id	sid	tid	token	lemma	pos
cet-3928	1	1	chemical	chemical	NOUN
cet-3928	1	2	engineering	engineering	NOUN
cet-3928	1	3	transactions	transaction	NOUN
cet-3928	1	4	vol	vol	NOUN
cet-3928	1	5	.	.	PROPN
cet-3928	2	1	51	51	NUM
cet-3928	2	2	,	,	PUNCT
cet-3928	2	3	2016	2016	NUM
cet-3928	2	4	a	a	DET
cet-3928	2	5	publication	publication	NOUN
cet-3928	2	6	of	of	ADP
cet-3928	2	7	the	the	DET
cet-3928	2	8	italian	italian	ADJ
cet-3928	2	9	association	association	NOUN
cet-3928	2	10	of	of	ADP
cet-3928	2	11	chemical	chemical	PROPN
cet-3928	2	12	engineering	engineering	NOUN
cet-3928	2	13	online	online	ADV
cet-3928	2	14	at	at	ADP
cet-3928	2	15	www.aidic.it/cet	www.aidic.it/cet	PROPN
cet-3928	2	16	guest	guest	NOUN
cet-3928	2	17	editors	editor	NOUN
cet-3928	2	18	:	:	PUNCT
cet-3928	2	19	tichun	tichun	PROPN
cet-3928	2	20	wang	wang	PROPN
cet-3928	2	21	,	,	PUNCT
cet-3928	2	22	hongyang	hongyang	PROPN
cet-3928	2	23	zhang	zhang	PROPN
cet-3928	2	24	,	,	PUNCT
cet-3928	2	25	lei	lei	PROPN
cet-3928	2	26	tian	tian	ADJ
cet-3928	2	27	copyright	copyright	NOUN
cet-3928	2	28	©	©	PROPN
cet-3928	2	29	2016	2016	NUM
cet-3928	2	30	,	,	PUNCT
cet-3928	2	31	aidic	aidic	ADJ
cet-3928	2	32	servizi	servizi	PROPN
cet-3928	2	33	s.r.l	s.r.l	NOUN
cet-3928	2	34	.	.	PUNCT
cet-3928	2	35	,	,	PUNCT
cet-3928	2	36	isbn	isbn	PROPN
cet-3928	2	37	978	978	NUM
cet-3928	2	38	-	-	SYM
cet-3928	2	39	88	88	NUM
cet-3928	2	40	-	-	PUNCT
cet-3928	2	41	95608	95608	NUM
cet-3928	2	42	-	-	PUNCT
cet-3928	2	43	43	43	NUM
cet-3928	2	44	-	-	SYM
cet-3928	2	45	3	3	NUM
cet-3928	2	46	;	;	PUNCT
cet-3928	2	47	issn	issn	PROPN
cet-3928	2	48	2283	2283	NUM
cet-3928	2	49	-	-	SYM
cet-3928	2	50	9216	9216	NUM
cet-3928	2	51	the	the	DET
cet-3928	2	52	multi	multi	ADJ
cet-3928	2	53	-	-	ADJ
cet-3928	2	54	dimensional	dimensional	ADJ
cet-3928	2	55	customer	customer	NOUN
cet-3928	2	56	behavior	behavior	NOUN
cet-3928	2	57	analysis	analysis	NOUN
cet-3928	2	58	based	base	VERB
cet-3928	2	59	on	on	ADP
cet-3928	2	60	biayes	biayes	PRON
cet-3928	2	61	and	and	CCONJ
cet-3928	2	62	fisher	fisher	PROPN
cet-3928	2	63	classification	classification	NOUN
cet-3928	2	64	algorithm	algorithm	NOUN
cet-3928	2	65	guanghui	guanghui	PROPN
cet-3928	2	66	wang*a	wang*a	PROPN
cet-3928	2	67	,	,	PUNCT
cet-3928	2	68	fengliang	fengliang	PROPN
cet-3928	2	69	jiaob	jiaob	PROPN
cet-3928	2	70	a	a	DET
cet-3928	2	71	heilongjiang	heilongjiang	PROPN
cet-3928	2	72	university	university	PROPN
cet-3928	2	73	of	of	ADP
cet-3928	2	74	science	science	NOUN
cet-3928	2	75	and	and	CCONJ
cet-3928	2	76	technology	technology	NOUN
cet-3928	2	77	,	,	PUNCT
cet-3928	2	78	computer	computer	NOUN
cet-3928	2	79	and	and	CCONJ
cet-3928	2	80	information	information	NOUN
cet-3928	2	81	engineering	engineering	PROPN
cet-3928	2	82	college	college	PROPN
cet-3928	2	83	,	,	PUNCT
cet-3928	2	84	harbin	harbin	PROPN
cet-3928	2	85	150022	150022	NUM
cet-3928	2	86	,	,	PUNCT
cet-3928	2	87	china	china	PROPN
cet-3928	2	88	;	;	PUNCT
cet-3928	2	89	b	b	X
cet-3928	2	90	information	information	NOUN
cet-3928	2	91	engineering	engineering	PROPN
cet-3928	2	92	department	department	PROPN
cet-3928	2	93	of	of	ADP
cet-3928	2	94	weifang	weifang	PROPN
cet-3928	2	95	business	business	PROPN
cet-3928	2	96	vocational	vocational	PROPN
cet-3928	2	97	college	college	PROPN
cet-3928	2	98	,	,	PUNCT
cet-3928	2	99	shandong	shandong	PROPN
cet-3928	2	100	province	province	PROPN
cet-3928	2	101	,	,	PUNCT
cet-3928	2	102	zhucheng	zhucheng	PROPN
cet-3928	2	103	262234	262234	NUM
cet-3928	2	104	,	,	PUNCT
cet-3928	2	105	china	china	PROPN
cet-3928	2	106	.	.	PUNCT
cet-3928	3	1	guanghuiwang8668@163.com	guanghuiwang8668@163.com	X
cet-3928	4	1	the	the	DET
cet-3928	4	2	biayes	biayes	ADV
cet-3928	4	3	classification	classification	NOUN
cet-3928	4	4	algorithm	algorithm	NOUN
cet-3928	4	5	was	be	AUX
cet-3928	4	6	based	base	VERB
cet-3928	4	7	on	on	ADP
cet-3928	4	8	the	the	DET
cet-3928	4	9	mutual	mutual	ADJ
cet-3928	4	10	independence	independence	NOUN
cet-3928	4	11	between	between	ADP
cet-3928	4	12	one	one	NUM
cet-3928	4	13	class	class	NOUN
cet-3928	4	14	and	and	CCONJ
cet-3928	4	15	another	another	DET
cet-3928	4	16	class	class	NOUN
cet-3928	4	17	,	,	PUNCT
cet-3928	4	18	and	and	CCONJ
cet-3928	4	19	the	the	DET
cet-3928	4	20	reality	reality	NOUN
cet-3928	4	21	of	of	ADP
cet-3928	4	22	multidimensional	multidimensional	ADJ
cet-3928	4	23	existence	existence	NOUN
cet-3928	4	24	dependency	dependency	NOUN
cet-3928	4	25	relationship	relationship	NOUN
cet-3928	4	26	with	with	ADP
cet-3928	4	27	the	the	DET
cet-3928	4	28	customer	customer	NOUN
cet-3928	4	29	class	class	NOUN
cet-3928	4	30	.	.	PUNCT
cet-3928	5	1	so	so	ADV
cet-3928	5	2	this	this	DET
cet-3928	5	3	paper	paper	NOUN
cet-3928	5	4	first	first	ADV
cet-3928	5	5	used	use	VERB
cet-3928	5	6	the	the	DET
cet-3928	5	7	fisher	fisher	PROPN
cet-3928	5	8	method	method	NOUN
cet-3928	5	9	to	to	PART
cet-3928	5	10	classify	classify	VERB
cet-3928	5	11	the	the	DET
cet-3928	5	12	class	class	NOUN
cet-3928	5	13	,	,	PUNCT
cet-3928	5	14	then	then	ADV
cet-3928	5	15	used	use	VERB
cet-3928	5	16	the	the	DET
cet-3928	5	17	bias	bias	NOUN
cet-3928	5	18	classification	classification	NOUN
cet-3928	5	19	algorithm	algorithm	NOUN
cet-3928	5	20	for	for	ADP
cet-3928	5	21	customer	customer	NOUN
cet-3928	5	22	segmentation	segmentation	NOUN
cet-3928	5	23	,	,	PUNCT
cet-3928	5	24	identified	identify	VERB
cet-3928	5	25	potential	potential	ADJ
cet-3928	5	26	customers	customer	NOUN
cet-3928	5	27	,	,	PUNCT
cet-3928	5	28	and	and	CCONJ
cet-3928	5	29	effectively	effectively	ADV
cet-3928	5	30	reduced	reduce	VERB
cet-3928	5	31	marketing	marketing	NOUN
cet-3928	5	32	costs	cost	NOUN
cet-3928	5	33	.	.	PUNCT
cet-3928	6	1	finally	finally	ADV
cet-3928	6	2	,	,	PUNCT
cet-3928	6	3	multigroup	multigroup	PROPN
cet-3928	6	4	data	datum	NOUN
cet-3928	6	5	were	be	AUX
cet-3928	6	6	used	use	VERB
cet-3928	6	7	to	to	PART
cet-3928	6	8	test	test	VERB
cet-3928	6	9	by	by	ADP
cet-3928	6	10	matlab	matlab	PROPN
cet-3928	6	11	.	.	PUNCT
cet-3928	7	1	compared	compare	VERB
cet-3928	7	2	to	to	ADP
cet-3928	7	3	the	the	DET
cet-3928	7	4	bias	bias	NOUN
cet-3928	7	5	algorithm	algorithm	NOUN
cet-3928	7	6	,	,	PUNCT
cet-3928	7	7	the	the	DET
cet-3928	7	8	results	result	NOUN
cet-3928	7	9	show	show	VERB
cet-3928	7	10	that	that	SCONJ
cet-3928	7	11	hybrid	hybrid	ADJ
cet-3928	7	12	algorithm	algorithm	NOUN
cet-3928	7	13	was	be	AUX
cet-3928	7	14	an	an	DET
cet-3928	7	15	effective	effective	ADJ
cet-3928	7	16	method	method	NOUN
cet-3928	7	17	.	.	PUNCT
cet-3928	8	1	1	1	X
cet-3928	8	2	.	.	X
cet-3928	8	3	introduction	introduction	NOUN
cet-3928	8	4	with	with	ADP
cet-3928	8	5	the	the	DET
cet-3928	8	6	development	development	NOUN
cet-3928	8	7	of	of	ADP
cet-3928	8	8	science	science	NOUN
cet-3928	8	9	and	and	CCONJ
cet-3928	8	10	technology	technology	NOUN
cet-3928	8	11	in	in	ADP
cet-3928	8	12	today	today	NOUN
cet-3928	8	13	's	's	PART
cet-3928	8	14	society	society	NOUN
cet-3928	8	15	,	,	PUNCT
cet-3928	8	16	the	the	DET
cet-3928	8	17	various	various	ADJ
cet-3928	8	18	aspects	aspect	NOUN
cet-3928	8	19	and	and	CCONJ
cet-3928	8	20	amount	amount	NOUN
cet-3928	8	21	of	of	ADP
cet-3928	8	22	social	social	ADJ
cet-3928	8	23	information	information	NOUN
cet-3928	8	24	is	be	AUX
cet-3928	8	25	increasingly	increasingly	ADV
cet-3928	8	26	large	large	ADJ
cet-3928	8	27	,	,	PUNCT
cet-3928	8	28	and	and	CCONJ
cet-3928	8	29	the	the	DET
cet-3928	8	30	dimensions	dimension	NOUN
cet-3928	8	31	of	of	ADP
cet-3928	8	32	the	the	DET
cet-3928	8	33	data	datum	NOUN
cet-3928	8	34	is	be	AUX
cet-3928	8	35	also	also	ADV
cet-3928	8	36	increasing	increase	VERB
cet-3928	8	37	.	.	PUNCT
cet-3928	9	1	classification	classification	NOUN
cet-3928	9	2	is	be	AUX
cet-3928	9	3	becoming	become	VERB
cet-3928	9	4	increasingly	increasingly	ADV
cet-3928	9	5	difficult	difficult	ADJ
cet-3928	9	6	and	and	CCONJ
cet-3928	9	7	at	at	ADP
cet-3928	9	8	the	the	DET
cet-3928	9	9	same	same	ADJ
cet-3928	9	10	time	time	NOUN
cet-3928	9	11	more	more	ADV
cet-3928	9	12	important	important	ADJ
cet-3928	9	13	(	(	PUNCT
cet-3928	9	14	abdelfattah	abdelfattah	PROPN
cet-3928	9	15	et	et	PROPN
cet-3928	9	16	al	al	PROPN
cet-3928	9	17	,	,	PUNCT
cet-3928	9	18	2013	2013	NUM
cet-3928	9	19	;	;	PUNCT
cet-3928	9	20	bouchaala	bouchaala	PROPN
cet-3928	9	21	et	et	PROPN
cet-3928	9	22	al	al	PROPN
cet-3928	9	23	,	,	PUNCT
cet-3928	9	24	2010	2010	NUM
cet-3928	9	25	)	)	PUNCT
cet-3928	9	26	.	.	PUNCT
cet-3928	10	1	according	accord	VERB
cet-3928	10	2	to	to	ADP
cet-3928	10	3	their	their	PRON
cet-3928	10	4	different	different	ADJ
cet-3928	10	5	social	social	ADJ
cet-3928	10	6	fields	field	NOUN
cet-3928	10	7	different	different	ADJ
cet-3928	10	8	classification	classification	NOUN
cet-3928	10	9	methods	method	NOUN
cet-3928	10	10	can	can	AUX
cet-3928	10	11	be	be	AUX
cet-3928	10	12	chosen	choose	VERB
cet-3928	10	13	,	,	PUNCT
cet-3928	10	14	such	such	ADJ
cet-3928	10	15	as	as	ADP
cet-3928	10	16	vector	vector	NOUN
cet-3928	10	17	machine	machine	NOUN
cet-3928	10	18	classification	classification	NOUN
cet-3928	10	19	,	,	PUNCT
cet-3928	10	20	clustering	cluster	VERB
cet-3928	10	21	analysis	analysis	NOUN
cet-3928	10	22	and	and	CCONJ
cet-3928	10	23	bp	bp	PROPN
cet-3928	10	24	neural	neural	ADJ
cet-3928	10	25	network	network	NOUN
cet-3928	10	26	,	,	PUNCT
cet-3928	10	27	etc	etc	X
cet-3928	10	28	.	.	X
cet-3928	11	1	in	in	ADP
cet-3928	11	2	numerous	numerous	ADJ
cet-3928	11	3	classification	classification	NOUN
cet-3928	11	4	methods	method	NOUN
cet-3928	11	5	,	,	PUNCT
cet-3928	11	6	bayes	bayes	PROPN
cet-3928	11	7	classification	classification	NOUN
cet-3928	11	8	algorithm	algorithm	NOUN
cet-3928	11	9	and	and	CCONJ
cet-3928	11	10	fisher	fisher	PROPN
cet-3928	11	11	discriminant	discriminant	PROPN
cet-3928	11	12	method	method	NOUN
cet-3928	11	13	have	have	AUX
cet-3928	11	14	been	be	AUX
cet-3928	11	15	of	of	ADP
cet-3928	11	16	great	great	ADJ
cet-3928	11	17	value	value	NOUN
cet-3928	11	18	.	.	PUNCT
cet-3928	12	1	the	the	DET
cet-3928	12	2	bayesian	bayesian	NOUN
cet-3928	12	3	classifier	classifier	NOUN
cet-3928	12	4	has	have	AUX
cet-3928	12	5	been	be	AUX
cet-3928	12	6	widely	widely	ADV
cet-3928	12	7	used	use	VERB
cet-3928	12	8	because	because	SCONJ
cet-3928	12	9	of	of	ADP
cet-3928	12	10	its	its	PRON
cet-3928	12	11	simple	simple	ADJ
cet-3928	12	12	structure	structure	NOUN
cet-3928	12	13	learning	learning	NOUN
cet-3928	12	14	and	and	CCONJ
cet-3928	12	15	parameter	parameter	PROPN
cet-3928	12	16	learning	learning	NOUN
cet-3928	12	17	,	,	PUNCT
cet-3928	12	18	classification	classification	NOUN
cet-3928	12	19	speed	speed	NOUN
cet-3928	12	20	when	when	SCONJ
cet-3928	12	21	the	the	PRON
cet-3928	12	22	on	on	ADP
cet-3928	12	23	class	class	NOUN
cet-3928	12	24	and	and	CCONJ
cet-3928	12	25	another	another	DET
cet-3928	12	26	class	class	NOUN
cet-3928	12	27	are	be	AUX
cet-3928	12	28	independent	independent	ADJ
cet-3928	12	29	of	of	ADP
cet-3928	12	30	each	each	DET
cet-3928	12	31	other	other	ADJ
cet-3928	12	32	,	,	PUNCT
cet-3928	12	33	and	and	CCONJ
cet-3928	12	34	its	its	PRON
cet-3928	12	35	lower	low	ADJ
cet-3928	12	36	calculation	calculation	NOUN
cet-3928	12	37	complexity	complexity	NOUN
cet-3928	12	38	.	.	PUNCT
