id	sid	tid	token	lemma	pos
ap-1075	1	1	ap08_6.vp	ap08_6.vp	NOUN
ap-1075	1	2	1	1	NUM
ap-1075	1	3	introduction	introduction	NOUN
ap-1075	1	4	in	in	ADP
ap-1075	1	5	some	some	DET
ap-1075	1	6	cases	case	NOUN
ap-1075	1	7	,	,	PUNCT
ap-1075	1	8	usual	usual	ADJ
ap-1075	1	9	methods	method	NOUN
ap-1075	1	10	of	of	ADP
ap-1075	1	11	supervised	supervised	ADJ
ap-1075	1	12	learning	learning	NOUN
ap-1075	1	13	are	be	AUX
ap-1075	1	14	not	not	PART
ap-1075	1	15	able	able	ADJ
ap-1075	1	16	to	to	PART
ap-1075	1	17	provide	provide	VERB
ap-1075	1	18	satisfactory	satisfactory	ADJ
ap-1075	1	19	results	result	NOUN
ap-1075	1	20	.	.	PUNCT
ap-1075	2	1	this	this	PRON
ap-1075	2	2	may	may	AUX
ap-1075	2	3	occur	occur	VERB
ap-1075	2	4	in	in	ADP
ap-1075	2	5	data	datum	NOUN
ap-1075	2	6	with	with	ADP
ap-1075	2	7	asymmetric	asymmetric	ADJ
ap-1075	2	8	distributed	distribute	VERB
ap-1075	2	9	error	error	NOUN
ap-1075	2	10	,	,	PUNCT
ap-1075	2	11	which	which	PRON
ap-1075	2	12	is	be	AUX
ap-1075	2	13	typical	typical	ADJ
ap-1075	2	14	in	in	ADP
ap-1075	2	15	insurance	insurance	NOUN
ap-1075	2	16	.	.	PUNCT
ap-1075	3	1	in	in	ADP
ap-1075	3	2	order	order	NOUN
ap-1075	3	3	to	to	PART
ap-1075	3	4	manage	manage	VERB
ap-1075	3	5	the	the	DET
ap-1075	3	6	asymmetry	asymmetry	NOUN
ap-1075	3	7	in	in	ADP
ap-1075	3	8	the	the	DET
ap-1075	3	9	sense	sense	NOUN
ap-1075	3	10	of	of	ADP
ap-1075	3	11	the	the	DET
ap-1075	3	12	law	law	NOUN
ap-1075	3	13	of	of	ADP
ap-1075	3	14	large	large	ADJ
ap-1075	3	15	numbers	number	NOUN
ap-1075	3	16	,	,	PUNCT
ap-1075	3	17	this	this	DET
ap-1075	3	18	paper	paper	NOUN
ap-1075	3	19	offers	offer	VERB
ap-1075	3	20	a	a	DET
ap-1075	3	21	new	new	ADJ
ap-1075	3	22	algorithm	algorithm	NOUN
ap-1075	3	23	,	,	PUNCT
ap-1075	3	24	which	which	PRON
ap-1075	3	25	constructs	construct	VERB
ap-1075	3	26	a	a	DET
ap-1075	3	27	predictor	predictor	NOUN
ap-1075	3	28	not	not	PART
ap-1075	3	29	for	for	ADP
ap-1075	3	30	points	point	NOUN
ap-1075	3	31	,	,	PUNCT
ap-1075	3	32	but	but	CCONJ
ap-1075	3	33	for	for	ADP
ap-1075	3	34	sets	set	NOUN
ap-1075	3	35	.	.	PUNCT
ap-1075	4	1	we	we	PRON
ap-1075	4	2	will	will	AUX
ap-1075	4	3	show	show	VERB
ap-1075	4	4	an	an	DET
ap-1075	4	5	algorithm	algorithm	NOUN
ap-1075	4	6	for	for	ADP
ap-1075	4	7	finding	find	VERB
ap-1075	4	8	sets	set	NOUN
ap-1075	4	9	of	of	ADP
ap-1075	4	10	units	unit	NOUN
ap-1075	4	11	with	with	ADP
ap-1075	4	12	above	above	ADP
ap-1075	4	13	-	-	PUNCT
ap-1075	4	14	average	average	ADJ
ap-1075	4	15	outputs	output	NOUN
ap-1075	4	16	.	.	PUNCT
ap-1075	5	1	let	let	VERB
ap-1075	5	2	x	x	PRON
ap-1075	5	3	be	be	AUX
ap-1075	5	4	a	a	DET
ap-1075	5	5	set	set	NOUN
ap-1075	5	6	,	,	PUNCT
ap-1075	5	7	and	and	CCONJ
ap-1075	5	8	let	let	VERB
ap-1075	5	9	�	�	PROPN
ap-1075	5	10	,	,	PUNCT
ap-1075	5	11	�	�	PROPN
ap-1075	5	12	be	be	AUX
ap-1075	5	13	measures	measure	NOUN
ap-1075	5	14	over	over	ADP
ap-1075	5	15	it	it	PRON
ap-1075	5	16	.	.	PUNCT
ap-1075	6	1	the	the	DET
ap-1075	6	2	pareto	pareto	ADJ
ap-1075	6	3	principle	principle	NOUN
ap-1075	6	4	arises	arise	VERB
ap-1075	6	5	if	if	SCONJ
ap-1075	6	6	there	there	PRON
ap-1075	6	7	is	be	VERB
ap-1075	6	8	a	a	DET
ap-1075	6	9	set	set	NOUN
ap-1075	6	10	p	p	NOUN
ap-1075	6	11	x	x	X
ap-1075	6	12	�	�	PROPN
ap-1075	6	13	where	where	SCONJ
ap-1075	6	14	p	p	PROPN
ap-1075	6	15	p	p	X
ap-1075	6	16	x	x	X
ap-1075	6	17	p	p	X
ap-1075	6	18	p	p	X
ap-1075	6	19	x	x	X
ap-1075	6	20	x	x	X
ap-1075	6	21	(	(	PUNCT
ap-1075	6	22	,	,	PUNCT
ap-1075	6	23	)	)	PUNCT
ap-1075	6	24	(	(	PUNCT
ap-1075	6	25	)	)	PUNCT
ap-1075	6	26	(	(	PUNCT
ap-1075	6	27	)	)	PUNCT
ap-1075	6	28	(	(	PUNCT
ap-1075	6	29	)	)	PUNCT
ap-1075	6	30	(	(	PUNCT
ap-1075	6	31	)	)	PUNCT
ap-1075	6	32	�	�	PROPN
ap-1075	6	33	�	�	PROPN
ap-1075	6	34	�	�	PROPN
ap-1075	6	35	�	�	PROPN
ap-1075	6	36	�	�	PROPN
ap-1075	6	37	�	�	PROPN
ap-1075	6	38	�	�	PROPN
ap-1075	6	39	�	�	PROPN
ap-1075	6	40	1	1	NUM
ap-1075	6	41	(	(	PUNCT
ap-1075	6	42	1	1	NUM
ap-1075	6	43	)	)	PUNCT
ap-1075	6	44	and	and	CCONJ
ap-1075	6	45	r	r	NOUN
ap-1075	6	46	p	p	X
ap-1075	6	47	p	p	X
ap-1075	6	48	x	x	X
ap-1075	6	49	(	(	PUNCT
ap-1075	6	50	)	)	PUNCT
ap-1075	6	51	(	(	PUNCT
ap-1075	6	52	)	)	PUNCT
ap-1075	6	53	(	(	PUNCT
ap-1075	6	54	)	)	PUNCT
ap-1075	6	55	�	�	PROPN
ap-1075	6	56	�	�	PROPN
ap-1075	6	57	�	�	PROPN
ap-1075	6	58	�	�	PROPN
ap-1075	6	59	�	�	PROPN
ap-1075	6	60	0	0	NUM
ap-1075	6	61	.	.	PUNCT
ap-1075	7	1	let	let	VERB
ap-1075	7	2	�	�	PROPN
ap-1075	7	3	stand	stand	VERB
ap-1075	7	4	for	for	ADP
ap-1075	7	5	volume	volume	NOUN
ap-1075	7	6	,	,	PUNCT
ap-1075	7	7	�	�	PROPN
ap-1075	7	8	for	for	ADP
ap-1075	7	9	production	production	NOUN
ap-1075	7	10	,	,	PUNCT
ap-1075	7	11	p	p	NOUN
ap-1075	7	12	for	for	ADP
ap-1075	7	13	productivity	productivity	NOUN
ap-1075	7	14	,	,	PUNCT
ap-1075	7	15	r	r	NOUN
ap-1075	7	16	for	for	ADP
ap-1075	7	17	proportion	proportion	NOUN
ap-1075	7	18	.	.	PUNCT
ap-1075	8	1	typically	typically	ADV
ap-1075	8	2	,	,	PUNCT
ap-1075	8	3	the	the	DET
ap-1075	8	4	pareto	pareto	ADJ
ap-1075	8	5	principle	principle	NOUN
ap-1075	8	6	is	be	AUX
ap-1075	8	7	considered	consider	VERB
ap-1075	8	8	as	as	ADP
ap-1075	8	9	a	a	DET
ap-1075	8	10	rule	rule	NOUN
ap-1075	8	11	that	that	SCONJ
ap-1075	8	12	20	20	NUM
ap-1075	8	13	%	%	NOUN
ap-1075	8	14	of	of	ADP
ap-1075	8	15	elements	element	NOUN
ap-1075	8	16	“	"	PUNCT
ap-1075	8	17	produces	produce	VERB
ap-1075	8	18	”	"	PUNCT
ap-1075	8	19	80	80	NUM
ap-1075	8	20	%	%	NOUN
ap-1075	8	21	or	or	CCONJ
ap-1075	8	22	more	more	ADJ
ap-1075	8	23	of	of	ADP
ap-1075	8	24	the	the	DET
ap-1075	8	25	output	output	NOUN
ap-1075	8	26	.	.	PUNCT
ap-1075	9	1	(	(	PUNCT
ap-1075	9	2	this	this	DET
ap-1075	9	3	principle	principle	NOUN
ap-1075	9	4	was	be	AUX
ap-1075	9	5	discovered	discover	VERB
ap-1075	9	6	by	by	ADP
ap-1075	9	7	vilfredo	vilfredo	NOUN
ap-1075	9	8	pareto	pareto	NOUN
ap-1075	9	9	while	while	SCONJ
ap-1075	9	10	assessing	assess	VERB
ap-1075	9	11	the	the	DET
ap-1075	9	12	welfare	welfare	NOUN
ap-1075	9	13	distribution	distribution	NOUN
ap-1075	9	14	in	in	ADP
ap-1075	9	15	the	the	DET
ap-1075	9	16	uk	uk	PROPN
ap-1075	9	17	at	at	ADP
ap-1075	9	18	the	the	DET
ap-1075	9	19	end	end	NOUN
ap-1075	9	20	of	of	ADP
ap-1075	9	21	the	the	DET
ap-1075	9	22	19th	19th	ADJ
ap-1075	9	23	century	century	NOUN
ap-1075	9	24	.	.	PUNCT
ap-1075	10	1	his	his	PRON
ap-1075	10	2	ideas	idea	NOUN
ap-1075	10	3	were	be	AUX
ap-1075	10	4	systematically	systematically	ADV
ap-1075	10	5	described	describe	VERB
ap-1075	10	6	,	,	PUNCT
ap-1075	10	7	applied	apply	VERB
ap-1075	10	8	and	and	CCONJ
ap-1075	10	9	extended	extend	VERB
ap-1075	10	10	by	by	ADP
ap-1075	10	11	max	max	PROPN
ap-1075	10	12	lorenz[7	lorenz[7	PROPN
ap-1075	10	13	]	]	PROPN
ap-1075	10	14	.	.	PUNCT
ap-1075	10	15	)	)	PUNCT
ap-1075	11	1	in	in	ADP
ap-1075	11	2	this	this	DET
ap-1075	11	3	case	case	NOUN
ap-1075	11	4	,	,	PUNCT
ap-1075	11	5	r	r	NOUN
ap-1075	11	6	p	p	X
ap-1075	11	7	(	(	PUNCT
ap-1075	11	8	)	)	PUNCT
ap-1075	11	9	.	.	PUNCT
ap-1075	12	1	�	�	PROPN
ap-1075	12	2	02	02	NUM
ap-1075	12	3	and	and	CCONJ
ap-1075	12	4	p	p	NOUN
ap-1075	12	5	p	p	X
ap-1075	12	6	(	(	PUNCT
ap-1075	12	7	)	)	PUNCT
ap-1075	12	8	�	�	PROPN
ap-1075	12	9	4	4	NUM
ap-1075	12	10	.	.	X
ap-1075	12	11	managerial	managerial	ADJ
ap-1075	12	12	science	science	NOUN
ap-1075	12	13	often	often	ADV
ap-1075	12	14	works	work	VERB
ap-1075	12	15	with	with	ADP
ap-1075	12	16	the	the	DET
ap-1075	12	17	pareto	pareto	ADJ
ap-1075	12	18	diagram	diagram	NOUN
ap-1075	12	19	[	[	X
ap-1075	12	20	1	1	NUM
ap-1075	12	21	]	]	PUNCT
ap-1075	12	22	.	.	PUNCT
ap-1075	13	1	x	x	PUNCT
ap-1075	13	2	is	be	AUX
ap-1075	13	3	discrete	discrete	ADJ
ap-1075	13	4	�	�	NOUN
ap-1075	13	5	x	x	PUNCT
ap-1075	13	6	x	x	PUNCT
ap-1075	13	7	xn1	xn1	PROPN
ap-1075	13	8	2	2	NUM
ap-1075	13	9	,	,	PUNCT
ap-1075	13	10	,	,	PUNCT
ap-1075	13	11	,	,	PUNCT
ap-1075	13	12	�	�	PROPN
ap-1075	13	13	.	.	PUNCT
ap-1075	14	1	the	the	DET
ap-1075	14	2	elements	element	NOUN
ap-1075	14	3	are	be	AUX
ap-1075	14	4	ordered	order	VERB
ap-1075	14	5	by	by	ADP
ap-1075	14	6	their	their	PRON
ap-1075	14	7	production	production	NOUN
ap-1075	14	8	�	�	PROPN
ap-1075	14	9	(	(	PUNCT
ap-1075	14	10	)	)	PUNCT
ap-1075	14	11	xi	xi	PROPN
ap-1075	14	12	,	,	PUNCT
ap-1075	14	13	and	and	CCONJ
ap-1075	14	14	the	the	DET
ap-1075	14	15	production	production	NOUN
ap-1075	14	16	is	be	AUX
ap-1075	14	17	drawn	draw	VERB
ap-1075	14	18	in	in	ADP
ap-1075	14	19	a	a	DET
ap-1075	14	20	chart	chart	NOUN
ap-1075	14	21	.	.	PUNCT
ap-1075	15	1	in	in	ADP
ap-1075	15	2	stastitics	stastitic	NOUN
ap-1075	15	3	,	,	PUNCT
ap-1075	15	4	the	the	DET
ap-1075	15	5	pareto	pareto	ADJ
ap-1075	15	6	principle	principle	NOUN
ap-1075	15	7	is	be	AUX
ap-1075	15	8	represented	represent	VERB
ap-1075	15	9	by	by	ADP
ap-1075	15	10	the	the	DET
ap-1075	15	11	continuous	continuous	ADJ
ap-1075	15	12	pareto	pareto	ADJ
ap-1075	15	13	distribution	distribution	NOUN
ap-1075	15	14	:	:	PUNCT
ap-1075	15	15	pr	pr	X
ap-1075	15	16	(	(	PUNCT
ap-1075	15	17	)	)	PUNCT
ap-1075	15	18	x	x	SYM
ap-1075	16	1	x	x	PUNCT
ap-1075	16	2	x	x	X
ap-1075	16	3	xm	xm	PROPN
ap-1075	16	4	k	k	PROPN
ap-1075	16	5	�	�	PROPN
ap-1075	16	6	�	�	PROPN
ap-1075	16	7	�	�	PROPN
ap-1075	16	8	�	�	PROPN
ap-1075	16	9	�	�	PROPN
ap-1075	16	10	�	�	PROPN
ap-1075	16	11	�	�	PROPN
ap-1075	16	12	�	�	PROPN
ap-1075	16	13	�	�	PROPN
ap-1075	16	14	(	(	PUNCT
ap-1075	16	15	2	2	NUM
ap-1075	16	16	)	)	PUNCT
ap-1075	16	17	for	for	ADP
ap-1075	16	18	all	all	PRON
ap-1075	16	19	x	x	SYM
ap-1075	16	20	xm	xm	PROPN
ap-1075	16	21	�	�	PROPN
ap-1075	16	22	,	,	PUNCT
ap-1075	16	23	where	where	SCONJ
ap-1075	16	24	xm	xm	PROPN
ap-1075	16	25	is	be	AUX
ap-1075	16	26	the	the	DET
ap-1075	16	27	(	(	PUNCT
ap-1075	16	28	necessarily	necessarily	ADV
ap-1075	16	29	positive	positive	ADJ
ap-1075	16	30	)	)	PUNCT
ap-1075	16	31	minimum	minimum	ADJ
ap-1075	16	32	possible	possible	ADJ
ap-1075	16	33	value	value	NOUN
ap-1075	16	34	of	of	ADP
ap-1075	16	35	x	x	NOUN
ap-1075	16	36	,	,	PUNCT
ap-1075	16	37	and	and	CCONJ
ap-1075	16	38	k	k	PROPN
ap-1075	16	39	is	be	AUX
ap-1075	16	40	a	a	DET
ap-1075	16	41	positive	positive	ADJ
ap-1075	16	42	parameter	parameter	NOUN
ap-1075	16	43	.	.	PUNCT
ap-1075	17	1	pareto	pareto	ADJ
ap-1075	17	2	distribution	distribution	NOUN
ap-1075	17	3	has	have	VERB
ap-1075	17	4	positive	positive	ADJ
ap-1075	17	5	skewness	skewness	NOUN
ap-1075	17	6	2	2	NUM
ap-1075	17	7	1	1	NUM
ap-1075	17	8	3	3	NUM
ap-1075	17	9	2	2	NUM
ap-1075	17	10	(	(	PUNCT
ap-1075	17	11	)	)	PUNCT
ap-1075	17	12	�	�	PROPN
ap-1075	17	13	�	�	PROPN
ap-1075	17	14	�	�	PROPN
ap-1075	17	15	k	k	PROPN
ap-1075	17	16	k	k	PROPN
ap-1075	17	17	k	k	PROPN
ap-1075	17	18	k	k	PROPN
ap-1075	17	19	,	,	PUNCT
ap-1075	17	20	which	which	PRON
ap-1075	17	21	means	mean	VERB
ap-1075	17	22	that	that	SCONJ
ap-1075	17	23	the	the	DET
ap-1075	17	24	below	below	ADJ
ap-1075	17	25	-	-	PUNCT
ap-1075	17	26	average	average	NOUN
ap-1075	17	27	subset	subset	NOUN
ap-1075	17	28	is	be	AUX
ap-1075	17	29	bigger	big	ADJ
ap-1075	17	30	than	than	ADP
ap-1075	17	31	the	the	DET
ap-1075	17	32	above	above	ADJ
ap-1075	17	33	-	-	PUNCT
ap-1075	17	34	average	average	NOUN
ap-1075	17	35	complement	complement	NOUN
ap-1075	17	36	.	.	PUNCT
ap-1075	18	1	this	this	PRON
ap-1075	18	2	occurs	occur	VERB
ap-1075	18	3	in	in	ADP
ap-1075	18	4	many	many	ADJ
ap-1075	18	5	real	real	ADJ
ap-1075	18	6	life	life	NOUN
ap-1075	18	7	situations	situation	NOUN
ap-1075	18	8	:	:	PUNCT
ap-1075	18	9	the	the	DET
ap-1075	18	10	median	median	ADJ
ap-1075	18	11	citizen	citizen	NOUN
ap-1075	18	12	has	have	VERB
ap-1075	18	13	a	a	DET
ap-1075	18	14	below	below	ADJ
ap-1075	18	15	-	-	PUNCT
ap-1075	18	16	average	average	NOUN
ap-1075	18	17	salary	salary	NOUN
ap-1075	18	18	,	,	PUNCT
ap-1075	18	19	the	the	DET
ap-1075	18	20	median	median	ADJ
ap-1075	18	21	driver	driver	NOUN
ap-1075	18	22	causes	cause	VERB
ap-1075	18	23	below	below	ADP
ap-1075	18	24	-	-	PUNCT
ap-1075	18	25	average	average	NOUN
ap-1075	18	26	claims	claim	NOUN
ap-1075	18	27	,	,	PUNCT
ap-1075	18	28	etc	etc	X
ap-1075	18	29	.	.	X
ap-1075	18	30	let	let	VERB
ap-1075	18	31	�	�	PROPN
ap-1075	18	32	:	:	PUNCT
ap-1075	18	33	x	x	SYM
ap-1075	18	34	n	n	CCONJ
ap-1075	18	35	�	�	PROPN
ap-1075	18	36	�	�	PROPN
ap-1075	18	37	be	be	AUX
ap-1075	18	38	attributes	attribute	NOUN
ap-1075	18	39	of	of	ADP
ap-1075	18	40	x.	x.	NOUN
ap-1075	18	41	(	(	PUNCT
ap-1075	18	42	attributes	attribute	NOUN
ap-1075	18	43	can	can	AUX
ap-1075	18	44	be	be	AUX
ap-1075	18	45	considered	consider	VERB
ap-1075	18	46	as	as	ADP
ap-1075	18	47	columns	column	NOUN
ap-1075	18	48	in	in	ADP
ap-1075	18	49	a	a	DET
ap-1075	18	50	data	datum	NOUN
ap-1075	18	51	table	table	NOUN
ap-1075	18	52	,	,	PUNCT
ap-1075	18	53	i.e.	i.e.	X
ap-1075	18	54	the	the	DET
ap-1075	18	55	n	n	CCONJ
ap-1075	18	56	-	-	PUNCT
ap-1075	18	57	tuple	tuple	NOUN
ap-1075	18	58	from	from	ADP
ap-1075	18	59	the	the	DET
ap-1075	18	60	i	i	PROPN
ap-1075	18	61	-	-	PUNCT
ap-1075	18	62	th	th	X
ap-1075	18	63	row	row	NOUN
ap-1075	18	64	.	.	PUNCT
ap-1075	19	1	mapping	mapping	NOUN
ap-1075	19	2	�	�	PROPN
ap-1075	19	3	can	can	AUX
ap-1075	19	4	also	also	ADV
ap-1075	19	5	involve	involve	VERB
ap-1075	19	6	preprocessing	preprocesse	VERB
ap-1075	19	7	.	.	PUNCT
ap-1075	20	1	if	if	SCONJ
ap-1075	20	2	x	x	PRON
ap-1075	20	3	is	be	AUX
ap-1075	20	4	�	�	PROPN
ap-1075	20	5	k	k	PROPN
ap-1075	20	6	for	for	ADP
ap-1075	20	7	some	some	DET
ap-1075	20	8	k	k	PROPN
ap-1075	20	9	�	�	PROPN
ap-1075	20	10	�	�	PROPN
