
hjic-96	289	7	petrick	petrick	PROPN
hjic-96	289	8	m.	m.	PROPN
hjic-96	289	9	h.	h.	PROPN
hjic-96	289	10	,	,	PUNCT
hjic-96	289	11	wigdorowitz	wigdorowitz	PROPN
hjic-96	289	12	b.	b.	PROPN
hjic-96	289	13	:	:	PUNCT
hjic-96	289	14	a	a	DET
hjic-96	289	15	priori	priori	X
hjic-96	289	16	nonlinear	nonlinear	ADJ
hjic-96	289	17	model	model	NOUN
hjic-96	289	18	structure	structure	NOUN
hjic-96	289	19	selection	selection	NOUN
hjic-96	289	20	for	for	ADP
hjic-96	289	21	system	system	NOUN
hjic-96	289	22	identification	identification	NOUN
hjic-96	289	23	.	.	PUNCT
hjic-96	290	1	control	control	PROPN
hjic-96	290	2	eng	eng	PROPN
hjic-96	290	3	.	.	PROPN
hjic-96	290	4	practise	practise	PROPN
hjic-96	290	5	,	,	PUNCT
hjic-96	290	6	1997	1997	NUM
hjic-96	290	7	,	,	PUNCT
hjic-96	290	8	5(8	5(8	NUM
hjic-96	290	9	)	)	PUNCT
hjic-96	290	10	,	,	PUNCT
hjic-96	290	11	1053	1053	NUM
hjic-96	290	12	-	-	SYM
hjic-96	290	13	1062	1062	NUM
hjic-96	290	14	3	3	NUM
hjic-96	290	15	.	.	PUNCT
hjic-96	291	1	winkler	winkler	PROPN
hjic-96	291	2	p.	p.	PROPN
hjic-96	291	3	:	:	PUNCT
hjic-96	291	4	optimized	optimize	VERB
hjic-96	291	5	multivariate	multivariate	NOUN
hjic-96	291	6	lag	lag	NOUN
hjic-96	291	7	structure	structure	NOUN
hjic-96	291	8	selection	selection	NOUN
hjic-96	291	9	.	.	PUNCT
hjic-96	292	1	computational	computational	ADJ
hjic-96	292	2	economics	economic	NOUN
hjic-96	292	3	,	,	PUNCT
hjic-96	292	4	springer	springer	NOUN
hjic-96	292	5	,	,	PUNCT
hjic-96	292	6	2000	2000	NUM
hjic-96	292	7	,	,	PUNCT
hjic-96	292	8	16	16	NUM
hjic-96	292	9	(	(	PUNCT
hjic-96	292	10	1/2	1/2	NUM
hjic-96	292	11	)	)	PUNCT
hjic-96	292	12	,	,	PUNCT
hjic-96	292	13	87	87	NUM
hjic-96	292	14	-	-	SYM
hjic-96	292	15	103	103	NUM
hjic-96	292	16	4	4	NUM
hjic-96	292	17	.	.	PUNCT
hjic-96	293	1	akaike	akaike	PROPN
hjic-96	293	2	h.	h.	PROPN
hjic-96	293	3	:	:	PUNCT
hjic-96	293	4	a	a	DET
hjic-96	293	5	new	new	ADJ
hjic-96	293	6	look	look	NOUN
hjic-96	293	7	at	at	ADP
hjic-96	293	8	the	the	DET
hjic-96	293	9	statistical	statistical	ADJ
hjic-96	293	10	model	model	NOUN
hjic-96	293	11	identification	identification	NOUN
hjic-96	293	12	.	.	PUNCT
hjic-96	294	1	ieee	ieee	PROPN
hjic-96	294	2	trans	trans	PROPN
hjic-96	294	3	.	.	PUNCT
hjic-96	295	1	autom	autom	PROPN
hjic-96	295	2	.	.	PUNCT
hjic-96	296	1	control	control	PROPN
hjic-96	296	2	,	,	PUNCT
hjic-96	296	3	1974	1974	NUM
hjic-96	296	4	,	,	PUNCT
hjic-96	296	5	19	19	NUM
hjic-96	296	6	,	,	PUNCT
hjic-96	296	7	716–723	716–723	NUM
hjic-96	296	8	5	5	NUM
hjic-96	296	9	.	.	PUNCT
hjic-96	297	1	liang	liang	PROPN
hjic-96	297	2	g.	g.	PROPN
hjic-96	297	3	,	,	PUNCT
hjic-96	297	4	wilkes	wilkes	PROPN
hjic-96	297	5	d.	d.	PROPN
hjic-96	297	6	and	and	CCONJ
hjic-96	297	7	cadzow	cadzow	PROPN
hjic-96	297	8	j.	j.	PROPN
hjic-96	297	9	:	:	PUNCT
hjic-96	297	10	arma	arma	PROPN
hjic-96	297	11	model	model	NOUN
hjic-96	297	12	order	order	NOUN
hjic-96	297	13	estimation	estimation	NOUN
hjic-96	297	14	based	base	VERB
hjic-96	297	15	on	on	ADP
hjic-96	297	16	the	the	DET
hjic-96	297	17	eigenvalues	eigenvalue	NOUN
hjic-96	297	18	of	of	ADP
hjic-96	297	19	the	the	DET
hjic-96	297	20	covariance	covariance	NOUN
hjic-96	297	21	matrix	matrix	NOUN
hjic-96	297	22	.	.	PUNCT
hjic-96	298	1	ieee	ieee	PROPN
hjic-96	298	2	trans	trans	PROPN
hjic-96	298	3	.	.	PROPN
hjic-96	298	4	signal	signal	PROPN
hjic-96	298	5	process	process	NOUN
hjic-96	298	6	,	,	PUNCT
hjic-96	298	7	1993	1993	NUM
hjic-96	298	8	,	,	PUNCT
hjic-96	298	9	41	41	NUM
hjic-96	298	10	(	(	PUNCT
hjic-96	298	11	10	10	NUM
hjic-96	298	12	)	)	PUNCT
hjic-96	298	13	,	,	PUNCT
hjic-96	298	14	3003–3009	3003–3009	NUM
hjic-96	298	15	6	6	NUM
hjic-96	298	16	.	.	PUNCT
hjic-96	298	17	schwarz	schwarz	PROPN
hjic-96	298	18	g.	g.	PROPN
hjic-96	298	19	:	:	PUNCT
hjic-96	298	20	estimating	estimate	VERB
hjic-96	298	21	the	the	DET
hjic-96	298	22	dimension	dimension	NOUN
hjic-96	298	23	of	of	ADP
hjic-96	298	24	a	a	DET
hjic-96	298	25	model	model	NOUN
hjic-96	298	26	.	.	PUNCT
hjic-96	299	1	annals	annal	NOUN
hjic-96	299	2	of	of	ADP
hjic-96	299	3	statistics	statistic	NOUN
hjic-96	299	4	,	,	PUNCT