cet-3928	13	1	but	but	CCONJ
cet-3928	13	2	in	in	ADP
cet-3928	13	3	real	real	ADJ
cet-3928	13	4	life	life	NOUN
cet-3928	13	5	,	,	PUNCT
cet-3928	13	6	when	when	SCONJ
cet-3928	13	7	classes	class	NOUN
cet-3928	13	8	can	can	AUX
cet-3928	13	9	not	not	PART
cet-3928	13	10	do	do	VERB
cet-3928	13	11	the	the	DET
cet-3928	13	12	math	math	NOUN
cet-3928	13	13	background	background	NOUN
cet-3928	13	14	independent	independent	ADJ
cet-3928	13	15	each	each	DET
cet-3928	13	16	other	other	ADJ
cet-3928	13	17	,	,	PUNCT
cet-3928	13	18	there	there	PRON
cet-3928	13	19	is	be	VERB
cet-3928	13	20	a	a	DET
cet-3928	13	21	mutual	mutual	ADJ
cet-3928	13	22	dependence	dependence	NOUN
cet-3928	13	23	between	between	ADP
cet-3928	13	24	the	the	DET
cet-3928	13	25	dimensions	dimension	NOUN
cet-3928	13	26	of	of	ADP
cet-3928	13	27	the	the	DET
cet-3928	13	28	classes	class	NOUN
cet-3928	13	29	.	.	PUNCT
cet-3928	14	1	in	in	ADP
cet-3928	14	2	the	the	DET
cet-3928	14	3	fisher	fisher	PROPN
cet-3928	14	4	discriminant	discriminant	NOUN
cet-3928	14	5	method	method	NOUN
cet-3928	14	6	of	of	ADP
cet-3928	14	7	projection	projection	NOUN
cet-3928	14	8	,	,	PUNCT
cet-3928	14	9	the	the	DET
cet-3928	14	10	basic	basic	ADJ
cet-3928	14	11	idea	idea	NOUN
cet-3928	14	12	is	be	AUX
cet-3928	14	13	to	to	ADP
cet-3928	14	14	group	group	NOUN
cet-3928	14	15	projection	projection	NOUN
cet-3928	14	16	data	datum	NOUN
cet-3928	14	17	to	to	ADP
cet-3928	14	18	a	a	DET
cet-3928	14	19	certain	certain	ADJ
cet-3928	14	20	direction	direction	NOUN
cet-3928	14	21	,	,	PUNCT
cet-3928	14	22	making	make	VERB
cet-3928	14	23	them	they	PRON
cet-3928	14	24	a	a	DET
cet-3928	14	25	projection	projection	NOUN
cet-3928	14	26	of	of	ADP
cet-3928	14	27	classes	class	NOUN
cet-3928	14	28	being	be	AUX
cet-3928	14	29	as	as	ADV
cet-3928	14	30	separate	separate	ADJ
cet-3928	14	31	from	from	ADP
cet-3928	14	32	each	each	DET
cet-3928	14	33	other	other	ADJ
cet-3928	14	34	as	as	ADV
cet-3928	14	35	much	much	ADV
cet-3928	14	36	as	as	ADP
cet-3928	14	37	possible	possible	ADJ
cet-3928	14	38	(	(	PUNCT
cet-3928	14	39	aquaro	aquaro	PROPN
cet-3928	14	40	et	et	PROPN
cet-3928	14	41	al	al	PROPN
cet-3928	14	42	,	,	PUNCT
cet-3928	14	43	2009	2009	NUM
cet-3928	14	44	;	;	PUNCT
cet-3928	14	45	cook	cook	VERB
cet-3928	14	46	et	et	PROPN
cet-3928	14	47	al	al	PROPN
cet-3928	14	48	,	,	PUNCT
cet-3928	14	49	2000	2000	NUM
cet-3928	14	50	)	)	PUNCT
cet-3928	14	51	.	.	PUNCT
cet-3928	15	1	in	in	ADP
cet-3928	15	2	order	order	NOUN
cet-3928	15	3	to	to	PART
cet-3928	15	4	improve	improve	VERB
cet-3928	15	5	on	on	ADP
cet-3928	15	6	this	this	DET
cet-3928	15	7	problem	problem	NOUN
cet-3928	15	8	,	,	PUNCT
cet-3928	15	9	this	this	DET
cet-3928	15	10	paper	paper	NOUN
cet-3928	15	11	proposes	propose	VERB
cet-3928	15	12	a	a	DET
cet-3928	15	13	kind	kind	NOUN
cet-3928	15	14	of	of	ADP
cet-3928	15	15	method	method	NOUN
cet-3928	15	16	based	base	VERB
cet-3928	15	17	on	on	ADP
cet-3928	15	18	fisher	fisher	PROPN
cet-3928	15	19	linear	linear	PROPN
cet-3928	15	20	discriminant	discriminant	ADJ
cet-3928	15	21	analysis	analysis	NOUN
cet-3928	15	22	and	and	CCONJ
cet-3928	15	23	an	an	DET
cet-3928	15	24	improved	improved	ADJ
cet-3928	15	25	algorithm	algorithm	NOUN
cet-3928	15	26	of	of	ADP
cet-3928	15	27	bayesian	bayesian	NOUN
cet-3928	15	28	classifier	classifier	NOUN
cet-3928	15	29	.	.	PUNCT
cet-3928	16	1	the	the	DET
cet-3928	16	2	main	main	ADJ
cet-3928	16	3	idea	idea	NOUN
cet-3928	16	4	of	of	ADP
cet-3928	16	5	this	this	DET
cet-3928	16	6	algorithm	algorithm	NOUN
cet-3928	16	7	is	be	AUX
cet-3928	16	8	that	that	SCONJ
cet-3928	16	9	by	by	ADP
cet-3928	16	10	using	use	VERB
cet-3928	16	11	the	the	DET
cet-3928	16	12	transformation	transformation	NOUN
cet-3928	16	13	matrix	matrix	NOUN
cet-3928	16	14	,	,	PUNCT
cet-3928	16	15	the	the	DET
cet-3928	16	16	original	original	ADJ
cet-3928	16	17	training	training	NOUN
cet-3928	16	18	samples	sample	NOUN
cet-3928	16	19	are	be	AUX
cet-3928	16	20	transformed	transform	VERB
cet-3928	16	21	,	,	PUNCT
cet-3928	16	22	and	and	CCONJ
cet-3928	16	23	use	use	VERB
cet-3928	16	24	the	the	DET
cet-3928	16	25	classifier	classifier	NOUN
cet-3928	16	26	in	in	ADP
cet-3928	16	27	the	the	DET
cet-3928	16	28	projection	projection	NOUN
cet-3928	16	29	to	to	ADP
cet-3928	16	30	the	the	DET
cet-3928	16	31	new	new	ADJ
cet-3928	16	32	sample	sample	NOUN
cet-3928	16	33	space	space	NOUN
cet-3928	16	34	for	for	ADP
cet-3928	16	35	learning	learn	VERB
cet-3928	16	36	classification	classification	NOUN
cet-3928	16	37	.	.	PUNCT
cet-3928	17	1	the	the	DET
cet-3928	17	2	original	original	ADJ
cet-3928	17	3	sample	sample	NOUN
cet-3928	17	4	property	property	NOUN
cet-3928	17	5	is	be	AUX
cet-3928	17	6	concentrated	concentrate	VERB
cet-3928	17	7	,	,	PUNCT
cet-3928	17	8	with	with	ADP
cet-3928	17	9	any	any	DET
cet-3928	17	10	two	two	NUM
cet-3928	17	11	may	may	AUX
cet-3928	17	12	having	have	VERB
cet-3928	17	13	certain	certain	ADJ
cet-3928	17	14	dependencies	dependency	NOUN
cet-3928	17	15	between	between	ADP
cet-3928	17	16	attributes	attribute	NOUN
cet-3928	17	17	,	,	PUNCT
cet-3928	17	18	and	and	CCONJ
cet-3928	17	19	the	the	DET
cet-3928	17	20	new	new	ADJ
cet-3928	17	21	samples	sample	NOUN
cet-3928	17	22	are	be	AUX
cet-3928	17	23	assumed	assume	VERB
cet-3928	17	24	to	to	PART
cet-3928	17	25	be	be	AUX
cet-3928	17	26	independent	independent	ADJ
cet-3928	17	27	of	of	ADP
cet-3928	17	28	each	each	DET
cet-3928	17	29	other	other	ADJ
cet-3928	17	30	after	after	ADP
cet-3928	17	31	the	the	DET
cet-3928	17	32	projection	projection	NOUN
cet-3928	17	33	in	in	ADP
cet-3928	17	34	the	the	DET
cet-3928	17	35	new	new	ADJ
cet-3928	17	36	sample	sample	NOUN
cet-3928	17	37	space	space	NOUN
cet-3928	17	38	(	(	PUNCT
cet-3928	17	39	duan	duan	PROPN
cet-3928	17	40	et	et	PROPN
cet-3928	17	41	al	al	PROPN
cet-3928	17	42	,	,	PUNCT
cet-3928	17	43	2009	2009	NUM
cet-3928	17	44	;	;	PUNCT
cet-3928	17	45	hao	hao	PROPN
cet-3928	17	46	,	,	PUNCT
cet-3928	17	47	2010	2010	NUM
cet-3928	17	48	)	)	PUNCT
cet-3928	17	49	.	.	PUNCT
cet-3928	18	1	through	through	ADP
cet-3928	18	2	the	the	DET
cet-3928	18	3	transformation	transformation	NOUN
cet-3928	18	4	,	,	PUNCT
cet-3928	18	5	the	the	DET
cet-3928	18	6	model	model	NOUN
cet-3928	18	7	which	which	PRON
cet-3928	18	8	can	can	AUX
cet-3928	18	9	be	be	AUX
cet-3928	18	10	expressed	express	VERB
cet-3928	18	11	in	in	ADP
cet-3928	18	12	the	the	DET
cet-3928	18	13	measurement	measurement	NOUN
cet-3928	18	14	space	space	NOUN
cet-3928	18	15	with	with	ADP
cet-3928	18	16	high	high	ADJ
cet-3928	18	17	dimension	dimension	NOUN
cet-3928	18	18	is	be	AUX
cet-3928	18	19	changed	change	VERB
cet-3928	18	20	into	into	ADP
cet-3928	18	21	the	the	DET
cet-3928	18	22	mode	mode	NOUN
cet-3928	18	23	of	of	ADP
cet-3928	18	24	representation	representation	NOUN
cet-3928	18	25	in	in	ADP
cet-3928	18	26	the	the	DET
cet-3928	18	27	feature	feature	NOUN
cet-3928	18	28	space	space	NOUN
cet-3928	18	29	with	with	ADP
cet-3928	18	30	lower	low	ADJ
cet-3928	18	31	dimension	dimension	NOUN
cet-3928	18	32	.	.	PUNCT
cet-3928	19	1	in	in	ADP
cet-3928	19	2	this	this	DET
cet-3928	19	3	way	way	NOUN
cet-3928	19	4	,	,	PUNCT
cet-3928	19	5	it	it	PRON
cet-3928	19	6	can	can	AUX
cet-3928	19	7	effectively	effectively	ADV
cet-3928	19	8	realize	realize	VERB
cet-3928	19	9	the	the	DET
cet-3928	19	10	classification	classification	NOUN
cet-3928	19	11	and	and	CCONJ
cet-3928	19	12	recognition	recognition	NOUN
cet-3928	19	13	,	,	PUNCT
cet-3928	19	14	which	which	PRON
cet-3928	19	15	can	can	AUX
cet-3928	19	16	more	more	ADV
cet-3928	19	17	accurately	accurately	ADV
cet-3928	19	18	reflect	reflect	VERB
cet-3928	19	19	the	the	DET
cet-3928	19	20	nature	nature	NOUN
cet-3928	19	21	of	of	ADP
cet-3928	19	22	the	the	DET
cet-3928	19	23	classification	classification	NOUN
cet-3928	19	24	(	(	PUNCT
cet-3928	19	25	guo	guo	PROPN
cet-3928	19	26	et	et	PROPN
cet-3928	19	27	al	al	PROPN
cet-3928	19	28	,	,	PUNCT
cet-3928	19	29	2012	2012	NUM
cet-3928	19	30	;	;	PUNCT
cet-3928	19	31	li	li	PROPN
cet-3928	19	32	et	et	PROPN
cet-3928	19	33	al	al	PROPN
cet-3928	19	34	,	,	PUNCT
cet-3928	19	35	2010	2010	NUM
cet-3928	19	36	)	)	PUNCT
cet-3928	19	37	.	.	PUNCT
cet-3928	20	1	this	this	DET
cet-3928	20	2	paper	paper	NOUN
cet-3928	20	3	gives	give	VERB
cet-3928	20	4	a	a	DET
cet-3928	20	5	kind	kind	NOUN
cet-3928	20	6	of	of	ADP
cet-3928	20	7	method	method	NOUN
cet-3928	20	8	based	base	VERB
cet-3928	20	9	on	on	ADP
cet-3928	20	10	bayesian	bayesian	NOUN
cet-3928	20	11	and	and	CCONJ
cet-3928	20	12	fisher	fisher	PROPN
cet-3928	20	13	algorithm	algorithm	NOUN
cet-3928	20	14	of	of	ADP
cet-3928	20	15	multi	multi	ADJ
cet-3928	20	16	-	-	ADJ
cet-3928	20	17	dimensional	dimensional	ADJ
cet-3928	20	18	customer	customer	NOUN
cet-3928	20	19	behavior	behavior	NOUN
cet-3928	20	20	analysis	analysis	NOUN
cet-3928	20	21	on	on	ADP
cet-3928	20	22	the	the	DET
cet-3928	20	23	basis	basis	NOUN
cet-3928	20	24	of	of	ADP
cet-3928	20	25	analyzing	analyze	VERB
cet-3928	20	26	the	the	DET
cet-3928	20	27	characteristics	characteristic	NOUN
cet-3928	20	28	of	of	ADP
cet-3928	20	29	the	the	DET
cet-3928	20	30	bayesian	bayesian	NOUN
cet-3928	20	31	model	model	NOUN
cet-3928	20	32	,	,	PUNCT
cet-3928	20	33	combined	combine	VERB
cet-3928	20	34	with	with	ADP
cet-3928	20	35	the	the	DET
cet-3928	20	36	fisher	fisher	PROPN
cet-3928	20	37	linear	linear	PROPN
cet-3928	20	38	discriminant	discriminant	ADJ
cet-3928	20	39	analysis	analysis	NOUN
cet-3928	20	40	..	..	PUNCT
cet-3928	20	41	doi	doi	NOUN
cet-3928	20	42	:	:	PUNCT
cet-3928	20	43	10.3303	10.3303	NUM
cet-3928	20	44	/	/	SYM
cet-3928	20	45	cet1651064	cet1651064	NOUN
cet-3928	20	46	please	please	INTJ
cet-3928	20	47	cite	cite	VERB
cet-3928	20	48	this	this	DET
cet-3928	20	49	article	article	NOUN
cet-3928	20	50	as	as	ADP
cet-3928	20	51	:	:	PUNCT
cet-3928	20	52	wang	wang	PROPN
cet-3928	20	53	g.h	g.h	PROPN
cet-3928	20	54	.	.	PROPN
cet-3928	20	55	,	,	PUNCT
cet-3928	20	56	jiao	jiao	PROPN
cet-3928	20	57	f.l	f.l	PROPN
cet-3928	20	58	.	.	PROPN
cet-3928	20	59	,	,	PUNCT
cet-3928	20	60	2016	2016	NUM
cet-3928	20	61	,	,	PUNCT
cet-3928	20	62	the	the	DET
cet-3928	20	63	multi	multi	ADJ
cet-3928	20	64	-	-	ADJ
cet-3928	20	65	dimensional	dimensional	ADJ
cet-3928	20	66	customer	customer	NOUN
cet-3928	20	67	behavior	behavior	NOUN
cet-3928	20	68	analysis	analysis	NOUN
cet-3928	20	69	based	base	VERB
cet-3928	20	70	on	on	ADP
cet-3928	20	71	biayes	biayes	PRON
cet-3928	20	72	and	and	CCONJ
cet-3928	20	73	fisher	fisher	PROPN
cet-3928	20	74	classification	classification	NOUN
cet-3928	20	75	algorithm	algorithm	NOUN
cet-3928	20	76	,	,	PUNCT
cet-3928	20	77	chemical	chemical	NOUN
cet-3928	20	78	engineering	engineering	NOUN
cet-3928	20	79	transactions	transaction	NOUN
cet-3928	20	80	,	,	PUNCT
cet-3928	20	81	51	51	NUM
cet-3928	20	82	,	,	PUNCT
cet-3928	20	83	379	379	NUM
cet-3928	20	84	-	-	SYM
cet-3928	20	85	384	384	NUM
cet-3928	20	86	doi:10.3303	doi:10.3303	NOUN
cet-3928	20	87	/	/	SYM
cet-3928	20	88	cet1651064	cet1651064	NOUN
cet-3928	20	89	379	379	NUM
cet-3928	20	90	2	2	NUM
cet-3928	20	91	.	.	PUNCT
cet-3928	21	1	the	the	DET
cet-3928	21	2	bayesian	bayesian	NOUN
cet-3928	21	3	classification	classification	NOUN