ap-1075	20	11	,	,	PUNCT
ap-1075	20	12	the	the	DET
ap-1075	20	13	�	�	PROPN
ap-1075	20	14	mapping	mapping	NOUN
ap-1075	20	15	may	may	AUX
ap-1075	20	16	also	also	ADV
ap-1075	20	17	be	be	AUX
ap-1075	20	18	an	an	DET
ap-1075	20	19	identity	identity	NOUN
ap-1075	20	20	.	.	PUNCT
ap-1075	20	21	)	)	PUNCT
ap-1075	21	1	the	the	DET
ap-1075	21	2	problem	problem	NOUN
ap-1075	21	3	of	of	ADP
ap-1075	21	4	prediction	prediction	NOUN
ap-1075	21	5	consists	consist	VERB
ap-1075	21	6	in	in	ADP
ap-1075	21	7	constructing	construct	VERB
ap-1075	21	8	the	the	DET
ap-1075	21	9	mapping	mapping	NOUN
ap-1075	21	10	�	�	NOUN
ap-1075	21	11	y	y	PROPN
ap-1075	21	12	so	so	SCONJ
ap-1075	21	13	that	that	SCONJ
ap-1075	21	14	�	�	PROPN
ap-1075	21	15	(	(	PUNCT
ap-1075	21	16	)	)	PUNCT
ap-1075	21	17	y	y	PROPN
ap-1075	22	1	i	i	PRON
ap-1075	22	2	i	i	INTJ
ap-1075	23	1	d	d	VERB
ap-1075	23	2	i	i	PRON
ap-1075	23	3	x	x	PROPN
ap-1075	23	4	�	�	PROPN
ap-1075	23	5	�	�	PROPN
ap-1075	23	6	�	�	PROPN
ap-1075	23	7	�	�	PROPN
ap-1075	23	8	�	�	PROPN
ap-1075	23	9	�	�	PROPN
ap-1075	23	10	�	�	PROPN
ap-1075	23	11	0	0	NUM
ap-1075	23	12	.	.	PUNCT
ap-1075	24	1	however	however	ADV
ap-1075	24	2	,	,	PUNCT
ap-1075	24	3	the	the	DET
ap-1075	24	4	construction	construction	NOUN
ap-1075	24	5	of	of	ADP
ap-1075	24	6	mapping	map	VERB
ap-1075	24	7	�	�	PROPN
ap-1075	24	8	y	y	PROPN
ap-1075	24	9	may	may	AUX
ap-1075	24	10	be	be	AUX
ap-1075	24	11	difficult	difficult	ADJ
ap-1075	24	12	if	if	SCONJ
ap-1075	24	13	the	the	DET
ap-1075	24	14	pareto	pareto	ADJ
ap-1075	24	15	principle	principle	NOUN
ap-1075	24	16	arises	arise	VERB
ap-1075	24	17	.	.	PUNCT
ap-1075	25	1	a	a	DET
ap-1075	25	2	small	small	ADJ
ap-1075	25	3	subset	subset	NOUN
ap-1075	25	4	of	of	ADP
ap-1075	25	5	high	high	ADJ
ap-1075	25	6	productivity	productivity	NOUN
ap-1075	25	7	(	(	PUNCT
ap-1075	25	8	called	call	VERB
ap-1075	25	9	outliers	outlier	NOUN
ap-1075	25	10	)	)	PUNCT
ap-1075	25	11	corrupts	corrupt	VERB
ap-1075	25	12	usual	usual	ADJ
ap-1075	25	13	assumptions	assumption	NOUN
ap-1075	25	14	.	.	PUNCT
ap-1075	26	1	usual	usual	ADJ
ap-1075	26	2	datamining	datamine	VERB
ap-1075	26	3	techniques	technique	NOUN
ap-1075	26	4	propose	propose	VERB
ap-1075	26	5	removing	remove	VERB
ap-1075	26	6	the	the	DET
ap-1075	26	7	set	set	NOUN
ap-1075	26	8	and	and	CCONJ
ap-1075	26	9	working	work	VERB
ap-1075	26	10	only	only	ADV
ap-1075	26	11	with	with	ADP
ap-1075	26	12	the	the	DET
ap-1075	26	13	rest	rest	NOUN
ap-1075	26	14	.	.	PUNCT
ap-1075	27	1	however	however	ADV
ap-1075	27	2	,	,	PUNCT
ap-1075	27	3	in	in	ADP
ap-1075	27	4	case	case	NOUN
ap-1075	27	5	of	of	ADP
ap-1075	27	6	the	the	DET
ap-1075	27	7	pareto	pareto	ADJ
ap-1075	27	8	principle	principle	NOUN
ap-1075	27	9	,	,	PUNCT
ap-1075	27	10	the	the	DET
ap-1075	27	11	small	small	ADJ
ap-1075	27	12	set	set	NOUN
ap-1075	27	13	is	be	AUX
ap-1075	27	14	very	very	ADV
ap-1075	27	15	interesting	interesting	ADJ
ap-1075	27	16	.	.	PUNCT
ap-1075	28	1	it	it	PRON
ap-1075	28	2	is	be	AUX
ap-1075	28	3	not	not	PART
ap-1075	28	4	adequate	adequate	ADJ
ap-1075	28	5	to	to	PART
ap-1075	28	6	speak	speak	VERB
ap-1075	28	7	about	about	ADP
ap-1075	28	8	outliers	outlier	NOUN
ap-1075	28	9	,	,	PUNCT
ap-1075	28	10	because	because	SCONJ
ap-1075	28	11	such	such	ADJ
ap-1075	28	12	data	datum	NOUN
ap-1075	28	13	is	be	AUX
ap-1075	28	14	relevant	relevant	ADJ
ap-1075	28	15	and	and	CCONJ
ap-1075	28	16	obvious	obvious	ADJ
ap-1075	28	17	.	.	PUNCT
ap-1075	29	1	therefore	therefore	ADV
ap-1075	29	2	,	,	PUNCT
ap-1075	29	3	we	we	PRON
ap-1075	29	4	are	be	AUX
ap-1075	29	5	dealing	deal	VERB
ap-1075	29	6	with	with	ADP
ap-1075	29	7	more	more	ADV
ap-1075	29	8	humble	humble	ADJ
ap-1075	29	9	result	result	NOUN
ap-1075	29	10	,	,	PUNCT
ap-1075	29	11	i.e.	i.e.	X
ap-1075	29	12	with	with	ADP
ap-1075	29	13	finding	find	VERB
ap-1075	29	14	the	the	DET
ap-1075	29	15	set	set	NOUN
ap-1075	29	16	p	p	NOUN
ap-1075	29	17	defined	define	VERB
ap-1075	29	18	in	in	ADP
ap-1075	29	19	(	(	PUNCT
ap-1075	29	20	1	1	NUM
ap-1075	29	21	)	)	PUNCT
ap-1075	29	22	.	.	PUNCT
ap-1075	30	1	the	the	DET
ap-1075	30	2	formulated	formulated	ADJ
ap-1075	30	3	problem	problem	NOUN
ap-1075	30	4	,	,	PUNCT
ap-1075	30	5	i.e.	i.e.	X
ap-1075	30	6	finding	find	VERB
ap-1075	30	7	arg	arg	NOUN
ap-1075	30	8	max	max	PROPN
ap-1075	30	9	(	(	PUNCT
ap-1075	30	10	,	,	PUNCT
ap-1075	30	11	)	)	PUNCT
ap-1075	30	12	p	p	X
ap-1075	31	1	x	x	X
ap-1075	31	2	p	p	X
ap-1075	31	3	x	x	X
ap-1075	31	4	p	p	X
ap-1075	31	5	�	�	PROPN
ap-1075	31	6	under	under	ADP
ap-1075	31	7	condition	condition	NOUN
ap-1075	31	8	r	r	NOUN
ap-1075	31	9	p	p	X
ap-1075	31	10	r	r	NOUN
ap-1075	31	11	(	(	PUNCT
ap-1075	31	12	)	)	PUNCT
ap-1075	31	13	�	�	PROPN
ap-1075	31	14	0	0	NUM
ap-1075	31	15	(	(	PUNCT
ap-1075	31	16	3	3	X
ap-1075	31	17	)	)	PUNCT
ap-1075	31	18	is	be	AUX
ap-1075	31	19	new	new	ADJ
ap-1075	31	20	,	,	PUNCT
ap-1075	31	21	and	and	CCONJ
ap-1075	31	22	has	have	AUX
ap-1075	31	23	not	not	PART
ap-1075	31	24	been	be	AUX
ap-1075	31	25	found	find	VERB
ap-1075	31	26	in	in	ADP
ap-1075	31	27	the	the	DET
ap-1075	31	28	current	current	ADJ
ap-1075	31	29	literature	literature	NOUN
ap-1075	31	30	.	.	PUNCT
ap-1075	32	1	however	however	ADV
ap-1075	32	2	,	,	PUNCT
ap-1075	32	3	many	many	ADJ
ap-1075	32	4	other	other	ADJ
ap-1075	32	5	topics	topic	NOUN
ap-1075	32	6	are	be	AUX
ap-1075	32	7	related	relate	VERB
ap-1075	32	8	to	to	ADP
ap-1075	32	9	it	it	PRON
ap-1075	32	10	.	.	PUNCT
ap-1075	33	1	first	first	ADV
ap-1075	33	2	,	,	PUNCT
ap-1075	33	3	clustering	clustering	ADJ
ap-1075	33	4	methods	method	NOUN
ap-1075	33	5	[	[	X
ap-1075	33	6	12	12	NUM
ap-1075	33	7	]	]	PUNCT
ap-1075	33	8	can	can	AUX
ap-1075	33	9	be	be	AUX
ap-1075	33	10	employed	employ	VERB
ap-1075	33	11	.	.	PUNCT
ap-1075	34	1	creating	create	VERB
ap-1075	34	2	clusters	cluster	NOUN
ap-1075	34	3	of	of	ADP
ap-1075	34	4	above	above	ADP
ap-1075	34	5	-	-	PUNCT
ap-1075	34	6	average	average	NOUN
ap-1075	34	7	individuals	individual	NOUN
ap-1075	34	8	,	,	PUNCT
ap-1075	34	9	the	the	DET
ap-1075	34	10	set	set	NOUN
ap-1075	34	11	p	p	NOUN
ap-1075	34	12	will	will	AUX
ap-1075	34	13	be	be	AUX
ap-1075	34	14	defined	define	VERB
ap-1075	34	15	as	as	SCONJ
ap-1075	34	16	these	these	DET
ap-1075	34	17	clusters.it	clusters.it	PRON
ap-1075	34	18	is	be	AUX
ap-1075	34	19	important	important	ADJ
ap-1075	34	20	to	to	PART
ap-1075	34	21	define	define	VERB
ap-1075	34	22	the	the	DET
ap-1075	34	23	border	border	NOUN
ap-1075	34	24	of	of	ADP
ap-1075	34	25	the	the	DET
ap-1075	34	26	clusters	cluster	NOUN
ap-1075	34	27	somehow	somehow	ADV
ap-1075	34	28	.	.	PUNCT
ap-1075	35	1	if	if	SCONJ
ap-1075	35	2	these	these	DET
ap-1075	35	3	clusters	cluster	NOUN
ap-1075	35	4	are	be	AUX
ap-1075	35	5	well	well	ADV
ap-1075	35	6	found	find	VERB
ap-1075	35	7	,	,	PUNCT
ap-1075	35	8	they	they	PRON
ap-1075	35	9	can	can	AUX
ap-1075	35	10	be	be	AUX
ap-1075	35	11	employed	employ	VERB
ap-1075	35	12	for	for	ADP
ap-1075	35	13	a	a	DET
ap-1075	35	14	more	more	ADV
ap-1075	35	15	precise	precise	ADJ
ap-1075	35	16	approximation	approximation	NOUN
ap-1075	35	17	[	[	X
ap-1075	35	18	6	6	NUM
ap-1075	35	19	]	]	PUNCT
ap-1075	35	20	.	.	PUNCT
ap-1075	36	1	another	another	DET
ap-1075	36	2	approach	approach	NOUN
ap-1075	36	3	is	be	AUX
ap-1075	36	4	to	to	PART
ap-1075	36	5	attempt	attempt	VERB
ap-1075	36	6	to	to	PART
ap-1075	36	7	find	find	VERB
ap-1075	36	8	a	a	DET
ap-1075	36	9	prediction	prediction	NOUN
ap-1075	36	10	mapping	mapping	NOUN
ap-1075	36	11	�	�	PROPN
ap-1075	36	12	y	y	PROPN
ap-1075	36	13	where	where	SCONJ
ap-1075	36	14	the	the	DET
ap-1075	36	15	set	set	NOUN
ap-1075	36	16	p	p	NOUN
ap-1075	36	17	is	be	AUX
ap-1075	36	18	afterwards	afterwards	ADV
ap-1075	36	19	defined	define	VERB
ap-1075	36	20	at	at	ADP
ap-1075	36	21	some	some	DET
ap-1075	36	22	level	level	NOUN
ap-1075	36	23	of	of	ADP
ap-1075	36	24	this	this	DET
ap-1075	36	25	mapping	mapping	NOUN
ap-1075	36	26	.	.	PUNCT
ap-1075	37	1	rbf	rbf	PROPN
ap-1075	37	2	neural	neural	PROPN
ap-1075	37	3	networks	network	NOUN
ap-1075	38	1	[	[	X
ap-1075	38	2	5	5	NUM
ap-1075	38	3	]	]	PUNCT
ap-1075	38	4	provide	provide	VERB
ap-1075	38	5	an	an	DET
ap-1075	38	6	example	example	NOUN
ap-1075	38	7	where	where	SCONJ
ap-1075	38	8	the	the	DET
ap-1075	38	9	approach	approach	NOUN
ap-1075	38	10	of	of	ADP
ap-1075	38	11	rough	rough	ADJ
ap-1075	38	12	sets	set	NOUN
ap-1075	38	13	is	be	AUX
ap-1075	38	14	employed	employ	VERB
ap-1075	38	15	.	.	PUNCT
ap-1075	39	1	finally	finally	ADV
ap-1075	39	2	,	,	PUNCT
ap-1075	39	3	effective	effective	ADJ
ap-1075	39	4	p	p	NOUN
ap-1075	39	5	can	can	AUX
ap-1075	39	6	also	also	ADV
ap-1075	39	7	be	be	AUX
ap-1075	39	8	detected	detect	VERB
ap-1075	39	9	also	also	ADV
ap-1075	39	10	data	data	VERB
ap-1075	39	11	envelopment	envelopment	ADJ
ap-1075	39	12	analysis	analysis	NOUN
ap-1075	40	1	[	[	X
ap-1075	40	2	2	2	NUM
ap-1075	40	3	]	]	PUNCT
ap-1075	40	4	.	.	PUNCT
ap-1075	41	1	however	however	ADV
ap-1075	41	2	,	,	PUNCT
ap-1075	41	3	none	none	NOUN
ap-1075	41	4	of	of	ADP
ap-1075	41	5	these	these	DET
ap-1075	41	6	methods	method	NOUN
ap-1075	41	7	–	–	PUNCT
ap-1075	41	8	as	as	ADP
ap-1075	41	9	the	the	DET
ap-1075	41	10	research	research	NOUN
ap-1075	41	11	in	in	ADP
ap-1075	41	12	the	the	DET
ap-1075	41	13	bibliography	bibliography	NOUN
ap-1075	41	14	shows	show	VERB
ap-1075	41	15	–	–	PUNCT
ap-1075	41	16	has	have	AUX
ap-1075	41	17	been	be	AUX
ap-1075	41	18	applied	apply	VERB
ap-1075	41	19	explicitly	explicitly	ADV
ap-1075	41	20	to	to	ADP
ap-1075	41	21	the	the	DET
ap-1075	41	22	problem	problem	NOUN
ap-1075	41	23	of	of	ADP
ap-1075	41	24	above	above	ADP
ap-1075	41	25	-	-	PUNCT
ap-1075	41	26	average	average	NOUN
ap-1075	41	27	subsets	subset	NOUN
ap-1075	41	28	.	.	PUNCT
ap-1075	42	1	2	2	NUM
ap-1075	42	2	the	the	DET
ap-1075	42	3	fencing	fence	VERB
ap-1075	42	4	algorithm	algorithm	NOUN
ap-1075	42	5	the	the	DET
ap-1075	42	6	following	follow	VERB
ap-1075	42	7	algorithm	algorithm	NOUN
ap-1075	42	8	is	be	AUX
ap-1075	42	9	the	the	DET
ap-1075	42	10	first	first	ADJ
ap-1075	42	11	attempt	attempt	NOUN
ap-1075	42	12	to	to	PART
ap-1075	42	13	solve	solve	VERB
ap-1075	42	14	this	this	DET
ap-1075	42	15	problem	problem	NOUN
ap-1075	42	16	(	(	PUNCT
ap-1075	42	17	3	3	NUM
ap-1075	42	18	)	)	PUNCT
ap-1075	42	19	.	.	PUNCT
ap-1075	43	1	it	it	PRON
ap-1075	43	2	offers	offer	VERB
ap-1075	43	3	the	the	DET
ap-1075	43	4	construction	construction	NOUN
ap-1075	43	5	of	of	ADP
ap-1075	43	6	�	�	PROPN
ap-1075	43	7	p	p	NOUN
ap-1075	43	8	x	x	NOUN
ap-1075	43	9	�	�	PROPN
ap-1075	43	10	with	with	ADP
ap-1075	43	11	above	above	ADP
ap-1075	43	12	-	-	PUNCT
ap-1075	43	13	average	average	NOUN
ap-1075	43	14	production	production	NOUN
ap-1075	43	15	,	,	PUNCT
ap-1075	43	16	i.e.	i.e.	X
ap-1075	43	17	with	with	ADP
ap-1075	43	18	high	high	ADJ
ap-1075	43	19	p.	p.	NOUN
ap-1075	43	20	the	the	DET
ap-1075	43	21	space	space	NOUN
ap-1075	43	22	�	�	PROPN
ap-1075	43	23	n	n	PRON
ap-1075	43	24	will	will	AUX
ap-1075	43	25	be	be	AUX
ap-1075	43	26	©	©	PROPN
ap-1075	43	27	czech	czech	PROPN
ap-1075	43	28	technical	technical	PROPN
ap-1075	43	29	university	university	PROPN
ap-1075	43	30	publishing	publishing	NOUN
ap-1075	43	31	house	house	NOUN
ap-1075	43	32	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1075	43	33	55	55	NUM
ap-1075	43	34	acta	acta	PROPN
ap-1075	43	35	polytechnica	polytechnica	PROPN
ap-1075	43	36	vol	vol	NOUN
ap-1075	43	37	.	.	PUNCT
ap-1075	44	1	48	48	NUM
ap-1075	44	2	no	no	NOUN
ap-1075	44	3	.	.	PUNCT
ap-1075	45	1	6/2008	6/2008	NOUN
ap-1075	45	2	the	the	DET
ap-1075	45	3	pareto	pareto	ADJ
ap-1075	45	4	principle	principle	NOUN
ap-1075	45	5	in	in	ADP
ap-1075	45	6	datamining	datamine	VERB
ap-1075	45	7	:	:	PUNCT
ap-1075	45	8	an	an	DET
ap-1075	45	9	above	above	ADJ
ap-1075	45	10	-	-	PUNCT
ap-1075	45	11	average	average	ADJ
ap-1075	45	12	fencing	fencing	NOUN
ap-1075	45	13	algorithm	algorithm	NOUN
ap-1075	45	14	k.	k.	PROPN
ap-1075	45	15	macek	macek	PROPN
ap-1075	46	1	this	this	DET
ap-1075	46	2	paper	paper	NOUN
ap-1075	46	3	formulates	formulate	VERB
ap-1075	46	4	a	a	DET
ap-1075	46	5	new	new	ADJ
ap-1075	46	6	datamining	datamining	NOUN
ap-1075	46	7	problem	problem	NOUN
ap-1075	46	8	:	:	PUNCT
ap-1075	46	9	which	which	PRON
ap-1075	46	10	subset	subset	VERB
ap-1075	46	11	of	of	ADP
ap-1075	46	12	input	input	NOUN
ap-1075	46	13	space	space	NOUN
ap-1075	46	14	has	have	VERB
ap-1075	46	15	the	the	DET
ap-1075	46	16	relatively	relatively	ADV
ap-1075	46	17	highest	high	ADJ
ap-1075	46	18	output	output	NOUN
ap-1075	46	19	where	where	SCONJ
ap-1075	46	20	the	the	DET
ap-1075	46	21	minimal	minimal	ADJ
ap-1075	46	22	size	size	NOUN
ap-1075	46	23	of	of	ADP
ap-1075	46	24	this	this	DET
ap-1075	46	25	subset	subset	NOUN
ap-1075	46	26	is	be	AUX
ap-1075	46	27	given	give	VERB
ap-1075	46	28	.	.	PUNCT
ap-1075	47	1	this	this	PRON
ap-1075	47	2	can	can	AUX
ap-1075	47	3	be	be	AUX
ap-1075	47	4	useful	useful	ADJ
ap-1075	47	5	where	where	SCONJ
ap-1075	47	6	usual	usual	ADJ
ap-1075	47	7	datamining	datamining	NOUN
ap-1075	47	8	methods	method	NOUN
ap-1075	47	9	fail	fail	VERB
ap-1075	47	10	because	because	SCONJ
ap-1075	47	11	of	of	ADP
ap-1075	47	12	error	error	NOUN
ap-1075	47	13	distribution	distribution	NOUN
ap-1075	47	14	asymmetry	asymmetry	NOUN
ap-1075	47	15	.	.	PUNCT
ap-1075	48	1	the	the	DET
ap-1075	48	2	paper	paper	NOUN
ap-1075	48	3	provides	provide	VERB
ap-1075	48	4	a	a	DET