hjic-96	299	5	1978	1978	NUM
hjic-96	299	6	,	,	PUNCT
hjic-96	299	7	6	6	NUM
hjic-96	299	8	,	,	PUNCT
hjic-96	299	9	461	461	NUM
hjic-96	299	10	-	-	SYM
hjic-96	299	11	464	464	NUM
hjic-96	299	12	7	7	NUM
hjic-96	299	13	.	.	PUNCT
hjic-96	300	1	hannan	hannan	PROPN
hjic-96	300	2	e.	e.	PROPN
hjic-96	300	3	j.	j.	PROPN
hjic-96	300	4	,	,	PUNCT
hjic-96	300	5	quinn	quinn	PROPN
hjic-96	300	6	b.	b.	PROPN
hjic-96	300	7	g.	g.	PROPN
hjic-96	300	8	:	:	PUNCT
hjic-96	300	9	the	the	DET
hjic-96	300	10	determination	determination	NOUN
hjic-96	300	11	of	of	ADP
hjic-96	300	12	the	the	DET
hjic-96	300	13	order	order	NOUN
hjic-96	300	14	of	of	ADP
hjic-96	300	15	an	an	DET
hjic-96	300	16	autoregression	autoregression	NOUN
hjic-96	300	17	.	.	PUNCT
hjic-96	301	1	journal	journal	NOUN
hjic-96	301	2	of	of	ADP
hjic-96	301	3	the	the	DET
hjic-96	301	4	royal	royal	ADJ
hjic-96	301	5	statistical	statistical	ADJ
hjic-96	301	6	society	society	NOUN
hjic-96	301	7	series	series	PROPN
hjic-96	301	8	b	b	PROPN
hjic-96	301	9	1979	1979	NUM
hjic-96	301	10	,	,	PUNCT
hjic-96	301	11	41	41	NUM
hjic-96	301	12	,	,	PUNCT
hjic-96	301	13	190	190	NUM
hjic-96	301	14	-	-	SYM
hjic-96	301	15	195	195	NUM
hjic-96	301	16	8	8	NUM
hjic-96	301	17	.	.	PUNCT
hjic-96	302	1	hidalgo	hidalgo	PROPN
hjic-96	302	2	j	j	PROPN
hjic-96	302	3	..	..	PUNCT
hjic-96	302	4	:	:	PUNCT
hjic-96	302	5	consistent	consistent	ADJ
hjic-96	302	6	order	order	NOUN
hjic-96	302	7	selection	selection	NOUN
hjic-96	302	8	with	with	ADP
hjic-96	302	9	strongly	strongly	ADV
hjic-96	302	10	dependent	dependent	ADJ
hjic-96	302	11	data	datum	NOUN
hjic-96	302	12	and	and	CCONJ
hjic-96	302	13	its	its	PRON
hjic-96	302	14	application	application	NOUN
hjic-96	302	15	to	to	ADP
hjic-96	302	16	efficient	efficient	ADJ
hjic-96	302	17	estimation	estimation	NOUN
hjic-96	302	18	.	.	PUNCT
hjic-96	303	1	journal	journal	PROPN
hjic-96	303	2	of	of	ADP
hjic-96	303	3	econometrics	econometric	NOUN
hjic-96	303	4	,	,	PUNCT
hjic-96	303	5	2002	2002	NUM
hjic-96	303	6	,	,	PUNCT
hjic-96	303	7	110	110	NUM
hjic-96	303	8	,	,	PUNCT
hjic-96	303	9	213	213	NUM
hjic-96	303	10	-	-	SYM
hjic-96	303	11	239	239	NUM
hjic-96	303	12	9	9	NUM
hjic-96	303	13	.	.	PUNCT
hjic-96	304	1	shibata	shibata	NOUN
hjic-96	304	2	r	r	PROPN
hjic-96	304	3	..	..	PUNCT
hjic-96	304	4	:	:	PUNCT
hjic-96	304	5	an	an	DET
hjic-96	304	6	optimal	optimal	ADJ
hjic-96	304	7	selection	selection	NOUN
hjic-96	304	8	of	of	ADP
hjic-96	304	9	regression	regression	NOUN
hjic-96	304	10	variables	variable	NOUN
hjic-96	304	11	.	.	PUNCT
hjic-96	305	1	biometrika	biometrika	NOUN
hjic-96	305	2	,	,	PUNCT
hjic-96	305	3	1981	1981	NUM
hjic-96	305	4	,	,	PUNCT
hjic-96	305	5	68	68	NUM
hjic-96	305	6	,	,	PUNCT
hjic-96	305	7	45	45	NUM
hjic-96	305	8	-	-	SYM
hjic-96	305	9	54	54	NUM
hjic-96	305	10	10	10	NUM
hjic-96	305	11	.	.	PUNCT
hjic-96	306	1	pötscher	pötscher	PROPN
hjic-96	306	2	b.	b.	PROPN
hjic-96	306	3	m.	m.	PROPN
hjic-96	306	4	:	:	PUNCT
hjic-96	306	5	model	model	NOUN
hjic-96	306	6	selection	selection	NOUN
hjic-96	306	7	under	under	ADP
hjic-96	306	8	nonstationarity	nonstationarity	NOUN
hjic-96	306	9	:	:	PUNCT
hjic-96	306	10	autoregressive	autoregressive	ADJ
hjic-96	306	11	models	model	NOUN
hjic-96	306	12	and	and	CCONJ
hjic-96	306	13	stochastic	stochastic	ADJ
hjic-96	306	14	linear	linear	ADJ
hjic-96	306	15	regression	regression	NOUN
hjic-96	306	16	models	model	NOUN
hjic-96	306	17	.	.	PUNCT
hjic-96	307	1	annals	annals	PROPN
hjic-96	307	2	statistics	statistic	NOUN
hjic-96	307	3	,	,	PUNCT
hjic-96	307	4	1989	1989	NUM
hjic-96	307	5	,	,	PUNCT
hjic-96	307	6	17	17	NUM
hjic-96	307	7	,	,	PUNCT
hjic-96	307	8	1257	1257	NUM
hjic-96	307	9	-	-	SYM
hjic-96	307	10	1274	1274	NUM
hjic-96	307	11	11	11	NUM
hjic-96	307	12	.	.	PUNCT
hjic-96	308	1	geweke	geweke	PROPN
hjic-96	308	2	j.	j.	PROPN
hjic-96	308	3	,	,	PUNCT
hjic-96	308	4	meese	meese	PROPN
hjic-96	308	5	r.	r.	PROPN
hjic-96	308	6	:	:	PUNCT
hjic-96	308	7	estimating	estimate	VERB
hjic-96	308	8	regression	regression	NOUN
hjic-96	308	9	models	model	NOUN
hjic-96	308	10	of	of	ADP
hjic-96	308	11	finite	finite	NOUN
hjic-96	308	12	but	but	CCONJ