cet-3928	21	4	algorithm	algorithm	NOUN
cet-3928	21	5	and	and	CCONJ
cet-3928	21	6	fisher	fisher	PROPN
cet-3928	21	7	discriminant	discriminant	VERB
cet-3928	21	8	analysis	analysis	NOUN
cet-3928	21	9	algorithm	algorithm	NOUN
cet-3928	21	10	the	the	DET
cet-3928	21	11	bayesian	bayesian	NOUN
cet-3928	21	12	classification	classification	NOUN
cet-3928	21	13	algorithm	algorithm	NOUN
cet-3928	21	14	,	,	PUNCT
cet-3928	21	15	using	use	VERB
cet-3928	21	16	probability	probability	NOUN
cet-3928	21	17	and	and	CCONJ
cet-3928	21	18	statistics	statistic	NOUN
cet-3928	21	19	to	to	ADP
cet-3928	21	20	classification	classification	NOUN
cet-3928	21	21	samples	sample	NOUN
cet-3928	21	22	,	,	PUNCT
cet-3928	21	23	is	be	AUX
cet-3928	21	24	one	one	NUM
cet-3928	21	25	of	of	ADP
cet-3928	21	26	the	the	DET
cet-3928	21	27	earliest	early	ADJ
cet-3928	21	28	methods	method	NOUN
cet-3928	21	29	for	for	ADP
cet-3928	21	30	dealing	deal	VERB
cet-3928	21	31	with	with	ADP
cet-3928	21	32	uncertainty	uncertainty	NOUN
cet-3928	21	33	by	by	ADP
cet-3928	21	34	classification	classification	NOUN
cet-3928	21	35	.	.	PUNCT
cet-3928	22	1	it	it	PRON
cet-3928	22	2	is	be	AUX
cet-3928	22	3	based	base	VERB
cet-3928	22	4	on	on	ADP
cet-3928	22	5	maximum	maximum	ADJ
cet-3928	22	6	a	a	DET
cet-3928	22	7	posteriori	posteriori	NOUN
cet-3928	22	8	probability	probability	NOUN
cet-3928	22	9	criterion	criterion	NOUN
cet-3928	22	10	,	,	PUNCT
cet-3928	22	11	namely	namely	ADV
cet-3928	22	12	the	the	DET
cet-3928	22	13	use	use	NOUN
cet-3928	22	14	of	of	ADP
cet-3928	22	15	a	a	DET
cet-3928	22	16	certain	certain	ADJ
cet-3928	22	17	object	object	NOUN
cet-3928	22	18	by	by	ADP
cet-3928	22	19	probabilistic	probabilistic	ADJ
cet-3928	22	20	prior	prior	ADJ
cet-3928	22	21	probability	probability	NOUN
cet-3928	22	22	calculation	calculation	NOUN
cet-3928	22	23	,	,	PUNCT
cet-3928	22	24	and	and	CCONJ
cet-3928	22	25	it	it	PRON
cet-3928	22	26	selects	select	VERB
cet-3928	22	27	the	the	DET
cet-3928	22	28	classes	class	NOUN
cet-3928	22	29	with	with	ADP
cet-3928	22	30	maximum	maximum	NOUN
cet-3928	22	31	a	a	DET
cet-3928	22	32	posteriori	posteriori	NOUN
cet-3928	22	33	probability	probability	NOUN
cet-3928	22	34	as	as	ADP
cet-3928	22	35	the	the	DET
cet-3928	22	36	object	object	NOUN
cet-3928	22	37	's	's	PART
cet-3928	22	38	class	class	NOUN
cet-3928	22	39	(	(	PUNCT
cet-3928	22	40	liu	liu	PROPN
cet-3928	22	41	,	,	PUNCT
cet-3928	22	42	2014	2014	NUM
cet-3928	22	43	;	;	PUNCT
cet-3928	22	44	zhang	zhang	PROPN
cet-3928	22	45	et	et	PROPN
cet-3928	22	46	al	al	PROPN
cet-3928	22	47	,	,	PUNCT
cet-3928	22	48	2010	2010	NUM
cet-3928	22	49	)	)	PUNCT
cet-3928	22	50	.	.	PUNCT
cet-3928	23	1	definition	definition	NOUN
cet-3928	23	2	1	1	NUM
cet-3928	23	3	bayes	bayes	PROPN
cet-3928	23	4	formula	formula	NOUN
cet-3928	23	5	:	:	PUNCT
cet-3928	23	6	set	set	VERB
cet-3928	23	7	state	state	NOUN
cet-3928	23	8	of	of	ADP
cet-3928	23	9	a	a	PRON
cet-3928	23	10	and	and	CCONJ
cet-3928	23	11	b	b	NOUN
cet-3928	23	12	to	to	PART
cet-3928	23	13	meet	meet	VERB
cet-3928	23	14	the	the	DET
cet-3928	23	15	following	following	ADJ
cet-3928	23	16	conditions	condition	NOUN
cet-3928	23	17	:	:	PUNCT
cet-3928	23	18	(	(	PUNCT
cet-3928	23	19	1	1	X
cet-3928	23	20	)	)	PUNCT
cet-3928	23	21	any	any	DET
cet-3928	23	22	two	two	NUM
cet-3928	23	23	states	state	NOUN
cet-3928	23	24	are	be	AUX
cet-3928	23	25	incompatible	incompatible	ADJ
cet-3928	23	26	,	,	PUNCT
cet-3928	23	27	when	when	SCONJ
cet-3928	23	28	ji	ji	PROPN
cet-3928	23	29			PROPN
cet-3928	23	30	,	,	PUNCT
cet-3928	23	31	there	there	PRON
cet-3928	23	32	is	be	VERB
cet-3928	23	33	ji	ji	PROPN
cet-3928	23	34	aa	aa	PROPN
cet-3928	23	35			PROPN
cet-3928	23	36	(	(	PUNCT
cet-3928	23	37	2	2	NUM
cet-3928	23	38	)	)	PUNCT
cet-3928	23	39	0	0	NUM
cet-3928	23	40	)	)	PUNCT
cet-3928	23	41	(	(	PUNCT
cet-3928	23	42	iap	iap	PUNCT
cet-3928	23	43	(	(	PUNCT
cet-3928	23	44	3	3	NUM
cet-3928	23	45	)	)	PUNCT
cet-3928	23	46	sample	sample	NOUN
cet-3928	23	47	space	space	NOUN
cet-3928	23	48	d	d	NOUN
cet-3928	23	49	is	be	AUX
cet-3928	23	50	a	a	DET
cet-3928	23	51	collection	collection	NOUN
cet-3928	23	52	of	of	ADP
cet-3928	23	53	i	i	PRON
cet-3928	24	1	n	n	NOUN
cet-3928	24	2	i	i	PRON
cet-3928	24	3	ad	ad	NOUN
cet-3928	24	4	1	1	NUM
cet-3928	25	1			NUM
cet-3928	25	2			NOUN
cet-3928	25	3	,	,	PUNCT
cet-3928	25	4	there	there	PRON
cet-3928	25	5	are	be	VERB
cet-3928	25	6	)	)	PUNCT
cet-3928	25	7	(	(	PUNCT
cet-3928	25	8	)	)	PUNCT
cet-3928	25	9	(	(	PUNCT
cet-3928	25	10	)	)	PUNCT
cet-3928	25	11	(	(	PUNCT
cet-3928	25	12	1	1	NUM
cet-3928	25	13	i	i	PRON
cet-3928	26	1	n	n	VERB
cet-3928	27	1	i	i	PRON
cet-3928	28	1	i	i	PRON
cet-3928	28	2	axpapxp	axpapxp	VERB
cet-3928	28	3			VERB
cet-3928	28	4			PRON
cet-3928	28	5	(	(	PUNCT
cet-3928	28	6	1	1	NUM
cet-3928	28	7	)	)	PUNCT
cet-3928	28	8	)	)	PUNCT
cet-3928	28	9	(	(	PUNCT
cet-3928	28	10	)	)	PUNCT
cet-3928	28	11	(	(	PUNCT
cet-3928	28	12	)	)	PUNCT
cet-3928	28	13	(	(	PUNCT
cet-3928	28	14	)	)	PUNCT
cet-3928	28	15	(	(	PUNCT
cet-3928	28	16	bp	bp	PROPN
cet-3928	28	17	axpap	axpap	PROPN
cet-3928	28	18	xap	xap	PROPN
cet-3928	29	1	ii	ii	PROPN
cet-3928	29	2	i	i	PRON
cet-3928	29	3			VERB
cet-3928	29	4			PRON
cet-3928	29	5	(	(	PUNCT
cet-3928	29	6	2	2	NUM
cet-3928	29	7	)	)	PUNCT
cet-3928	29	8			X
cet-3928	30	1			NUM
cet-3928	30	2			INTJ
cet-3928	30	3			PROPN
cet-3928	30	4			PROPN
cet-3928	30	5	n	n	PROPN
cet-3928	30	6	j	j	PROPN
cet-3928	30	7	jj	jj	PROPN
cet-3928	30	8	ii	ii	PROPN
cet-3928	31	1	i	i	PRON
cet-3928	31	2	axpap	axpap	PROPN
cet-3928	31	3	axpap	axpap	PROPN
cet-3928	31	4	xap	xap	PROPN
cet-3928	31	5	1	1	NUM
cet-3928	31	6	)	)	PUNCT
cet-3928	31	7	(	(	PUNCT
cet-3928	31	8	)	)	PUNCT
cet-3928	31	9	(	(	PUNCT
cet-3928	31	10	)	)	PUNCT
cet-3928	31	11	(	(	PUNCT
cet-3928	31	12	)	)	PUNCT
cet-3928	31	13	(	(	PUNCT
cet-3928	31	14	)	)	PUNCT
cet-3928	31	15	(	(	PUNCT
cet-3928	31	16	(	(	PUNCT
cet-3928	31	17	3	3	X
cet-3928	31	18	)	)	PUNCT
cet-3928	31	19	among	among	ADP
cet-3928	31	20	them	they	PRON
cet-3928	31	21	,	,	PUNCT
cet-3928	31	22	)	)	PUNCT
cet-3928	31	23	(	(	PUNCT
cet-3928	31	24	iap	iap	PROPN
cet-3928	31	25	is	be	AUX
cet-3928	31	26	ia	ia	PROPN
cet-3928	31	27	prior	prior	ADJ
cet-3928	31	28	probability	probability	NOUN
cet-3928	31	29	,	,	PUNCT
cet-3928	31	30	)	)	PUNCT
cet-3928	31	31	(	(	PUNCT
cet-3928	31	32	iaxp	iaxp	NOUN
cet-3928	31	33	is	be	AUX
cet-3928	31	34	the	the	DET
cet-3928	31	35	conditional	conditional	ADJ
cet-3928	31	36	probability	probability	NOUN
cet-3928	31	37	of	of	ADP
cet-3928	31	38	sample	sample	NOUN
cet-3928	31	39	x	x	PUNCT
cet-3928	31	40	under	under	ADP
cet-3928	31	41	the	the	DET
cet-3928	31	42	condition	condition	NOUN
cet-3928	31	43	ia	ia	PROPN
cet-3928	31	44	.	.	PUNCT
cet-3928	31	45	)	)	PUNCT
cet-3928	32	1	(	(	PUNCT
cet-3928	32	2	xap	xap	PRON
cet-3928	32	3	i	i	PRON
cet-3928	32	4	is	be	AUX
cet-3928	32	5	the	the	DET
cet-3928	32	6	conditional	conditional	ADJ
cet-3928	32	7	probability	probability	NOUN
cet-3928	32	8	of	of	ADP
cet-3928	32	9	the	the	DET
cet-3928	32	10	condition	condition	NOUN
cet-3928	32	11	ia	ia	NOUN
cet-3928	32	12	in	in	ADP
cet-3928	32	13	the	the	DET
cet-3928	32	14	condition	condition	NOUN
cet-3928	32	15	of	of	ADP
cet-3928	32	16	sample	sample	NOUN
cet-3928	32	17	x	x	X
cet-3928	32	18	,	,	PUNCT
cet-3928	32	19	also	also	ADV
cet-3928	32	20	known	know	VERB
cet-3928	32	21	as	as	ADP
cet-3928	32	22	the	the	DET
cet-3928	32	23	posteriori	posteriori	NOUN
cet-3928	32	24	probability	probability	NOUN
cet-3928	32	25	(	(	PUNCT
cet-3928	32	26	when	when	SCONJ
cet-3928	32	27	the	the	DET
cet-3928	32	28	sample	sample	NOUN
cet-3928	32	29	x	x	VERB
cet-3928	32	30	is	be	AUX
cet-3928	32	31	known	know	VERB
cet-3928	32	32	,	,	PUNCT
cet-3928	32	33	it	it	PRON
cet-3928	32	34	belongs	belong	VERB
cet-3928	32	35	to	to	ADP
cet-3928	32	36	the	the	DET
cet-3928	32	37	probability	probability	NOUN
cet-3928	32	38	of	of	ADP
cet-3928	32	39	the	the	DET
cet-3928	32	40	state	state	NOUN
cet-3928	32	41	ia	ia	PROPN
cet-3928	32	42	)	)	PUNCT
cet-3928	32	43	.	.	PUNCT
cet-3928	33	1	so	so	ADV
cet-3928	33	2	sample	sample	VERB
cet-3928	33	3	a	a	PRON
cet-3928	33	4	is	be	AUX
cet-3928	33	5	assigned	assign	VERB
cet-3928	33	6	to	to	ADP
cet-3928	33	7	the	the	DET
cet-3928	33	8	posterior	posterior	ADJ
cet-3928	33	9	probability	probability	NOUN
cet-3928	33	10	of	of	ADP
cet-3928	33	11	the	the	DET
cet-3928	33	12	largest	large	ADJ
cet-3928	33	13	in	in	ADP
cet-3928	33	14	the	the	DET
cet-3928	33	15	class	class	NOUN
cet-3928	33	16	(	(	PUNCT
cet-3928	33	17	li	li	PROPN
cet-3928	33	18	l	l	PROPN
cet-3928	33	19	,	,	PUNCT
cet-3928	33	20	ma	ma	PROPN
cet-3928	33	21	s	s	PROPN
cet-3928	33	22	,	,	PUNCT
cet-3928	33	23	zhang	zhang	PROPN
cet-3928	33	24	y	y	PROPN
cet-3928	33	25	,	,	PUNCT
cet-3928	33	26	2014	2014	NUM
cet-3928	33	27	;	;	PUNCT
cet-3928	33	28	sun	sun	PROPN
cet-3928	33	29	y	y	PROPN
cet-3928	33	30	,	,	PUNCT
cet-3928	33	31	tang	tang	PROPN
cet-3928	33	32	y	y	PROPN
cet-3928	33	33	,	,	PUNCT
cet-3928	33	34	ding	ding	NOUN
cet-3928	33	35	sl	sl	NOUN
cet-3928	33	36	,	,	PUNCT
cet-3928	33	37	2011	2011	NUM
cet-3928	33	38	)	)	PUNCT
cet-3928	33	39	.	.	PUNCT
cet-3928	34	1	supposing	suppose	VERB
cet-3928	34	2	that	that	SCONJ
cet-3928	34	3	there	there	PRON
cet-3928	34	4	are	be	VERB
cet-3928	34	5	k	k	PRON
cet-3928	34	6	p	p	NOUN
cet-3928	34	7	-dimensional	-dimensional	ADJ
cet-3928	34	8	overall	overall	ADJ
cet-3928	34	9	kggg	kggg	NOUN
cet-3928	34	10	,	,	PUNCT
cet-3928	34	11	,	,	PUNCT
cet-3928	34	12	,	,	PUNCT
cet-3928	34	13	21	21	NUM
cet-3928	34	14			NOUN
cet-3928	34	15	,	,	PUNCT
cet-3928	34	16	the	the	DET
cet-3928	34	17	probability	probability	NOUN
cet-3928	34	18	density	density	NOUN
cet-3928	34	19	function	function	NOUN
cet-3928	34	20	are	be	AUX
cet-3928	34	21	)	)	PUNCT
cet-3928	34	22	(	(	PUNCT
cet-3928	34	23	,	,	PUNCT
cet-3928	34	24	)	)	PUNCT
cet-3928	34	25	,	,	PUNCT
cet-3928	34	26	(	(	PUNCT
cet-3928	34	27	)	)	PUNCT
cet-3928	34	28	,	,	PUNCT
cet-3928	34	29	(	(	PUNCT
cet-3928	34	30	21	21	NUM
cet-3928	34	31	xfxfxf	xfxfxf	PROPN
cet-3928	34	32	k	k	X
cet-3928	34	33	.	.	PUNCT
cet-3928	35	1	assume	assume	VERB
cet-3928	35	2	that	that	SCONJ
cet-3928	35	3	the	the	DET
cet-3928	35	4	sample	sample	NOUN
cet-3928	35	5	x	x	PUNCT
cet-3928	35	6	prior	prior	ADJ
cet-3928	35	7	probability	probability	NOUN
cet-3928	35	8	from	from	ADP
cet-3928	35	9	general	general	ADJ
cet-3928	35	10	ig	ig	PROPN
cet-3928	35	11	to	to	ADP
cet-3928	35	12	)	)	PUNCT
cet-3928	35	13	,	,	PUNCT
cet-3928	35	14	,	,	PUNCT
cet-3928	35	15	2,1	2,1	NUM
cet-3928	35	16	(	(	PUNCT
cet-3928	35	17	kipi	kipi	NOUN
cet-3928	35	18			NUM
cet-3928	35	19	,	,	PUNCT
cet-3928	35	20	then	then	ADV
cet-3928	35	21	121	121	NUM
cet-3928	35	22			NOUN
cet-3928	35	23	kppp	kppp	PROPN
cet-3928	35	24			NOUN
cet-3928	35	25	.	.	PUNCT
cet-3928	36	1	according	accord	VERB
cet-3928	36	2	to	to	ADP
cet-3928	36	3	the	the	DET
cet-3928	36	4	bayes	bayes	PROPN
cet-3928	36	5	theory	theory	NOUN
cet-3928	36	6	,	,	PUNCT
cet-3928	36	7	the	the	DET
cet-3928	36	8	posterior	posterior	ADJ
cet-3928	36	9	probability	probability	NOUN
cet-3928	36	10	of	of	ADP
cet-3928	36	11	sample	sample	NOUN
cet-3928	36	12	a	a	PRON
cet-3928	36	13	from	from	ADP