ap-1075	48	5	novel	novel	ADJ
ap-1075	48	6	algorithm	algorithm	NOUN
ap-1075	48	7	for	for	ADP
ap-1075	48	8	this	this	DET
ap-1075	48	9	datamining	datamine	VERB
ap-1075	48	10	problem	problem	NOUN
ap-1075	48	11	,	,	PUNCT
ap-1075	48	12	and	and	CCONJ
ap-1075	48	13	compares	compare	VERB
ap-1075	48	14	it	it	PRON
ap-1075	48	15	with	with	ADP
ap-1075	48	16	clustering	clustering	NOUN
ap-1075	48	17	of	of	ADP
ap-1075	48	18	above	above	ADP
ap-1075	48	19	-	-	PUNCT
ap-1075	48	20	average	average	NOUN
ap-1075	48	21	individuals	individual	NOUN
ap-1075	48	22	.	.	PUNCT
ap-1075	49	1	keywords	keyword	NOUN
ap-1075	49	2	:	:	PUNCT
ap-1075	49	3	art	art	NOUN
ap-1075	49	4	,	,	PUNCT
ap-1075	49	5	pareto	pareto	ADJ
ap-1075	49	6	principle	principle	NOUN
ap-1075	49	7	,	,	PUNCT
ap-1075	49	8	insurance	insurance	NOUN
ap-1075	49	9	risk	risk	NOUN
ap-1075	49	10	.	.	PUNCT
ap-1075	50	1	considered	consider	VERB
ap-1075	50	2	as	as	ADP
ap-1075	50	3	x.	x.	NOUN
ap-1075	50	4	the	the	DET
ap-1075	50	5	set	set	NOUN
ap-1075	50	6	p	p	NOUN
ap-1075	50	7	is	be	AUX
ap-1075	50	8	represented	represent	VERB
ap-1075	50	9	by	by	ADP
ap-1075	50	10	union	union	NOUN
ap-1075	50	11	intervals	interval	NOUN
ap-1075	50	12	(	(	PUNCT
ap-1075	50	13	from	from	ADP
ap-1075	50	14	points	point	NOUN
ap-1075	50	15	to	to	ADP
ap-1075	50	16	hyperboxes	hyperboxe	NOUN
ap-1075	50	17	)	)	PUNCT
ap-1075	50	18	represented	represent	VERB
ap-1075	50	19	by	by	ADP
ap-1075	50	20	means	mean	NOUN
ap-1075	50	21	of	of	ADP
ap-1075	50	22	complement	complement	NOUN
ap-1075	50	23	coding	coding	NOUN
ap-1075	50	24	.	.	PUNCT
ap-1075	51	1	(	(	PUNCT
ap-1075	51	2	complement	complement	NOUN
ap-1075	51	3	coding	coding	NOUN
ap-1075	51	4	is	be	AUX
ap-1075	51	5	a	a	DET
ap-1075	51	6	concept	concept	NOUN
ap-1075	51	7	applied	apply	VERB
ap-1075	51	8	in	in	ADP
ap-1075	51	9	art	art	NOUN
ap-1075	51	10	and	and	CCONJ
ap-1075	51	11	artmap	artmap	PROPN
ap-1075	51	12	neural	neural	ADJ
ap-1075	51	13	networks	network	NOUN
ap-1075	51	14	,	,	PUNCT
ap-1075	51	15	e.g.[3	e.g.[3	PROPN
ap-1075	51	16	]	]	PUNCT
ap-1075	51	17	.	.	PUNCT
ap-1075	52	1	however	however	ADV
ap-1075	52	2	,	,	PUNCT
ap-1075	52	3	the	the	DET
ap-1075	52	4	objective	objective	NOUN
ap-1075	52	5	of	of	ADP
ap-1075	52	6	the	the	DET
ap-1075	52	7	fencing	fence	VERB
ap-1075	52	8	algorithm	algorithm	NOUN
ap-1075	52	9	is	be	AUX
ap-1075	52	10	different	different	ADJ
ap-1075	52	11	.	.	PUNCT
ap-1075	53	1	while	while	SCONJ
ap-1075	53	2	art	art	NOUN
ap-1075	53	3	and	and	CCONJ
ap-1075	53	4	artmap	artmap	NOUN
ap-1075	53	5	work	work	NOUN
ap-1075	53	6	iteratively	iteratively	ADV
ap-1075	53	7	,	,	PUNCT
ap-1075	53	8	the	the	DET
ap-1075	53	9	fencing	fence	VERB
ap-1075	53	10	algorithm	algorithm	NOUN
ap-1075	53	11	must	must	AUX
ap-1075	53	12	often	often	ADV
ap-1075	53	13	go	go	VERB
ap-1075	53	14	through	through	ADP
ap-1075	53	15	the	the	DET
ap-1075	53	16	entire	entire	ADJ
ap-1075	53	17	training	training	NOUN
ap-1075	53	18	set	set	NOUN
ap-1075	53	19	.	.	PUNCT
ap-1075	53	20	)	)	PUNCT
ap-1075	54	1	this	this	DET
ap-1075	54	2	algorithm	algorithm	NOUN
ap-1075	54	3	works	work	VERB
ap-1075	54	4	only	only	ADV
ap-1075	54	5	with	with	ADP
ap-1075	54	6	finite	finite	ADJ
ap-1075	54	7	data	data	NOUN
ap-1075	54	8	sets	set	VERB
ap-1075	54	9	d	d	NOUN
ap-1075	54	10	,	,	PUNCT
ap-1075	54	11	namely	namely	ADV
ap-1075	54	12	with	with	ADP
ap-1075	54	13	(	(	PUNCT
ap-1075	54	14	,	,	PUNCT
ap-1075	54	15	)	)	PUNCT
ap-1075	54	16	xi	xi	PROPN
ap-1075	54	17	iy	iy	PROPN
ap-1075	54	18	pairs	pair	NOUN
ap-1075	54	19	.	.	PUNCT
ap-1075	55	1	therefore	therefore	ADV
ap-1075	55	2	,	,	PUNCT
ap-1075	55	3	for	for	ADP
ap-1075	55	4	all	all	DET
ap-1075	55	5	subsets	subset	NOUN
ap-1075	55	6	of	of	ADP
ap-1075	55	7	d	d	PROPN
ap-1075	55	8	,	,	PUNCT
ap-1075	55	9	the	the	DET
ap-1075	55	10	volume	volume	NOUN
ap-1075	55	11	�	�	PROPN
ap-1075	55	12	is	be	AUX
ap-1075	55	13	defined	define	VERB
ap-1075	55	14	as	as	ADP
ap-1075	55	15	count	count	PROPN
ap-1075	55	16	�	�	PROPN
ap-1075	55	17	�	�	PROPN
ap-1075	55	18	(	(	PUNCT
ap-1075	55	19	)	)	PUNCT
ap-1075	55	20	(	(	PUNCT
ap-1075	55	21	)	)	PUNCT
ap-1075	55	22	m	m	VERB
ap-1075	55	23	m	m	VERB
ap-1075	55	24	d	d	PROPN
ap-1075	55	25	�	�	PROPN
ap-1075	55	26	�	�	PROPN
ap-1075	55	27	and	and	CCONJ
ap-1075	55	28	the	the	DET
ap-1075	55	29	production	production	NOUN
ap-1075	55	30	as	as	ADP
ap-1075	55	31	the	the	DET
ap-1075	55	32	sum	sum	NOUN
ap-1075	55	33	of	of	ADP
ap-1075	55	34	the	the	DET
ap-1075	55	35	production	production	NOUN
ap-1075	55	36	of	of	ADP
ap-1075	55	37	particular	particular	ADJ
ap-1075	55	38	items	item	NOUN
ap-1075	55	39	�	�	PROPN
ap-1075	55	40	�	�	PROPN
ap-1075	55	41	(	(	PUNCT
ap-1075	55	42	)	)	PUNCT
ap-1075	55	43	(	(	PUNCT
ap-1075	55	44	)	)	PUNCT
ap-1075	55	45	m	m	VERB
ap-1075	55	46	yii	yii	ADJ
ap-1075	55	47	m	m	PROPN
ap-1075	55	48	d	d	PROPN
ap-1075	55	49	�	�	PROPN
ap-1075	55	50	�	�	PROPN
ap-1075	55	51	�	�	PROPN
ap-1075	55	52	�	�	PROPN
ap-1075	55	53	1	1	NUM
ap-1075	55	54	�	�	PROPN
ap-1075	55	55	.	.	PUNCT
ap-1075	56	1	other	other	ADJ
ap-1075	56	2	ways	way	NOUN
ap-1075	56	3	to	to	PART
ap-1075	56	4	construct	construct	VERB
ap-1075	56	5	such	such	ADJ
ap-1075	56	6	intervals	interval	NOUN
ap-1075	56	7	may	may	AUX
ap-1075	56	8	be	be	AUX
ap-1075	56	9	considered	consider	VERB
ap-1075	56	10	.	.	PUNCT
ap-1075	57	1	the	the	DET
ap-1075	57	2	following	follow	VERB
ap-1075	57	3	algorithm	algorithm	NOUN
ap-1075	57	4	uses	use	VERB
ap-1075	57	5	fencing	fence	VERB
ap-1075	57	6	.	.	PUNCT
ap-1075	58	1	fencing	fencing	NOUN
ap-1075	58	2	is	be	AUX
ap-1075	58	3	a	a	DET
ap-1075	58	4	heuristic	heuristic	ADJ
ap-1075	58	5	approachwhich	approachwhich	NOUN
ap-1075	58	6	anticipates	anticipate	VERB
ap-1075	58	7	that	that	SCONJ
ap-1075	58	8	areas	area	NOUN
ap-1075	58	9	of	of	ADP
ap-1075	58	10	higher	high	ADJ
ap-1075	58	11	average	average	ADJ
ap-1075	58	12	production	production	NOUN
ap-1075	58	13	are	be	AUX
ap-1075	58	14	located	locate	VERB
ap-1075	58	15	between	between	ADP
ap-1075	58	16	mutually	mutually	ADV
ap-1075	58	17	close	close	ADJ
ap-1075	58	18	points	point	NOUN
ap-1075	58	19	with	with	ADP
ap-1075	58	20	high	high	ADJ
ap-1075	58	21	production	production	NOUN
ap-1075	58	22	.	.	PUNCT
ap-1075	59	1	the	the	DET
ap-1075	59	2	algorithm	algorithm	NOUN
ap-1075	59	3	attempts	attempt	VERB
ap-1075	59	4	to	to	PART
ap-1075	59	5	build	build	VERB
ap-1075	59	6	a	a	DET
ap-1075	59	7	rectangular	rectangular	ADJ
ap-1075	59	8	fence	fence	NOUN
ap-1075	59	9	around	around	ADP
ap-1075	59	10	the	the	DET
ap-1075	59	11	area	area	NOUN
ap-1075	59	12	of	of	ADP
ap-1075	59	13	above	above	ADP
ap-1075	59	14	-	-	PUNCT
ap-1075	59	15	average	average	NOUN
ap-1075	59	16	production	production	NOUN
ap-1075	59	17	,	,	PUNCT
ap-1075	59	18	as	as	SCONJ
ap-1075	59	19	shown	show	VERB
ap-1075	59	20	in	in	ADP
ap-1075	59	21	fig	fig	NOUN
ap-1075	59	22	.	.	PUNCT
ap-1075	60	1	1	1	NUM
ap-1075	60	2	.	.	X
ap-1075	60	3	2.1	2.1	NUM
ap-1075	60	4	measuring	measuring	NOUN
ap-1075	60	5	and	and	CCONJ
ap-1075	60	6	data	datum	NOUN
ap-1075	60	7	preprocessing	preprocesse	VERB
ap-1075	60	8	�	�	PROPN
ap-1075	60	9	mapping	mapping	NOUN
ap-1075	60	10	is	be	AUX
ap-1075	60	11	necessary	necessary	ADJ
ap-1075	60	12	.	.	PUNCT
ap-1075	61	1	this	this	DET
ap-1075	61	2	mapping	mapping	NOUN
ap-1075	61	3	involves	involve	VERB
ap-1075	61	4	measuring	measure	VERB
ap-1075	61	5	and	and	CCONJ
ap-1075	61	6	data	datum	NOUN
ap-1075	61	7	preprocessing	preprocessing	NOUN
ap-1075	61	8	.	.	PUNCT
ap-1075	62	1	the	the	DET
ap-1075	62	2	simplest	simple	ADJ
ap-1075	62	3	way	way	NOUN
ap-1075	62	4	is	be	AUX
ap-1075	62	5	to	to	PART
ap-1075	62	6	transform	transform	VERB
ap-1075	62	7	binary	binary	ADJ
ap-1075	62	8	attributes	attribute	NOUN
ap-1075	62	9	into	into	ADP
ap-1075	62	10	real	real	ADJ
ap-1075	62	11	attributes	attribute	NOUN
ap-1075	62	12	by	by	ADP
ap-1075	62	13	0–1	0–1	NOUN
ap-1075	62	14	coding	code	VERB
ap-1075	62	15	.	.	PUNCT
ap-1075	63	1	categorical	categorical	ADJ
ap-1075	63	2	attributes	attribute	NOUN
ap-1075	63	3	are	be	AUX
ap-1075	63	4	transformed	transform	VERB
ap-1075	63	5	into	into	ADP
ap-1075	63	6	more	more	ADJ
ap-1075	63	7	binary	binary	ADJ
ap-1075	63	8	binary	binary	ADJ
ap-1075	63	9	attributes	attribute	NOUN
ap-1075	63	10	.	.	PUNCT
ap-1075	64	1	it	it	PRON
ap-1075	64	2	is	be	AUX
ap-1075	64	3	very	very	ADV
ap-1075	64	4	useful	useful	ADJ
ap-1075	64	5	to	to	PART
ap-1075	64	6	reduce	reduce	VERB
ap-1075	64	7	the	the	DET
ap-1075	64	8	input	input	NOUN
ap-1075	64	9	vector	vector	NOUN
ap-1075	64	10	dimension	dimension	NOUN
ap-1075	64	11	,	,	PUNCT
ap-1075	64	12	e.g.	e.g.	ADV
ap-1075	64	13	by	by	ADP
ap-1075	64	14	principal	principal	ADJ
ap-1075	64	15	components	component	NOUN
ap-1075	64	16	analysis	analysis	NOUN
ap-1075	64	17	[	[	X
ap-1075	64	18	11	11	NUM
ap-1075	64	19	]	]	PUNCT
ap-1075	64	20	.	.	PUNCT
ap-1075	65	1	let	let	VERB
ap-1075	65	2	us	we	PRON
ap-1075	65	3	define	define	VERB
ap-1075	65	4	xi	xi	ADP
ap-1075	65	5	i	i	PROPN
ap-1075	65	6	�	�	PROPN
ap-1075	65	7	�	�	PROPN
ap-1075	65	8	(	(	PUNCT
ap-1075	65	9	)	)	PUNCT
ap-1075	65	10	and	and	CCONJ
ap-1075	65	11	the	the	DET
ap-1075	65	12	vector	vector	NOUN
ap-1075	65	13	x	x	PUNCT
ap-1075	65	14	x	x	PUNCT
ap-1075	65	15	x	x	X
ap-1075	65	16	xmax	xmax	PROPN
ap-1075	65	17	(	(	PUNCT
ap-1075	65	18	,	,	PUNCT
ap-1075	65	19	,	,	PUNCT
ap-1075	65	20	,	,	PUNCT
ap-1075	65	21	)	)	PUNCT
ap-1075	65	22	max	max	PROPN
ap-1075	65	23	max	max	PROPN
ap-1075	65	24	max	max	PROPN
ap-1075	65	25	�	�	PROPN
ap-1075	65	26	1	1	NUM
ap-1075	65	27	2	2	NUM
ap-1075	65	28	�	�	NOUN
ap-1075	65	29	n	n	CCONJ
ap-1075	65	30	so	so	ADV
ap-1075	65	31	x	x	PROPN
ap-1075	65	32	xj	xj	PROPN
ap-1075	65	33	j	j	PROPN
ap-1075	66	1	i	i	PRON
ap-1075	66	2	i	i	PRON
ap-1075	66	3	dmax	dmax	VERB
ap-1075	66	4	�	�	PROPN
ap-1075	66	5	�	�	PROPN
ap-1075	66	6	�	�	PROPN
ap-1075	66	7	.	.	PUNCT
ap-1075	67	1	the	the	DET
ap-1075	67	2	vector	vector	PROPN
ap-1075	67	3	xmax	xmax	PROPN
ap-1075	67	4	is	be	AUX
ap-1075	67	5	used	use	VERB
ap-1075	67	6	for	for	ADP
ap-1075	67	7	complementary	complementary	ADJ
ap-1075	67	8	coding	coding	NOUN
ap-1075	67	9	x.	x.	NOUN
ap-1075	67	10	2.2	2.2	NUM
ap-1075	67	11	data	datum	NOUN
ap-1075	67	12	splitting	split	VERB
ap-1075	67	13	the	the	DET
ap-1075	67	14	data	datum	NOUN
ap-1075	67	15	set	set	VERB
ap-1075	67	16	d	d	VERB
ap-1075	67	17	is	be	AUX
ap-1075	67	18	divided	divide	VERB
ap-1075	67	19	randomly	randomly	ADV
ap-1075	67	20	into	into	ADP
ap-1075	67	21	three	three	NUM
ap-1075	67	22	subsets	subset	NOUN
ap-1075	67	23	:	:	PUNCT
ap-1075	67	24	base	base	NOUN
ap-1075	67	25	subset	subset	NOUN
ap-1075	67	26	b	b	NOUN
ap-1075	67	27	,	,	PUNCT
ap-1075	67	28	training	training	NOUN
ap-1075	67	29	subset	subset	NOUN
ap-1075	67	30	t	t	PROPN
ap-1075	67	31	and	and	CCONJ
ap-1075	67	32	validation	validation	NOUN
ap-1075	67	33	subset	subset	NOUN
ap-1075	67	34	v.	v.	ADP
ap-1075	67	35	sets	set	NOUN
ap-1075	67	36	b	b	PROPN
ap-1075	67	37	and	and	CCONJ
ap-1075	67	38	t	t	PROPN
ap-1075	67	39	are	be	AUX
ap-1075	67	40	used	use	VERB
ap-1075	67	41	for	for	ADP
ap-1075	67	42	constructing	construct	VERB
ap-1075	67	43	the	the	DET
ap-1075	67	44	predictor	predictor	NOUN
ap-1075	67	45	y	y	PROPN
ap-1075	67	46	,	,	PUNCT
ap-1075	67	47	whereby	whereby	SCONJ
ap-1075	67	48	their	their	PRON
ap-1075	67	49	size	size	NOUN
ap-1075	67	50	will	will	AUX
ap-1075	67	51	be	be	AUX
ap-1075	67	52	represented	represent	VERB
ap-1075	67	53	by	by	ADP
ap-1075	67	54	b	b	PROPN
ap-1075	67	55	t	t	PROPN
ap-1075	67	56	�	�	PROPN
ap-1075	67	57	�	�	PROPN
ap-1075	67	58	,	,	PUNCT
ap-1075	67	59	say10	say10	NOUN
ap-1075	67	60	�	�	PROPN
ap-1075	67	61	�	�	PROPN
ap-1075	67	62	b	b	PROPN
ap-1075	67	63	t	t	PROPN
ap-1075	67	64	.	.	PUNCT
ap-1075	68	1	the	the	DET
ap-1075	68	2	size	size	NOUN
ap-1075	68	3	of	of	ADP
ap-1075	68	4	v	v	NOUN
ap-1075	68	5	is	be	AUX
ap-1075	68	6	chosen	choose	VERB
ap-1075	68	7	with	with	ADP
ap-1075	68	8	respect	respect	NOUN
ap-1075	68	9	to	to	PART
ap-1075	68	10	cross	cross	VERB
ap-1075	68	11	validation	validation	NOUN
ap-1075	68	12	[	[	X
ap-1075	68	13	8	8	NUM
ap-1075	68	14	]	]	X
ap-1075	68	15	.	.	PUNCT
ap-1075	69	1	2.3	2.3	NUM
ap-1075	69	2	starting	start	VERB
ap-1075	69	3	set	set	NOUN
ap-1075	69	4	of	of	ADP
ap-1075	69	5	intervals	interval	NOUN
ap-1075	69	6	the	the	DET
ap-1075	69	7	starting	starting	NOUN
ap-1075	69	8	set	set	NOUN
ap-1075	69	9	of	of	ADP
ap-1075	69	10	intervals	interval	NOUN
ap-1075	69	11	is	be	AUX
ap-1075	69	12	defined	define	VERB
ap-1075	69	13	as	as	SCONJ
ap-1075	69	14	follows	follow	VERB
ap-1075	69	15	r	r	NOUN
ap-1075	69	16	xi	xi	INTJ
ap-1075	70	1	i	i	PRON
ap-1075	70	2	bo	bo	PROPN
ap-1075	70	3	o	o	PROPN
ap-1075	70	4	�	�	PROPN
ap-1075	70	5	�	�	PROPN
ap-1075	70	6	cc	cc	PROPN
ap-1075	70	7	(	(	PUNCT
ap-1075	70	8	)	)	PUNCT
ap-1075	70	9	,	,	PUNCT
ap-1075	71	1	whereby	whereby	SCONJ
ap-1075	71	2	b	b	PROPN
ap-1075	71	3	ni	ni	PROPN
ap-1075	71	4	b	b	PROPN
ap-1075	71	5	y	y	PROPN
ap-1075	71	6	k	k	PROPN
ap-1075	71	7	b	b	X
ap-1075	71	8	bo	bo	PROPN
ap-1075	71	9	i	i	PRON
ap-1075	71	10	�	�	PROPN
ap-1075	71	11	�	�	PROPN
ap-1075	71	12	�	�	PROPN
ap-1075	71	13	�	�	PROPN
ap-1075	71	14	�	�	PROPN
ap-1075	71	15	�	�	PROPN
ap-1075	71	16	�	�	PROPN
ap-1075	71	17	�	�	PROPN
ap-1075	71	18	�	�	PROPN
ap-1075	71	19	�	�	PROPN
ap-1075	71	20	�	�	PROPN
ap-1075	71	21	�	�	PROPN
ap-1075	71	22	(	(	PUNCT
ap-1075	71	23	)	)	PUNCT