hjic-96	308	13	unknown	unknown	ADJ
hjic-96	308	14	order	order	NOUN
hjic-96	308	15	.	.	PUNCT
hjic-96	309	1	international	international	ADJ
hjic-96	309	2	economic	economic	ADJ
hjic-96	309	3	review	review	NOUN
hjic-96	309	4	,	,	PUNCT
hjic-96	309	5	1981	1981	NUM
hjic-96	309	6	,	,	PUNCT
hjic-96	309	7	22	22	NUM
hjic-96	309	8	,	,	PUNCT
hjic-96	309	9	55	55	NUM
hjic-96	309	10	-	-	SYM
hjic-96	309	11	70	70	NUM
hjic-96	309	12	12	12	NUM
hjic-96	309	13	.	.	PUNCT
hjic-96	310	1	shibata	shibata	PROPN
hjic-96	310	2	r	r	PROPN
hjic-96	310	3	..	..	PUNCT
hjic-96	310	4	:	:	PUNCT
hjic-96	310	5	selection	selection	NOUN
hjic-96	310	6	of	of	ADP
hjic-96	310	7	the	the	DET
hjic-96	310	8	order	order	NOUN
hjic-96	310	9	of	of	ADP
hjic-96	310	10	an	an	DET
hjic-96	310	11	autoregressive	autoregressive	ADJ
hjic-96	310	12	model	model	NOUN
hjic-96	310	13	by	by	ADP
hjic-96	310	14	akaike	akaike	PROPN
hjic-96	310	15	’s	’s	PART
hjic-96	310	16	information	information	NOUN
hjic-96	310	17	criterion	criterion	NOUN
hjic-96	310	18	.	.	PUNCT
hjic-96	311	1	biometrika	biometrika	NOUN
hjic-96	311	2	,	,	PUNCT
hjic-96	311	3	1976	1976	NUM
hjic-96	311	4	,	,	PUNCT
hjic-96	311	5	63	63	NUM
hjic-96	311	6	,	,	PUNCT
hjic-96	311	7	117	117	NUM
hjic-96	311	8	-	-	SYM
hjic-96	311	9	126	126	NUM
hjic-96	311	10	13	13	NUM
hjic-96	311	11	.	.	PUNCT
hjic-96	312	1	shibata	shibata	NOUN
hjic-96	312	2	r	r	PROPN
hjic-96	312	3	..	..	PUNCT
hjic-96	312	4	:	:	PUNCT
hjic-96	312	5	asymptotic	asymptotic	ADJ
hjic-96	312	6	efficiency	efficiency	NOUN
hjic-96	312	7	selection	selection	NOUN
hjic-96	312	8	of	of	ADP
hjic-96	312	9	the	the	DET
hjic-96	312	10	order	order	NOUN
hjic-96	312	11	of	of	ADP
hjic-96	312	12	the	the	DET
hjic-96	312	13	model	model	NOUN
hjic-96	312	14	for	for	ADP
hjic-96	312	15	estimating	estimate	VERB
hjic-96	312	16	parameters	parameter	NOUN
hjic-96	312	17	of	of	ADP
hjic-96	312	18	a	a	DET
hjic-96	312	19	linear	linear	ADJ
hjic-96	312	20	process	process	NOUN
hjic-96	312	21	.	.	PUNCT
hjic-96	313	1	annals	annal	NOUN
hjic-96	313	2	of	of	ADP
hjic-96	313	3	statistics	statistic	NOUN
hjic-96	313	4	,	,	PUNCT
hjic-96	313	5	1980	1980	NUM
hjic-96	313	6	,	,	PUNCT
hjic-96	313	7	8	8	NUM
hjic-96	313	8	,	,	PUNCT
hjic-96	313	9	147164	147164	NUM
hjic-96	313	10	14	14	NUM
hjic-96	313	11	.	.	PUNCT
hjic-96	314	1	hannan	hannan	PROPN
hjic-96	314	2	e.	e.	PROPN
hjic-96	314	3	j.	j.	PROPN
hjic-96	314	4	:	:	PUNCT
hjic-96	314	5	the	the	DET
hjic-96	314	6	estimation	estimation	NOUN
hjic-96	314	7	of	of	ADP
hjic-96	314	8	the	the	DET
hjic-96	314	9	order	order	NOUN
hjic-96	314	10	of	of	ADP
hjic-96	314	11	an	an	DET
hjic-96	314	12	arma	arma	NOUN
hjic-96	314	13	process	process	NOUN
hjic-96	314	14	.	.	PUNCT
hjic-96	315	1	annals	annal	NOUN
hjic-96	315	2	of	of	ADP
hjic-96	315	3	statistics	statistic	NOUN
hjic-96	315	4	,	,	PUNCT
hjic-96	315	5	1980	1980	NUM
hjic-96	315	6	,	,	PUNCT
hjic-96	315	7	10711081	10711081	NUM
hjic-96	315	8	15	15	NUM
hjic-96	315	9	.	.	PUNCT
hjic-96	316	1	pötscher	pötscher	PROPN
hjic-96	316	2	b.	b.	PROPN
hjic-96	316	3	m.	m.	PROPN
hjic-96	316	4	:	:	PUNCT
hjic-96	316	5	effects	effect	NOUN
hjic-96	316	6	of	of	ADP
hjic-96	316	7	model	model	NOUN
hjic-96	316	8	selection	selection	NOUN
hjic-96	316	9	on	on	ADP
hjic-96	316	10	inference	inference	PROPN
hjic-96	316	11	.	.	PUNCT
hjic-96	317	1	econometric	econometric	PROPN
hjic-96	317	2	theory	theory	NOUN
hjic-96	317	3	,	,	PUNCT
hjic-96	317	4	1991	1991	NUM
hjic-96	317	5	,	,	PUNCT
hjic-96	317	6	7	7	NUM
hjic-96	317	7	,	,	PUNCT
hjic-96	317	8	163	163	NUM
hjic-96	317	9	-	-	SYM
hjic-96	317	10	185	185	NUM
hjic-96	317	11	16	16	NUM
hjic-96	317	12	.	.	PUNCT
hjic-96	318	1	george	george	PROPN
hjic-96	318	2	e.	e.	PROPN
hjic-96	318	3	i.	i.	PROPN
hjic-96	318	4	:	:	PUNCT
hjic-96	318	5	the	the	DET
hjic-96	318	6	variable	variable	ADJ
hjic-96	318	7	selection	selection	NOUN
hjic-96	318	8	problem	problem	NOUN
hjic-96	318	9	.	.	PUNCT
hjic-96	319	1	journal	journal	NOUN
hjic-96	319	2	of	of	ADP
hjic-96	319	3	the	the	DET
hjic-96	319	4	american	american	PROPN
hjic-96	319	5	statistical	statistical	PROPN