cet-3928	36	14	total	total	ADJ
cet-3928	36	15	b	b	PROPN
cet-3928	36	16	is	be	AUX
cet-3928	36	17	ki	ki	PROPN
cet-3928	36	18	xfp	xfp	PROPN
cet-3928	37	1	xfp	xfp	PROPN
cet-3928	37	2	xgp	xgp	PROPN
cet-3928	38	1	k	k	PROPN
cet-3928	38	2	j	j	PROPN
cet-3928	38	3	jj	jj	PROPN
cet-3928	38	4	ii	ii	PROPN
cet-3928	39	1	i	i	PRON
cet-3928	39	2	,	,	PUNCT
cet-3928	39	3	,	,	PUNCT
cet-3928	39	4	2,1	2,1	NUM
cet-3928	39	5	,	,	PUNCT
cet-3928	39	6	)	)	PUNCT
cet-3928	39	7	(	(	PUNCT
cet-3928	39	8	)	)	PUNCT
cet-3928	39	9	(	(	PUNCT
cet-3928	39	10	)	)	PUNCT
cet-3928	39	11	(	(	PUNCT
cet-3928	39	12	1	1	NUM
cet-3928	39	13			PROPN
cet-3928	39	14			X
cet-3928	39	15			NUM
cet-3928	39	16	(	(	PUNCT
cet-3928	39	17	4	4	NUM
cet-3928	39	18	)	)	PUNCT
cet-3928	39	19	the	the	DET
cet-3928	39	20	following	follow	VERB
cet-3928	39	21	discriminant	discriminant	NOUN
cet-3928	39	22	rule	rule	NOUN
cet-3928	39	23	applies	apply	VERB
cet-3928	39	24	under	under	ADP
cet-3928	39	25	the	the	DET
cet-3928	39	26	condition	condition	NOUN
cet-3928	39	27	of	of	ADP
cet-3928	39	28	not	not	PART
cet-3928	39	29	considering	consider	VERB
cet-3928	39	30	miscalculation	miscalculation	NOUN
cet-3928	39	31	cost	cost	NOUN
cet-3928	39	32	:	:	PUNCT
cet-3928	39	33	igx	igx	PROPN
cet-3928	39	34	if	if	SCONJ
cet-3928	39	35	)	)	PUNCT
cet-3928	39	36	(	(	PUNCT
cet-3928	39	37	max	max	PROPN
cet-3928	39	38	)	)	PUNCT
cet-3928	39	39	(	(	PUNCT
cet-3928	39	40	1	1	NUM
cet-3928	39	41	xgpxgp	xgpxgp	VERB
cet-3928	40	1	j	j	PROPN
cet-3928	41	1	kj	kj	PROPN
cet-3928	41	2	i	i	PROPN
cet-3928	41	3			VERB
cet-3928	41	4			PROPN
cet-3928	41	5	.	.	PUNCT
cet-3928	42	1	if	if	SCONJ
cet-3928	42	2	misjudgment	misjudgment	NOUN
cet-3928	42	3	is	be	AUX
cet-3928	42	4	considered	consider	VERB
cet-3928	42	5	,	,	PUNCT
cet-3928	42	6	ir	ir	PROPN
cet-3928	42	7	means	mean	VERB
cet-3928	42	8	that	that	SCONJ
cet-3928	42	9	according	accord	VERB
cet-3928	42	10	to	to	ADP
cet-3928	42	11	certain	certain	ADJ
cet-3928	42	12	discriminant	discriminant	NOUN
cet-3928	42	13	rule	rule	VERB
cet-3928	42	14	it	it	PRON
cet-3928	42	15	may	may	AUX
cet-3928	42	16	be	be	AUX
cet-3928	42	17	sentenced	sentence	VERB
cet-3928	42	18	to	to	ADP
cet-3928	42	19	a	a	DET
cet-3928	42	20	collection	collection	NOUN
cet-3928	42	21	of	of	ADP
cet-3928	42	22	all	all	DET
cet-3928	42	23	samples	sample	NOUN
cet-3928	42	24	)	)	PUNCT
cet-3928	42	25	,	,	PUNCT
cet-3928	42	26	2,1	2,1	NUM
cet-3928	42	27	(	(	PUNCT
cet-3928	42	28	kigi	kigi	X
cet-3928	42	29			NUM
cet-3928	42	30	,	,	PUNCT
cet-3928	42	31	)	)	PUNCT
cet-3928	42	32	,	,	PUNCT
cet-3928	42	33	,	,	PUNCT
cet-3928	42	34	2,1	2,1	NUM
cet-3928	42	35	,	,	PUNCT
cet-3928	42	36	)	)	PUNCT
cet-3928	42	37	(	(	PUNCT
cet-3928	42	38	(	(	PUNCT
cet-3928	42	39	kjiijc	kjiijc	NOUN
cet-3928	42	40			PUNCT
cet-3928	42	41	meaning	mean	VERB
cet-3928	42	42	that	that	SCONJ
cet-3928	42	43	it	it	PRON
cet-3928	42	44	will	will	AUX
cet-3928	42	45	from	from	ADP
cet-3928	42	46	the	the	DET
cet-3928	42	47	price	price	NOUN
cet-3928	42	48	of	of	ADP
cet-3928	42	49	the	the	DET
cet-3928	42	50	sample	sample	NOUN
cet-3928	42	51	x	x	PUNCT
cet-3928	42	52	of	of	ADP
cet-3928	42	53	the	the	DET
cet-3928	42	54	ig	ig	PROPN
cet-3928	42	55	be	be	AUX
cet-3928	42	56	mistaken	mistaken	ADJ
cet-3928	42	57	for	for	ADP
cet-3928	42	58	jg	jg	PROPN
cet-3928	42	59	,	,	PUNCT
cet-3928	42	60	then	then	ADV
cet-3928	42	61	0	0	NUM
cet-3928	42	62	)	)	PUNCT
cet-3928	42	63	(	(	PUNCT
cet-3928	42	64	iic	iic	NUM
cet-3928	42	65	.	.	PUNCT
cet-3928	43	1	the	the	DET
cet-3928	43	2	conditional	conditional	ADJ
cet-3928	43	3	probability	probability	NOUN
cet-3928	43	4	of	of	ADP
cet-3928	43	5	sample	sample	NOUN
cet-3928	43	6	x	x	PUNCT
cet-3928	43	7	comes	come	VERB
cet-3928	43	8	from	from	ADP
cet-3928	43	9	ig	ig	PROPN
cet-3928	43	10	misjudgment	misjudgment	NOUN
cet-3928	43	11	of	of	ADP
cet-3928	43	12	jg	jg	PROPN
cet-3928	43	13	is	be	AUX
cet-3928	43	14	dxxfgxrxpijp	dxxfgxrxpijp	PROPN
cet-3928	43	15	jr	jr	PROPN
cet-3928	43	16	iij	iij	PROPN
cet-3928	43	17			PROPN
cet-3928	43	18	)	)	PUNCT
cet-3928	43	19	(	(	PUNCT
cet-3928	43	20	)	)	PUNCT
cet-3928	43	21	(	(	PUNCT
cet-3928	43	22	)	)	PUNCT
cet-3928	43	23	(	(	PUNCT
cet-3928	43	24	.	.	PUNCT
cet-3928	44	1	the	the	DET
cet-3928	44	2	average	average	ADJ
cet-3928	44	3	miscalculation	miscalculation	NOUN
cet-3928	44	4	cost	cost	NOUN
cet-3928	44	5	for	for	ADP
cet-3928	44	6	any	any	DET
cet-3928	44	7	discriminant	discriminant	NOUN
cet-3928	44	8	rule	rule	NOUN
cet-3928	44	9	is	be	AUX
cet-3928	44	10	:	:	PUNCT
cet-3928	44	11	)	)	PUNCT
cet-3928	44	12	(	(	PUNCT
cet-3928	44	13	)	)	PUNCT
cet-3928	44	14	)	)	PUNCT
cet-3928	44	15	(	(	PUNCT
cet-3928	44	16	(	(	PUNCT
cet-3928	44	17	)	)	PUNCT
cet-3928	44	18	)	)	PUNCT
cet-3928	44	19	(	(	PUNCT
cet-3928	44	20	(	(	PUNCT
cet-3928	44	21	)	)	PUNCT
cet-3928	44	22	,	,	PUNCT
cet-3928	44	23	,	,	PUNCT
cet-3928	44	24	(	(	PUNCT
cet-3928	44	25	11	11	NUM
cet-3928	44	26	21	21	NUM
cet-3928	44	27	ijpijcp	ijpijcp	NOUN
cet-3928	44	28	ijcerrrecm	ijcerrrecm	VERB
cet-3928	45	1	k	k	PROPN
cet-3928	45	2	j	j	PROPN
cet-3928	46	1	k	k	INTJ
cet-3928	47	1	i	i	PRON
cet-3928	48	1	i	i	PRON
cet-3928	48	2	k	k	PROPN
cet-3928	48	3			ADV
cet-3928	48	4			NUM
cet-3928	48	5			PROPN
cet-3928	48	6			NOUN
cet-3928	48	7	(	(	PUNCT
cet-3928	48	8	5	5	NUM
cet-3928	48	9	)	)	PUNCT
cet-3928	48	10	380	380	NUM
cet-3928	48	11	the	the	DET
cet-3928	48	12	average	average	ADJ
cet-3928	48	13	misclassification	misclassification	NOUN
cet-3928	48	14	cost	cost	NOUN
cet-3928	48	15	ecm	ecm	NOUN
cet-3928	48	16	to	to	ADP
cet-3928	48	17	minimum	minimum	NOUN
cet-3928	48	18	is	be	AUX
cet-3928	48	19	discriminant	discriminant	ADJ
cet-3928	48	20	rules	rule	NOUN
cet-3928	48	21	igx	igx	PROPN
cet-3928	48	22	if	if	SCONJ
cet-3928	48	23	)	)	PUNCT
cet-3928	48	24	(	(	PUNCT
cet-3928	48	25	)	)	PUNCT
cet-3928	48	26	(	(	PUNCT
cet-3928	48	27	min	min	NOUN
cet-3928	48	28	)	)	PUNCT
cet-3928	48	29	(	(	PUNCT
cet-3928	48	30	)	)	PUNCT
cet-3928	48	31	(	(	PUNCT
cet-3928	48	32	1	1	NUM
cet-3928	48	33	1	1	NUM
cet-3928	48	34	1	1	NUM
cet-3928	48	35	jhcxfpjicxfp	jhcxfpjicxfp	PROPN
cet-3928	48	36	j	j	PROPN
cet-3928	49	1	k	k	PROPN
cet-3928	49	2	j	j	PROPN
cet-3928	50	1	j	j	PROPN
cet-3928	50	2	kh	kh	PROPN
cet-3928	50	3	j	j	PROPN
cet-3928	51	1	k	k	PROPN
cet-3928	51	2	j	j	PROPN
cet-3928	51	3	j	j	PROPN
cet-3928	51	4			DET
cet-3928	51	5			PROPN
cet-3928	51	6			VERB
cet-3928	51	7			NOUN
cet-3928	51	8			PROPN
cet-3928	51	9	.	.	PUNCT
cet-3928	52	1	the	the	DET
cet-3928	52	2	average	average	ADJ
cet-3928	52	3	misclassification	misclassification	NOUN
cet-3928	52	4	cost	cost	NOUN
cet-3928	52	5	if	if	SCONJ
cet-3928	52	6	the	the	DET
cet-3928	52	7	sample	sample	NOUN
cet-3928	52	8	was	be	AUX
cet-3928	52	9	adjusted	adjust	VERB
cet-3928	52	10	to	to	ADP
cet-3928	52	11	the	the	DET
cet-3928	52	12	ig	ig	PROPN
cet-3928	52	13	than	than	SCONJ
cet-3928	52	14	the	the	DET
cet-3928	52	15	average	average	ADJ
cet-3928	52	16	misclassification	misclassification	NOUN
cet-3928	52	17	cost	cost	NOUN
cet-3928	52	18	attributed	attribute	VERB
cet-3928	52	19	to	to	ADP
cet-3928	52	20	other	other	ADJ
cet-3928	52	21	general	general	NOUN
cet-3928	52	22	is	be	AUX
cet-3928	52	23	small	small	ADJ
cet-3928	52	24	,	,	PUNCT
cet-3928	52	25	and	and	CCONJ
cet-3928	52	26	will	will	AUX
cet-3928	52	27	be	be	AUX
cet-3928	52	28	assigned	assign	VERB
cet-3928	52	29	to	to	ADP
cet-3928	52	30	group	group	VERB
cet-3928	52	31	ig	ig	PROPN
cet-3928	52	32	samples	sample	NOUN
cet-3928	52	33	.	.	PUNCT
cet-3928	53	1	definition	definition	NOUN
cet-3928	53	2	2	2	NUM
cet-3928	53	3	fisher	fisher	PROPN
cet-3928	53	4	criterion	criterion	NOUN
cet-3928	53	5	function	function	NOUN
cet-3928	53	6	:	:	PUNCT
cet-3928	53	7	supposing	suppose	VERB
cet-3928	53	8	there	there	PRON
cet-3928	53	9	are	be	VERB
cet-3928	53	10	n	n	PRON
cet-3928	53	11	k	k	ADJ
cet-3928	53	12	-status	-status	PROPN
cet-3928	53	13	naaa	naaa	NOUN
cet-3928	53	14	,	,	PUNCT
cet-3928	53	15	,	,	PUNCT
cet-3928	53	16	,	,	PUNCT
cet-3928	53	17	21	21	NUM
cet-3928	53	18			NOUN
cet-3928	53	19	,	,	PUNCT
cet-3928	53	20	the	the	DET
cet-3928	53	21	sample	sample	NOUN
cet-3928	53	22	taken	take	VERB
cet-3928	53	23	from	from	ADP
cet-3928	53	24	the	the	DET
cet-3928	53	25	overall	overall	ADJ
cet-3928	53	26	ia	ia	NOUN
cet-3928	53	27	is	be	AUX
cet-3928	53	28	denoted	denote	VERB
cet-3928	53	29	as	as	ADP
cet-3928	53	30	)	)	PUNCT
cet-3928	53	31	,	,	PUNCT
cet-3928	53	32	2,1	2,1	NUM
cet-3928	53	33	(	(	PUNCT
cet-3928	53	34	,	,	PUNCT
cet-3928	53	35	,	,	PUNCT
cet-3928	53	36	,	,	PUNCT
cet-3928	53	37	21	21	NUM
cet-3928	53	38	nixxx	nixxx	ADV
cet-3928	53	39	iinii	iinii	ADJ
cet-3928	53	40			ADV
cet-3928	53	41			NOUN
cet-3928	53	42	,	,	PUNCT
cet-3928	53	43	and	and	CCONJ
cet-3928	53	44	the	the	DET
cet-3928	53	45	sample	sample	NOUN
cet-3928	53	46	observation	observation	NOUN
cet-3928	53	47	data	datum	NOUN
cet-3928	53	48	matrix	matrix	NOUN
cet-3928	53	49	and	and	CCONJ
cet-3928	53	50	the	the	DET
cet-3928	53	51	sample	sample	NOUN
cet-3928	53	52	mean	mean	NOUN
cet-3928	53	53	value	value	NOUN
cet-3928	53	54	are	be	AUX
cet-3928	53	55	:	:	PUNCT
cet-3928	53	56			ADJ
cet-3928	53	57			PROPN
cet-3928	54	1			PUNCT
cet-3928	54	2			NOUN
cet-3928	54	3			PROPN
cet-3928	54	4			PROPN
cet-3928	54	5			X
cet-3928	54	6			NOUN
cet-3928	54	7			NOUN
cet-3928	54	8			NOUN
cet-3928	54	9			NOUN
cet-3928	54	10			NOUN
cet-3928	54	11			VERB
cet-3928	54	12			PROPN
cet-3928	54	13	k	k	PROPN
cet-3928	54	14	n	n	PROPN
cet-3928	54	15	knkk	knkk	VERB
cet-3928	55	1	n	n	CCONJ
cet-3928	55	2	xxx	xxx	NOUN
cet-3928	55	3	xxx	xxx	NOUN
cet-3928	55	4	xxx	xxx	NOUN
cet-3928	55	5			NOUN
cet-3928	55	6			ADJ
cet-3928	55	7			NOUN
cet-3928	55	8			NOUN
cet-3928	55	9	21	21	NUM
cet-3928	55	10	22221	22221	NUM
cet-3928	55	11	11211	11211	NUM
cet-3928	55	12	2	2	NUM
cet-3928	55	13	1	1	NUM
cet-3928	55	14	(	(	PUNCT
cet-3928	55	15	6	6	NUM
cet-3928	55	16	)	)	PUNCT
cet-3928	55	17	)	)	PUNCT
cet-3928	55	18	,	,	PUNCT
cet-3928	55	19	2,1	2,1	NUM
cet-3928	55	20	(	(	PUNCT
cet-3928	55	21	1	1	NUM
cet-3928	55	22	1	1	NUM
cet-3928	55	23	kix	kix	NOUN
cet-3928	55	24	n	n	CCONJ
cet-3928	55	25	x	x	PROPN
cet-3928	55	26	in	in	ADP
cet-3928	55	27	j	j	PROPN
cet-3928	55	28	ij	ij	INTJ
cet-3928	55	29	i	i	PRON
cet-3928	56	1	i	i	PRON
cet-3928	56	2			X
cet-3928	56	3			X
cet-3928	56	4			NUM
cet-3928	56	5	(	(	PUNCT
cet-3928	56	6	7	7	NUM
cet-3928	56	7	)	)	PUNCT
cet-3928	57	1			VERB
cet-3928	57	2			NOUN
cet-3928	58	1			NUM
cet-3928	59	1			NOUN
cet-3928	60	1	k	k	INTJ
cet-3928	61	1	i	i	PRON
cet-3928	61	2	k	k	PROPN
cet-3928	62	1	j	j	PROPN
cet-3928	62	2	ijx	ijx	NOUN
cet-3928	62	3	n	n	PROPN
cet-3928	62	4	x	x	SYM
cet-3928	62	5	1	1	NUM
cet-3928	62	6	1	1	NUM
cet-3928	62	7	1	1	NUM
cet-3928	62	8	(	(	PUNCT
cet-3928	62	9	8)	8)	NUM
cet-3928	62	10	assuming	assume	VERB
cet-3928	62	11	two	two	NUM
cet-3928	62	12	classification	classification	NOUN
cet-3928	62	13	problems	problem	NOUN
cet-3928	62	14	21/	21/	PROPN
cet-3928	62	15	ww	ww	PROPN
cet-3928	62	16	,	,	PUNCT
cet-3928	62	17	there	there	PRON
cet-3928	62	18	are	be	VERB
cet-3928	62	19	n	n	PRON
cet-3928	62	20	training	training	NOUN
cet-3928	62	21	samples	sample	NOUN
cet-3928	62	22	)	)	PUNCT
cet-3928	62	23	,	,	PUNCT