ap-1075	71	24	(	(	PUNCT
ap-1075	71	25	)	)	PUNCT
ap-1075	71	26	,	,	PUNCT
ap-1075	71	27	cc	cc	PROPN
ap-1075	71	28	is	be	AUX
ap-1075	71	29	the	the	DET
ap-1075	71	30	complement	complement	NOUN
ap-1075	71	31	coding	coding	NOUN
ap-1075	71	32	cc	cc	PROPN
ap-1075	71	33	:	:	PUNCT
ap-1075	71	34	�	�	PROPN
ap-1075	71	35	�	�	PROPN
ap-1075	71	36	n	n	CCONJ
ap-1075	71	37	n	n	CCONJ
ap-1075	71	38	�	�	PROPN
ap-1075	71	39	2	2	NUM
ap-1075	71	40	and	and	CCONJ
ap-1075	71	41	k	k	PROPN
ap-1075	71	42	is	be	AUX
ap-1075	71	43	a	a	DET
ap-1075	71	44	parameter	parameter	NOUN
ap-1075	71	45	.	.	PUNCT
ap-1075	72	1	the	the	DET
ap-1075	72	2	definition	definition	NOUN
ap-1075	72	3	of	of	ADP
ap-1075	72	4	bo	bo	PROPN
ap-1075	72	5	ensures	ensure	VERB
ap-1075	72	6	that	that	SCONJ
ap-1075	72	7	p	p	PROPN
ap-1075	72	8	b	b	PROPN
ap-1075	72	9	b	b	X
ap-1075	72	10	ko	ko	PROPN
ap-1075	72	11	(	(	PUNCT
ap-1075	72	12	,	,	PUNCT
ap-1075	72	13	)	)	PUNCT
ap-1075	72	14	�	�	PROPN
ap-1075	72	15	.	.	PUNCT
ap-1075	73	1	2.4	2.4	NUM
ap-1075	73	2	interval	interval	NOUN
ap-1075	73	3	expansion	expansion	NOUN
ap-1075	73	4	two	two	NUM
ap-1075	73	5	intervals	interval	NOUN
ap-1075	73	6	r1	r1	NOUN
ap-1075	73	7	,	,	PUNCT
ap-1075	73	8	r2	r2	PROPN
ap-1075	73	9	can	can	AUX
ap-1075	73	10	be	be	AUX
ap-1075	73	11	expanded	expand	VERB
ap-1075	73	12	as	as	SCONJ
ap-1075	73	13	follows	follow	VERB
ap-1075	74	1	r	r	NOUN
ap-1075	74	2	r	r	NOUN
ap-1075	74	3	ri	ri	NOUN
ap-1075	75	1	i	i	PRON
ap-1075	75	2	i	i	PRON
ap-1075	75	3	new	new	PROPN
ap-1075	75	4	�	�	PROPN
ap-1075	75	5	min	min	PROPN
ap-1075	75	6	(	(	PUNCT
ap-1075	75	7	,	,	PUNCT
ap-1075	75	8	)	)	PUNCT
ap-1075	75	9	1	1	NUM
ap-1075	75	10	2	2	NUM
ap-1075	75	11	,	,	PUNCT
ap-1075	75	12	i	i	PRON
ap-1075	75	13	n	n	X
ap-1075	75	14	�	�	PROPN
ap-1075	75	15	1	1	NUM
ap-1075	75	16	2	2	NUM
ap-1075	75	17	2	2	NUM
ap-1075	75	18	,	,	PUNCT
ap-1075	75	19	,	,	PUNCT
ap-1075	75	20	,	,	PUNCT
ap-1075	75	21	�	�	PROPN
ap-1075	75	22	.	.	PUNCT
ap-1075	76	1	the	the	DET
ap-1075	76	2	construction	construction	NOUN
ap-1075	76	3	of	of	ADP
ap-1075	76	4	�	�	PROPN
ap-1075	76	5	p	p	NOUN
ap-1075	76	6	consists	consist	VERB
ap-1075	76	7	in	in	ADP
ap-1075	76	8	iterative	iterative	ADJ
ap-1075	76	9	expansion	expansion	NOUN
ap-1075	76	10	of	of	ADP
ap-1075	76	11	intervals	interval	NOUN
ap-1075	76	12	.	.	PUNCT
ap-1075	77	1	the	the	DET
ap-1075	77	2	process	process	NOUN
ap-1075	77	3	starts	start	VERB
ap-1075	77	4	with	with	ADP
ap-1075	77	5	ro	ro	PROPN
ap-1075	77	6	.	.	PROPN
ap-1075	77	7	two	two	NUM
ap-1075	77	8	intervals	interval	NOUN
ap-1075	77	9	are	be	AUX
ap-1075	77	10	expanded	expand	VERB
ap-1075	77	11	only	only	ADV
ap-1075	77	12	if	if	SCONJ
ap-1075	77	13	the	the	DET
ap-1075	77	14	new	new	ADJ
ap-1075	77	15	interval	interval	NOUN
ap-1075	77	16	covers	cover	VERB
ap-1075	77	17	p	p	NOUN
ap-1075	77	18	i	i	PRON
ap-1075	77	19	t	t	X
ap-1075	77	20	qt	qt	PROPN
ap-1075	77	21	(	(	PUNCT
ap-1075	77	22	(	(	PUNCT
ap-1075	77	23	)	)	PUNCT
ap-1075	77	24	,	,	PUNCT
ap-1075	77	25	)	)	PUNCT
ap-1075	77	26	rnew	rnew	PROPN
ap-1075	77	27	�	�	PROPN
ap-1075	77	28	,	,	PUNCT
ap-1075	77	29	where	where	SCONJ
ap-1075	77	30	qt	qt	NOUN
ap-1075	77	31	is	be	AUX
ap-1075	77	32	a	a	DET
ap-1075	77	33	parameter	parameter	NOUN
ap-1075	77	34	that	that	PRON
ap-1075	77	35	sinks	sink	VERB
ap-1075	77	36	linearly	linearly	ADV
ap-1075	77	37	during	during	ADP
ap-1075	77	38	the	the	DET
ap-1075	77	39	process	process	NOUN
ap-1075	77	40	from	from	ADP
ap-1075	77	41	p0	p0	NOUN
ap-1075	77	42	to	to	ADP
ap-1075	77	43	p1	p1	PROPN
ap-1075	77	44	.	.	PUNCT
ap-1075	78	1	in	in	ADP
ap-1075	78	2	order	order	NOUN
ap-1075	78	3	to	to	PART
ap-1075	78	4	expand	expand	VERB
ap-1075	78	5	the	the	DET
ap-1075	78	6	compared	compare	VERB
ap-1075	78	7	intervals	interval	NOUN
ap-1075	78	8	,	,	PUNCT
ap-1075	78	9	a	a	DET
ap-1075	78	10	heuristic	heuristic	NOUN
ap-1075	78	11	is	be	AUX
ap-1075	78	12	used	use	VERB
ap-1075	78	13	.	.	PUNCT
ap-1075	79	1	two	two	NUM
ap-1075	79	2	intervals	interval	NOUN
ap-1075	79	3	i	i	PRON
ap-1075	79	4	a	a	X
ap-1075	79	5	(	(	PUNCT
ap-1075	79	6	)	)	PUNCT
ap-1075	79	7	r	r	NOUN
ap-1075	79	8	,	,	PUNCT
ap-1075	79	9	i	i	PRON
ap-1075	79	10	b	b	PROPN
ap-1075	79	11	(	(	PUNCT
ap-1075	79	12	)	)	PUNCT
ap-1075	79	13	r	r	NOUN
ap-1075	79	14	are	be	AUX
ap-1075	79	15	suitable	suitable	ADJ
ap-1075	79	16	for	for	ADP
ap-1075	79	17	expansion	expansion	NOUN
ap-1075	79	18	if	if	SCONJ
ap-1075	79	19	p	p	PROPN
ap-1075	79	20	i	i	PRON
ap-1075	79	21	a	a	X
ap-1075	79	22	(	(	PUNCT
ap-1075	79	23	(	(	PUNCT
ap-1075	79	24	)	)	PUNCT
ap-1075	79	25	)	)	PUNCT
ap-1075	80	1	r	r	NOUN
ap-1075	80	2	and	and	CCONJ
ap-1075	80	3	p	p	NOUN
ap-1075	80	4	i	i	PROPN
ap-1075	80	5	b	b	PROPN
ap-1075	80	6	(	(	PUNCT
ap-1075	80	7	(	(	PUNCT
ap-1075	80	8	)	)	PUNCT
ap-1075	80	9	)	)	PUNCT
ap-1075	81	1	r	r	NOUN
ap-1075	81	2	are	be	AUX
ap-1075	81	3	high	high	ADJ
ap-1075	81	4	,	,	PUNCT
ap-1075	81	5	and	and	CCONJ
ap-1075	81	6	if	if	SCONJ
ap-1075	81	7	ra	ra	PROPN
ap-1075	81	8	and	and	CCONJ
ap-1075	81	9	rb	rb	NOUN
ap-1075	81	10	are	be	AUX
ap-1075	81	11	close	close	ADJ
ap-1075	81	12	.	.	PUNCT
ap-1075	82	1	let	let	VERB
ap-1075	82	2	us	we	PRON
ap-1075	82	3	define	define	VERB
ap-1075	82	4	suitability	suitability	NOUN
ap-1075	82	5	as	as	ADP
ap-1075	82	6	:	:	PUNCT
ap-1075	82	7	v	v	ADP
ap-1075	82	8	p	p	NOUN
ap-1075	83	1	i	i	PRON
ap-1075	84	1	t	t	X
ap-1075	85	1	p	p	X
ap-1075	86	1	i	i	PRON
ap-1075	86	2	t	t	VERB
ap-1075	86	3	a	a	DET
ap-1075	86	4	b	b	NOUN
ap-1075	86	5	a	a	DET
ap-1075	86	6	b	b	NOUN
ap-1075	86	7	a	a	DET
ap-1075	86	8	b	b	NOUN
ap-1075	86	9	,	,	PUNCT
ap-1075	86	10	(	(	PUNCT
ap-1075	86	11	(	(	PUNCT
ap-1075	86	12	)	)	PUNCT
ap-1075	86	13	,	,	PUNCT
ap-1075	86	14	)	)	PUNCT
ap-1075	87	1	(	(	PUNCT
ap-1075	87	2	(	(	PUNCT
ap-1075	87	3	)	)	PUNCT
ap-1075	87	4	,	,	PUNCT
ap-1075	87	5	)	)	PUNCT
ap-1075	87	6	(	(	PUNCT
ap-1075	87	7	,	,	PUNCT
ap-1075	87	8	)	)	PUNCT
ap-1075	87	9	�	�	PROPN
ap-1075	87	10	�	�	PROPN
ap-1075	87	11	r	r	NOUN
ap-1075	87	12	r	r	NOUN
ap-1075	87	13	r	r	NOUN
ap-1075	87	14	r	r	NOUN
ap-1075	87	15	�	�	PROPN
ap-1075	87	16	,	,	PUNCT
ap-1075	87	17	(	(	PUNCT
ap-1075	87	18	4	4	X
ap-1075	87	19	)	)	PUNCT
ap-1075	87	20	where	where	SCONJ
ap-1075	87	21	�	�	PROPN
ap-1075	87	22	is	be	AUX
ap-1075	87	23	a	a	DET
ap-1075	87	24	metrics	metric	NOUN
ap-1075	87	25	.	.	PUNCT
ap-1075	88	1	the	the	DET
ap-1075	88	2	first	first	ADJ
ap-1075	88	3	version	version	NOUN
ap-1075	88	4	of	of	ADP
ap-1075	88	5	the	the	DET
ap-1075	88	6	algorithm	algorithm	NOUN
ap-1075	88	7	worked	work	VERB
ap-1075	88	8	with	with	ADP
ap-1075	88	9	hamming	hamming	NOUN
ap-1075	88	10	distance	distance	NOUN
ap-1075	88	11	[	[	X
ap-1075	88	12	6	6	NUM
ap-1075	88	13	]	]	PUNCT
ap-1075	88	14	,	,	PUNCT
ap-1075	88	15	but	but	CCONJ
ap-1075	88	16	other	other	ADJ
ap-1075	88	17	metrics	metric	NOUN
ap-1075	88	18	can	can	AUX
ap-1075	88	19	be	be	AUX
ap-1075	88	20	also	also	ADV
ap-1075	88	21	applied	apply	VERB
ap-1075	88	22	.	.	PUNCT
ap-1075	89	1	in	in	ADP
ap-1075	89	2	each	each	DET
ap-1075	89	3	step	step	NOUN
ap-1075	89	4	,	,	PUNCT
ap-1075	89	5	a	a	DET
ap-1075	89	6	pair	pair	NOUN
ap-1075	89	7	of	of	ADP
ap-1075	89	8	intervals	interval	NOUN
ap-1075	89	9	is	be	AUX
ap-1075	89	10	tested	test	VERB
ap-1075	89	11	for	for	ADP
ap-1075	89	12	expansion	expansion	NOUN
ap-1075	89	13	.	.	PUNCT
ap-1075	90	1	the	the	DET
ap-1075	90	2	pair	pair	NOUN
ap-1075	90	3	is	be	AUX
ap-1075	90	4	selected	select	VERB
ap-1075	90	5	partly	partly	ADV
ap-1075	90	6	randomly	randomly	ADV
ap-1075	90	7	as	as	SCONJ
ap-1075	90	8	follows	follow	VERB
ap-1075	90	9	:	:	PUNCT
ap-1075	90	10	the	the	DET
ap-1075	90	11	pair	pair	NOUN
ap-1075	90	12	with	with	ADP
ap-1075	90	13	highest	high	ADJ
ap-1075	90	14	suitability	suitability	NOUN
ap-1075	90	15	(	(	PUNCT
ap-1075	90	16	probability	probability	NOUN
ap-1075	90	17	0.8	0.8	NUM
ap-1075	90	18	)	)	PUNCT
ap-1075	90	19	,	,	PUNCT
ap-1075	90	20	the	the	DET
ap-1075	90	21	pair	pair	NOUN
ap-1075	90	22	with	with	ADP
ap-1075	90	23	lowest	low	ADJ
ap-1075	90	24	suitability	suitability	NOUN
ap-1075	90	25	(	(	PUNCT
ap-1075	90	26	0.1	0.1	NUM
ap-1075	90	27	)	)	PUNCT
ap-1075	90	28	,	,	PUNCT
ap-1075	90	29	or	or	CCONJ
ap-1075	90	30	a	a	DET
ap-1075	90	31	random	random	ADJ
ap-1075	90	32	pair	pair	NOUN
ap-1075	90	33	(	(	PUNCT
ap-1075	90	34	0.1	0.1	NUM
ap-1075	90	35	)	)	PUNCT
ap-1075	90	36	.	.	PUNCT
ap-1075	91	1	if	if	SCONJ
ap-1075	91	2	a	a	DET
ap-1075	91	3	pair	pair	NOUN
ap-1075	91	4	is	be	AUX
ap-1075	91	5	expanded	expand	VERB
ap-1075	91	6	,	,	PUNCT
ap-1075	91	7	its	its	PRON
ap-1075	91	8	suitability	suitability	NOUN
ap-1075	91	9	is	be	AUX
ap-1075	91	10	recalculated	recalculate	VERB
ap-1075	91	11	for	for	ADP
ap-1075	91	12	all	all	DET
ap-1075	91	13	other	other	ADJ
ap-1075	91	14	intervals	interval	NOUN
ap-1075	91	15	.	.	PUNCT
ap-1075	92	1	56	56	NUM
ap-1075	92	2	©	©	PROPN
ap-1075	92	3	czech	czech	PROPN
ap-1075	92	4	technical	technical	PROPN
ap-1075	92	5	university	university	PROPN
ap-1075	92	6	publishing	publishing	NOUN
ap-1075	92	7	house	house	NOUN
ap-1075	92	8	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1075	92	9	acta	acta	PROPN
ap-1075	92	10	polytechnica	polytechnica	PROPN
ap-1075	92	11	vol	vol	NOUN
ap-1075	92	12	.	.	PUNCT
ap-1075	93	1	48	48	NUM
ap-1075	93	2	no	no	NOUN
ap-1075	93	3	.	.	PUNCT
ap-1075	94	1	6/2008	6/2008	NOUN
ap-1075	94	2	1	1	NUM
ap-1075	94	3	2	2	NUM
ap-1075	94	4	3	3	NUM
ap-1075	94	5	4	4	NUM
ap-1075	94	6	1	1	NUM
ap-1075	94	7	2	2	NUM
ap-1075	94	8	3	3	NUM
ap-1075	94	9	�	�	PROPN
ap-1075	94	10	�	�	PROPN
ap-1075	94	11	4	4	NUM
ap-1075	94	12	�	�	PROPN
ap-1075	94	13	�	�	PROPN
ap-1075	94	14	10	10	NUM
ap-1075	94	15	�	�	PROPN
ap-1075	94	16	�	�	PROPN
ap-1075	94	17	10	10	NUM
ap-1075	94	18	x2	x2	PROPN
ap-1075	94	19	x2	x2	PROPN
ap-1075	94	20	fig	fig	NOUN
ap-1075	94	21	.	.	PUNCT
ap-1075	95	1	1	1	NUM
ap-1075	95	2	:	:	PUNCT
ap-1075	95	3	fencing	fencing	NOUN
ap-1075	95	4	:	:	PUNCT
ap-1075	95	5	expanding	expand	VERB
ap-1075	95	6	the	the	DET
ap-1075	95	7	square	square	NOUN
ap-1075	95	8	,	,	PUNCT
ap-1075	95	9	a	a	DET
ap-1075	95	10	new	new	ADJ
ap-1075	95	11	fence	fence	NOUN
ap-1075	95	12	(	(	PUNCT
ap-1075	95	13	dashed	dash	VERB
ap-1075	95	14	)	)	PUNCT
ap-1075	95	15	is	be	AUX
ap-1075	95	16	recommanded	recommande	VERB
ap-1075	95	17	to	to	ADP
ap-1075	95	18	the	the	DET
ap-1075	95	19	rectangle	rectangle	NOUN
ap-1075	95	20	that	that	PRON
ap-1075	95	21	is	be	AUX
ap-1075	95	22	close	close	ADJ
ap-1075	95	23	and	and	CCONJ
ap-1075	95	24	has	have	VERB
ap-1075	95	25	high	high	ADJ
ap-1075	95	26	productivity	productivity	NOUN
ap-1075	95	27	�	�	PROPN
ap-1075	95	28	2.5	2.5	NUM
ap-1075	95	29	termination	termination	NOUN
ap-1075	95	30	the	the	DET
ap-1075	95	31	algorithm	algorithm	NOUN
ap-1075	95	32	terminates	terminate	VERB
ap-1075	95	33	after	after	SCONJ
ap-1075	95	34	all	all	DET
ap-1075	95	35	pairs	pair	NOUN
ap-1075	95	36	of	of	ADP
ap-1075	95	37	intervals	interval	NOUN
ap-1075	95	38	have	have	AUX
ap-1075	95	39	been	be	AUX
ap-1075	95	40	tested	test	VERB
ap-1075	95	41	and	and	CCONJ
ap-1075	95	42	none	none	NOUN
ap-1075	95	43	can	can	AUX
ap-1075	95	44	be	be	AUX
ap-1075	95	45	expanded	expand	VERB
ap-1075	95	46	.	.	PUNCT
ap-1075	96	1	afterwards	afterwards	ADV
ap-1075	96	2	,	,	PUNCT
ap-1075	96	3	unexpanded	unexpanded	ADJ
ap-1075	96	4	intervals	interval	NOUN
ap-1075	96	5	(	(	PUNCT
ap-1075	96	6	i.e.	i.e.	X
ap-1075	96	7	points	point	NOUN
ap-1075	96	8	)	)	PUNCT
ap-1075	96	9	are	be	AUX
ap-1075	96	10	deleted	delete	VERB
ap-1075	96	11	.	.	PUNCT
ap-1075	97	1	because	because	SCONJ
ap-1075	97	2	intervals	interval	NOUN
ap-1075	97	3	may	may	AUX
ap-1075	97	4	overlap	overlap	VERB
ap-1075	97	5	,	,	PUNCT
ap-1075	97	6	their	their	PRON
ap-1075	97	7	conjunction	conjunction	NOUN
ap-1075	97	8	may	may	AUX
ap-1075	97	9	have	have	VERB
ap-1075	97	10	lower	low	ADJ
ap-1075	97	11	p	p	NOUN
ap-1075	97	12	than	than	ADP
ap-1075	97	13	average	average	ADJ
ap-1075	97	14	p	p	NOUN
ap-1075	97	15	of	of	ADP
ap-1075	97	16	all	all	DET
ap-1075	97	17	intervals	interval	NOUN
ap-1075	97	18	.	.	PUNCT
ap-1075	98	1	therefore	therefore	ADV
ap-1075	98	2	,	,	PUNCT
ap-1075	98	3	only	only	ADJ
ap-1075	98	4	intervals	interval	NOUN
ap-1075	98	5	with	with	ADP
ap-1075	98	6	highest	high	ADJ
ap-1075	98	7	p	p	NOUN
ap-1075	98	8	are	be	AUX
ap-1075	98	9	considered	consider	VERB
ap-1075	98	10	as	as	ADP
ap-1075	98	11	results	result	NOUN
ap-1075	98	12	so	so	SCONJ
ap-1075	98	13	their	their	PRON
ap-1075	98	14	conjunction	conjunction	NOUN
ap-1075	98	15	has	have	VERB
ap-1075	98	16	p	p	NOUN
ap-1075	98	17	high	high	ADJ
ap-1075	98	18	enough	enough	ADV
ap-1075	98	19	(	(	PUNCT
ap-1075	98	20	e.g.	e.g.	ADV
ap-1075	98	21	higher	high	ADJ
ap-1075	98	22	than	than	ADP
ap-1075	98	23	a	a	DET
ap-1075	98	24	given	give	VERB
ap-1075	98	25	threshold	threshold	NOUN
ap-1075	98	26	)	)	PUNCT
ap-1075	98	27	.	.	PUNCT
ap-1075	99	1	2.6	2.6	NUM
ap-1075	99	2	validation	validation	NOUN
ap-1075	99	3	finally	finally	ADV
ap-1075	99	4	,	,	PUNCT
ap-1075	99	5	the	the	DET
ap-1075	99	6	results	result	NOUN
ap-1075	99	7	are	be	AUX
ap-1075	99	8	validated	validate	VERB
ap-1075	99	9	with	with	ADP
ap-1075	99	10	respect	respect	NOUN
ap-1075	99	11	to	to	ADP
ap-1075	99	12	the	the	DET
ap-1075	99	13	validation	validation	NOUN
ap-1075	99	14	set	set	VERB
ap-1075	99	15	r	r	NOUN
ap-1075	99	16	p	p	X
ap-1075	99	17	v	v	NOUN
ap-1075	99	18	v	v	NOUN
ap-1075	99	19	(	(	PUNCT