hjic-96	319	6	association	association	NOUN
hjic-96	319	7	,	,	PUNCT
hjic-96	319	8	2000	2000	NUM
hjic-96	319	9	,	,	PUNCT
hjic-96	319	10	95	95	NUM
hjic-96	319	11	,	,	PUNCT
hjic-96	319	12	1304	1304	NUM
hjic-96	319	13	-	-	SYM
hjic-96	319	14	1308	1308	NUM
hjic-96	319	15	17	17	NUM
hjic-96	319	16	.	.	PUNCT
hjic-96	320	1	aguirre	aguirre	PROPN
hjic-96	320	2	l.	l.	PROPN
hjic-96	320	3	a.	a.	PROPN
hjic-96	320	4	,	,	PUNCT
hjic-96	320	5	billings	billing	NOUN
hjic-96	320	6	s.	s.	PROPN
hjic-96	320	7	a.	a.	PROPN
hjic-96	320	8	:	:	PUNCT
hjic-96	320	9	improved	improved	ADJ
hjic-96	320	10	structure	structure	NOUN
hjic-96	320	11	selection	selection	NOUN
hjic-96	320	12	for	for	ADP
hjic-96	320	13	nonlinear	nonlinear	ADJ
hjic-96	320	14	models	model	NOUN
hjic-96	320	15	based	base	VERB
hjic-96	320	16	on	on	ADP
hjic-96	320	17	term	term	NOUN
hjic-96	320	18	clustering	clustering	NOUN
hjic-96	320	19	.	.	PUNCT
hjic-96	321	1	int	int	NOUN
hjic-96	321	2	.	.	PUNCT
hjic-96	322	1	j.	j.	PROPN
hjic-96	322	2	control	control	PROPN
hjic-96	322	3	,	,	PUNCT
hjic-96	322	4	1995	1995	NUM
hjic-96	322	5	,	,	PUNCT
hjic-96	322	6	62	62	NUM
hjic-96	322	7	,	,	PUNCT
hjic-96	322	8	569–587	569–587	NUM
hjic-96	322	9	18	18	NUM
hjic-96	322	10	.	.	PUNCT
hjic-96	323	1	aguirre	aguirre	PROPN
hjic-96	323	2	l.	l.	PROPN
hjic-96	323	3	a.	a.	PROPN
hjic-96	323	4	,	,	PUNCT
hjic-96	323	5	mendes	mendes	PROPN
hjic-96	323	6	e.	e.	PROPN
hjic-96	323	7	m.	m.	PROPN
hjic-96	323	8	a.	a.	PROPN
hjic-96	323	9	m.	m.	PROPN
hjic-96	323	10	:	:	PUNCT
hjic-96	323	11	global	global	ADJ
hjic-96	323	12	nonlinear	nonlinear	ADJ
hjic-96	323	13	polynomial	polynomial	ADJ
hjic-96	323	14	models	model	NOUN
hjic-96	323	15	:	:	PUNCT
hjic-96	323	16	structure	structure	NOUN
hjic-96	323	17	,	,	PUNCT
hjic-96	323	18	term	term	NOUN
hjic-96	323	19	clusters	cluster	NOUN
hjic-96	323	20	and	and	CCONJ
hjic-96	323	21	fixed	fix	VERB
hjic-96	323	22	points	point	NOUN
hjic-96	323	23	.	.	PUNCT
hjic-96	324	1	int	int	NOUN
hjic-96	324	2	.	.	PUNCT
hjic-96	325	1	j.	j.	PROPN
hjic-96	325	2	bifurcation	bifurcation	PROPN
hjic-96	325	3	chaos	chaos	PROPN
hjic-96	325	4	,	,	PUNCT
hjic-96	325	5	1996	1996	NUM
hjic-96	325	6	,	,	PUNCT
hjic-96	325	7	6	6	NUM
hjic-96	325	8	,	,	PUNCT
hjic-96	325	9	279–294	279–294	NUM
hjic-96	325	10	19	19	NUM
hjic-96	325	11	.	.	PUNCT
hjic-96	326	1	mendes	mende	NOUN
hjic-96	326	2	e.	e.	PROPN
hjic-96	326	3	m.	m.	PROPN
hjic-96	326	4	a.	a.	PROPN
hjic-96	326	5	m.	m.	PROPN
hjic-96	326	6	,	,	PUNCT
hjic-96	326	7	billings	billing	NOUN
hjic-96	326	8	s.	s.	PROPN
hjic-96	327	1	a	a	DET
hjic-96	327	2	:	:	PUNCT
hjic-96	327	3	an	an	DET
hjic-96	327	4	alternative	alternative	ADJ
hjic-96	327	5	solution	solution	NOUN
hjic-96	327	6	to	to	ADP
hjic-96	327	7	the	the	DET
hjic-96	327	8	model	model	NOUN
hjic-96	327	9	structure	structure	NOUN
hjic-96	327	10	selection	selection	NOUN
hjic-96	327	11	problem	problem	NOUN
hjic-96	327	12	.	.	PUNCT
hjic-96	328	1	ieee	ieee	PROPN
hjic-96	328	2	trans	trans	PROPN
hjic-96	328	3	.	.	PUNCT
hjic-96	329	1	syst	syst	PROPN
hjic-96	329	2	.	.	PUNCT
hjic-96	330	1	man	man	PROPN
hjic-96	330	2	cybernetics	cybernetic	NOUN
hjic-96	330	3	,	,	PUNCT
hjic-96	330	4	part	part	NOUN
hjic-96	330	5	a	a	DET
hjic-96	330	6	:	:	PUNCT
hjic-96	330	7	syst	syst	NOUN
hjic-96	330	8	.	.	PUNCT
hjic-96	331	1	humans	human	NOUN
hjic-96	331	2	,	,	PUNCT
hjic-96	331	3	2001	2001	NUM
hjic-96	331	4	,	,	PUNCT
hjic-96	331	5	31	31	NUM
hjic-96	331	6	(	(	PUNCT
hjic-96	331	7	6	6	NUM
hjic-96	331	8	)	)	PUNCT
hjic-96	331	9	,	,	PUNCT
hjic-96	331	10	597–608	597–608	NUM
hjic-96	331	11	20	20	NUM
hjic-96	331	12	.	.	PUNCT
hjic-96	332	1	korenberg	korenberg	PROPN
hjic-96	332	2	m.	m.	PROPN
hjic-96	332	3	,	,	PUNCT
hjic-96	332	4	billings	billing	NOUN
hjic-96	332	5	s.	s.	PROPN
hjic-96	332	6	a	a	PRON
hjic-96	332	7	,	,	PUNCT
hjic-96	332	8	liu	liu	PROPN
hjic-96	332	9	y.	y.	PROPN
hjic-96	332	10	,	,	PUNCT
hjic-96	332	11	mcoilroy	mcoilroy	PROPN
hjic-96	332	12	p.	p.	NOUN
hjic-96	332	13	:	:	PUNCT
hjic-96	332	14	algorithm	algorithm	NOUN
hjic-96	332	15	for	for	ADP
hjic-96	332	16	nonlinear	nonlinear	ADJ