cet-3928	62	24	....	....	PUNCT
cet-3928	62	25	,	,	PUNCT
cet-3928	62	26	2,1	2,1	NUM
cet-3928	62	27	(	(	PUNCT
cet-3928	62	28	nkxk	nkxk	VERB
cet-3928	62	29			PROPN
cet-3928	62	30	,	,	PUNCT
cet-3928	62	31	where	where	SCONJ
cet-3928	62	32	1n	1n	NUM
cet-3928	62	33	samples	sample	NOUN
cet-3928	62	34	from	from	ADP
cet-3928	62	35	type	type	NOUN
cet-3928	62	36	iw	iw	PROPN
cet-3928	62	37	,	,	PUNCT
cet-3928	62	38	2n	2n	NUM
cet-3928	62	39	samples	sample	NOUN
cet-3928	62	40	from	from	ADP
cet-3928	62	41	type	type	NOUN
cet-3928	62	42	jw	jw	PROPN
cet-3928	62	43	.	.	PUNCT
cet-3928	63	1	two	two	NUM
cet-3928	63	2	types	type	NOUN
cet-3928	63	3	of	of	ADP
cet-3928	63	4	training	training	NOUN
cet-3928	63	5	samples	sample	NOUN
cet-3928	63	6	were	be	AUX
cet-3928	63	7	used	use	VERB
cet-3928	63	8	to	to	PART
cet-3928	63	9	construct	construct	VERB
cet-3928	63	10	the	the	DET
cet-3928	63	11	subset	subset	NOUN
cet-3928	63	12	of	of	ADP
cet-3928	63	13	the	the	DET
cet-3928	63	14	training	training	NOUN
cet-3928	63	15	samples	sample	NOUN
cet-3928	63	16	1x	1x	NUM
cet-3928	63	17	and	and	CCONJ
cet-3928	63	18	2x	2x	NUM
cet-3928	63	19	.	.	PUNCT
cet-3928	64	1	make	make	VERB
cet-3928	64	2	k	k	PROPN
cet-3928	64	3	t	t	PROPN
cet-3928	64	4	k	k	PROPN
cet-3928	64	5	xwy	xwy	PROPN
cet-3928	64	6			PROPN
cet-3928	64	7	,	,	PUNCT
cet-3928	64	8	nk	nk	PROPN
cet-3928	64	9	,	,	PUNCT
cet-3928	64	10	...	...	PUNCT
cet-3928	64	11	,	,	PUNCT
cet-3928	64	12	2,1	2,1	NUM
cet-3928	64	13	,	,	PUNCT
cet-3928	64	14	ky	ky	PROPN
cet-3928	64	15	as	as	ADP
cet-3928	64	16	the	the	DET
cet-3928	64	17	projection	projection	NOUN
cet-3928	64	18	of	of	ADP
cet-3928	64	19	kx	kx	PROPN
cet-3928	64	20	.	.	PUNCT
cet-3928	65	1	projection	projection	PROPN
cet-3928	65	2	within	within	ADP
cet-3928	65	3	class	class	NOUN
cet-3928	65	4	alienation	alienation	NOUN
cet-3928	65	5	sum	sum	NOUN
cet-3928	65	6	of	of	ADP
cet-3928	65	7	squared	square	VERB
cet-3928	65	8	residuals	residual	NOUN
cet-3928	65	9	and	and	CCONJ
cet-3928	65	10	class	class	NOUN
cet-3928	65	11	from	from	ADP
cet-3928	65	12	the	the	DET
cet-3928	65	13	sum	sum	NOUN
cet-3928	65	14	of	of	ADP
cet-3928	65	15	squared	square	VERB
cet-3928	65	16	residuals	residual	NOUN
cet-3928	65	17	are	be	AUX
cet-3928	65	18	respectively	respectively	ADV
cet-3928	65	19	:	:	PUNCT
cet-3928	65	20	wxxxxwyyns	wxxxxwyyns	PROPN
cet-3928	66	1	k	k	INTJ
cet-3928	67	1	i	i	PRON
cet-3928	67	2	t	t	PROPN
cet-3928	67	3	ii	ii	PROPN
cet-3928	68	1	t	t	INTJ
cet-3928	69	1	i	i	PRON
cet-3928	69	2	k	k	PROPN
cet-3928	70	1	i	i	PRON
cet-3928	70	2	ig	ig	PROPN
cet-3928	70	3	]	]	X
cet-3928	70	4	)	)	PUNCT
cet-3928	70	5	)	)	PUNCT
cet-3928	70	6	(	(	PUNCT
cet-3928	70	7	(	(	PUNCT
cet-3928	70	8	[	[	X
cet-3928	70	9	)	)	PUNCT
cet-3928	70	10	(	(	PUNCT
cet-3928	70	11	1	1	NUM
cet-3928	70	12	2	2	NUM
cet-3928	70	13	1	1	NUM
cet-3928	70	14			ADP
cet-3928	70	15			NUM
cet-3928	70	16			PROPN
cet-3928	70	17	(	(	PUNCT
cet-3928	70	18	9	9	NUM
cet-3928	70	19	)	)	PUNCT
cet-3928	70	20			PROPN
cet-3928	71	1			NUM
cet-3928	71	2			NUM
cet-3928	71	3			NUM
cet-3928	71	4			PROPN
cet-3928	71	5	k	k	PROPN
cet-3928	72	1	i	i	PRON
cet-3928	72	2	n	n	VERB
cet-3928	72	3	j	j	NOUN
cet-3928	73	1	i	i	PRON
cet-3928	73	2	t	t	VERB
cet-3928	74	1	ij	ij	INTJ
cet-3928	74	2	t	t	PROPN
cet-3928	75	1	k	k	PROPN
cet-3928	75	2	i	i	PRON
cet-3928	75	3	n	n	PROPN
cet-3928	75	4	j	j	PROPN
cet-3928	75	5	iije	iije	PROPN
cet-3928	75	6	ii	ii	PROPN
cet-3928	75	7	ywxwyys	ywxwyys	NOUN
cet-3928	76	1	1	1	NUM
cet-3928	76	2	1	1	NUM
cet-3928	76	3	2	2	NUM
cet-3928	76	4	1	1	NUM
cet-3928	76	5	1	1	NUM
cet-3928	76	6	2	2	NUM
cet-3928	76	7	)	)	PUNCT
cet-3928	76	8	(	(	PUNCT
cet-3928	76	9	)	)	PUNCT
cet-3928	76	10	(	(	PUNCT
cet-3928	76	11	(	(	PUNCT
cet-3928	76	12	10	10	NUM
cet-3928	76	13	)	)	PUNCT
cet-3928	76	14	obviously	obviously	ADV
cet-3928	76	15	,	,	PUNCT
cet-3928	76	16	the	the	DET
cet-3928	76	17	sum	sum	NOUN
cet-3928	76	18	of	of	ADP
cet-3928	76	19	squared	square	VERB
cet-3928	76	20	residuals	residual	NOUN
cet-3928	76	21	in	in	ADP
cet-3928	76	22	a	a	DET
cet-3928	76	23	class	class	NOUN
cet-3928	76	24	reflects	reflect	VERB
cet-3928	76	25	test	test	NOUN
cet-3928	76	26	results	result	NOUN
cet-3928	76	27	caused	cause	VERB
cet-3928	76	28	by	by	ADP
cet-3928	76	29	many	many	ADJ
cet-3928	76	30	kinds	kind	NOUN
cet-3928	76	31	of	of	ADP
cet-3928	76	32	various	various	ADJ
cet-3928	76	33	random	random	ADJ
cet-3928	76	34	factors	factor	NOUN
cet-3928	76	35	in	in	ADP
cet-3928	76	36	the	the	DET
cet-3928	76	37	process	process	NOUN
cet-3928	76	38	of	of	ADP
cet-3928	76	39	the	the	DET
cet-3928	76	40	test	test	NOUN
cet-3928	76	41	error	error	NOUN
cet-3928	76	42	,	,	PUNCT
cet-3928	76	43	such	such	DET
cet-3928	76	44	an	an	DET
cet-3928	76	45	alienation	alienation	NOUN
cet-3928	76	46	sum	sum	NOUN
cet-3928	76	47	of	of	ADP
cet-3928	76	48	squared	square	VERB
cet-3928	76	49	residuals	residual	NOUN
cet-3928	76	50	reflects	reflect	VERB
cet-3928	76	51	the	the	DET
cet-3928	76	52	degree	degree	NOUN
cet-3928	76	53	of	of	ADP
cet-3928	76	54	difference	difference	NOUN
cet-3928	76	55	between	between	ADP
cet-3928	76	56	various	various	ADJ
cet-3928	76	57	kinds	kind	NOUN
cet-3928	76	58	of	of	ADP
cet-3928	76	59	samples	sample	NOUN
cet-3928	76	60	,	,	PUNCT
cet-3928	76	61	and	and	CCONJ
cet-3928	77	1	the	the	DET
cet-3928	77	2	system	system	NOUN
cet-3928	77	3	error	error	NOUN
cet-3928	77	4	caused	cause	VERB
cet-3928	77	5	by	by	ADP
cet-3928	77	6	different	different	ADJ
cet-3928	77	7	levels	level	NOUN
cet-3928	77	8	of	of	ADP
cet-3928	77	9	variation	variation	NOUN
cet-3928	77	10	factors	factor	NOUN
cet-3928	77	11	.	.	PUNCT
cet-3928	78	1	if	if	SCONJ
cet-3928	78	2	it	it	PRON
cet-3928	78	3	can	can	AUX
cet-3928	78	4	make	make	VERB
cet-3928	78	5	the	the	DET
cet-3928	78	6	space	space	NOUN
cet-3928	78	7	behind	behind	ADP
cet-3928	78	8	the	the	DET
cet-3928	78	9	projection	projection	NOUN
cet-3928	78	10	,	,	PUNCT
cet-3928	78	11	classes	class	NOUN
cet-3928	78	12	within	within	ADP
cet-3928	78	13	the	the	DET
cet-3928	78	14	sample	sample	NOUN
cet-3928	78	15	concentration	concentration	NOUN
cet-3928	78	16	and	and	CCONJ
cet-3928	78	17	sample	sample	NOUN
cet-3928	78	18	separation	separation	NOUN
cet-3928	78	19	between	between	ADP
cet-3928	78	20	classes	class	NOUN
cet-3928	78	21	,	,	PUNCT
cet-3928	78	22	it	it	PRON
cet-3928	78	23	can	can	AUX
cet-3928	78	24	achieve	achieve	VERB
cet-3928	78	25	the	the	DET
cet-3928	78	26	purpose	purpose	NOUN
cet-3928	78	27	.	.	PUNCT
cet-3928	79	1	if	if	SCONJ
cet-3928	79	2	the	the	DET
cet-3928	79	3	effect	effect	NOUN
cet-3928	79	4	of	of	ADP
cet-3928	79	5	the	the	DET
cet-3928	79	6	projection	projection	NOUN
cet-3928	79	7	is	be	AUX
cet-3928	79	8	good	good	ADJ
cet-3928	79	9	,	,	PUNCT
cet-3928	79	10	then	then	ADV
cet-3928	79	11	e	e	X
cet-3928	79	12	g	g	NOUN
cet-3928	79	13	s	s	PROPN
cet-3928	79	14	s	s	X
cet-3928	79	15	f	f	NOUN
cet-3928	79	16			PRON
cet-3928	79	17	should	should	AUX
cet-3928	79	18	be	be	AUX
cet-3928	79	19	large	large	ADJ
cet-3928	79	20	(	(	PUNCT
cet-3928	79	21	sun	sun	PROPN
cet-3928	79	22	et	et	PROPN
cet-3928	79	23	al	al	PROPN
cet-3928	79	24	,	,	PUNCT
cet-3928	79	25	2011	2011	NUM
cet-3928	79	26	;	;	PUNCT
cet-3928	79	27	tseng	tseng	PROPN
cet-3928	79	28	et	et	PROPN
cet-3928	79	29	al	al	PROPN
cet-3928	79	30	,	,	PUNCT
cet-3928	79	31	2012	2012	NUM
cet-3928	79	32	)	)	PUNCT
cet-3928	79	33	.	.	PUNCT
cet-3928	80	1	the	the	DET
cet-3928	80	2	main	main	ADJ
cet-3928	80	3	idea	idea	NOUN
cet-3928	80	4	of	of	ADP
cet-3928	80	5	this	this	DET
cet-3928	80	6	algorithm	algorithm	NOUN
cet-3928	80	7	is	be	AUX
cet-3928	80	8	to	to	PART
cet-3928	80	9	use	use	VERB
cet-3928	80	10	the	the	DET
cet-3928	80	11	transformation	transformation	NOUN
cet-3928	80	12	matrix	matrix	NOUN
cet-3928	80	13	,	,	PUNCT
cet-3928	80	14	to	to	PART
cet-3928	80	15	transform	transform	VERB
cet-3928	80	16	the	the	DET
cet-3928	80	17	original	original	ADJ
cet-3928	80	18	training	training	NOUN
cet-3928	80	19	sample	sample	NOUN
cet-3928	80	20	,	,	PUNCT
cet-3928	80	21	project	project	NOUN
cet-3928	80	22	to	to	ADP
cet-3928	80	23	a	a	DET
cet-3928	80	24	new	new	ADJ
cet-3928	80	25	sample	sample	NOUN
cet-3928	80	26	space	space	NOUN
cet-3928	80	27	,	,	PUNCT
cet-3928	80	28	classify	classify	VERB
cet-3928	80	29	in	in	ADP
cet-3928	80	30	the	the	DET
cet-3928	80	31	projection	projection	NOUN
cet-3928	80	32	of	of	ADP
cet-3928	80	33	the	the	DET
cet-3928	80	34	new	new	ADJ
cet-3928	80	35	sample	sample	NOUN
cet-3928	80	36	space	space	NOUN
cet-3928	80	37	for	for	ADP
cet-3928	80	38	learning	learn	VERB
cet-3928	80	39	classification	classification	NOUN
cet-3928	80	40	.	.	PUNCT
cet-3928	81	1	among	among	ADP
cet-3928	81	2	the	the	DET
cet-3928	81	3	original	original	ADJ
cet-3928	81	4	sample	sample	NOUN
cet-3928	81	5	properties	property	NOUN
cet-3928	81	6	,	,	PUNCT
cet-3928	81	7	there	there	PRON
cet-3928	81	8	may	may	AUX
cet-3928	81	9	be	be	AUX
cet-3928	81	10	some	some	DET
cet-3928	81	11	dependence	dependence	NOUN
cet-3928	81	12	between	between	ADP
cet-3928	81	13	any	any	DET
cet-3928	81	14	two	two	NUM
cet-3928	81	15	attributes	attribute	NOUN
cet-3928	81	16	,	,	PUNCT
cet-3928	81	17	but	but	CCONJ
cet-3928	81	18	in	in	ADP
cet-3928	81	19	the	the	DET
cet-3928	81	20	projection	projection	NOUN
cet-3928	81	21	in	in	ADP
cet-3928	81	22	the	the	DET
cet-3928	81	23	new	new	ADJ
cet-3928	81	24	sample	sample	NOUN
cet-3928	81	25	space	space	NOUN
cet-3928	81	26	,	,	PUNCT
cet-3928	81	27	the	the	DET
cet-3928	81	28	properties	property	NOUN
cet-3928	81	29	of	of	ADP
cet-3928	81	30	the	the	DET
cet-3928	81	31	new	new	ADJ
cet-3928	81	32	sample	sample	NOUN
cet-3928	81	33	are	be	AUX
cet-3928	81	34	assumed	assume	VERB
cet-3928	81	35	to	to	PART
cet-3928	81	36	be	be	AUX
cet-3928	81	37	independent	independent	ADJ
cet-3928	81	38	of	of	ADP
cet-3928	81	39	each	each	DET
cet-3928	81	40	other	other	ADJ
cet-3928	81	41	.	.	PUNCT
cet-3928	82	1	through	through	ADP
cet-3928	82	2	the	the	DET
cet-3928	82	3	transformation	transformation	NOUN
cet-3928	82	4	it	it	PRON
cet-3928	82	5	can	can	AUX
cet-3928	82	6	indicate	indicate	VERB
cet-3928	82	7	in	in	ADP
cet-3928	82	8	the	the	DET
cet-3928	82	9	measurement	measurement	NOUN
cet-3928	82	10	of	of	ADP
cet-3928	82	11	a	a	DET
cet-3928	82	12	high	high	ADJ
cet-3928	82	13	dimension	dimension	NOUN
cet-3928	82	14	space	space	NOUN
cet-3928	82	15	model	model	NOUN
cet-3928	82	16	into	into	ADP
cet-3928	82	17	indicating	indicate	VERB
cet-3928	82	18	the	the	DET
cet-3928	82	19	characteristics	characteristic	NOUN
cet-3928	82	20	of	of	ADP
cet-3928	82	21	a	a	DET
cet-3928	82	22	low	low	ADJ
cet-3928	82	23	dimension	dimension	NOUN
cet-3928	82	24	space	space	NOUN
cet-3928	82	25	model	model	NOUN
cet-3928	82	26	in	in	ADP
cet-3928	82	27	this	this	DET
cet-3928	82	28	way	way	NOUN
cet-3928	82	29	it	it	PRON
cet-3928	82	30	can	can	AUX
cet-3928	82	31	effectively	effectively	ADV
cet-3928	82	32	realize	realize	VERB
cet-3928	82	33	classification	classification	NOUN
cet-3928	82	34	recognition	recognition	NOUN
cet-3928	82	35	,	,	PUNCT
cet-3928	82	36	and	and	CCONJ
cet-3928	82	37	can	can	AUX
cet-3928	82	38	more	more	ADV
cet-3928	82	39	accurately	accurately	ADV
cet-3928	82	40	reflect	reflect	VERB