ap-1075	99	20	,	,	PUNCT
ap-1075	99	21	)	)	PUNCT
ap-1075	99	22	�	�	PROPN
ap-1075	99	23	,	,	PUNCT
ap-1075	99	24	and	and	CCONJ
ap-1075	99	25	p	p	X
ap-1075	99	26	p	p	X
ap-1075	99	27	v	v	NUM
ap-1075	99	28	v	v	NOUN
ap-1075	99	29	(	(	PUNCT
ap-1075	99	30	,	,	PUNCT
ap-1075	99	31	)	)	PUNCT
ap-1075	99	32	�	�	PROPN
ap-1075	99	33	are	be	AUX
ap-1075	99	34	calculated	calculate	VERB
ap-1075	99	35	.	.	PUNCT
ap-1075	100	1	such	such	ADJ
ap-1075	100	2	values	value	NOUN
ap-1075	100	3	can	can	AUX
ap-1075	100	4	be	be	AUX
ap-1075	100	5	considered	consider	VERB
ap-1075	100	6	as	as	ADP
ap-1075	100	7	the	the	DET
ap-1075	100	8	quality	quality	NOUN
ap-1075	100	9	of	of	ADP
ap-1075	100	10	the	the	DET
ap-1075	100	11	algorithm	algorithm	NOUN
ap-1075	100	12	.	.	PUNCT
ap-1075	101	1	3	3	NUM
ap-1075	101	2	results	result	VERB
ap-1075	101	3	the	the	DET
ap-1075	101	4	fencing	fence	VERB
ap-1075	101	5	algorithm	algorithm	NOUN
ap-1075	101	6	has	have	AUX
ap-1075	101	7	been	be	AUX
ap-1075	101	8	applied	apply	VERB
ap-1075	101	9	successfully	successfully	ADV
ap-1075	101	10	on	on	ADP
ap-1075	101	11	data	datum	NOUN
ap-1075	101	12	on	on	ADP
ap-1075	101	13	18	18	NUM
ap-1075	101	14	177	177	NUM
ap-1075	101	15	insurance	insurance	NOUN
ap-1075	101	16	claims	claim	NOUN
ap-1075	101	17	related	relate	VERB
ap-1075	101	18	to	to	ADP
ap-1075	101	19	traffic	traffic	NOUN
ap-1075	101	20	accidents	accident	NOUN
ap-1075	101	21	in	in	ADP
ap-1075	101	22	the	the	DET
ap-1075	101	23	czech	czech	PROPN
ap-1075	101	24	republic	republic	NOUN
ap-1075	101	25	in	in	ADP
ap-1075	101	26	2003–2005	2003–2005	NUM
ap-1075	101	27	.	.	PUNCT
ap-1075	102	1	categorical	categorical	ADJ
ap-1075	102	2	and	and	CCONJ
ap-1075	102	3	numerical	numerical	ADJ
ap-1075	102	4	attributes	attribute	NOUN
ap-1075	102	5	were	be	AUX
ap-1075	102	6	transformed	transform	VERB
ap-1075	102	7	into	into	ADP
ap-1075	102	8	binary	binary	ADJ
ap-1075	102	9	attributes	attribute	NOUN
ap-1075	102	10	.	.	PUNCT
ap-1075	103	1	there	there	PRON
ap-1075	103	2	was	be	VERB
ap-1075	103	3	a	a	DET
ap-1075	103	4	total	total	NOUN
ap-1075	103	5	of	of	ADP
ap-1075	103	6	135	135	NUM
ap-1075	103	7	binary	binary	ADJ
ap-1075	103	8	attributes	attribute	NOUN
ap-1075	103	9	.	.	PUNCT
ap-1075	104	1	the	the	DET
ap-1075	104	2	considered	consider	VERB
ap-1075	104	3	attributes	attribute	NOUN
ap-1075	104	4	and	and	CCONJ
ap-1075	104	5	their	their	PRON
ap-1075	104	6	transformation	transformation	NOUN
ap-1075	104	7	is	be	AUX
ap-1075	104	8	summarized	summarize	VERB
ap-1075	104	9	in	in	ADP
ap-1075	104	10	table	table	NOUN
ap-1075	104	11	1	1	NUM
ap-1075	104	12	.	.	PUNCT
ap-1075	105	1	the	the	DET
ap-1075	105	2	fencing	fence	VERB
ap-1075	105	3	algorithm	algorithm	NOUN
ap-1075	105	4	has	have	AUX
ap-1075	105	5	been	be	AUX
ap-1075	105	6	implemented	implement	VERB
ap-1075	105	7	in	in	ADP
ap-1075	105	8	matlab	matlab	PROPN
ap-1075	105	9	as	as	ADP
ap-1075	105	10	a	a	DET
ap-1075	105	11	set	set	NOUN
ap-1075	105	12	of	of	ADP
ap-1075	105	13	simple	simple	ADJ
ap-1075	105	14	scripts	script	NOUN
ap-1075	105	15	.	.	PUNCT
ap-1075	106	1	it	it	PRON
ap-1075	106	2	should	should	AUX
ap-1075	106	3	be	be	AUX
ap-1075	106	4	mentioned	mention	VERB
ap-1075	106	5	that	that	SCONJ
ap-1075	106	6	this	this	DET
ap-1075	106	7	particular	particular	ADJ
ap-1075	106	8	data	datum	NOUN
ap-1075	106	9	set	set	VERB
ap-1075	106	10	inspired	inspire	VERB
ap-1075	106	11	the	the	DET
ap-1075	106	12	author	author	NOUN
ap-1075	106	13	to	to	PART
ap-1075	106	14	invent	invent	NOUN
ap-1075	106	15	of	of	ADP
ap-1075	106	16	the	the	DET
ap-1075	106	17	fencing	fence	VERB
ap-1075	106	18	algorithm	algorithm	NOUN
ap-1075	106	19	,	,	PUNCT
ap-1075	106	20	after	after	SCONJ
ap-1075	106	21	attempts	attempt	NOUN
ap-1075	106	22	to	to	PART
ap-1075	106	23	build	build	VERB
ap-1075	106	24	some	some	DET
ap-1075	106	25	regression	regression	NOUN
ap-1075	106	26	model	model	NOUN
ap-1075	106	27	failed	fail	VERB
ap-1075	106	28	.	.	PUNCT
ap-1075	107	1	generalized	generalized	ADJ
ap-1075	107	2	linear	linear	ADJ
ap-1075	107	3	models	model	NOUN
ap-1075	107	4	[	[	X
ap-1075	107	5	4	4	NUM
ap-1075	107	6	]	]	PUNCT
ap-1075	107	7	,	,	PUNCT
ap-1075	107	8	which	which	PRON
ap-1075	107	9	are	be	AUX
ap-1075	107	10	typical	typical	ADJ
ap-1075	107	11	in	in	ADP
ap-1075	107	12	insurance	insurance	NOUN
ap-1075	107	13	mathematics	mathematic	NOUN
ap-1075	107	14	,	,	PUNCT
ap-1075	107	15	and	and	CCONJ
ap-1075	107	16	multilayer	multilayer	ADJ
ap-1075	107	17	perceptrons	perceptron	NOUN
ap-1075	107	18	[	[	X
ap-1075	107	19	8	8	NUM
ap-1075	107	20	]	]	PUNCT
ap-1075	107	21	did	do	AUX
ap-1075	107	22	not	not	PART
ap-1075	107	23	provide	provide	VERB
ap-1075	107	24	sufficient	sufficient	ADJ
ap-1075	107	25	results	result	NOUN
ap-1075	107	26	,	,	PUNCT
ap-1075	107	27	as	as	SCONJ
ap-1075	107	28	shown	show	VERB
ap-1075	107	29	in	in	ADP
ap-1075	107	30	table	table	NOUN
ap-1075	107	31	2	2	NUM
ap-1075	107	32	.	.	PUNCT
ap-1075	108	1	the	the	DET
ap-1075	108	2	data	datum	NOUN
ap-1075	108	3	set	set	VERB
ap-1075	108	4	was	be	AUX
ap-1075	108	5	split	split	VERB
ap-1075	108	6	into	into	ADP
ap-1075	108	7	10	10	NUM
ap-1075	108	8	subsets	subset	NOUN
ap-1075	108	9	and	and	CCONJ
ap-1075	108	10	one	one	NUM
ap-1075	108	11	subset	subset	NOUN
ap-1075	108	12	was	be	AUX
ap-1075	108	13	always	always	ADV
ap-1075	108	14	tested	test	VERB
ap-1075	108	15	.	.	PUNCT
ap-1075	109	1	the	the	DET
ap-1075	109	2	logarithm	logarithm	NOUN
ap-1075	109	3	of	of	ADP
ap-1075	109	4	total	total	ADJ
ap-1075	109	5	costs	cost	NOUN
ap-1075	109	6	was	be	AUX
ap-1075	109	7	taken	take	VERB
ap-1075	109	8	as	as	ADP
ap-1075	109	9	an	an	DET
ap-1075	109	10	output	output	NOUN
ap-1075	109	11	variable	variable	NOUN
ap-1075	109	12	.	.	PUNCT
ap-1075	110	1	however	however	ADV
ap-1075	110	2	,	,	PUNCT
ap-1075	110	3	the	the	DET
ap-1075	110	4	mean	mean	ADJ
ap-1075	110	5	absolute	absolute	ADJ
ap-1075	110	6	error	error	NOUN
ap-1075	110	7	remains	remain	VERB
ap-1075	110	8	very	very	ADV
ap-1075	110	9	high	high	ADJ
ap-1075	110	10	(	(	PUNCT
ap-1075	110	11	the	the	DET
ap-1075	110	12	prediction	prediction	NOUN
ap-1075	110	13	and	and	CCONJ
ap-1075	110	14	reality	reality	NOUN
ap-1075	110	15	differ	differ	VERB
ap-1075	110	16	over	over	ADP
ap-1075	110	17	twentyfold	twentyfold	ADJ
ap-1075	110	18	on	on	ADP
ap-1075	110	19	average	average	ADJ
ap-1075	110	20	!	!	PUNCT
ap-1075	110	21	)	)	PUNCT
ap-1075	110	22	.	.	PUNCT
ap-1075	111	1	first	first	ADJ
ap-1075	111	2	experiments	experiment	NOUN
ap-1075	111	3	showed	show	VERB
ap-1075	111	4	that	that	SCONJ
ap-1075	111	5	the	the	DET
ap-1075	111	6	135	135	NUM
ap-1075	111	7	dimensional	dimensional	ADJ
ap-1075	111	8	space	space	NOUN
ap-1075	111	9	is	be	AUX
ap-1075	111	10	too	too	ADV
ap-1075	111	11	sparse	sparse	ADJ
ap-1075	111	12	and	and	CCONJ
ap-1075	111	13	than	than	SCONJ
ap-1075	111	14	there	there	PRON
ap-1075	111	15	are	be	VERB
ap-1075	111	16	many	many	ADJ
ap-1075	111	17	futher	futher	VERB
ap-1075	111	18	unexpandable	unexpandable	ADJ
ap-1075	111	19	intervals	interval	NOUN
ap-1075	111	20	.	.	PUNCT
ap-1075	112	1	therefore	therefore	ADV
ap-1075	112	2	,	,	PUNCT
ap-1075	112	3	the	the	DET
ap-1075	112	4	dimension	dimension	NOUN
ap-1075	112	5	was	be	AUX
ap-1075	112	6	reduced	reduce	VERB
ap-1075	112	7	by	by	ADP
ap-1075	112	8	selecting	select	VERB
ap-1075	112	9	36	36	NUM
ap-1075	112	10	attributes	attribute	NOUN
ap-1075	112	11	describing	describe	VERB
ap-1075	112	12	the	the	DET
ap-1075	112	13	region	region	NOUN
ap-1075	112	14	of	of	ADP
ap-1075	112	15	the	the	DET
ap-1075	112	16	claimant	claimant	ADJ
ap-1075	112	17	,	,	PUNCT
ap-1075	112	18	road	road	NOUN
ap-1075	112	19	type	type	NOUN
ap-1075	112	20	,	,	PUNCT
ap-1075	112	21	and	and	CCONJ
ap-1075	112	22	cause	cause	NOUN
ap-1075	112	23	of	of	ADP
ap-1075	112	24	the	the	DET
ap-1075	112	25	accident	accident	NOUN
ap-1075	112	26	.	.	PUNCT
ap-1075	113	1	after	after	ADP
ap-1075	113	2	next	next	ADJ
ap-1075	113	3	unsuccessful	unsuccessful	ADJ
ap-1075	113	4	experiments	experiment	NOUN
ap-1075	113	5	with	with	ADP
ap-1075	113	6	p1	p1	PROPN
ap-1075	113	7	4	4	NUM
ap-1075	113	8	�	�	PROPN
ap-1075	113	9	and	and	CCONJ
ap-1075	113	10	p1	p1	PROPN
ap-1075	113	11	2	2	NUM
ap-1075	113	12	�	�	PROPN
ap-1075	113	13	,	,	PUNCT
ap-1075	113	14	it	it	PRON
ap-1075	113	15	was	be	AUX
ap-1075	113	16	neccessary	neccessary	ADJ
ap-1075	113	17	to	to	PART
ap-1075	113	18	set	set	VERB
ap-1075	113	19	p1	p1	PROPN
ap-1075	113	20	15	15	NUM
ap-1075	113	21	�	�	PROPN
ap-1075	113	22	.	.	PUNCT
ap-1075	113	23	.	.	PUNCT
ap-1075	114	1	then	then	ADV
ap-1075	114	2	9	9	NUM
ap-1075	114	3	intervals	interval	NOUN
ap-1075	114	4	were	be	AUX
ap-1075	114	5	found	find	VERB
ap-1075	114	6	.	.	PUNCT
ap-1075	115	1	however	however	ADV
ap-1075	115	2	,	,	PUNCT
ap-1075	115	3	the	the	DET
ap-1075	115	4	conjunction	conjunction	NOUN
ap-1075	115	5	of	of	ADP
ap-1075	115	6	them	they	PRON
ap-1075	115	7	had	have	VERB
ap-1075	115	8	p	p	NOUN
ap-1075	115	9	�	�	PROPN
ap-1075	115	10	119	119	NUM
ap-1075	115	11	.	.	PUNCT
ap-1075	116	1	only	only	ADV
ap-1075	116	2	.	.	PUNCT
ap-1075	117	1	therefore	therefore	ADV
ap-1075	117	2	only	only	ADV
ap-1075	117	3	3	3	NUM
ap-1075	117	4	best	good	ADJ
ap-1075	117	5	intervals	interval	NOUN
ap-1075	117	6	were	be	AUX
ap-1075	117	7	selected	select	VERB
ap-1075	117	8	,	,	PUNCT
ap-1075	117	9	with	with	ADP
ap-1075	117	10	p	p	PROPN
ap-1075	117	11	�	�	PROPN
ap-1075	117	12	1	1	NUM
ap-1075	117	13	48	48	NUM
ap-1075	117	14	.	.	PUNCT
ap-1075	118	1	and	and	CCONJ
ap-1075	118	2	r	r	NOUN
ap-1075	118	3	�	�	PROPN
ap-1075	118	4	0	0	NUM
ap-1075	118	5	32	32	NUM
ap-1075	118	6	.	.	PUNCT
ap-1075	118	7	.	.	PUNCT
ap-1075	119	1	©	©	PROPN
ap-1075	119	2	czech	czech	PROPN
ap-1075	119	3	technical	technical	PROPN
ap-1075	119	4	university	university	PROPN
ap-1075	119	5	publishing	publishing	NOUN
ap-1075	119	6	house	house	NOUN
ap-1075	119	7	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1075	119	8	57	57	NUM
ap-1075	119	9	acta	acta	PROPN
ap-1075	119	10	polytechnica	polytechnica	PROPN
ap-1075	119	11	vol	vol	NOUN
ap-1075	119	12	.	.	PUNCT
ap-1075	120	1	48	48	NUM
ap-1075	120	2	no	no	NOUN
ap-1075	120	3	.	.	PUNCT
ap-1075	121	1	6/2008	6/2008	NUM
ap-1075	121	2	observed	observe	VERB
ap-1075	121	3	values	value	NOUN
ap-1075	121	4	data	datum	NOUN
ap-1075	121	5	type	type	NOUN
ap-1075	121	6	used	use	VERB
ap-1075	121	7	as	as	ADP
ap-1075	121	8	accident	accident	NOUN
ap-1075	121	9	-	-	PUNCT
ap-1075	121	10	related	relate	VERB
ap-1075	121	11	information	information	NOUN
ap-1075	121	12	hour	hour	NOUN
ap-1075	121	13	numerical	numerical	ADJ
ap-1075	121	14	24	24	NUM
ap-1075	121	15	input	input	NOUN
ap-1075	121	16	binary	binary	PROPN
ap-1075	121	17	variables	variable	NOUN
ap-1075	121	18	day	day	NOUN
ap-1075	121	19	numerical	numerical	ADJ
ap-1075	121	20	7	7	NUM
ap-1075	121	21	input	input	NOUN
ap-1075	121	22	binary	binary	PROPN
ap-1075	121	23	variables	variable	NOUN
ap-1075	121	24	month	month	NOUN
ap-1075	121	25	numerical	numerical	ADJ
ap-1075	121	26	12	12	NUM
ap-1075	121	27	input	input	NOUN
ap-1075	121	28	binary	binary	PROPN
ap-1075	121	29	variables	variable	NOUN
ap-1075	121	30	year	year	NOUN
ap-1075	121	31	numerical	numerical	PROPN
ap-1075	121	32	6	6	NUM
ap-1075	121	33	input	input	NOUN
ap-1075	121	34	binary	binary	PROPN
ap-1075	121	35	variables	variable	NOUN
ap-1075	121	36	district	district	PROPN
ap-1075	121	37	categorical	categorical	ADJ
ap-1075	121	38	not	not	PART
ap-1075	121	39	used	use	VERB
ap-1075	121	40	municipality	municipality	NOUN
ap-1075	121	41	size	size	NOUN
ap-1075	121	42	numerical	numerical	ADJ
ap-1075	121	43	6	6	NUM
ap-1075	121	44	input	input	NOUN
ap-1075	121	45	binary	binary	NOUN
ap-1075	121	46	variables	variable	NOUN
ap-1075	121	47	cause	cause	VERB
ap-1075	121	48	categorical	categorical	ADJ
ap-1075	121	49	11	11	NUM
ap-1075	121	50	input	input	NOUN
ap-1075	121	51	binary	binary	PROPN
ap-1075	121	52	variables	variables	PROPN
ap-1075	121	53	road	road	NOUN
ap-1075	121	54	type	type	NOUN
ap-1075	121	55	categorical	categorical	ADJ
ap-1075	121	56	10	10	NUM
ap-1075	121	57	input	input	NOUN
ap-1075	121	58	binary	binary	PROPN
ap-1075	121	59	variables	variable	NOUN
ap-1075	121	60	tariff	tariff	NOUN
ap-1075	121	61	group	group	NOUN
ap-1075	121	62	categorical	categorical	ADJ
ap-1075	121	63	25	25	NUM
ap-1075	121	64	input	input	NOUN
ap-1075	121	65	binary	binary	PROPN
ap-1075	121	66	variables	variable	NOUN
ap-1075	121	67	car	car	NOUN
ap-1075	121	68	make	make	VERB
ap-1075	121	69	categorical	categorical	ADJ
ap-1075	121	70	not	not	PART
ap-1075	121	71	used	use	VERB
ap-1075	121	72	information	information	NOUN
ap-1075	121	73	about	about	ADP
ap-1075	121	74	causing	cause	VERB
ap-1075	121	75	person	person	NOUN
ap-1075	121	76	age	age	NOUN
ap-1075	121	77	numerical	numerical	ADJ
ap-1075	121	78	8	8	NUM
ap-1075	121	79	input	input	NOUN
ap-1075	121	80	binary	binary	NOUN
ap-1075	121	81	variables	variable	NOUN
ap-1075	121	82	sex	sex	PROPN
ap-1075	121	83	categorical	categorical	ADJ
ap-1075	121	84	3	3	NUM
ap-1075	121	85	input	input	NOUN
ap-1075	121	86	binary	binary	PROPN
ap-1075	121	87	variables	variable	NOUN
ap-1075	121	88	district	district	PROPN
ap-1075	121	89	categorical	categorical	ADJ
ap-1075	121	90	not	not	PART
ap-1075	121	91	used	use	VERB
ap-1075	121	92	municipality	municipality	NOUN
ap-1075	121	93	size	size	NOUN