hjic-96	332	17	stochastic	stochastic	ADJ
hjic-96	332	18	systems	system	NOUN
hjic-96	332	19	.	.	PUNCT
hjic-96	333	1	int	int	NOUN
hjic-96	333	2	.	.	PUNCT
hjic-96	334	1	j.	j.	PROPN
hjic-96	334	2	control	control	PROPN
hjic-96	334	3	,	,	PUNCT
hjic-96	334	4	1988	1988	NUM
hjic-96	334	5	,	,	PUNCT
hjic-96	334	6	48	48	NUM
hjic-96	334	7	,	,	PUNCT
hjic-96	334	8	193–210	193–210	NUM
hjic-96	334	9	21	21	NUM
hjic-96	334	10	.	.	PUNCT
hjic-96	335	1	abonyi	abonyi	PROPN
hjic-96	335	2	j.	j.	PROPN
hjic-96	335	3	:	:	PUNCT
hjic-96	335	4	fuzzy	fuzzy	ADJ
hjic-96	335	5	model	model	NOUN
hjic-96	335	6	identification	identification	NOUN
hjic-96	335	7	for	for	ADP
hjic-96	335	8	control	control	NOUN
hjic-96	335	9	,	,	PUNCT
hjic-96	335	10	2001	2001	NUM
hjic-96	335	11	,	,	PUNCT
hjic-96	335	12	birkhauser	birkhauser	PROPN
hjic-96	335	13	,	,	PUNCT
hjic-96	335	14	boston	boston	PROPN
hjic-96	335	15	67	67	NUM
hjic-96	335	16	22	22	NUM
hjic-96	335	17	.	.	PUNCT
hjic-96	336	1	petrovic	petrovic	PROPN
hjic-96	336	2	i.	i.	PROPN
hjic-96	336	3	,	,	PUNCT
hjic-96	336	4	baotic	baotic	ADJ
hjic-96	336	5	m.	m.	NOUN
hjic-96	336	6	,	,	PUNCT
hjic-96	336	7	peric	peric	ADJ
hjic-96	336	8	n.	n.	NOUN
hjic-96	336	9	:	:	PUNCT
hjic-96	336	10	model	model	NOUN
hjic-96	336	11	structure	structure	NOUN
hjic-96	336	12	selection	selection	NOUN
hjic-96	336	13	for	for	ADP
hjic-96	336	14	nonlinear	nonlinear	ADJ
hjic-96	336	15	system	system	NOUN
hjic-96	336	16	identification	identification	NOUN
hjic-96	336	17	using	use	VERB
hjic-96	336	18	feedforward	feedforward	ADJ
hjic-96	336	19	neural	neural	ADJ
hjic-96	336	20	network	network	NOUN
hjic-96	336	21	.	.	PUNCT
hjic-96	337	1	international	international	ADJ
hjic-96	337	2	joint	joint	ADJ
hjic-96	337	3	conference	conference	NOUN
hjic-96	337	4	on	on	ADP
hjic-96	337	5	neural	neural	ADJ
hjic-96	337	6	networks	network	NOUN
hjic-96	337	7	(	(	PUNCT
hjic-96	337	8	ijcnn'00	ijcnn'00	PROPN
hjic-96	337	9	)	)	PUNCT
hjic-96	337	10	,	,	PUNCT
hjic-96	337	11	2000	2000	NUM
hjic-96	337	12	,	,	PUNCT
hjic-96	337	13	1	1	NUM
hjic-96	337	14	,	,	PUNCT
hjic-96	337	15	53	53	NUM
hjic-96	337	16	-	-	SYM
hjic-96	337	17	57	57	NUM
hjic-96	337	18	23	23	NUM
hjic-96	337	19	.	.	PUNCT
hjic-96	338	1	yu	yu	PROPN
hjic-96	338	2	d.	d.	PROPN
hjic-96	338	3	l.	l.	PROPN
hjic-96	338	4	,	,	PUNCT
hjic-96	338	5	gomm	gomm	PROPN
hjic-96	338	6	j.	j.	PROPN
hjic-96	338	7	b.	b.	PROPN
hjic-96	338	8	,	,	PUNCT
hjic-96	338	9	williams	williams	PROPN
hjic-96	338	10	d.	d.	PROPN
hjic-96	338	11	:	:	PUNCT
hjic-96	338	12	neural	neural	ADJ
hjic-96	338	13	model	model	NOUN
hjic-96	338	14	input	input	NOUN
hjic-96	338	15	selection	selection	NOUN
hjic-96	338	16	for	for	ADP
hjic-96	338	17	a	a	DET
hjic-96	338	18	mimo	mimo	PROPN
hjic-96	338	19	chemical	chemical	PROPN
hjic-96	338	20	process	process	NOUN
hjic-96	338	21	.	.	PUNCT
hjic-96	339	1	eng	eng	PROPN
hjic-96	339	2	.	.	PUNCT
hjic-96	340	1	app	app	PROPN
hjic-96	340	2	.	.	PROPN
hjic-96	341	1	of	of	ADP
hjic-96	341	2	artificial	artificial	ADJ
hjic-96	341	3	intelligence	intelligence	NOUN
hjic-96	341	4	,	,	PUNCT
hjic-96	341	5	2000	2000	NUM
hjic-96	341	6	,	,	PUNCT
hjic-96	341	7	13	13	NUM
hjic-96	341	8	,	,	PUNCT
hjic-96	341	9	15	15	NUM
hjic-96	341	10	-	-	SYM
hjic-96	341	11	23	23	NUM
hjic-96	341	12	24	24	NUM
hjic-96	341	13	.	.	PUNCT
hjic-96	342	1	menold	menold	PROPN
hjic-96	342	2	p.	p.	PROPN
hjic-96	342	3	h.	h.	PROPN
hjic-96	342	4	,	,	PUNCT
hjic-96	342	5	allgöwer	allgöwer	PROPN
hjic-96	342	6	f.	f.	PROPN
hjic-96	342	7	,	,	PUNCT
hjic-96	342	8	pearson	pearson	PROPN
hjic-96	342	9	r.	r.	PROPN
hjic-96	342	10	k.	k.	PROPN
hjic-96	342	11	:	:	PUNCT
hjic-96	342	12	nonlinear	nonlinear	ADJ
hjic-96	342	13	structure	structure	NOUN
hjic-96	342	14	identification	identification	NOUN
hjic-96	342	15	of	of	ADP
hjic-96	342	16	chemical	chemical	NOUN
hjic-96	342	17	processes	process	NOUN
hjic-96	342	18	.	.	PUNCT
hjic-96	343	1	computers	computer	NOUN
hjic-96	343	2	chem	chem	NOUN
hjic-96	343	3	.	.	PUNCT
hjic-96	344	1	engng	engng	PROPN
hjic-96	344	2	.	.	PUNCT
hjic-96	344	3	,	,	PUNCT
hjic-96	344	4	1997	1997	NUM
hjic-96	344	5	,	,	PUNCT