cet-3928	82	41	the	the	DET
cet-3928	82	42	characteristics	characteristic	NOUN
cet-3928	82	43	of	of	ADP
cet-3928	82	44	the	the	DET
cet-3928	82	45	nature	nature	NOUN
cet-3928	82	46	of	of	ADP
cet-3928	82	47	classification	classification	NOUN
cet-3928	82	48	(	(	PUNCT
cet-3928	82	49	thalayasingam	thalayasingam	ADP
cet-3928	82	50	,	,	PUNCT
cet-3928	82	51	2012	2012	NUM
cet-3928	82	52	;	;	PUNCT
cet-3928	82	53	yang	yang	PROPN
cet-3928	82	54	and	and	CCONJ
cet-3928	82	55	wu	wu	PROPN
cet-3928	82	56	,	,	PUNCT
cet-3928	82	57	2012	2012	NUM
cet-3928	82	58	)	)	PUNCT
cet-3928	82	59	.	.	PUNCT
cet-3928	83	1	381	381	NUM
cet-3928	83	2	3	3	NUM
cet-3928	83	3	.	.	PUNCT
cet-3928	83	4	case	case	NOUN
cet-3928	83	5	analysis	analysis	NOUN
cet-3928	83	6	a	a	DET
cet-3928	83	7	value	value	NOUN
cet-3928	83	8	-	-	PUNCT
cet-3928	83	9	added	add	VERB
cet-3928	83	10	service	service	NOUN
cet-3928	83	11	operator	operator	NOUN
cet-3928	83	12	is	be	AUX
cet-3928	83	13	on	on	ADP
cet-3928	83	14	the	the	DET
cet-3928	83	15	basis	basis	NOUN
cet-3928	83	16	of	of	ADP
cet-3928	83	17	the	the	DET
cet-3928	83	18	basic	basic	ADJ
cet-3928	83	19	telecom	telecom	NOUN
cet-3928	83	20	voice	voice	NOUN
cet-3928	83	21	business	business	NOUN
cet-3928	83	22	,	,	PUNCT
cet-3928	83	23	according	accord	VERB
cet-3928	83	24	to	to	ADP
cet-3928	83	25	different	different	ADJ
cet-3928	83	26	user	user	NOUN
cet-3928	83	27	groups	group	NOUN
cet-3928	83	28	and	and	CCONJ
cet-3928	83	29	the	the	DET
cet-3928	83	30	opening	opening	NOUN
cet-3928	83	31	of	of	ADP
cet-3928	83	32	the	the	DET
cet-3928	83	33	market	market	NOUN
cet-3928	83	34	demand	demand	NOUN
cet-3928	83	35	for	for	ADP
cet-3928	83	36	the	the	DET
cet-3928	83	37	user	user	NOUN
cet-3928	83	38	to	to	PART
cet-3928	83	39	choose	choose	VERB
cet-3928	83	40	to	to	PART
cet-3928	83	41	use	use	VERB
cet-3928	83	42	the	the	DET
cet-3928	83	43	business	business	NOUN
cet-3928	83	44	’s	’s	PART
cet-3928	83	45	service	service	NOUN
cet-3928	83	46	.	.	PUNCT
cet-3928	84	1	valueadded	valueadde	VERB
cet-3928	84	2	services	service	NOUN
cet-3928	84	3	are	be	AUX
cet-3928	84	4	the	the	DET
cet-3928	84	5	result	result	NOUN
cet-3928	84	6	of	of	ADP
cet-3928	84	7	market	market	NOUN
cet-3928	84	8	segmentation	segmentation	NOUN
cet-3928	84	9	,	,	PUNCT
cet-3928	84	10	and	and	CCONJ
cet-3928	84	11	value	value	NOUN
cet-3928	84	12	-	-	PUNCT
cet-3928	84	13	added	add	VERB
cet-3928	84	14	service	service	NOUN
cet-3928	84	15	operators	operator	NOUN
cet-3928	84	16	provide	provide	VERB
cet-3928	84	17	customers	customer	NOUN
cet-3928	84	18	a	a	DET
cet-3928	84	19	higher	high	ADJ
cet-3928	84	20	level	level	NOUN
cet-3928	84	21	of	of	ADP
cet-3928	84	22	information	information	NOUN
cet-3928	84	23	demand	demand	NOUN
cet-3928	84	24	(	(	PUNCT
cet-3928	84	25	tseng	tseng	PROPN
cet-3928	84	26	p	p	PROPN
cet-3928	84	27	c	c	PROPN
cet-3928	84	28	,	,	PUNCT
cet-3928	84	29	woung	woung	ADJ
cet-3928	84	30	l	l	PROPN
cet-3928	84	31	c	c	PROPN
cet-3928	84	32	,	,	PUNCT
cet-3928	84	33	tseng	tseng	PROPN
cet-3928	84	34	g	g	PROPN
cet-3928	84	35	l	l	PROPN
cet-3928	84	36	,	,	PUNCT
cet-3928	84	37	2012	2012	NUM
cet-3928	84	38	;	;	PUNCT
cet-3928	84	39	yoon	yoon	PROPN
cet-3928	84	40	i	i	PROPN
cet-3928	84	41	p	p	PROPN
cet-3928	84	42	b	b	PROPN
cet-3928	84	43	,	,	PUNCT
cet-3928	84	44	2014	2014	NUM
cet-3928	84	45	)	)	PUNCT
cet-3928	84	46	.	.	PUNCT
cet-3928	85	1	therefore	therefore	ADV
cet-3928	85	2	,	,	PUNCT
cet-3928	85	3	it	it	PRON
cet-3928	85	4	must	must	AUX
cet-3928	85	5	provide	provide	VERB
cet-3928	85	6	better	well	ADJ
cet-3928	85	7	,	,	PUNCT
cet-3928	85	8	more	more	ADV
cet-3928	85	9	thoughtful	thoughtful	ADJ
cet-3928	85	10	and	and	CCONJ
cet-3928	85	11	more	more	ADV
cet-3928	85	12	diverse	diverse	ADJ
cet-3928	85	13	services	service	NOUN
cet-3928	85	14	,	,	PUNCT
cet-3928	85	15	in	in	ADP
cet-3928	85	16	order	order	NOUN
cet-3928	85	17	to	to	PART
cet-3928	85	18	meet	meet	VERB
cet-3928	85	19	different	different	ADJ
cet-3928	85	20	customers	customer	NOUN
cet-3928	85	21	personalized	personalize	VERB
cet-3928	85	22	requirements	requirement	NOUN
cet-3928	85	23	.	.	PUNCT
cet-3928	86	1	as	as	SCONJ
cet-3928	86	2	the	the	DET
cet-3928	86	3	communication	communication	NOUN
cet-3928	86	4	network	network	NOUN
cet-3928	86	5	of	of	ADP
cet-3928	86	6	broadband	broadband	NOUN
cet-3928	86	7	,	,	PUNCT
cet-3928	86	8	intelligent	intelligent	ADJ
cet-3928	86	9	,	,	PUNCT
cet-3928	86	10	integrated	integrate	VERB
cet-3928	86	11	,	,	PUNCT
cet-3928	86	12	personal	personal	ADJ
cet-3928	86	13	direction	direction	NOUN
cet-3928	86	14	,	,	PUNCT
cet-3928	86	15	the	the	DET
cet-3928	86	16	boundaries	boundary	NOUN
cet-3928	86	17	of	of	ADP
cet-3928	86	18	value	value	NOUN
cet-3928	86	19	-	-	PUNCT
cet-3928	86	20	added	add	VERB
cet-3928	86	21	service	service	NOUN
cet-3928	86	22	and	and	CCONJ
cet-3928	86	23	the	the	DET
cet-3928	86	24	basic	basic	ADJ
cet-3928	86	25	business	business	NOUN
cet-3928	86	26	are	be	AUX
cet-3928	86	27	becoming	becoming	AUX
cet-3928	86	28	increasingly	increasingly	ADV
cet-3928	86	29	blurred	blur	VERB
cet-3928	86	30	,	,	PUNCT
cet-3928	86	31	development	development	NOUN
cet-3928	86	32	of	of	ADP
cet-3928	86	33	more	more	ADV
cet-3928	86	34	effective	effective	ADJ
cet-3928	86	35	,	,	PUNCT
cet-3928	86	36	more	more	ADJ
cet-3928	86	37	value	value	NOUN
cet-3928	86	38	creating	create	VERB
cet-3928	86	39	business	business	NOUN
cet-3928	86	40	will	will	AUX
cet-3928	86	41	always	always	ADV
cet-3928	86	42	be	be	AUX
cet-3928	86	43	the	the	DET
cet-3928	86	44	result	result	NOUN
cet-3928	86	45	of	of	ADP
cet-3928	86	46	the	the	DET
cet-3928	86	47	telecom	telecom	NOUN
cet-3928	86	48	industry	industry	NOUN
cet-3928	86	49	looking	look	VERB
cet-3928	86	50	for	for	ADP
cet-3928	86	51	new	new	ADJ
cet-3928	86	52	economic	economic	ADJ
cet-3928	86	53	growth	growth	NOUN
cet-3928	86	54	points	point	NOUN
cet-3928	86	55	,	,	PUNCT
cet-3928	86	56	this	this	PRON
cet-3928	86	57	is	be	AUX
cet-3928	86	58	the	the	DET
cet-3928	86	59	focus	focus	NOUN
cet-3928	86	60	of	of	ADP
cet-3928	86	61	the	the	DET
cet-3928	86	62	competition	competition	NOUN
cet-3928	86	63	between	between	ADP
cet-3928	86	64	them	they	PRON
cet-3928	86	65	(	(	PUNCT
cet-3928	86	66	yu	yu	PROPN
cet-3928	86	67	et	et	PROPN
cet-3928	86	68	al	al	PROPN
cet-3928	86	69	,	,	PUNCT
cet-3928	86	70	2014	2014	NUM
cet-3928	86	71	)	)	PUNCT
cet-3928	86	72	.	.	PUNCT
cet-3928	87	1	this	this	DET
cet-3928	87	2	paper	paper	NOUN
cet-3928	87	3	is	be	AUX
cet-3928	87	4	based	base	VERB
cet-3928	87	5	on	on	ADP
cet-3928	87	6	using	use	VERB
cet-3928	87	7	the	the	DET
cet-3928	87	8	bayesian	bayesian	NOUN
cet-3928	87	9	and	and	CCONJ
cet-3928	87	10	fisher	fisher	PROPN
cet-3928	87	11	algorithms	algorithm	NOUN
cet-3928	87	12	for	for	ADP
cet-3928	87	13	analysis	analysis	NOUN
cet-3928	87	14	of	of	ADP
cet-3928	87	15	customer	customer	NOUN
cet-3928	87	16	behavior	behavior	NOUN
cet-3928	87	17	data	datum	NOUN
cet-3928	87	18	,	,	PUNCT
cet-3928	87	19	identifying	identify	VERB
cet-3928	87	20	the	the	DET
cet-3928	87	21	customer	customer	NOUN
cet-3928	87	22	's	's	PART
cet-3928	87	23	behavior	behavior	NOUN
cet-3928	87	24	characteristics	characteristic	NOUN
cet-3928	87	25	,	,	PUNCT
cet-3928	87	26	through	through	ADP
cet-3928	87	27	the	the	DET
cet-3928	87	28	customer	customer	NOUN
cet-3928	87	29	providing	provide	VERB
cet-3928	87	30	information	information	NOUN
cet-3928	87	31	about	about	ADP
cet-3928	87	32	his	his	PRON
cet-3928	87	33	own	own	ADJ
cet-3928	87	34	hobbies	hobby	NOUN
cet-3928	87	35	and	and	CCONJ
cet-3928	87	36	value	value	NOUN
cet-3928	87	37	-	-	PUNCT
cet-3928	87	38	added	add	VERB
cet-3928	87	39	services	service	NOUN
cet-3928	87	40	.	.	PUNCT
cet-3928	88	1	this	this	PRON
cet-3928	88	2	increases	increase	VERB
cet-3928	88	3	customer	customer	NOUN
cet-3928	88	4	loyalty	loyalty	NOUN
cet-3928	88	5	,	,	PUNCT
cet-3928	88	6	reduces	reduce	VERB
cet-3928	88	7	marketing	marketing	NOUN
cet-3928	88	8	costs	cost	NOUN
cet-3928	88	9	,	,	PUNCT
cet-3928	88	10	and	and	CCONJ
cet-3928	88	11	enhances	enhance	VERB
cet-3928	88	12	the	the	DET
cet-3928	88	13	competitiveness	competitiveness	NOUN
cet-3928	88	14	of	of	ADP
cet-3928	88	15	the	the	DET
cet-3928	88	16	enterprises	enterprise	NOUN
cet-3928	88	17	.	.	PUNCT
cet-3928	89	1	the	the	DET
cet-3928	89	2	original	original	ADJ
cet-3928	89	3	data	data	NOUN
cet-3928	89	4	is	be	AUX
cet-3928	89	5	from	from	ADP
cet-3928	89	6	some	some	DET
cet-3928	89	7	operators	operator	NOUN
cet-3928	89	8	in	in	ADP
cet-3928	89	9	harbin	harbin	PROPN
cet-3928	89	10	in	in	ADP
cet-3928	89	11	heilongjiang	heilongjiang	PROPN
cet-3928	89	12	province	province	NOUN
cet-3928	89	13	,	,	PUNCT
cet-3928	89	14	and	and	CCONJ
cet-3928	89	15	from	from	ADP
cet-3928	89	16	sample	sample	NOUN
cet-3928	89	17	data	datum	NOUN
cet-3928	89	18	for	for	ADP
cet-3928	89	19	the	the	DET
cet-3928	89	20	data	data	NOUN
cet-3928	89	21	flow	flow	NOUN
cet-3928	89	22	gas	gas	NOUN
cet-3928	89	23	package	package	NOUN
cet-3928	89	24	users	user	NOUN
cet-3928	89	25	in	in	ADP
cet-3928	89	26	march	march	PROPN
cet-3928	89	27	.	.	PUNCT
cet-3928	90	1	figure	figure	NOUN
cet-3928	90	2	1	1	NUM
cet-3928	90	3	:	:	PUNCT
cet-3928	90	4	algorithm	algorithm	NOUN
cet-3928	90	5	flow	flow	NOUN
cet-3928	90	6	chart	chart	NOUN
cet-3928	90	7	3.1	3.1	NUM
cet-3928	90	8	the	the	DET
cet-3928	90	9	standardization	standardization	NOUN
cet-3928	90	10	of	of	ADP
cet-3928	90	11	the	the	DET
cet-3928	90	12	data	datum	NOUN
cet-3928	90	13	processing	processing	NOUN
cet-3928	90	14	because	because	SCONJ
cet-3928	90	15	the	the	DET
cet-3928	90	16	input	input	NOUN
cet-3928	90	17	samples	sample	NOUN
cet-3928	90	18	belong	belong	VERB
cet-3928	90	19	to	to	ADP
cet-3928	90	20	different	different	ADJ
cet-3928	90	21	dimensions	dimension	NOUN
cet-3928	90	22	,	,	PUNCT
cet-3928	90	23	all	all	DET
cet-3928	90	24	the	the	DET
cet-3928	90	25	input	input	NOUN
cet-3928	90	26	samples	sample	NOUN
cet-3928	90	27	,	,	PUNCT
cet-3928	90	28	such	such	ADJ
cet-3928	90	29	as	as	ADP
cet-3928	90	30	talk_fee	talk_fee	PROPN
cet-3928	90	31	,	,	PUNCT
cet-3928	90	32	city_phone_fee	city_phone_fee	PROPN
cet-3928	90	33	,	,	PUNCT
cet-3928	90	34	arpu_fee	arpu_fee	NOUN
cet-3928	90	35	are	be	AUX
cet-3928	90	36	normalized	normalize	VERB
cet-3928	90	37	and	and	CCONJ
cet-3928	90	38	transformed	transform	VERB
cet-3928	90	39	into	into	ADP
cet-3928	90	40	0~1	0~1	PRON
cet-3928	90	41	.	.	PUNCT
cet-3928	91	1	using	use	VERB
cet-3928	91	2	the	the	DET
cet-3928	91	3	method	method	NOUN
cet-3928	91	4	of	of	ADP
cet-3928	91	5	proportional	proportional	ADJ
cet-3928	91	6	compression	compression	NOUN
cet-3928	91	7	,	,	PUNCT
cet-3928	91	8	the	the	DET
cet-3928	91	9	specific	specific	ADJ
cet-3928	91	10	formula	formula	NOUN
cet-3928	91	11	is	be	AUX
cet-3928	91	12	:	:	PUNCT
cet-3928	91	13	max	max	PROPN
cet-3928	91	14	min	min	PROPN
cet-3928	91	15	min	min	PROPN
cet-3928	91	16	(	(	PUNCT
cet-3928	91	17	min	min	PROPN
cet-3928	91	18	)	)	PUNCT
cet-3928	91	19	max	max	PROPN
cet-3928	91	20	min	min	PROPN
cet-3928	91	21	t	t	PROPN
cet-3928	91	22	t	t	PROPN
cet-3928	91	23	t	t	PROPN
cet-3928	91	24	t	t	NOUN
cet-3928	91	25	x	x	PUNCT