ap-1075	121	94	numerical	numerical	ADJ
ap-1075	121	95	6	6	NUM
ap-1075	121	96	input	input	NOUN
ap-1075	121	97	binary	binary	PROPN
ap-1075	121	98	variables	variables	PROPN
ap-1075	121	99	region	region	NOUN
ap-1075	121	100	categorical	categorical	ADJ
ap-1075	121	101	15	15	NUM
ap-1075	121	102	input	input	NOUN
ap-1075	121	103	binary	binary	NOUN
ap-1075	121	104	variables	variable	NOUN
ap-1075	121	105	accident	accident	NOUN
ap-1075	121	106	at	at	ADP
ap-1075	121	107	place	place	NOUN
ap-1075	121	108	of	of	ADP
ap-1075	121	109	abode	abode	NOUN
ap-1075	121	110	binary	binary	NOUN
ap-1075	121	111	1	1	NUM
ap-1075	121	112	input	input	NOUN
ap-1075	121	113	binary	binary	NOUN
ap-1075	121	114	variables	variable	NOUN
ap-1075	121	115	claim	claim	VERB
ap-1075	121	116	costs	cost	VERB
ap-1075	121	117	1	1	NUM
ap-1075	121	118	output	output	NOUN
ap-1075	121	119	numerical	numerical	ADJ
ap-1075	121	120	variable	variable	PROPN
ap-1075	121	121	paid	pay	VERB
ap-1075	121	122	numerical	numerical	ADJ
ap-1075	121	123	additional	additional	ADJ
ap-1075	121	124	expected	expect	VERB
ap-1075	121	125	numerical	numerical	ADJ
ap-1075	121	126	table	table	NOUN
ap-1075	121	127	1	1	NUM
ap-1075	121	128	:	:	PUNCT
ap-1075	121	129	transformation	transformation	NOUN
ap-1075	121	130	of	of	ADP
ap-1075	121	131	observed	observed	ADJ
ap-1075	121	132	values	value	NOUN
ap-1075	121	133	into	into	ADP
ap-1075	121	134	input	input	NOUN
ap-1075	121	135	and	and	CCONJ
ap-1075	121	136	output	output	NOUN
ap-1075	121	137	variables	variable	VERB
ap-1075	121	138	3.1	3.1	NUM
ap-1075	121	139	comparison	comparison	NOUN
ap-1075	121	140	the	the	DET
ap-1075	121	141	problem	problem	NOUN
ap-1075	121	142	(	(	PUNCT
ap-1075	121	143	3	3	X
ap-1075	121	144	)	)	PUNCT
ap-1075	121	145	formulated	formulate	VERB
ap-1075	121	146	here	here	ADV
ap-1075	121	147	is	be	AUX
ap-1075	121	148	novel	novel	ADJ
ap-1075	121	149	and	and	CCONJ
ap-1075	121	150	the	the	DET
ap-1075	121	151	fencing	fence	VERB
ap-1075	121	152	algorithm	algorithm	NOUN
ap-1075	121	153	is	be	AUX
ap-1075	121	154	the	the	DET
ap-1075	121	155	only	only	ADJ
ap-1075	121	156	solution	solution	NOUN
ap-1075	121	157	so	so	ADV
ap-1075	121	158	far	far	ADV
ap-1075	121	159	.	.	PUNCT
ap-1075	122	1	however	however	ADV
ap-1075	122	2	,	,	PUNCT
ap-1075	122	3	for	for	ADP
ap-1075	122	4	a	a	DET
ap-1075	122	5	simple	simple	ADJ
ap-1075	122	6	comparison	comparison	NOUN
ap-1075	122	7	a	a	DET
ap-1075	122	8	clustering	cluster	VERB
ap-1075	122	9	based	base	VERB
ap-1075	122	10	method	method	NOUN
ap-1075	122	11	was	be	AUX
ap-1075	122	12	involved	involve	VERB
ap-1075	122	13	that	that	PRON
ap-1075	122	14	can	can	AUX
ap-1075	122	15	be	be	AUX
ap-1075	122	16	described	describe	VERB
ap-1075	122	17	briefly	briefly	ADV
ap-1075	122	18	as	as	SCONJ
ap-1075	122	19	follows	follow	VERB
ap-1075	122	20	:	:	PUNCT
ap-1075	123	1	1	1	X
ap-1075	123	2	.	.	X
ap-1075	123	3	building	build	VERB
ap-1075	123	4	above	above	ADP
ap-1075	123	5	-	-	PUNCT
ap-1075	123	6	average	average	ADJ
ap-1075	123	7	clusters	cluster	NOUN
ap-1075	123	8	from	from	ADP
ap-1075	123	9	training	train	VERB
ap-1075	123	10	data	datum	NOUN
ap-1075	123	11	:	:	PUNCT
ap-1075	123	12	best	good	ADJ
ap-1075	123	13	20	20	NUM
ap-1075	123	14	%	%	NOUN
ap-1075	123	15	records	record	NOUN
ap-1075	123	16	were	be	AUX
ap-1075	123	17	extracted	extract	VERB
ap-1075	123	18	and	and	CCONJ
ap-1075	123	19	clustered	cluster	VERB
ap-1075	123	20	via	via	ADP
ap-1075	123	21	the	the	DET
ap-1075	123	22	k	k	NOUN
ap-1075	123	23	-	-	PUNCT
ap-1075	123	24	means	means	NOUN
ap-1075	123	25	algorithm	algorithm	NOUN
ap-1075	123	26	.	.	PUNCT
ap-1075	124	1	for	for	ADP
ap-1075	124	2	each	each	DET
ap-1075	124	3	cluster	cluster	NOUN
ap-1075	124	4	,	,	PUNCT
ap-1075	124	5	the	the	DET
ap-1075	124	6	diameter	diameter	NOUN
ap-1075	124	7	was	be	AUX
ap-1075	124	8	calculated	calculate	VERB
ap-1075	124	9	as	as	ADP
ap-1075	124	10	the	the	DET
ap-1075	124	11	maximum	maximum	NOUN
ap-1075	124	12	of	of	ADP
ap-1075	124	13	distance	distance	NOUN
ap-1075	124	14	between	between	ADP
ap-1075	124	15	the	the	DET
ap-1075	124	16	center	center	NOUN
ap-1075	124	17	and	and	CCONJ
ap-1075	124	18	the	the	DET
ap-1075	124	19	record	record	NOUN
ap-1075	124	20	belonging	belong	VERB
ap-1075	124	21	to	to	ADP
ap-1075	124	22	it	it	PRON
ap-1075	124	23	.	.	PUNCT
ap-1075	125	1	2	2	X
ap-1075	125	2	.	.	X
ap-1075	125	3	finding	find	VERB
ap-1075	125	4	above	above	ADP
ap-1075	125	5	-	-	PUNCT
ap-1075	125	6	average	average	NOUN
ap-1075	125	7	records	record	NOUN
ap-1075	125	8	in	in	ADP
ap-1075	125	9	the	the	DET
ap-1075	125	10	testing	testing	NOUN
ap-1075	125	11	data	datum	NOUN
ap-1075	125	12	:	:	PUNCT
ap-1075	125	13	for	for	ADP
ap-1075	125	14	each	each	DET
ap-1075	125	15	record	record	NOUN
ap-1075	125	16	,	,	PUNCT
ap-1075	125	17	we	we	PRON
ap-1075	125	18	test	test	VERB
ap-1075	125	19	whether	whether	SCONJ
ap-1075	125	20	there	there	PRON
ap-1075	125	21	is	be	VERB
ap-1075	125	22	a	a	DET
ap-1075	125	23	cluster	cluster	NOUN
ap-1075	125	24	whose	whose	DET
ap-1075	125	25	center	center	NOUN
ap-1075	125	26	is	be	AUX
ap-1075	125	27	closer	close	ADJ
ap-1075	125	28	to	to	ADP
ap-1075	125	29	the	the	DET
ap-1075	125	30	record	record	NOUN
ap-1075	125	31	than	than	ADP
ap-1075	125	32	the	the	DET
ap-1075	125	33	c	c	NOUN
ap-1075	125	34	multiplied	multiply	VERB
ap-1075	125	35	diameter	diameter	NOUN
ap-1075	125	36	of	of	ADP
ap-1075	125	37	the	the	DET
ap-1075	125	38	cluster	cluster	NOUN
ap-1075	125	39	.	.	PUNCT
ap-1075	126	1	parameter	parameter	PROPN
ap-1075	126	2	c	c	PROPN
ap-1075	126	3	is	be	AUX
ap-1075	126	4	set	set	VERB
ap-1075	126	5	up	up	ADP
ap-1075	126	6	so	so	SCONJ
ap-1075	126	7	that	that	SCONJ
ap-1075	126	8	the	the	DET
ap-1075	126	9	level	level	NOUN
ap-1075	126	10	of	of	ADP
ap-1075	126	11	r	r	NOUN
ap-1075	126	12	is	be	AUX
ap-1075	126	13	satisfied	satisfied	ADJ
ap-1075	126	14	.	.	PUNCT
ap-1075	127	1	so	so	ADV
ap-1075	127	2	p	p	NOUN
ap-1075	127	3	is	be	AUX
ap-1075	127	4	defined	define	VERB
ap-1075	127	5	and	and	CCONJ
ap-1075	127	6	r	r	NOUN
ap-1075	127	7	ensured	ensure	VERB
ap-1075	127	8	.	.	PUNCT
ap-1075	128	1	3	3	X
ap-1075	128	2	.	.	X
ap-1075	128	3	calculation	calculation	NOUN
ap-1075	128	4	of	of	ADP
ap-1075	128	5	p	p	NOUN
ap-1075	128	6	from	from	ADP
ap-1075	128	7	provided	provide	VERB
ap-1075	128	8	data	datum	NOUN
ap-1075	128	9	,	,	PUNCT
ap-1075	128	10	p	p	PROPN
ap-1075	128	11	is	be	AUX
ap-1075	128	12	calculated	calculate	VERB
ap-1075	128	13	.	.	PUNCT
ap-1075	129	1	table	table	NOUN
ap-1075	129	2	3	3	NUM
ap-1075	129	3	shows	show	VERB
ap-1075	129	4	the	the	DET
ap-1075	129	5	results	result	NOUN
ap-1075	129	6	achieved	achieve	VERB
ap-1075	129	7	by	by	ADP
ap-1075	129	8	this	this	DET
ap-1075	129	9	method	method	NOUN
ap-1075	129	10	,	,	PUNCT
ap-1075	129	11	and	and	CCONJ
ap-1075	129	12	compares	compare	VERB
ap-1075	129	13	them	they	PRON
ap-1075	129	14	with	with	ADP
ap-1075	129	15	the	the	DET
ap-1075	129	16	fencing	fence	VERB
ap-1075	129	17	algorithm	algorithm	NOUN
ap-1075	129	18	:	:	PUNCT
ap-1075	129	19	the	the	DET
ap-1075	129	20	alternative	alternative	ADJ
ap-1075	129	21	method	method	NOUN
ap-1075	129	22	based	base	VERB
ap-1075	129	23	on	on	ADP
ap-1075	129	24	known	know	VERB
ap-1075	129	25	algorihm	algorihm	NOUN
ap-1075	129	26	provides	provide	VERB
ap-1075	129	27	less	less	ADV
ap-1075	129	28	narrow	narrow	ADJ
ap-1075	129	29	results	result	NOUN
ap-1075	129	30	.	.	PUNCT
ap-1075	130	1	however	however	ADV
ap-1075	130	2	,	,	PUNCT
ap-1075	130	3	the	the	DET
ap-1075	130	4	goal	goal	NOUN
ap-1075	130	5	of	of	ADP
ap-1075	130	6	this	this	DET
ap-1075	130	7	paper	paper	NOUN
ap-1075	130	8	was	be	AUX
ap-1075	130	9	not	not	PART
ap-1075	130	10	test	test	NOUN
ap-1075	130	11	proposed	propose	VERB
ap-1075	130	12	fencing	fencing	NOUN
ap-1075	130	13	algorithm	algorithm	NOUN
ap-1075	130	14	,	,	PUNCT
ap-1075	130	15	but	but	CCONJ
ap-1075	130	16	to	to	PART
ap-1075	130	17	show	show	VERB
ap-1075	130	18	that	that	SCONJ
ap-1075	130	19	this	this	DET
ap-1075	130	20	algorithm	algorithm	NOUN
ap-1075	130	21	is	be	AUX
ap-1075	130	22	able	able	ADJ
ap-1075	130	23	to	to	PART
ap-1075	130	24	solve	solve	VERB
ap-1075	130	25	problem	problem	NOUN
ap-1075	130	26	formulated	formulate	VERB
ap-1075	130	27	above	above	ADV
ap-1075	130	28	(	(	PUNCT
ap-1075	130	29	3	3	NUM
ap-1075	130	30	)	)	PUNCT
ap-1075	130	31	.	.	PUNCT
ap-1075	131	1	more	more	ADJ
ap-1075	131	2	experiments	experiment	NOUN
ap-1075	131	3	with	with	ADP
ap-1075	131	4	the	the	DET
ap-1075	131	5	k	k	NOUN
ap-1075	131	6	-	-	PUNCT
ap-1075	131	7	means	means	NOUN
ap-1075	131	8	based	base	VERB
ap-1075	131	9	approach	approach	NOUN
ap-1075	131	10	might	might	AUX
ap-1075	131	11	provide	provide	VERB
ap-1075	131	12	better	well	ADJ
ap-1075	131	13	results	result	NOUN
ap-1075	131	14	.	.	PUNCT
ap-1075	132	1	4	4	NUM
ap-1075	132	2	discussion	discussion	NOUN
ap-1075	132	3	and	and	CCONJ
ap-1075	132	4	further	further	ADJ
ap-1075	132	5	work	work	VERB
ap-1075	132	6	the	the	DET
ap-1075	132	7	fencing	fence	VERB
ap-1075	132	8	algorithm	algorithm	NOUN
ap-1075	132	9	can	can	AUX
ap-1075	132	10	be	be	AUX
ap-1075	132	11	modified	modify	VERB
ap-1075	132	12	so	so	SCONJ
ap-1075	132	13	the	the	DET
ap-1075	132	14	suitability	suitability	PROPN
ap-1075	132	15	va	va	PROPN
ap-1075	132	16	,	,	PUNCT
ap-1075	132	17	b	b	PROPN
ap-1075	132	18	is	be	AUX
ap-1075	132	19	calculated	calculate	VERB
ap-1075	132	20	in	in	ADP
ap-1075	132	21	another	another	DET
ap-1075	132	22	way	way	NOUN
ap-1075	132	23	.	.	PUNCT
ap-1075	133	1	there	there	PRON
ap-1075	133	2	should	should	AUX
ap-1075	133	3	be	be	AUX
ap-1075	133	4	an	an	DET
ap-1075	133	5	increase	increase	NOUN
ap-1075	133	6	in	in	ADP
ap-1075	133	7	p	p	NOUN
ap-1075	133	8	in	in	ADP
ap-1075	133	9	both	both	DET
ap-1075	133	10	intervals	interval	NOUN
ap-1075	133	11	and	and	CCONJ
ap-1075	133	12	a	a	DET
ap-1075	133	13	decrease	decrease	NOUN
ap-1075	133	14	in	in	ADP
ap-1075	133	15	distance	distance	NOUN
ap-1075	133	16	between	between	ADP
ap-1075	133	17	r(a	r(a	PROPN
ap-1075	133	18	)	)	PUNCT
ap-1075	133	19	and	and	CCONJ
ap-1075	133	20	r(b	r(b	PROPN
ap-1075	133	21	)	)	PUNCT
ap-1075	133	22	.	.	PUNCT
ap-1075	134	1	the	the	DET
ap-1075	134	2	randomized	randomized	ADJ
ap-1075	134	3	selection	selection	NOUN
ap-1075	134	4	rule	rule	NOUN
ap-1075	134	5	can	can	AUX
ap-1075	134	6	also	also	ADV
ap-1075	134	7	be	be	AUX
ap-1075	134	8	modified	modify	VERB
ap-1075	134	9	.	.	PUNCT
ap-1075	135	1	if	if	SCONJ
ap-1075	135	2	a	a	DET
ap-1075	135	3	pair	pair	NOUN
ap-1075	135	4	of	of	ADP
ap-1075	135	5	intervals	interval	NOUN
ap-1075	135	6	is	be	AUX
ap-1075	135	7	tested	test	VERB
ap-1075	135	8	,	,	PUNCT
ap-1075	135	9	the	the	DET
ap-1075	135	10	whole	whole	ADJ
ap-1075	135	11	training	training	NOUN
ap-1075	135	12	set	set	NOUN
ap-1075	135	13	t	t	PROPN
ap-1075	135	14	is	be	AUX
ap-1075	135	15	gone	go	VERB
ap-1075	135	16	through	through	ADV
ap-1075	135	17	.	.	PUNCT
ap-1075	136	1	this	this	PRON
ap-1075	136	2	is	be	AUX
ap-1075	136	3	probably	probably	ADV
ap-1075	136	4	the	the	DET
ap-1075	136	5	achiles	achiles	PROPN
ap-1075	136	6	tendon	tendon	NOUN
ap-1075	136	7	,	,	PUNCT
ap-1075	136	8	because	because	SCONJ
ap-1075	136	9	the	the	DET
ap-1075	136	10	size	size	NOUN
ap-1075	136	11	of	of	ADP
ap-1075	136	12	t	t	PROPN
ap-1075	136	13	is	be	AUX
ap-1075	136	14	usually	usually	ADV
ap-1075	136	15	very	very	ADV
ap-1075	136	16	large	large	ADJ
ap-1075	136	17	.	.	PUNCT
ap-1075	137	1	therefore	therefore	ADV
ap-1075	137	2	more	more	ADV
ap-1075	137	3	detailed	detailed	ADJ
ap-1075	137	4	examination	examination	NOUN
ap-1075	137	5	complexity	complexity	NOUN
ap-1075	137	6	and	and	CCONJ
ap-1075	137	7	the	the	DET
ap-1075	137	8	design	design	NOUN
ap-1075	137	9	of	of	ADP
ap-1075	137	10	more	more	ADV
ap-1075	137	11	suitable	suitable	ADJ
ap-1075	137	12	data	data	NOUN
ap-1075	137	13	structures	structure	NOUN
ap-1075	137	14	are	be	AUX
ap-1075	137	15	desirable	desirable	ADJ
ap-1075	137	16	.	.	PUNCT
ap-1075	138	1	the	the	DET
ap-1075	138	2	basic	basic	ADJ
ap-1075	138	3	idea	idea	NOUN
ap-1075	138	4	of	of	ADP
ap-1075	138	5	constructing	construct	VERB
ap-1075	138	6	an	an	DET
ap-1075	138	7	above	above	ADJ
ap-1075	138	8	-	-	PUNCT
ap-1075	138	9	average	average	NOUN
ap-1075	138	10	subset	subset	NOUN
ap-1075	138	11	can	can	AUX
ap-1075	138	12	be	be	AUX
ap-1075	138	13	evolved	evolve	VERB
ap-1075	138	14	in	in	ADP
ap-1075	138	15	many	many	ADJ
ap-1075	138	16	ways	way	NOUN
ap-1075	138	17	.	.	PUNCT
ap-1075	139	1	the	the	DET
ap-1075	139	2	subset	subset	NOUN
ap-1075	139	3	need	need	AUX
ap-1075	139	4	not	not	PART
ap-1075	139	5	be	be	AUX
ap-1075	139	6	a	a	DET
ap-1075	139	7	union	union	NOUN
ap-1075	139	8	of	of	ADP
ap-1075	139	9	intervals	interval	NOUN
ap-1075	139	10	,	,	PUNCT
ap-1075	139	11	but	but	CCONJ
ap-1075	139	12	they	they	PRON
ap-1075	139	13	may	may	AUX
ap-1075	139	14	be	be	AUX
ap-1075	139	15	simplexes	simplexe	NOUN
ap-1075	139	16	.	.	PUNCT
ap-1075	140	1	the	the	DET
ap-1075	140	2	set	set	NOUN
ap-1075	140	3	must	must	AUX
ap-1075	140	4	not	not	PART
ap-1075	140	5	be	be	AUX
ap-1075	140	6	narrow	narrow	ADJ
ap-1075	140	7	,	,	PUNCT
ap-1075	140	8	it	it	PRON
ap-1075	140	9	may	may	AUX
ap-1075	140	10	be	be	AUX
ap-1075	140	11	fuzzy	fuzzy	ADJ
ap-1075	140	12	.	.	PUNCT
ap-1075	141	1	or	or	CCONJ
ap-1075	141	2	the	the	DET
ap-1075	141	3	subset	subset	NOUN