hjic-96	344	6	21	21	NUM
hjic-96	344	7	,	,	PUNCT
hjic-96	344	8	137147	137147	NUM
hjic-96	344	9	25	25	NUM
hjic-96	344	10	.	.	PUNCT
hjic-96	345	1	lendasse	lendasse	PROPN
hjic-96	345	2	a.	a.	PROPN
hjic-96	345	3	,	,	PUNCT
hjic-96	345	4	simon	simon	PROPN
hjic-96	345	5	g.	g.	PROPN
hjic-96	345	6	,	,	PUNCT
hjic-96	345	7	wertz	wertz	PROPN
hjic-96	345	8	v.	v.	PROPN
hjic-96	345	9	,	,	PUNCT
hjic-96	345	10	verleysen	verleysen	NOUN
hjic-96	345	11	m.	m.	NOUN
hjic-96	345	12	:	:	PUNCT
hjic-96	345	13	fast	fast	ADJ
hjic-96	345	14	bootstrap	bootstrap	NOUN
hjic-96	345	15	methodology	methodology	NOUN
hjic-96	345	16	for	for	ADP
hjic-96	345	17	regression	regression	NOUN
hjic-96	345	18	model	model	NOUN
hjic-96	345	19	selection	selection	NOUN
hjic-96	345	20	.	.	PUNCT
hjic-96	346	1	neurocomputing	neurocomputing	NOUN
hjic-96	346	2	,	,	PUNCT
hjic-96	346	3	2005	2005	NUM
hjic-96	346	4	,	,	PUNCT
hjic-96	346	5	64	64	NUM
hjic-96	346	6	,	,	PUNCT
hjic-96	346	7	161181	161181	NUM
hjic-96	346	8	26	26	NUM
hjic-96	346	9	.	.	PUNCT
hjic-96	347	1	ahmad	ahmad	PROPN
hjic-96	347	2	r.	r.	PROPN
hjic-96	347	3	,	,	PUNCT
hjic-96	347	4	jamaluddin	jamaluddin	PROPN
hjic-96	347	5	h.	h.	PROPN
hjic-96	347	6	,	,	PUNCT
hjic-96	347	7	hussian	hussian	PROPN
hjic-96	347	8	m.	m.	PROPN
hjic-96	347	9	a.	a.	PROPN
hjic-96	347	10	:	:	PUNCT
hjic-96	347	11	model	model	NOUN
hjic-96	347	12	structure	structure	NOUN
hjic-96	347	13	selection	selection	NOUN
hjic-96	347	14	for	for	ADP
hjic-96	347	15	a	a	DET
hjic-96	347	16	discrete	discrete	ADJ
hjic-96	347	17	-	-	PUNCT
hjic-96	347	18	time	time	NOUN
hjic-96	347	19	non	non	ADJ
hjic-96	347	20	-	-	ADJ
hjic-96	347	21	linear	linear	ADJ
hjic-96	347	22	system	system	NOUN
hjic-96	347	23	using	use	VERB
hjic-96	347	24	a	a	DET
hjic-96	347	25	genetic	genetic	ADJ
hjic-96	347	26	algorithm	algorithm	NOUN
hjic-96	347	27	,	,	PUNCT
hjic-96	347	28	in	in	ADP
hjic-96	347	29	proceedings	proceeding	NOUN
hjic-96	347	30	of	of	ADP
hjic-96	347	31	the	the	DET
hjic-96	347	32	i	i	PROPN
hjic-96	347	33	mech	mech	NOUN
hjic-96	347	34	e	e	NOUN
hjic-96	347	35	part	part	NOUN
hjic-96	347	36	i	i	PRON
hjic-96	347	37	journal	journal	PROPN
hjic-96	347	38	of	of	ADP
hjic-96	347	39	systems	systems	PROPN
hjic-96	347	40	&	&	CCONJ
hjic-96	347	41	control	control	PROPN
hjic-96	347	42	engineering	engineering	PROPN
hjic-96	347	43	,	,	PUNCT
hjic-96	347	44	2004	2004	NUM
hjic-96	347	45	,	,	PUNCT
hjic-96	347	46	85	85	NUM
hjic-96	347	47	-	-	SYM
hjic-96	347	48	98	98	NUM
hjic-96	347	49	27	27	NUM
hjic-96	347	50	.	.	PUNCT
hjic-96	348	1	metenidis	metenidis	PROPN
hjic-96	348	2	m.	m.	PROPN
hjic-96	348	3	f.	f.	PROPN
hjic-96	348	4	,	,	PUNCT
hjic-96	348	5	witczak	witczak	ADJ
hjic-96	348	6	m.	m.	NOUN
hjic-96	348	7	,	,	PUNCT
hjic-96	348	8	korbicz	korbicz	PROPN
hjic-96	348	9	j.	j.	PROPN
hjic-96	348	10	x.	x.	PROPN
hjic-96	348	11	:	:	PUNCT
hjic-96	348	12	a	a	DET
hjic-96	348	13	novel	novel	ADJ
hjic-96	348	14	genetic	genetic	ADJ
hjic-96	348	15	programming	programming	NOUN
hjic-96	348	16	approach	approach	NOUN
hjic-96	348	17	to	to	ADP
hjic-96	348	18	nonlinear	nonlinear	ADJ
hjic-96	348	19	system	system	NOUN
hjic-96	348	20	modeling	modeling	NOUN
hjic-96	348	21	:	:	PUNCT
hjic-96	348	22	application	application	NOUN
hjic-96	348	23	to	to	ADP
hjic-96	348	24	the	the	DET
hjic-96	348	25	damadics	damadic	NOUN
hjic-96	348	26	benchmark	benchmark	NOUN
hjic-96	348	27	problem	problem	NOUN
hjic-96	348	28	.	.	PUNCT
hjic-96	349	1	eng	eng	PROPN
hjic-96	349	2	.	.	PUNCT
hjic-96	350	1	app	app	PROPN
hjic-96	350	2	.	.	PROPN
hjic-96	351	1	of	of	ADP
hjic-96	351	2	artificial	artificial	ADJ
hjic-96	351	3	intelligence	intelligence	NOUN
hjic-96	351	4	,	,	PUNCT
hjic-96	351	5	2004	2004	NUM
hjic-96	351	6	,	,	PUNCT
hjic-96	351	7	17	17	NUM
hjic-96	351	8	,	,	PUNCT
hjic-96	351	9	363	363	NUM
hjic-96	351	10	-	-	SYM
hjic-96	351	11	370	370	NUM
hjic-96	351	12	28	28	NUM
hjic-96	351	13	.	.	PUNCT
hjic-96	352	1	hong	hong	PROPN
hjic-96	352	2	x.	x.	PROPN
hjic-96	352	3	,	,	PUNCT
hjic-96	352	4	harris	harris	PROPN
hjic-96	352	5	c.	c.	PROPN
hjic-96	352	6	j.	j.	PROPN
hjic-96	352	7	:	:	PUNCT