cet-3928	91	26	x	x	PUNCT
cet-3928	91	27	x	x	PUNCT
cet-3928	91	28	x	x	SYM
cet-3928	91	29			PROPN
cet-3928	91	30			NUM
cet-3928	91	31			PUNCT
cet-3928	91	32			PROPN
cet-3928	91	33			NOUN
cet-3928	91	34	(	(	PUNCT
cet-3928	91	35	11	11	NUM
cet-3928	91	36	)	)	PUNCT
cet-3928	91	37	here	here	ADV
cet-3928	91	38	,	,	PUNCT
cet-3928	91	39	x	x	X
cet-3928	91	40	is	be	AUX
cet-3928	91	41	the	the	DET
cet-3928	91	42	original	original	ADJ
cet-3928	91	43	data	datum	NOUN
cet-3928	91	44	,	,	PUNCT
cet-3928	91	45	and	and	CCONJ
cet-3928	91	46	the	the	DET
cet-3928	91	47	maximum	maximum	ADJ
cet-3928	91	48	and	and	CCONJ
cet-3928	91	49	minimum	minimum	NOUN
cet-3928	91	50	for	for	ADP
cet-3928	91	51	each	each	DET
cet-3928	91	52	dimension	dimension	NOUN
cet-3928	91	53	of	of	ADP
cet-3928	91	54	the	the	DET
cet-3928	91	55	original	original	ADJ
cet-3928	91	56	data	datum	NOUN
cet-3928	91	57	.	.	PUNCT
cet-3928	92	1	a	a	DET
cet-3928	92	2	is	be	AUX
cet-3928	92	3	transformed	transform	VERB
cet-3928	92	4	data	datum	NOUN
cet-3928	92	5	,	,	PUNCT
cet-3928	92	6	also	also	ADV
cet-3928	92	7	known	know	VERB
cet-3928	92	8	as	as	ADP
cet-3928	92	9	the	the	DET
cet-3928	92	10	target	target	NOUN
cet-3928	92	11	data	datum	NOUN
cet-3928	92	12	.	.	PUNCT
cet-3928	93	1	for	for	ADP
cet-3928	93	2	each	each	DET
cet-3928	93	3	dimension	dimension	NOUN
cet-3928	93	4	of	of	ADP
cet-3928	93	5	the	the	DET
cet-3928	93	6	target	target	NOUN
cet-3928	93	7	data	datum	NOUN
cet-3928	93	8	’s	’s	PART
cet-3928	93	9	maximum	maximum	ADJ
cet-3928	93	10	and	and	CCONJ
cet-3928	93	11	minimum	minimum	ADJ
cet-3928	93	12	,	,	PUNCT
cet-3928	93	13	take	take	VERB
cet-3928	93	14	=	=	NOUN
cet-3928	93	15	0.9	0.9	NUM
cet-3928	93	16	,	,	PUNCT
cet-3928	93	17	=	=	NOUN
cet-3928	93	18	0.1	0.1	NUM
cet-3928	93	19	.	.	PUNCT
cet-3928	94	1	next	next	ADV
cet-3928	94	2	,	,	PUNCT
cet-3928	94	3	through	through	ADP
cet-3928	94	4	the	the	DET
cet-3928	94	5	fisher	fisher	PROPN
cet-3928	94	6	discriminant	discriminant	NOUN
cet-3928	94	7	method	method	NOUN
cet-3928	94	8	is	be	AUX
cet-3928	94	9	used	use	VERB
cet-3928	94	10	to	to	PART
cet-3928	94	11	do	do	VERB
cet-3928	94	12	the	the	DET
cet-3928	94	13	pre	pre	NOUN
cet-3928	94	14	-	-	NOUN
cet-3928	94	15	treatment	treatment	NOUN
cet-3928	94	16	between	between	ADP
cet-3928	94	17	attributes	attribute	NOUN
cet-3928	94	18	.	.	PUNCT
cet-3928	95	1	the	the	DET
cet-3928	95	2	data	data	NOUN
cet-3928	95	3	is	be	AUX
cet-3928	95	4	read	read	VERB
cet-3928	95	5	(	(	PUNCT
cet-3928	95	6	data	data	NOUN
cet-3928	95	7	=	=	SYM
cet-3928	95	8	xlsread	xlsread	PROPN
cet-3928	95	9	)	)	PUNCT
cet-3928	95	10	,	,	PUNCT
cet-3928	95	11	data1	data1	PROPN
cet-3928	95	12	and	and	CCONJ
cet-3928	95	13	data2	data2	PROPN
cet-3928	95	14	respectively	respectively	ADV
cet-3928	95	15	for	for	ADP
cet-3928	95	16	class	class	NOUN
cet-3928	95	17	1	1	NUM
cet-3928	95	18	and	and	CCONJ
cet-3928	95	19	class	class	NOUN
cet-3928	95	20	2	2	NUM
cet-3928	95	21	test	test	NOUN
cet-3928	95	22	sample	sample	NOUN
cet-3928	95	23	data	datum	NOUN
cet-3928	95	24	.	.	PUNCT
cet-3928	96	1	the	the	DET
cet-3928	96	2	sample	sample	NOUN
cet-3928	96	3	number	number	NOUN
cet-3928	96	4	of	of	ADP
cet-3928	96	5	class	class	NOUN
cet-3928	96	6	1	1	NUM
cet-3928	96	7	and	and	CCONJ
cet-3928	96	8	class	class	NOUN
cet-3928	96	9	2	2	NUM
cet-3928	96	10	is	be	AUX
cet-3928	96	11	calculated	calculate	VERB
cet-3928	96	12	(	(	PUNCT
cet-3928	96	13	r1	r1	PROPN
cet-3928	96	14	=	=	NOUN
cet-3928	96	15	size(data1,1	size(data1,1	NOUN
cet-3928	96	16	)	)	PUNCT
cet-3928	96	17	;	;	PUNCT
cet-3928	96	18	r2	r2	PROPN
cet-3928	96	19	=	=	SYM
cet-3928	96	20	size(data2,1	size(data2,1	PROPN
cet-3928	96	21	)	)	PUNCT
cet-3928	96	22	;)	;)	PUNCT
cet-3928	96	23	.	.	PUNCT
cet-3928	97	1	the	the	DET
cet-3928	97	2	mean	mean	NOUN
cet-3928	97	3	of	of	ADP
cet-3928	97	4	class	class	NOUN
cet-3928	97	5	1	1	NUM
cet-3928	97	6	and	and	CCONJ
cet-3928	97	7	class	class	NOUN
cet-3928	97	8	2	2	NUM
cet-3928	97	9	(	(	PUNCT
cet-3928	97	10	matrix	matrix	NOUN
cet-3928	97	11	)	)	PUNCT
cet-3928	97	12	is	be	AUX
cet-3928	97	13	calculated	calculate	VERB
cet-3928	97	14	(	(	PUNCT
cet-3928	97	15	m1	m1	NOUN
cet-3928	97	16	=	=	NOUN
cet-3928	97	17	mean(w1	mean(w1	NOUN
cet-3928	97	18	)	)	PUNCT
cet-3928	97	19	;	;	PUNCT
cet-3928	97	20	m2	m2	PROPN
cet-3928	97	21	=	=	NOUN
cet-3928	97	22	mean(w2	mean(w2	NOUN
cet-3928	97	23	)	)	PUNCT
cet-3928	97	24	)	)	PUNCT
cet-3928	97	25	.	.	PUNCT
cet-3928	98	1	various	various	ADJ
cet-3928	98	2	kinds	kind	NOUN
cet-3928	98	3	of	of	ADP
cet-3928	98	4	classes	class	NOUN
cet-3928	98	5	in	in	ADP
cet-3928	98	6	discrete	discrete	ADJ
cet-3928	98	7	degree	degree	NOUN
cet-3928	98	8	matrix	matrix	NOUN
cet-3928	98	9	(	(	PUNCT
cet-3928	98	10	covariance	covariance	NOUN
cet-3928	98	11	matrix	matrix	NOUN
cet-3928	98	12	)	)	PUNCT
cet-3928	98	13	are	be	AUX
cet-3928	98	14	caculated	caculate	VERB
cet-3928	98	15	(	(	PUNCT
cet-3928	98	16	s1	s1	PROPN
cet-3928	98	17	=	=	SYM
cet-3928	98	18	cov(data1)*(r1	cov(data1)*(r1	NOUN
cet-3928	98	19	-	-	PUNCT
cet-3928	98	20	1	1	NUM
cet-3928	98	21	)	)	PUNCT
cet-3928	98	22	;	;	PUNCT
cet-3928	98	23	s2	s2	PROPN
cet-3928	98	24	=	=	NOUN
cet-3928	98	25	cov(data2)*(r2	cov(data2)*(r2	NOUN
cet-3928	98	26	-	-	PUNCT
cet-3928	98	27	1	1	NUM
cet-3928	98	28	)	)	PUNCT
cet-3928	98	29	;)	;)	PUNCT
cet-3928	98	30	.	.	PUNCT
cet-3928	99	1	the	the	DET
cet-3928	99	2	total	total	ADJ
cet-3928	99	3	class	class	NOUN
cet-3928	99	4	scatter	scatter	NOUN
cet-3928	99	5	matrix	matrix	NOUN
cet-3928	99	6	is	be	AUX
cet-3928	99	7	calculated	calculate	VERB
cet-3928	99	8	(	(	PUNCT
cet-3928	99	9	sw	sw	PROPN
cet-3928	99	10	=	=	SYM
cet-3928	99	11	s1+s2	s1+s2	NOUN
cet-3928	99	12	;)	;)	NUM
cet-3928	99	13	.	.	PUNCT
cet-3928	100	1	the	the	DET
cet-3928	100	2	formula	formula	NOUN
cet-3928	100	3	of	of	ADP
cet-3928	100	4	the	the	DET
cet-3928	100	5	projection	projection	NOUN
cet-3928	100	6	vector	vector	NOUN
cet-3928	100	7	is	be	AUX
cet-3928	100	8	(	(	PUNCT
cet-3928	100	9	w	w	NOUN
cet-3928	100	10	=	=	NOUN
cet-3928	100	11	inv(sw)*(m1	inv(sw)*(m1	NOUN
cet-3928	100	12	-	-	PUNCT
cet-3928	100	13	m2	m2	NOUN
cet-3928	100	14	)	)	PUNCT
cet-3928	100	15	'	'	PUNCT
cet-3928	100	16	)	)	PUNCT
cet-3928	100	17	.	.	PUNCT
cet-3928	101	1	various	various	ADJ
cet-3928	101	2	kinds	kind	NOUN
cet-3928	101	3	of	of	ADP
cet-3928	101	4	mean	mean	NOUN
cet-3928	101	5	of	of	ADP
cet-3928	101	6	post	post	ADJ
cet-3928	101	7	-	-	ADJ
cet-3928	101	8	projection	projection	NOUN
cet-3928	101	9	of	of	ADP
cet-3928	101	10	a	a	DET
cet-3928	101	11	space	space	NOUN
cet-3928	101	12	is	be	AUX
cet-3928	101	13	calculated	calculate	VERB
cet-3928	101	14	(	(	PUNCT
cet-3928	101	15	y1	y1	INTJ
cet-3928	101	16	=	=	NOUN
cet-3928	101	17	w'*m1	w'*m1	NOUN
cet-3928	101	18	'	'	PUNCT
cet-3928	101	19	;	;	PUNCT
cet-3928	101	20	y2	y2	PROPN
cet-3928	101	21	=	=	SYM
cet-3928	101	22	w'*m2	w'*m2	X
cet-3928	101	23	'	'	NUM
cet-3928	101	24	;)	;)	PUNCT
cet-3928	101	25	the	the	DET
cet-3928	101	26	calculated	calculate	VERB
cet-3928	101	27	threshold	threshold	NOUN
cet-3928	101	28	is	be	AUX
cet-3928	101	29	(	(	PUNCT
cet-3928	101	30	w0=1/2*(y1+y2	w0=1/2*(y1+y2	PROPN
cet-3928	101	31	)	)	PUNCT
cet-3928	101	32	)	)	PUNCT
cet-3928	101	33	.	.	PUNCT
cet-3928	102	1	the	the	DET
cet-3928	102	2	data	datum	NOUN
cet-3928	102	3	to	to	PART
cet-3928	102	4	be	be	AUX
cet-3928	102	5	measured	measure	VERB
cet-3928	102	6	and	and	CCONJ
cet-3928	102	7	the	the	DET
cet-3928	102	8	class	class	NOUN
cet-3928	102	9	of	of	ADP
cet-3928	102	10	the	the	DET
cet-3928	102	11	same	same	ADJ
cet-3928	102	12	symbol	symbol	NOUN
cet-3928	102	13	are	be	AUX
cet-3928	102	14	classified	classify	VERB
cet-3928	102	15	as	as	ADP
cet-3928	102	16	similar	similar	ADJ
cet-3928	102	17	.	.	PUNCT
cet-3928	103	1	next	next	ADV
cet-3928	103	2	,	,	PUNCT
cet-3928	103	3	network	network	NOUN
cet-3928	103	4	building	building	NOUN
cet-3928	103	5	can	can	AUX
cet-3928	103	6	be	be	AUX
cet-3928	103	7	used	use	VERB
cet-3928	103	8	in	in	ADP
cet-3928	103	9	the	the	DET
cet-3928	103	10	inference	inference	NOUN
cet-3928	103	11	of	of	ADP
cet-3928	103	12	bayesian	bayesian	NOUN
cet-3928	103	13	network	network	NOUN
cet-3928	103	14	,	,	PUNCT
cet-3928	103	15	which	which	PRON
cet-3928	103	16	is	be	AUX
cet-3928	103	17	divided	divide	VERB
cet-3928	103	18	into	into	ADP
cet-3928	103	19	the	the	DET
cet-3928	103	20	following	follow	VERB
cet-3928	103	21	three	three	NUM
cet-3928	103	22	steps	step	NOUN
cet-3928	103	23	.	.	PUNCT
cet-3928	104	1	1	1	X
cet-3928	104	2	.	.	X
cet-3928	104	3	determine	determine	VERB
cet-3928	104	4	the	the	DET
cet-3928	104	5	network	network	NOUN
cet-3928	104	6	nodes	node	NOUN
cet-3928	104	7	and	and	CCONJ
cet-3928	104	8	the	the	DET
cet-3928	104	9	distribution	distribution	NOUN
cet-3928	104	10	parameters	parameter	NOUN
cet-3928	104	11	.	.	PUNCT
cet-3928	105	1	by	by	ADP
cet-3928	105	2	means	mean	NOUN
cet-3928	105	3	of	of	ADP
cet-3928	105	4	expert	expert	ADJ
cet-3928	105	5	knowledge	knowledge	NOUN
cet-3928	105	6	this	this	PRON
cet-3928	105	7	will	will	AUX
cet-3928	105	8	determine	determine	VERB
cet-3928	105	9	the	the	DET
cet-3928	105	10	predictive	predictive	ADJ
cet-3928	105	11	factors	factor	NOUN
cet-3928	105	12	of	of	ADP
cet-3928	105	13	the	the	DET
cet-3928	105	14	problems	problem	NOUN
cet-3928	105	15	involved	involve	VERB
cet-3928	105	16	in	in	ADP
cet-3928	105	17	these	these	DET
cet-3928	105	18	factors	factor	NOUN
cet-3928	105	19	as	as	ADP
cet-3928	105	20	network	network	NOUN
cet-3928	105	21	nodes	node	NOUN
cet-3928	105	22	,	,	PUNCT
cet-3928	105	23	and	and	CCONJ
cet-3928	105	24	further	far	ADV
cet-3928	105	25	determine	determine	VERB
cet-3928	105	26	the	the	DET
cet-3928	105	27	possible	possible	ADJ
cet-3928	105	28	values	value	NOUN
cet-3928	105	29	of	of	ADP
cet-3928	105	30	each	each	PRON
cet-3928	105	31	of	of	ADP
cet-3928	105	32	the	the	DET
cet-3928	105	33	node	node	ADJ
cet-3928	105	34	variables	variable	NOUN
cet-3928	105	35	.	.	PUNCT
cet-3928	106	1	2	2	X
cet-3928	106	2	.	.	X
cet-3928	106	3	determine	determine	VERB
cet-3928	106	4	the	the	DET
cet-3928	106	5	network	network	NOUN
cet-3928	106	6	structure	structure	NOUN
cet-3928	106	7	of	of	ADP
cet-3928	106	8	g	g	NOUN
cet-3928	106	9	;	;	PUNCT
cet-3928	106	10	that	that	PRON
cet-3928	106	11	is	is	ADV
cet-3928	106	12	,	,	PUNCT
cet-3928	106	13	the	the	DET
cet-3928	106	14	identification	identification	NOUN
cet-3928	106	15	of	of	ADP
cet-3928	106	16	the	the	DET
cet-3928	106	17	causal	causal	ADJ
cet-3928	106	18	relationship	relationship	NOUN
cet-3928	106	19	between	between	ADP
cet-3928	106	20	the	the	DET
cet-3928	106	21	prediction	prediction	NOUN
cet-3928	106	22	of	of	ADP
cet-3928	106	23	various	various	ADJ
cet-3928	106	24	factors	factor	NOUN
cet-3928	106	25	,	,	PUNCT
cet-3928	106	26	and	and	CCONJ
cet-3928	106	27	graphical	graphical	ADJ
cet-3928	106	28	representation	representation	NOUN
cet-3928	106	29	.	.	PUNCT
cet-3928	107	1	3	3	X
cet-3928	107	2	.	.	X
cet-3928	107	3	determine	determine	VERB
cet-3928	107	4	the	the	DET
cet-3928	107	5	variable	variable	ADJ
cet-3928	107	6	probability	probability	NOUN
cet-3928	107	7	distribution	distribution	NOUN
cet-3928	107	8	θ	θ	NOUN
cet-3928	107	9	,	,	PUNCT