ap-1075	141	4	can	can	AUX
ap-1075	141	5	be	be	AUX
ap-1075	141	6	given	give	VERB
ap-1075	141	7	in	in	ADP
ap-1075	141	8	an	an	DET
ap-1075	141	9	algebraic	algebraic	ADJ
ap-1075	141	10	form	form	NOUN
ap-1075	141	11	and	and	CCONJ
ap-1075	141	12	detected	detect	VERB
ap-1075	141	13	by	by	ADP
ap-1075	141	14	genetic	genetic	ADJ
ap-1075	141	15	programming	programming	NOUN
ap-1075	141	16	or	or	CCONJ
ap-1075	141	17	other	other	ADJ
ap-1075	141	18	optimization	optimization	NOUN
ap-1075	141	19	methods	method	NOUN
ap-1075	141	20	,	,	PUNCT
ap-1075	141	21	such	such	ADJ
ap-1075	141	22	as	as	ADP
ap-1075	141	23	ant	ant	ADJ
ap-1075	141	24	colony	colony	NOUN
ap-1075	141	25	optimization	optimization	NOUN
ap-1075	141	26	[	[	X
ap-1075	141	27	10	10	NUM
ap-1075	141	28	]	]	PUNCT
ap-1075	141	29	.	.	PUNCT
ap-1075	142	1	the	the	DET
ap-1075	142	2	fencing	fence	VERB
ap-1075	142	3	algorithm	algorithm	NOUN
ap-1075	142	4	will	will	AUX
ap-1075	142	5	be	be	AUX
ap-1075	142	6	compared	compare	VERB
ap-1075	142	7	with	with	ADP
ap-1075	142	8	these	these	DET
ap-1075	142	9	other	other	ADJ
ap-1075	142	10	approaches	approach	NOUN
ap-1075	142	11	in	in	ADP
ap-1075	142	12	terms	term	NOUN
ap-1075	142	13	of	of	ADP
ap-1075	142	14	complexity	complexity	NOUN
ap-1075	142	15	and	and	CCONJ
ap-1075	142	16	effectiveness	effectiveness	NOUN
ap-1075	142	17	on	on	ADP
ap-1075	142	18	more	more	ADJ
ap-1075	142	19	data	datum	NOUN
ap-1075	142	20	sets	set	NOUN
ap-1075	142	21	.	.	PUNCT
ap-1075	143	1	systematic	systematic	ADJ
ap-1075	143	2	examination	examination	NOUN
ap-1075	143	3	of	of	ADP
ap-1075	143	4	relevant	relevant	ADJ
ap-1075	143	5	preprocessing	preprocessing	NOUN
ap-1075	143	6	methods	method	NOUN
ap-1075	143	7	is	be	AUX
ap-1075	143	8	also	also	ADV
ap-1075	143	9	desirable	desirable	ADJ
ap-1075	143	10	.	.	PUNCT
ap-1075	144	1	finally	finally	ADV
ap-1075	144	2	,	,	PUNCT
ap-1075	144	3	the	the	DET
ap-1075	144	4	algorithm	algorithm	NOUN
ap-1075	144	5	could	could	AUX
ap-1075	144	6	be	be	AUX
ap-1075	144	7	modified	modify	VERB
ap-1075	144	8	not	not	PART
ap-1075	144	9	for	for	ADP
ap-1075	144	10	data	datum	NOUN
ap-1075	144	11	,	,	PUNCT
ap-1075	144	12	but	but	CCONJ
ap-1075	144	13	for	for	ADP
ap-1075	144	14	an	an	DET
ap-1075	144	15	estimated	estimate	VERB
ap-1075	144	16	probability	probability	NOUN
ap-1075	144	17	function	function	NOUN
ap-1075	144	18	,	,	PUNCT
ap-1075	144	19	e.g.	e.g.	ADV
ap-1075	144	20	in	in	ADP
ap-1075	144	21	form	form	NOUN
ap-1075	144	22	of	of	ADP
ap-1075	144	23	copulas	copula	NOUN
ap-1075	144	24	[	[	X
ap-1075	144	25	9	9	NUM
ap-1075	144	26	]	]	PUNCT
ap-1075	144	27	which	which	PRON
ap-1075	144	28	are	be	AUX
ap-1075	144	29	more	more	ADV
ap-1075	144	30	appropriate	appropriate	ADJ
ap-1075	144	31	for	for	ADP
ap-1075	144	32	assymetric	assymetric	ADJ
ap-1075	144	33	distributions	distribution	NOUN
ap-1075	144	34	.	.	PUNCT
ap-1075	145	1	5	5	NUM
ap-1075	145	2	conclusion	conclusion	NOUN
ap-1075	145	3	the	the	DET
ap-1075	145	4	fencing	fence	VERB
ap-1075	145	5	algorithm	algorithm	NOUN
ap-1075	145	6	is	be	AUX
ap-1075	145	7	a	a	DET
ap-1075	145	8	novel	novel	ADJ
ap-1075	145	9	heuristic	heuristic	ADJ
ap-1075	145	10	method	method	NOUN
ap-1075	145	11	for	for	ADP
ap-1075	145	12	finding	find	VERB
ap-1075	145	13	a	a	DET
ap-1075	145	14	subset	subset	NOUN
ap-1075	145	15	of	of	ADP
ap-1075	145	16	with	with	ADP
ap-1075	145	17	above	above	ADP
ap-1075	145	18	-	-	PUNCT
ap-1075	145	19	average	average	NOUN
ap-1075	145	20	production	production	NOUN
ap-1075	145	21	.	.	PUNCT
ap-1075	146	1	the	the	DET
ap-1075	146	2	main	main	ADJ
ap-1075	146	3	idea	idea	NOUN
ap-1075	146	4	of	of	ADP
ap-1075	146	5	the	the	DET
ap-1075	146	6	algorithm	algorithm	NOUN
ap-1075	146	7	is	be	AUX
ap-1075	146	8	to	to	PART
ap-1075	146	9	join	join	VERB
ap-1075	146	10	intervals	interval	NOUN
ap-1075	146	11	with	with	ADP
ap-1075	146	12	high	high	ADJ
ap-1075	146	13	production	production	NOUN
ap-1075	146	14	and	and	CCONJ
ap-1075	146	15	small	small	ADJ
ap-1075	146	16	mutual	mutual	ADJ
ap-1075	146	17	distance	distance	NOUN
ap-1075	146	18	.	.	PUNCT
ap-1075	147	1	the	the	DET
ap-1075	147	2	fencing	fence	VERB
ap-1075	147	3	algorithm	algorithm	NOUN
ap-1075	147	4	has	have	AUX
ap-1075	147	5	been	be	AUX
ap-1075	147	6	successfully	successfully	ADV
ap-1075	147	7	applied	apply	VERB
ap-1075	147	8	to	to	ADP
ap-1075	147	9	insurance	insurance	NOUN
ap-1075	147	10	data	datum	NOUN
ap-1075	147	11	.	.	PUNCT
ap-1075	148	1	further	further	ADJ
ap-1075	148	2	work	work	NOUN
ap-1075	148	3	has	have	AUX
ap-1075	148	4	been	be	AUX
ap-1075	148	5	discussed	discuss	VERB
ap-1075	148	6	above	above	ADV
ap-1075	148	7	.	.	PUNCT
ap-1075	149	1	references	reference	NOUN
ap-1075	149	2	[	[	X
ap-1075	149	3	1	1	NUM
ap-1075	149	4	]	]	PUNCT
ap-1075	149	5	akpolat	akpolat	NOUN
ap-1075	149	6	,	,	PUNCT
ap-1075	149	7	h.	h.	PROPN
ap-1075	149	8	:	:	PUNCT
ap-1075	149	9	six	six	NUM
ap-1075	149	10	sigma	sigma	NOUN
ap-1075	149	11	in	in	ADP
ap-1075	149	12	transactional	transactional	ADJ
ap-1075	149	13	and	and	CCONJ
ap-1075	149	14	service	service	NOUN
ap-1075	149	15	environments	environment	NOUN
ap-1075	149	16	.	.	PUNCT
ap-1075	149	17	.	.	PUNCT
ap-1075	150	1	gower	gower	PROPN
ap-1075	150	2	,	,	PUNCT
ap-1075	150	3	burlington	burlington	PROPN
ap-1075	150	4	,	,	PUNCT
ap-1075	150	5	vt.:,hasan	vt.:,hasan	ADJ
ap-1075	150	6	akpolat	akpolat	NOUN
ap-1075	150	7	2004	2004	NUM
ap-1075	150	8	.	.	PUNCT
ap-1075	151	1	[	[	X
ap-1075	151	2	2	2	NUM
ap-1075	151	3	]	]	PUNCT
ap-1075	151	4	andersen	andersen	PROPN
ap-1075	151	5	,	,	PUNCT
ap-1075	151	6	p.	p.	PROPN
ap-1075	151	7	,	,	PUNCT
ap-1075	151	8	petersen	petersen	PROPN
ap-1075	151	9	,	,	PUNCT
ap-1075	151	10	n.	n.	PROPN
ap-1075	151	11	c.	c.	PROPN
ap-1075	151	12	:	:	PUNCT
ap-1075	151	13	a	a	DET
ap-1075	151	14	procedure	procedure	NOUN
ap-1075	151	15	for	for	ADP
ap-1075	151	16	ranking	rank	VERB
ap-1075	151	17	efficient	efficient	ADJ
ap-1075	151	18	units	unit	NOUN
ap-1075	151	19	in	in	ADP
ap-1075	151	20	data	datum	NOUN
ap-1075	151	21	envelopment	envelopment	ADJ
ap-1075	151	22	analysis	analysis	NOUN
ap-1075	151	23	.	.	PUNCT
ap-1075	152	1	manage	manage	VERB
ap-1075	152	2	.	.	PUNCT
ap-1075	153	1	sci	sci	PROPN
ap-1075	153	2	.	.	PROPN
ap-1075	153	3	,	,	PUNCT
ap-1075	153	4	vol	vol	NOUN
ap-1075	153	5	.	.	PROPN
ap-1075	153	6	39	39	NUM
ap-1075	153	7	(	(	PUNCT
ap-1075	153	8	1993	1993	NUM
ap-1075	153	9	)	)	PUNCT
ap-1075	153	10	,	,	PUNCT
ap-1075	153	11	no	no	INTJ
ap-1075	153	12	.	.	NOUN
ap-1075	153	13	10	10	NUM
ap-1075	153	14	,	,	PUNCT
ap-1075	153	15	p.	p.	NOUN
ap-1075	153	16	1261–1264	1261–1264	NUM
ap-1075	153	17	.	.	PUNCT
ap-1075	154	1	[	[	X
ap-1075	154	2	3	3	NUM
ap-1075	154	3	]	]	X
ap-1075	154	4	dagher	dagher	NOUN
ap-1075	154	5	,	,	PUNCT
ap-1075	154	6	i.	i.	NOUN
ap-1075	154	7	:	:	PUNCT
ap-1075	154	8	l	l	NOUN
ap-1075	154	9	-	-	ADJ
ap-1075	154	10	p	p	ADJ
ap-1075	154	11	fuzzy	fuzzy	ADJ
ap-1075	154	12	artmap	artmap	NOUN
ap-1075	154	13	neural	neural	ADJ
ap-1075	154	14	network	network	NOUN
ap-1075	154	15	architecture	architecture	NOUN
ap-1075	154	16	.	.	PUNCT
ap-1075	155	1	soft	soft	ADJ
ap-1075	155	2	comput	comput	NOUN
ap-1075	155	3	.	.	PUNCT
ap-1075	156	1	,	,	PUNCT
ap-1075	156	2	vol	vol	NOUN
ap-1075	156	3	.	.	PROPN
ap-1075	157	1	10	10	NUM
ap-1075	157	2	(	(	PUNCT
ap-1075	157	3	2006	2006	NUM
ap-1075	157	4	)	)	PUNCT
ap-1075	157	5	,	,	PUNCT
ap-1075	157	6	no	no	INTJ
ap-1075	157	7	.	.	NOUN
ap-1075	157	8	8	8	NUM
ap-1075	157	9	,	,	PUNCT
ap-1075	157	10	p.	p.	NOUN
ap-1075	157	11	649–656	649–656	NUM
ap-1075	157	12	.	.	PUNCT
ap-1075	158	1	[	[	X
ap-1075	158	2	4	4	NUM
ap-1075	158	3	]	]	X
ap-1075	158	4	de	de	X
ap-1075	158	5	jong	jong	PROPN
ap-1075	158	6	,	,	PUNCT
ap-1075	158	7	p.	p.	PROPN
ap-1075	158	8	,	,	PUNCT
ap-1075	158	9	heller	heller	NOUN
ap-1075	158	10	,	,	PUNCT
ap-1075	158	11	g.	g.	PROPN
ap-1075	158	12	z.	z.	PROPN
ap-1075	158	13	:	:	PUNCT
ap-1075	158	14	generalized	generalize	VERB
ap-1075	158	15	linear	linear	NOUN
ap-1075	158	16	models	model	NOUN
ap-1075	158	17	for	for	ADP
ap-1075	158	18	insurance	insurance	NOUN
ap-1075	158	19	data	datum	NOUN
ap-1075	158	20	.	.	PUNCT
ap-1075	159	1	cambridge	cambridge	PROPN
ap-1075	159	2	press	press	PROPN
ap-1075	159	3	,	,	PUNCT
ap-1075	159	4	2008	2008	NUM
ap-1075	159	5	.	.	PUNCT
ap-1075	160	1	58	58	NUM
ap-1075	161	1	©	©	PROPN
ap-1075	161	2	czech	czech	PROPN
ap-1075	161	3	technical	technical	PROPN
ap-1075	161	4	university	university	PROPN
ap-1075	161	5	publishing	publishing	NOUN
ap-1075	161	6	house	house	NOUN
ap-1075	161	7	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1075	161	8	acta	acta	PROPN
ap-1075	161	9	polytechnica	polytechnica	PROPN
ap-1075	161	10	vol	vol	NOUN
ap-1075	161	11	.	.	PUNCT
ap-1075	162	1	48	48	NUM
ap-1075	162	2	no	no	NOUN
ap-1075	162	3	.	.	PUNCT
ap-1075	163	1	6/2008	6/2008	NOUN
ap-1075	163	2	validation	validation	NOUN
ap-1075	163	3	sets	set	VERB
ap-1075	163	4	#	#	NOUN
ap-1075	163	5	1	1	NUM
ap-1075	163	6	2	2	NUM
ap-1075	163	7	3	3	NUM
ap-1075	163	8	4	4	NUM
ap-1075	163	9	5	5	NUM
ap-1075	163	10	6	6	NUM
ap-1075	163	11	7	7	NUM
ap-1075	163	12	8	8	NUM
ap-1075	163	13	9	9	NUM
ap-1075	163	14	10	10	NUM
ap-1075	163	15	glm	glm	PROPN
ap-1075	163	16	3.43	3.43	NUM
ap-1075	163	17	3.37	3.37	NUM
ap-1075	163	18	3.27	3.27	NUM
ap-1075	163	19	3.33	3.33	NUM
ap-1075	163	20	3.30	3.30	NUM
ap-1075	163	21	3.22	3.22	NUM
ap-1075	163	22	3.35	3.35	NUM
ap-1075	163	23	3.27	3.27	NUM
ap-1075	163	24	3.43	3.43	NUM
ap-1075	163	25	3.41	3.41	NUM
ap-1075	163	26	mlp	mlp	NOUN
ap-1075	163	27	3.35	3.35	NUM
ap-1075	163	28	3.29	3.29	NUM
ap-1075	163	29	3.24	3.24	NUM
ap-1075	163	30	3.30	3.30	NUM
ap-1075	163	31	3.23	3.23	NUM
ap-1075	163	32	3.10	3.10	NUM
ap-1075	163	33	3.27	3.27	NUM
ap-1075	163	34	3.28	3.28	NUM
ap-1075	163	35	3.44	3.44	NUM
ap-1075	163	36	3.34	3.34	NUM
ap-1075	163	37	table	table	NOUN
ap-1075	163	38	2	2	NUM
ap-1075	163	39	:	:	PUNCT
ap-1075	163	40	mean	mean	VERB
ap-1075	163	41	absolute	absolute	ADJ
ap-1075	163	42	error	error	NOUN
ap-1075	163	43	of	of	ADP
ap-1075	163	44	machine	machine	NOUN
ap-1075	163	45	learning	learn	VERB
ap-1075	163	46	for	for	ADP
ap-1075	163	47	different	different	ADJ
ap-1075	163	48	validation	validation	NOUN
ap-1075	163	49	sets	set	NOUN
ap-1075	163	50	method	method	NOUN
ap-1075	163	51	r	r	NOUN
ap-1075	163	52	(	(	PUNCT
ap-1075	163	53	fixed	fix	VERB
ap-1075	163	54	)	)	PUNCT
ap-1075	163	55	p	p	NOUN
ap-1075	163	56	means	mean	VERB
ap-1075	163	57	based	base	VERB
ap-1075	163	58	approach	approach	NOUN
ap-1075	163	59	(	(	PUNCT
ap-1075	163	60	6	6	NUM
ap-1075	163	61	means	mean	NOUN
ap-1075	163	62	)	)	PUNCT
ap-1075	163	63	0.32	0.32	NUM
ap-1075	163	64	0.96	0.96	NUM
ap-1075	163	65	means	mean	NOUN
ap-1075	163	66	based	base	VERB
ap-1075	163	67	approach	approach	NOUN
ap-1075	163	68	(	(	PUNCT
ap-1075	163	69	20	20	NUM
ap-1075	163	70	means	mean	NOUN
ap-1075	163	71	)	)	PUNCT
ap-1075	163	72	0.32	0.32	NUM
ap-1075	163	73	0.94	0.94	NUM
ap-1075	163	74	fencing	fence	VERB
ap-1075	163	75	algorithm	algorithm	NOUN
ap-1075	163	76	(	(	PUNCT
ap-1075	163	77	raw	raw	ADJ
ap-1075	163	78	results	result	NOUN
ap-1075	163	79	)	)	PUNCT
ap-1075	163	80	0.48	0.48	NUM
ap-1075	163	81	1.19	1.19	NUM
ap-1075	163	82	fencing	fence	VERB
ap-1075	163	83	algorithm	algorithm	NOUN
ap-1075	163	84	(	(	PUNCT
ap-1075	163	85	results	result	NOUN
ap-1075	163	86	after	after	ADP
ap-1075	163	87	best	good	ADJ
ap-1075	163	88	interval	interval	NOUN
ap-1075	163	89	selection	selection	NOUN
ap-1075	163	90	)	)	PUNCT
ap-1075	163	91	0.32	0.32	NUM
ap-1075	163	92	1.48	1.48	NUM
ap-1075	163	93	table	table	NOUN
ap-1075	163	94	3	3	NUM
ap-1075	163	95	:	:	PUNCT
ap-1075	163	96	comparison	comparison	NOUN
ap-1075	163	97	of	of	ADP
ap-1075	163	98	the	the	DET
ap-1075	163	99	fencing	fence	VERB
ap-1075	163	100	algorithm	algorithm	NOUN
ap-1075	163	101	with	with	ADP
ap-1075	163	102	the	the	DET
ap-1075	163	103	k	k	NOUN
ap-1075	163	104	-	-	PUNCT
ap-1075	163	105	means	mean	NOUN
ap-1075	163	106	based	base	VERB
ap-1075	163	107	approach	approach	NOUN
ap-1075	163	108	[	[	X
ap-1075	163	109	5	5	NUM
ap-1075	163	110	]	]	X
ap-1075	163	111	jia	jia	PROPN
ap-1075	163	112	,	,	PUNCT
ap-1075	163	113	z.	z.	PROPN
ap-1075	163	114	,	,	PUNCT
ap-1075	163	115	gong	gong	PROPN
ap-1075	163	116	,	,	PUNCT
ap-1075	163	117	l.	l.	PROPN
ap-1075	163	118	:	:	PUNCT
ap-1075	163	119	the	the	DET
ap-1075	163	120	project	project	NOUN
ap-1075	163	121	risk	risk	NOUN
ap-1075	163	122	assessment	assessment	NOUN
ap-1075	163	123	based	base	VERB
ap-1075	163	124	on	on	ADP
ap-1075	163	125	rough	rough	ADJ
ap-1075	163	126	sets	set	NOUN
ap-1075	163	127	and	and	CCONJ
ap-1075	163	128	neural	neural	ADJ
ap-1075	163	129	network	network	NOUN
ap-1075	163	130	(	(	PUNCT
ap-1075	163	131	rs	rs	PROPN
ap-1075	163	132	-	-	PUNCT
ap-1075	163	133	rbf	rbf	PROPN
ap-1075	163	134	)	)	PUNCT
ap-1075	163	135	.	.	PUNCT
ap-1075	164	1	in	in	ADP
ap-1075	164	2	networking	networking	NOUN
ap-1075	164	3	and	and	CCONJ
ap-1075	164	4	mobile	mobile	NOUN
ap-1075	164	5	computing	computing	NOUN
ap-1075	164	6	,	,	PUNCT
ap-1075	164	7	2008	2008	NUM
ap-1075	164	8	.	.	PUNCT
ap-1075	165	1	wicom	wicom	PROPN
ap-1075	165	2	’	'	PUNCT
ap-1075	165	3	08	08	NUM
ap-1075	165	4	.	.	PUNCT
ap-1075	166	1	4th	4th	ADJ
ap-1075	166	2	international	international	ADJ
ap-1075	166	3	conference	conference	NOUN
ap-1075	166	4	on	on	ADP
ap-1075	166	5	wireless	wireless	ADJ