hjic-96	352	8	nonlinear	nonlinear	ADJ
hjic-96	352	9	model	model	NOUN
hjic-96	352	10	structure	structure	NOUN
hjic-96	352	11	detection	detection	NOUN
hjic-96	352	12	using	use	VERB
hjic-96	352	13	optimum	optimum	ADJ
hjic-96	352	14	experimental	experimental	ADJ
hjic-96	352	15	design	design	NOUN
hjic-96	352	16	and	and	CCONJ
hjic-96	352	17	orthogonal	orthogonal	ADJ
hjic-96	352	18	least	least	ADJ
hjic-96	352	19	squares	square	NOUN
hjic-96	352	20	.	.	PUNCT
hjic-96	353	1	ieee	ieee	PROPN
hjic-96	353	2	trans	trans	PROPN
hjic-96	353	3	neural	neural	PROPN
hjic-96	353	4	networks	network	NOUN
hjic-96	353	5	,	,	PUNCT
hjic-96	353	6	2001	2001	NUM
hjic-96	353	7	,	,	PUNCT
hjic-96	353	8	12	12	NUM
hjic-96	353	9	(	(	PUNCT
hjic-96	353	10	2	2	NUM
hjic-96	353	11	)	)	PUNCT
hjic-96	353	12	,	,	PUNCT
hjic-96	353	13	435	435	NUM
hjic-96	353	14	-	-	SYM
hjic-96	353	15	439	439	NUM
hjic-96	353	16	29	29	NUM
hjic-96	353	17	.	.	PUNCT
hjic-96	353	18	basso	basso	NOUN
hjic-96	353	19	m.	m.	NOUN
hjic-96	353	20	,	,	PUNCT
hjic-96	353	21	giarré	giarré	ADJ
hjic-96	353	22	l.	l.	PROPN
hjic-96	353	23	,	,	PUNCT
hjic-96	353	24	groppi	groppi	PROPN
hjic-96	353	25	s.	s.	PROPN
hjic-96	353	26	,	,	PUNCT
hjic-96	353	27	zappa	zappa	PROPN
hjic-96	353	28	g.	g.	PROPN
hjic-96	353	29	:	:	PUNCT
hjic-96	353	30	narx	narx	NOUN
hjic-96	353	31	models	model	NOUN
hjic-96	353	32	of	of	ADP
hjic-96	353	33	an	an	DET
hjic-96	353	34	industrial	industrial	ADJ
hjic-96	353	35	power	power	NOUN
hjic-96	353	36	plant	plant	NOUN
hjic-96	353	37	gas	gas	NOUN
hjic-96	353	38	turbine	turbine	NOUN
hjic-96	353	39	.	.	PUNCT
hjic-96	354	1	ieee	ieee	PROPN
hjic-96	354	2	trans	trans	PROPN
hjic-96	354	3	.	.	PUNCT
hjic-96	355	1	on	on	ADP
hjic-96	355	2	control	control	NOUN
hjic-96	355	3	systems	system	NOUN
hjic-96	355	4	technology	technology	NOUN
hjic-96	355	5	,	,	PUNCT
hjic-96	355	6	2005	2005	NUM
hjic-96	355	7	,	,	PUNCT
hjic-96	355	8	13	13	NUM
hjic-96	355	9	(	(	PUNCT
hjic-96	355	10	4	4	NUM
hjic-96	355	11	)	)	PUNCT
hjic-96	355	12	30	30	NUM
hjic-96	355	13	.	.	PUNCT
hjic-96	356	1	agrawal	agrawal	PROPN
hjic-96	356	2	r.	r.	PROPN
hjic-96	356	3	,	,	PUNCT
hjic-96	356	4	imielinski	imielinski	PROPN
hjic-96	356	5	t.	t.	PROPN
hjic-96	356	6	and	and	CCONJ
hjic-96	356	7	swami	swami	PROPN
hjic-96	356	8	a.	a.	PROPN
hjic-96	356	9	:	:	PUNCT
hjic-96	357	1	database	database	PROPN
hjic-96	357	2	mining	mining	NOUN
hjic-96	357	3	:	:	PUNCT
hjic-96	357	4	a	a	DET
hjic-96	357	5	performance	performance	NOUN
hjic-96	357	6	perspective	perspective	NOUN
hjic-96	357	7	.	.	PUNCT
hjic-96	358	1	ieee	ieee	NOUN
hjic-96	358	2	transactions	transaction	NOUN
hjic-96	358	3	on	on	ADP
hjic-96	358	4	knowledge	knowledge	NOUN
hjic-96	358	5	and	and	CCONJ
hjic-96	358	6	data	datum	NOUN
hjic-96	358	7	engeneering	engeneere	VERB
hjic-96	358	8	,	,	PUNCT
hjic-96	358	9	december	december	PROPN
hjic-96	358	10	1993	1993	NUM
hjic-96	358	11	,	,	PUNCT
hjic-96	358	12	5(6):914	5(6):914	NUM
hjic-96	358	13	-	-	SYM
hjic-96	358	14	925	925	NUM
hjic-96	358	15	,	,	PUNCT
hjic-96	358	16	special	special	ADJ
hjic-96	358	17	issue	issue	NOUN
hjic-96	358	18	on	on	ADP
hjic-96	358	19	learning	learning	NOUN
hjic-96	358	20	and	and	CCONJ
hjic-96	358	21	discovery	discovery	NOUN
hjic-96	358	22	in	in	ADP
hjic-96	358	23	knowledge	knowledge	NOUN
hjic-96	358	24	-	-	PUNCT
hjic-96	358	25	based	base	VERB
hjic-96	358	26	databases	database	NOUN
hjic-96	358	27	31	31	NUM
hjic-96	358	28	.	.	PUNCT
hjic-96	359	1	sjöberg	sjöberg	PROPN
hjic-96	359	2	j.	j.	PROPN
hjic-96	359	3	,	,	PUNCT
hjic-96	359	4	zhang	zhang	PROPN
hjic-96	359	5	q.	q.	PROPN
hjic-96	359	6	,	,	PUNCT
hjic-96	359	7	ljung	ljung	PROPN
hjic-96	359	8	l.	l.	PROPN
hjic-96	359	9	,	,	PUNCT
hjic-96	359	10	benveniste	benveniste	NOUN
hjic-96	359	11	a.	a.	NOUN
hjic-96	359	12	,	,	PUNCT
hjic-96	359	13	deylon	deylon	PROPN
hjic-96	359	14	b.	b.	PROPN
hjic-96	359	15	,	,	PUNCT
hjic-96	359	16	glorennec	glorennec	PROPN
hjic-96	359	17	p	p	PROPN
hjic-96	359	18	-	-	PUNCT
hjic-96	359	19	y.	y.	PROPN
hjic-96	359	20	,	,	PUNCT
hjic-96	359	21	hjalmarsson	hjalmarsson	PROPN
hjic-96	359	22	h.	h.	PROPN
hjic-96	359	23	,	,	PUNCT