ap-1075	166	6	communications	communication	NOUN
ap-1075	166	7	,	,	PUNCT
ap-1075	166	8	2008	2008	NUM
ap-1075	166	9	.	.	PUNCT
ap-1075	167	1	[	[	X
ap-1075	167	2	6	6	NUM
ap-1075	167	3	]	]	X
ap-1075	167	4	kreinovich	kreinovich	X
ap-1075	167	5	,	,	PUNCT
ap-1075	167	6	v.	v.	ADP
ap-1075	167	7	,	,	PUNCT
ap-1075	167	8	yam	yam	NOUN
ap-1075	167	9	,	,	PUNCT
ap-1075	167	10	y.	y.	NOUN
ap-1075	167	11	:	:	PUNCT
ap-1075	167	12	why	why	SCONJ
ap-1075	167	13	clustering	cluster	VERB
ap-1075	167	14	in	in	ADP
ap-1075	167	15	function	function	NOUN
ap-1075	167	16	approximation	approximation	NOUN
ap-1075	167	17	?	?	PUNCT
ap-1075	168	1	theoretical	theoretical	ADJ
ap-1075	168	2	explanation	explanation	NOUN
ap-1075	168	3	,	,	PUNCT
ap-1075	168	4	2001	2001	NUM
ap-1075	168	5	.	.	PUNCT
ap-1075	169	1	[	[	X
ap-1075	169	2	7	7	NUM
ap-1075	169	3	]	]	X
ap-1075	169	4	lorenz	lorenz	PROPN
ap-1075	169	5	,	,	PUNCT
ap-1075	169	6	m.	m.	NOUN
ap-1075	169	7	o.	o.	PROPN
ap-1075	169	8	:	:	PUNCT
ap-1075	169	9	methods	method	NOUN
ap-1075	169	10	of	of	ADP
ap-1075	169	11	measuring	measure	VERB
ap-1075	169	12	concentration	concentration	NOUN
ap-1075	169	13	and	and	CCONJ
ap-1075	169	14	wealth	wealth	NOUN
ap-1075	169	15	.	.	PUNCT
ap-1075	170	1	journal	journal	NOUN
ap-1075	170	2	of	of	ADP
ap-1075	170	3	the	the	DET
ap-1075	170	4	american	american	PROPN
ap-1075	170	5	statistical	statistical	PROPN
ap-1075	170	6	association	association	PROPN
ap-1075	170	7	,	,	PUNCT
ap-1075	170	8	vol	vol	NOUN
ap-1075	170	9	.	.	PROPN
ap-1075	170	10	9	9	NUM
ap-1075	170	11	(	(	PUNCT
ap-1075	170	12	1905	1905	NUM
ap-1075	170	13	)	)	PUNCT
ap-1075	170	14	,	,	PUNCT
ap-1075	171	1	p.	p.	NOUN
ap-1075	171	2	209–219	209–219	NUM
ap-1075	171	3	.	.	PUNCT
ap-1075	172	1	[	[	X
ap-1075	172	2	8	8	NUM
ap-1075	172	3	]	]	X
ap-1075	172	4	mitchell	mitchell	NOUN
ap-1075	172	5	,	,	PUNCT
ap-1075	172	6	t.	t.	PROPN
ap-1075	172	7	m.	m.	NOUN
ap-1075	172	8	:	:	PUNCT
ap-1075	172	9	machine	machine	NOUN
ap-1075	172	10	learning	learning	NOUN
ap-1075	172	11	.	.	PUNCT
ap-1075	173	1	mcgraw	mcgraw	PROPN
ap-1075	173	2	-	-	PUNCT
ap-1075	173	3	hill	hill	PROPN
ap-1075	173	4	science/	science/	NUM
ap-1075	173	5	engineering	engineering	NOUN
ap-1075	173	6	/	/	SYM
ap-1075	173	7	math	math	NOUN
ap-1075	173	8	,	,	PUNCT
ap-1075	173	9	march	march	PROPN
ap-1075	173	10	1997	1997	NUM
ap-1075	173	11	.	.	PUNCT
ap-1075	174	1	[	[	X
ap-1075	174	2	9	9	NUM
ap-1075	174	3	]	]	X
ap-1075	174	4	nelsen	nelsen	PROPN
ap-1075	174	5	,	,	PUNCT
ap-1075	174	6	r.	r.	PROPN
ap-1075	174	7	b.	b.	PROPN
ap-1075	174	8	:	:	PUNCT
ap-1075	174	9	an	an	DET
ap-1075	174	10	introduction	introduction	NOUN
ap-1075	174	11	to	to	ADP
ap-1075	174	12	copulas	copula	NOUN
ap-1075	174	13	,	,	PUNCT
ap-1075	174	14	volume	volume	NOUN
ap-1075	174	15	139	139	NUM
ap-1075	174	16	of	of	ADP
ap-1075	174	17	lecture	lecture	NOUN
ap-1075	174	18	notes	note	NOUN
ap-1075	174	19	in	in	ADP
ap-1075	174	20	statistics	statistic	NOUN
ap-1075	174	21	.	.	PUNCT
ap-1075	175	1	new	new	PROPN
ap-1075	175	2	york	york	PROPN
ap-1075	175	3	:	:	PUNCT
ap-1075	175	4	springer	springer	NOUN
ap-1075	175	5	-	-	PUNCT
ap-1075	175	6	verlag	verlag	PROPN
ap-1075	175	7	,	,	PUNCT
ap-1075	175	8	1999	1999	NUM
ap-1075	175	9	.	.	PUNCT
ap-1075	176	1	[	[	X
ap-1075	176	2	10	10	NUM
ap-1075	176	3	]	]	X
ap-1075	176	4	ramos	ramos	PROPN
ap-1075	176	5	,	,	PUNCT
ap-1075	176	6	g.	g.	PROPN
ap-1075	176	7	n.	n.	PROPN
ap-1075	176	8	,	,	PUNCT
ap-1075	176	9	hatakeyama	hatakeyama	PROPN
ap-1075	176	10	,	,	PUNCT
ap-1075	176	11	y.	y.	PROPN
ap-1075	176	12	,	,	PUNCT
ap-1075	176	13	dong	dong	PROPN
ap-1075	176	14	,	,	PUNCT
ap-1075	176	15	f.	f.	PROPN
ap-1075	176	16	,	,	PUNCT
ap-1075	176	17	hirota	hirota	PROPN
ap-1075	176	18	,	,	PUNCT
ap-1075	176	19	k.	k.	PROPN
ap-1075	176	20	:	:	PUNCT
ap-1075	176	21	hyperbox	hyperbox	NOUN
ap-1075	176	22	clustering	cluster	VERB
ap-1075	176	23	with	with	ADP
ap-1075	176	24	ant	ant	ADJ
ap-1075	176	25	colony	colony	NOUN
ap-1075	176	26	optimization	optimization	NOUN
ap-1075	176	27	(	(	PUNCT
ap-1075	176	28	haco	haco	NOUN
ap-1075	176	29	)	)	PUNCT
ap-1075	176	30	method	method	NOUN
ap-1075	176	31	and	and	CCONJ
ap-1075	176	32	its	its	PRON
ap-1075	176	33	application	application	NOUN
ap-1075	176	34	to	to	ADP
ap-1075	176	35	medical	medical	ADJ
ap-1075	176	36	risk	risk	NOUN
ap-1075	176	37	profile	profile	NOUN
ap-1075	176	38	recognition	recognition	NOUN
ap-1075	176	39	.	.	PUNCT
ap-1075	177	1	appl	appl	PROPN
ap-1075	177	2	.	.	PUNCT
ap-1075	177	3	soft	soft	ADJ
ap-1075	177	4	comput	comput	NOUN
ap-1075	177	5	.	.	PUNCT
ap-1075	177	6	,	,	PUNCT
ap-1075	177	7	vol	vol	NOUN
ap-1075	177	8	.	.	PROPN
ap-1075	177	9	9	9	NUM
ap-1075	177	10	(	(	PUNCT
ap-1075	177	11	2009	2009	NUM
ap-1075	177	12	)	)	PUNCT
ap-1075	177	13	,	,	PUNCT
ap-1075	177	14	no	no	INTJ
ap-1075	177	15	.	.	NOUN
ap-1075	177	16	2	2	NUM
ap-1075	177	17	,	,	PUNCT
ap-1075	177	18	p.	p.	NOUN
ap-1075	177	19	632–640	632–640	NUM
ap-1075	177	20	.	.	PUNCT
ap-1075	178	1	[	[	X
ap-1075	178	2	11	11	NUM
ap-1075	178	3	]	]	PUNCT
ap-1075	178	4	theodoridis	theodoridis	PROPN
ap-1075	178	5	,	,	PUNCT
ap-1075	178	6	s.	s.	PROPN
ap-1075	178	7	,	,	PUNCT
ap-1075	178	8	koutroumbas	koutroumbas	PROPN
ap-1075	178	9	,	,	PUNCT
ap-1075	178	10	k.	k.	PROPN
ap-1075	178	11	:	:	PUNCT
ap-1075	178	12	pattern	pattern	NOUN
ap-1075	178	13	recognition	recognition	NOUN
ap-1075	178	14	,	,	PUNCT
ap-1075	178	15	third	third	ADJ
ap-1075	178	16	edition	edition	NOUN
ap-1075	178	17	.	.	PUNCT
ap-1075	179	1	academic	academic	ADJ
ap-1075	179	2	press	press	NOUN
ap-1075	179	3	,	,	PUNCT
ap-1075	179	4	february	february	PROPN
ap-1075	179	5	2006	2006	NUM
ap-1075	179	6	.	.	PUNCT
ap-1075	180	1	[	[	X
ap-1075	180	2	12	12	NUM
ap-1075	180	3	]	]	X
ap-1075	180	4	xu	xu	PROPN
ap-1075	180	5	,	,	PUNCT
ap-1075	180	6	r.	r.	PROPN
ap-1075	180	7	,	,	PUNCT
ap-1075	180	8	wunsch	wunsch	PROPN
ap-1075	180	9	,	,	PUNCT
ap-1075	180	10	d.	d.	PROPN
ap-1075	180	11	:	:	PUNCT
ap-1075	180	12	clustering	cluster	VERB
ap-1075	180	13	.	.	PUNCT
ap-1075	181	1	ieee	ieee	NOUN
ap-1075	181	2	press	press	PROPN
ap-1075	181	3	series	series	NOUN
ap-1075	181	4	on	on	ADP
ap-1075	181	5	computational	computational	ADJ
ap-1075	181	6	intelligence	intelligence	NOUN
ap-1075	181	7	.	.	PUNCT
ap-1075	182	1	john	john	PROPN
ap-1075	182	2	wiley	wiley	PROPN
ap-1075	182	3	&	&	CCONJ
ap-1075	182	4	sons	son	NOUN
ap-1075	182	5	,	,	PUNCT
ap-1075	182	6	2009	2009	NUM
ap-1075	182	7	.	.	PUNCT
ap-1075	183	1	mgr	mgr	PROPN
ap-1075	183	2	.	.	PUNCT
ap-1075	184	1	karel	karel	PROPN
ap-1075	184	2	macek	macek	PROPN
ap-1075	185	1	e	e	NOUN
ap-1075	185	2	-	-	NOUN
ap-1075	185	3	mail	mail	NOUN
ap-1075	185	4	:	:	PUNCT
ap-1075	185	5	karel.macek@fjfi.cvut.cz	karel.macek@fjfi.cvut.cz	PROPN
ap-1075	185	6	department	department	PROPN
ap-1075	185	7	of	of	ADP
ap-1075	185	8	mathematics	mathematics	PROPN
ap-1075	185	9	czech	czech	PROPN
ap-1075	185	10	technical	technical	PROPN
ap-1075	185	11	university	university	PROPN
ap-1075	185	12	in	in	ADP
ap-1075	185	13	prague	prague	PROPN
ap-1075	185	14	faculty	faculty	NOUN
ap-1075	185	15	of	of	ADP
ap-1075	185	16	nuclear	nuclear	ADJ
ap-1075	185	17	sciences	science	NOUN
ap-1075	185	18	and	and	CCONJ
ap-1075	185	19	physical	physical	ADJ
ap-1075	185	20	engineering	engineering	NOUN
ap-1075	185	21	trojanova	trojanova	ADP
ap-1075	185	22	13	13	NUM
ap-1075	185	23	120	120	NUM
ap-1075	185	24	00	00	NUM
ap-1075	185	25	praha2	praha2	NOUN
ap-1075	185	26	,	,	PUNCT
ap-1075	185	27	czech	czech	PROPN
ap-1075	185	28	republic	republic	NOUN
ap-1075	185	29	©	©	PROPN
ap-1075	185	30	czech	czech	PROPN
ap-1075	185	31	technical	technical	PROPN
ap-1075	185	32	university	university	PROPN
ap-1075	185	33	publishing	publishing	NOUN
ap-1075	185	34	house	house	NOUN
ap-1075	185	35	http://ctn.cvut.cz/ap/	http://ctn.cvut.cz/ap/	PROPN
ap-1075	185	36	59	59	NUM
ap-1075	185	37	acta	acta	PROPN
ap-1075	185	38	polytechnica	polytechnica	PROPN
ap-1075	185	39	vol	vol	NOUN
ap-1075	185	40	.	.	PUNCT
ap-1075	186	1	48	48	NUM
ap-1075	186	2	no	no	NOUN
ap-1075	186	3	.	.	PUNCT
ap-1075	187	1	6/2008	6/2008	NOUN
ap-1075	187	2	table	table	NOUN
ap-1075	187	3	of	of	ADP
ap-1075	187	4	contents	content	NOUN
ap-1075	187	5	an	an	DET
ap-1075	187	6	intelligent	intelligent	ADJ
ap-1075	187	7	system	system	NOUN
ap-1075	187	8	for	for	ADP
ap-1075	187	9	structural	structural	ADJ
ap-1075	187	10	analysis	analysis	NOUN
ap-1075	187	11	-	-	PUNCT
ap-1075	187	12	based	base	VERB
ap-1075	187	13	design	design	NOUN
ap-1075	187	14	improvements	improvement	NOUN
ap-1075	187	15	3	3	NUM
ap-1075	187	16	m.	m.	NOUN
ap-1075	187	17	novak	novak	PROPN
ap-1075	187	18	,	,	PUNCT
ap-1075	187	19	b.	b.	PROPN
ap-1075	187	20	dolšak	dolšak	VERB
ap-1075	187	21	the	the	DET
ap-1075	187	22	amount	amount	NOUN
ap-1075	187	23	of	of	ADP
ap-1075	187	24	regenerated	regenerated	ADJ
ap-1075	187	25	heat	heat	NOUN
ap-1075	187	26	inside	inside	ADP
ap-1075	187	27	the	the	DET
ap-1075	187	28	regenerator	regenerator	NOUN
ap-1075	187	29	of	of	ADP
ap-1075	187	30	a	a	DET
ap-1075	187	31	stirling	stirling	NOUN
ap-1075	187	32	engine	engine	NOUN
ap-1075	187	33	10	10	NUM
ap-1075	187	34	j.	j.	PROPN
ap-1075	187	35	škorpík	škorpík	PROPN
ap-1075	187	36	prerequisites	prerequisite	NOUN
ap-1075	187	37	for	for	ADP
ap-1075	187	38	increasing	increase	VERB
ap-1075	187	39	the	the	DET
ap-1075	187	40	axle	axle	NOUN
ap-1075	187	41	load	load	NOUN
ap-1075	187	42	on	on	ADP
ap-1075	187	43	railway	railway	NOUN
ap-1075	187	44	tracks	track	NOUN
ap-1075	187	45	in	in	ADP
ap-1075	187	46	the	the	DET
ap-1075	187	47	czech	czech	PROPN
ap-1075	187	48	republic	republic	PROPN
ap-1075	187	49	15	15	NUM
ap-1075	187	50	m.	m.	NOUN
ap-1075	187	51	lidmila	lidmila	PROPN
ap-1075	187	52	,	,	PUNCT
ap-1075	187	53	l.	l.	PROPN
ap-1075	187	54	horníèek	horníèek	PROPN
ap-1075	187	55	,	,	PUNCT
ap-1075	187	56	h.	h.	PROPN
ap-1075	187	57	krejèiøíková	krejèiøíková	PROPN
ap-1075	187	58	,	,	PUNCT
ap-1075	187	59	p.	p.	NOUN
ap-1075	187	60	tyc	tyc	PROPN
ap-1075	188	1	simple	simple	ADJ
ap-1075	188	2	numerical	numerical	ADJ
ap-1075	188	3	model	model	NOUN
ap-1075	188	4	of	of	ADP
ap-1075	188	5	laminated	laminate	VERB
ap-1075	188	6	glass	glass	NOUN
ap-1075	188	7	beams	beam	NOUN
ap-1075	188	8	22	22	NUM
ap-1075	188	9	a.	a.	NOUN
ap-1075	188	10	zemanová	zemanová	PROPN
ap-1075	188	11	,	,	PUNCT
ap-1075	188	12	j.	j.	PROPN
ap-1075	188	13	zeman	zeman	PROPN
ap-1075	188	14	,	,	PUNCT
ap-1075	188	15	m.	m.	NOUN
ap-1075	188	16	šejnoha	šejnoha	PROPN
ap-1075	188	17	influence	influence	NOUN
ap-1075	188	18	of	of	ADP
ap-1075	188	19	simulated	simulated	ADJ
ap-1075	188	20	loca	loca	NOUN
ap-1075	188	21	on	on	ADP
ap-1075	188	22	the	the	DET
ap-1075	188	23	properties	property	NOUN
ap-1075	188	24	of	of	ADP
ap-1075	188	25	zircaloy	zircaloy	PROPN
ap-1075	188	26	oxide	oxide	NOUN
ap-1075	188	27	layers	layer	NOUN
ap-1075	188	28	27	27	NUM
ap-1075	188	29	h.	h.	PROPN
ap-1075	188	30	frank	frank	PROPN
ap-1075	188	31	evaluation	evaluation	NOUN
ap-1075	188	32	of	of	ADP
ap-1075	188	33	methods	method	NOUN
ap-1075	188	34	used	use	VERB
ap-1075	188	35	for	for	ADP
ap-1075	188	36	separation	separation	NOUN
ap-1075	188	37	of	of	ADP
ap-1075	188	38	vibrations	vibration	NOUN
ap-1075	188	39	produced	produce	VERB
ap-1075	188	40	by	by	ADP
ap-1075	188	41	gear	gear	NOUN
ap-1075	188	42	transmissions	transmission	NOUN
ap-1075	188	43	31	31	NUM
ap-1075	188	44	a.	a.	NOUN
ap-1075	188	45	doèekal	doèekal	NOUN
ap-1075	188	46	,	,	PUNCT
ap-1075	188	47	m.	m.	NOUN
ap-1075	188	48	kreidl	kreidl	PROPN
ap-1075	188	49	,	,	PUNCT
ap-1075	188	50	r.	r.	PROPN
ap-1075	188	51	šmíd	šmíd	PROPN
ap-1075	188	52	rock	rock	PROPN
ap-1075	188	53	burst	burst	PROPN
ap-1075	188	54	mechanics	mechanic	NOUN
ap-1075	188	55	:	:	PUNCT
ap-1075	188	56	insight	insight	NOUN
ap-1075	188	57	from	from	ADP
ap-1075	188	58	physical	physical	ADJ
ap-1075	188	59	and	and	CCONJ
ap-1075	188	60	mathematical	mathematical	ADJ
ap-1075	188	61	modelling	model	VERB
ap-1075	188	62	38	38	NUM
ap-1075	188	63	j.	j.	PROPN
ap-1075	188	64	vacek	vacek	PROPN
ap-1075	188	65	,	,	PUNCT
ap-1075	188	66	j.	j.	PROPN
ap-1075	188	67	vacek	vacek	PROPN
ap-1075	188	68	,	,	PUNCT
ap-1075	188	69	j.	j.	PROPN
ap-1075	188	70	chocholoušová	chocholoušová	PROPN
ap-1075	188	71	properties	property	NOUN
ap-1075	188	72	of	of	ADP
ap-1075	188	73	starch	starch	NOUN
ap-1075	188	74	based	base	VERB
ap-1075	188	75	foams	foam	NOUN
ap-1075	188	76	made	make	VERB
ap-1075	188	77	by	by	ADP
ap-1075	188	78	thermal	thermal	ADJ
ap-1075	188	79	pressure	pressure	NOUN
ap-1075	188	80	forming	form	VERB
ap-1075	188	81	45	45	NUM
ap-1075	188	82	j.	j.	PROPN
ap-1075	188	83	štancl	štancl	PROPN
ap-1075	188	84	,	,	PUNCT
ap-1075	188	85	j.	j.	PROPN
ap-1075	188	86	skoèilas	skoèilas	PROPN
ap-1075	188	87	,	,	PUNCT
ap-1075	188	88	j.	j.	PROPN
ap-1075	188	89	šesták	šesták	PROPN
ap-1075	188	90	,	,	PUNCT
ap-1075	188	91	r.	r.	PROPN
ap-1075	188	92	žitný	žitný	PROPN
ap-1075	189	1	the	the	DET
ap-1075	189	2	pareto	pareto	ADJ
ap-1075	189	3	principle	principle	NOUN
ap-1075	189	4	in	in	ADP
ap-1075	189	5	datamining	datamine	VERB
ap-1075	189	6	:	:	PUNCT
ap-1075	189	7	an	an	DET
ap-1075	189	8	above	above	ADJ
ap-1075	189	9	-	-	PUNCT
ap-1075	189	10	average	average	ADJ
ap-1075	189	11	fencing	fencing	NOUN
ap-1075	189	12	algorithm	algorithm	NOUN
ap-1075	189	13	55	55	NUM
ap-1075	189	14	k.	k.	PROPN
ap-1075	189	15	macek	macek	PROPN