hjic-96	359	24	juditsky	juditsky	PROPN
hjic-96	359	25	a.	a.	PROPN
hjic-96	359	26	:	:	PUNCT
hjic-96	359	27	nonlinear	nonlinear	VERB
hjic-96	359	28	black.box	black.box	NOUN
hjic-96	359	29	modeling	modeling	NOUN
hjic-96	359	30	in	in	ADP
hjic-96	359	31	system	system	NOUN
hjic-96	359	32	identification	identification	NOUN
hjic-96	359	33	:	:	PUNCT
hjic-96	359	34	a	a	DET
hjic-96	359	35	unified	unified	ADJ
hjic-96	359	36	overview	overview	NOUN
hjic-96	359	37	.	.	PUNCT
hjic-96	360	1	automatica	automatica	PROPN
hjic-96	360	2	1995	1995	NUM
hjic-96	360	3	,	,	PUNCT
hjic-96	360	4	31(12	31(12	NUM
hjic-96	360	5	)	)	PUNCT
hjic-96	360	6	,	,	PUNCT
hjic-96	360	7	1691	1691	NUM
hjic-96	360	8	-	-	SYM
hjic-96	360	9	1724	1724	NUM
hjic-96	360	10	32	32	NUM
hjic-96	360	11	.	.	PUNCT
hjic-96	361	1	gustafson	gustafson	PROPN
hjic-96	361	2	d.	d.	PROPN
hjic-96	361	3	e.	e.	PROPN
hjic-96	361	4	and	and	CCONJ
hjic-96	361	5	kessel	kessel	PROPN
hjic-96	361	6	w.	w.	PROPN
hjic-96	361	7	c.	c.	PROPN
hjic-96	361	8	:	:	PUNCT
hjic-96	361	9	fuzzy	fuzzy	ADJ
hjic-96	361	10	clustering	clustering	NOUN
hjic-96	361	11	with	with	ADP
hjic-96	361	12	fuzzy	fuzzy	ADJ
hjic-96	361	13	covariance	covariance	NOUN
hjic-96	361	14	matrix	matrix	NOUN
hjic-96	361	15	,	,	PUNCT
hjic-96	361	16	in	in	ADP
hjic-96	361	17	proceedings	proceeding	NOUN
hjic-96	361	18	of	of	ADP
hjic-96	361	19	the	the	DET
hjic-96	361	20	ieee	ieee	NOUN
hjic-96	361	21	cdc	cdc	PROPN
hjic-96	361	22	,	,	PUNCT
hjic-96	361	23	san	san	PROPN
hjic-96	361	24	diego	diego	PROPN
hjic-96	361	25	,	,	PUNCT
hjic-96	361	26	1979	1979	NUM
hjic-96	361	27	,	,	PUNCT
hjic-96	361	28	pages	page	VERB
hjic-96	361	29	761–766	761–766	NUM
hjic-96	361	30	33	33	NUM
hjic-96	361	31	.	.	PUNCT
hjic-96	362	1	hidalgo	hidalgo	PROPN
hjic-96	362	2	p.	p.	PROPN
hjic-96	362	3	m.	m.	NOUN
hjic-96	362	4	and	and	CCONJ
hjic-96	362	5	brosilov	brosilov	PROPN
hjic-96	362	6	c.	c.	PROPN
hjic-96	362	7	b.	b.	PROPN
hjic-96	362	8	:	:	PUNCT
hjic-96	362	9	nonlinear	nonlinear	ADJ
hjic-96	362	10	model	model	PROPN
hjic-96	362	11	predictive	predictive	PROPN
hjic-96	362	12	control	control	NOUN
hjic-96	362	13	of	of	ADP
hjic-96	362	14	styrene	styrene	ADJ
hjic-96	362	15	polymerization	polymerization	NOUN
hjic-96	362	16	at	at	ADP
hjic-96	362	17	unstable	unstable	ADJ
hjic-96	362	18	operating	operating	NOUN
hjic-96	362	19	points	point	NOUN
hjic-96	362	20	,	,	PUNCT
hjic-96	362	21	comp	comp	NOUN
hjic-96	362	22	.	.	PUNCT
hjic-96	362	23	chem	chem	PROPN
hjic-96	362	24	.	.	PUNCT
hjic-96	363	1	eng	eng	PROPN
hjic-96	363	2	.	.	PROPN
hjic-96	363	3	,	,	PUNCT
hjic-96	363	4	1990	1990	NUM
hjic-96	363	5	,	,	PUNCT
hjic-96	363	6	14	14	NUM
hjic-96	363	7	,	,	PUNCT
hjic-96	363	8	481	481	NUM
hjic-96	363	9	-	-	SYM
hjic-96	363	10	494	494	NUM
hjic-96	363	11	34	34	NUM
hjic-96	363	12	.	.	PUNCT
hjic-96	364	1	russo	russo	PROPN
hjic-96	364	2	l.	l.	PROPN
hjic-96	364	3	p.	p.	PROPN
hjic-96	364	4	and	and	CCONJ
hjic-96	364	5	bequette	bequette	PROPN
hjic-96	364	6	b.	b.	PROPN
hjic-96	364	7	w.	w.	PROPN
hjic-96	364	8	:	:	PUNCT
hjic-96	364	9	operability	operability	NOUN
hjic-96	364	10	of	of	ADP
hjic-96	364	11	chemical	chemical	ADJ
hjic-96	364	12	ractors	ractor	NOUN
hjic-96	364	13	:	:	PUNCT
hjic-96	364	14	multiplicity	multiplicity	NOUN
hjic-96	364	15	behavior	behavior	NOUN
hjic-96	364	16	of	of	ADP
hjic-96	364	17	a	a	DET
hjic-96	364	18	jacketed	jacketed	ADJ
hjic-96	364	19	styrene	styrene	ADJ
hjic-96	364	20	polymerization	polymerization	NOUN
hjic-96	364	21	reactor	reactor	NOUN
hjic-96	364	22	,	,	PUNCT
hjic-96	364	23	chem	chem	NOUN
hjic-96	364	24	.	.	PUNCT
hjic-96	365	1	eng	eng	PROPN
hjic-96	365	2	.	.	PROPN
hjic-96	365	3	science	science	PROPN
hjic-96	365	4	,	,	PUNCT
hjic-96	365	5	1998	1998	NUM
hjic-96	365	6	,	,	PUNCT
hjic-96	365	7	53	53	NUM
hjic-96	365	8	(	(	PUNCT
hjic-96	365	9	1	1	NUM
hjic-96	365	10	)	)	PUNCT
hjic-96	365	11	,	,	PUNCT
hjic-96	365	12	27	27	NUM
hjic-96	365	13	-	-	SYM
hjic-96	365	14	45	45	NUM
hjic-96	365	15	35	35	NUM
hjic-96	365	16	.	.	PUNCT
hjic-96	366	1	rendszergazda	rendszergazda	NOUN
hjic-96	366	2	rectangle	rectangle	NOUN