cet-3928	107	10	and	and	CCONJ
cet-3928	107	11	on	on	ADP
cet-3928	107	12	the	the	DET
cet-3928	107	13	premise	premise	NOUN
cet-3928	107	14	of	of	ADP
cet-3928	107	15	known	know	VERB
cet-3928	107	16	network	network	NOUN
cet-3928	107	17	structure	structure	NOUN
cet-3928	107	18	,	,	PUNCT
cet-3928	107	19	determine	determine	VERB
cet-3928	107	20	the	the	DET
cet-3928	107	21	conditional	conditional	ADJ
cet-3928	107	22	probability	probability	NOUN
cet-3928	107	23	of	of	ADP
cet-3928	107	24	each	each	DET
cet-3928	107	25	network	network	NOUN
cet-3928	107	26	node	node	NOUN
cet-3928	107	27	.	.	PUNCT
cet-3928	108	1	because	because	SCONJ
cet-3928	108	2	the	the	DET
cet-3928	108	3	paper	paper	NOUN
cet-3928	108	4	uses	use	VERB
cet-3928	108	5	the	the	DET
cet-3928	108	6	bayesian	bayesian	NOUN
cet-3928	108	7	network	network	NOUN
cet-3928	108	8	toolbox	toolbox	NOUN
cet-3928	108	9	(	(	PUNCT
cet-3928	108	10	bnt	bnt	PROPN
cet-3928	108	11	)	)	PUNCT
cet-3928	108	12	of	of	ADP
cet-3928	108	13	matlab	matlab	PROPN
cet-3928	108	14	software	software	NOUN
cet-3928	108	15	to	to	PART
cet-3928	108	16	build	build	VERB
cet-3928	108	17	the	the	DET
cet-3928	108	18	prediction	prediction	NOUN
cet-3928	108	19	model	model	NOUN
cet-3928	108	20	，	，	PROPN
cet-3928	108	21	through	through	ADP
cet-3928	108	22	discretization	discretization	NOUN
cet-3928	108	23	processing	processing	NOUN
cet-3928	108	24	,	,	PUNCT
cet-3928	108	25	500	500	NUM
cet-3928	108	26	records	record	NOUN
cet-3928	108	27	from	from	ADP
cet-3928	108	28	the	the	DET
cet-3928	108	29	sample	sample	NOUN
cet-3928	108	30	data	datum	NOUN
cet-3928	108	31	were	be	AUX
cet-3928	108	32	randomly	randomly	ADV
cet-3928	108	33	selected	select	VERB
cet-3928	108	34	to	to	PART
cet-3928	108	35	form	form	VERB
cet-3928	108	36	a	a	DET
cet-3928	108	37	training	training	NOUN
cet-3928	108	38	set	set	NOUN
cet-3928	108	39	.	.	PUNCT
cet-3928	109	1	the	the	DET
cet-3928	109	2	other	other	ADJ
cet-3928	109	3	records	record	NOUN
cet-3928	109	4	are	be	AUX
cet-3928	109	5	included	include	VERB
cet-3928	109	6	in	in	ADP
cet-3928	109	7	the	the	DET
cet-3928	109	8	test	test	NOUN
cet-3928	109	9	set	set	NOUN
cet-3928	109	10	.	.	PUNCT
cet-3928	110	1	through	through	ADP
cet-3928	110	2	machine	machine	NOUN
cet-3928	110	3	learning	learning	NOUN
cet-3928	110	4	applied	apply	VERB
cet-3928	110	5	to	to	ADP
cet-3928	110	6	the	the	DET
cet-3928	110	7	training	training	NOUN
cet-3928	110	8	set	set	VERB
cet-3928	110	9	data	datum	NOUN
cet-3928	110	10	,	,	PUNCT
cet-3928	110	11	the	the	DET
cet-3928	110	12	network	network	NOUN
cet-3928	110	13	structure	structure	NOUN
cet-3928	110	14	can	can	AUX
cet-3928	110	15	be	be	AUX
cet-3928	110	16	determined	determine	VERB
cet-3928	110	17	.	.	PUNCT
cet-3928	111	1	this	this	DET
cet-3928	111	2	article	article	NOUN
cet-3928	111	3	selects	select	VERB
cet-3928	111	4	k2	k2	ADJ
cet-3928	111	5	algorithm	algorithm	NOUN
cet-3928	111	6	for	for	ADP
cet-3928	111	7	network	network	NOUN
cet-3928	111	8	structure	structure	NOUN
cet-3928	111	9	learning	learning	NOUN
cet-3928	111	10	,	,	PUNCT
cet-3928	111	11	which	which	PRON
cet-3928	111	12	is	be	AUX
cet-3928	111	13	one	one	NUM
cet-3928	111	14	of	of	ADP
cet-3928	111	15	the	the	DET
cet-3928	111	16	earliest	early	ADJ
cet-3928	111	17	batches	batch	NOUN
cet-3928	111	18	of	of	ADP
cet-3928	111	19	bayesian	bayesian	NOUN
cet-3928	111	20	network	network	NOUN
cet-3928	111	21	structure	structure	NOUN
cet-3928	111	22	learning	learn	VERB
cet-3928	111	23	algorithms	algorithm	NOUN
cet-3928	111	24	.	.	PUNCT
cet-3928	112	1	after	after	SCONJ
cet-3928	112	2	the	the	DET
cet-3928	112	3	inference	inference	NOUN
cet-3928	112	4	of	of	ADP
cet-3928	112	5	bayesian	bayesian	NOUN
cet-3928	112	6	network	network	NOUN
cet-3928	112	7	the	the	DET
cet-3928	112	8	fisher	fisher	PROPN
cet-3928	112	9	discriminant	discriminant	NOUN
cet-3928	112	10	method	method	NOUN
cet-3928	112	11	standardization	standardization	NOUN
cet-3928	112	12	of	of	ADP
cet-3928	112	13	the	the	DET
cet-3928	112	14	data	datum	NOUN
cet-3928	112	15	the	the	DET
cet-3928	112	16	original	original	ADJ
cet-3928	112	17	data	datum	NOUN
cet-3928	112	18	382	382	NUM
cet-3928	112	19	network	network	NOUN
cet-3928	112	20	structure	structure	NOUN
cet-3928	112	21	is	be	AUX
cet-3928	112	22	determined	determine	VERB
cet-3928	112	23	,	,	PUNCT
cet-3928	112	24	the	the	DET
cet-3928	112	25	conditional	conditional	ADJ
cet-3928	112	26	probability	probability	NOUN
cet-3928	112	27	is	be	AUX
cet-3928	112	28	calculated	calculate	VERB
cet-3928	112	29	by	by	ADP
cet-3928	112	30	using	use	VERB
cet-3928	112	31	the	the	DET
cet-3928	112	32	maximum	maximum	ADJ
cet-3928	112	33	likelihood	likelihood	NOUN
cet-3928	112	34	estimation	estimation	NOUN
cet-3928	112	35	(	(	PUNCT
cet-3928	112	36	mle	mle	NOUN
cet-3928	112	37	)	)	PUNCT
cet-3928	112	38	algorithm	algorithm	NOUN
cet-3928	112	39	.	.	PUNCT
cet-3928	113	1	after	after	ADP
cet-3928	113	2	the	the	DET
cet-3928	113	3	operation	operation	NOUN
cet-3928	113	4	of	of	ADP
cet-3928	113	5	the	the	DET
cet-3928	113	6	network	network	NOUN
cet-3928	113	7	,	,	PUNCT
cet-3928	113	8	the	the	DET
cet-3928	113	9	data	data	NOUN
cet-3928	113	10	reduction	reduction	NOUN
cet-3928	113	11	process	process	NOUN
cet-3928	113	12	can	can	AUX
cet-3928	113	13	eventually	eventually	ADV
cet-3928	113	14	be	be	AUX
cet-3928	113	15	applied	apply	VERB
cet-3928	113	16	.	.	PUNCT
cet-3928	114	1	3.2	3.2	NUM
cet-3928	114	2	the	the	PRON
cet-3928	114	3	results	result	VERB
cet-3928	114	4	analysis	analysis	NOUN
cet-3928	114	5	in	in	ADP
cet-3928	114	6	this	this	DET
cet-3928	114	7	paper	paper	NOUN
cet-3928	114	8	,	,	PUNCT
cet-3928	114	9	we	we	PRON
cet-3928	114	10	took	take	VERB
cet-3928	114	11	10,000	10,000	NUM
cet-3928	114	12	samples	sample	NOUN
cet-3928	114	13	to	to	PART
cet-3928	114	14	test	test	VERB
cet-3928	114	15	,	,	PUNCT
cet-3928	114	16	the	the	DET
cet-3928	114	17	samples	sample	NOUN
cet-3928	114	18	includes	include	VERB
cet-3928	114	19	24	24	NUM
cet-3928	114	20	selected	select	VERB
cet-3928	114	21	dimensions	dimension	NOUN
cet-3928	114	22	of	of	ADP
cet-3928	114	23	talk_fee	talk_fee	PROPN
cet-3928	114	24	,	,	PUNCT
cet-3928	114	25	city_phone_fee	city_phone_fee	PROPN
cet-3928	114	26	,	,	PUNCT
cet-3928	114	27	arpu_fee	arpu_fee	X
cet-3928	114	28	etc	etc	X
cet-3928	114	29	.	.	X
cet-3928	114	30	,	,	PUNCT
cet-3928	114	31	1	1	NUM
cet-3928	114	32	class	class	NOUN
cet-3928	114	33	attributes	attribute	NOUN
cet-3928	114	34	.	.	PUNCT
cet-3928	115	1	classes	class	NOUN
cet-3928	115	2	were	be	AUX
cet-3928	115	3	divided	divide	VERB
cet-3928	115	4	into	into	ADP
cet-3928	115	5	two	two	NUM
cet-3928	115	6	classes	class	NOUN
cet-3928	115	7	,	,	PUNCT
cet-3928	115	8	recorded	record	VERB
cet-3928	115	9	as	as	ADP
cet-3928	115	10	1	1	NUM
cet-3928	115	11	(	(	PUNCT
cet-3928	115	12	set	set	VERB
cet-3928	115	13	customers	customer	NOUN
cet-3928	115	14	)	)	PUNCT
cet-3928	115	15	and	and	CCONJ
cet-3928	115	16	2(customers	2(customer	NOUN
cet-3928	115	17	said	say	VERB
cet-3928	115	18	to	to	PART
cet-3928	115	19	have	have	AUX
cet-3928	115	20	unsubscribed	unsubscribe	VERB
cet-3928	115	21	due	due	ADJ
cet-3928	115	22	to	to	ADP
cet-3928	115	23	dissatisfaction	dissatisfaction	NOUN
cet-3928	115	24	)	)	PUNCT
cet-3928	115	25	.	.	PUNCT
cet-3928	116	1	the	the	DET
cet-3928	116	2	first	first	ADJ
cet-3928	116	3	24	24	NUM
cet-3928	116	4	dimension	dimension	NOUN
cet-3928	116	5	properties	property	NOUN
cet-3928	116	6	by	by	ADP
cet-3928	116	7	fisher	fisher	PROPN
cet-3928	116	8	criterion	criterion	NOUN
cet-3928	116	9	function	function	NOUN
cet-3928	116	10	classes	class	NOUN
cet-3928	116	11	alienation	alienation	VERB
cet-3928	116	12	sum	sum	NOUN
cet-3928	116	13	of	of	ADP
cet-3928	116	14	squared	square	VERB
cet-3928	116	15	residuals	residual	NOUN
cet-3928	116	16	and	and	CCONJ
cet-3928	116	17	were	be	AUX
cet-3928	116	18	calculated	calculate	VERB
cet-3928	116	19	from	from	ADP
cet-3928	116	20	the	the	DET
cet-3928	116	21	sum	sum	NOUN
cet-3928	116	22	of	of	ADP
cet-3928	116	23	squared	square	VERB
cet-3928	116	24	residuals	residual	NOUN
cet-3928	116	25	,	,	PUNCT
cet-3928	116	26	thus	thus	ADV
cet-3928	116	27	obtaining	obtain	VERB
cet-3928	116	28	a	a	DET
cet-3928	116	29	new	new	ADJ
cet-3928	116	30	sample	sample	NOUN
cet-3928	116	31	set	set	NOUN
cet-3928	116	32	.	.	PUNCT
cet-3928	117	1	then	then	ADV
cet-3928	117	2	,	,	PUNCT
cet-3928	117	3	the	the	DET
cet-3928	117	4	bayesian	bayesian	NOUN
cet-3928	117	5	classification	classification	NOUN
cet-3928	117	6	algorithm	algorithm	NOUN
cet-3928	117	7	was	be	AUX
cet-3928	117	8	used	use	VERB
cet-3928	117	9	to	to	PART
cet-3928	117	10	classify	classify	VERB
cet-3928	117	11	the	the	DET
cet-3928	117	12	new	new	ADJ
cet-3928	117	13	sample	sample	NOUN
cet-3928	117	14	set	set	NOUN
cet-3928	117	15	.	.	PUNCT
cet-3928	118	1	in	in	ADP
cet-3928	118	2	order	order	NOUN
cet-3928	118	3	to	to	PART
cet-3928	118	4	analyze	analyze	VERB
cet-3928	118	5	the	the	DET
cet-3928	118	6	forecast	forecast	NOUN
cet-3928	118	7	accuracy	accuracy	NOUN
cet-3928	118	8	,	,	PUNCT
cet-3928	118	9	a	a	DET
cet-3928	118	10	five	five	NUM
cet-3928	118	11	-	-	ADJ
cet-3928	118	12	fold	fold	ADJ
cet-3928	118	13	cross	cross	NOUN
cet-3928	118	14	-	-	ADJ
cet-3928	118	15	validation	validation	NOUN
cet-3928	118	16	was	be	AUX
cet-3928	118	17	used	use	VERB
cet-3928	118	18	to	to	PART
cet-3928	118	19	test	test	VERB
cet-3928	118	20	classification	classification	NOUN
cet-3928	118	21	results	result	NOUN
cet-3928	118	22	.	.	PUNCT
cet-3928	119	1	initial	initial	ADJ
cet-3928	119	2	data	datum	NOUN
cet-3928	119	3	sets	set	NOUN
cet-3928	119	4	were	be	AUX
cet-3928	119	5	randomly	randomly	ADV
cet-3928	119	6	divided	divide	VERB
cet-3928	119	7	into	into	ADP
cet-3928	119	8	five	five	NUM
cet-3928	119	9	mutually	mutually	ADV
cet-3928	119	10	disjointed	disjointed	ADJ
cet-3928	119	11	subsets	subset	NOUN
cet-3928	119	12	54321	54321	NUM
cet-3928	119	13	,	,	PUNCT
cet-3928	119	14	,	,	PUNCT
cet-3928	119	15	,	,	PUNCT
cet-3928	119	16	,	,	PUNCT
cet-3928	119	17	ddddd	ddddd	PROPN
cet-3928	119	18	,	,	PUNCT
cet-3928	119	19	and	and	CCONJ
cet-3928	119	20	the	the	DET
cet-3928	119	21	sizes	size	NOUN
cet-3928	119	22	of	of	ADP
cet-3928	119	23	each	each	DET
cet-3928	119	24	subset	subset	NOUN
cet-3928	119	25	are	be	AUX
cet-3928	119	26	basically	basically	ADV
cet-3928	119	27	the	the	DET
cet-3928	119	28	same	same	ADJ
cet-3928	119	29	.	.	PUNCT
cet-3928	120	1	each	each	PRON
cet-3928	120	2	was	be	AUX
cet-3928	120	3	studied	study	VERB
cet-3928	120	4	and	and	CCONJ
cet-3928	120	5	tested	test	VERB
cet-3928	120	6	five	five	NUM
cet-3928	120	7	times	time	NOUN
cet-3928	120	8	.	.	PUNCT
cet-3928	121	1	in	in	ADP
cet-3928	121	2	the	the	DET
cet-3928	121	3	i	i	PROPN
cet-3928	121	4	iteration	iteration	NOUN
cet-3928	121	5	,	,	PUNCT
cet-3928	121	6	si	si	PROPN
cet-3928	121	7	was	be	AUX
cet-3928	121	8	used	use	VERB
cet-3928	121	9	as	as	ADP
cet-3928	121	10	a	a	DET
cet-3928	121	11	test	test	NOUN
cet-3928	121	12	set	set	NOUN
cet-3928	121	13	,	,	PUNCT
cet-3928	121	14	and	and	CCONJ
cet-3928	121	15	the	the	DET
cet-3928	121	16	rest	rest	NOUN
cet-3928	121	17	of	of	ADP
cet-3928	121	18	the	the	DET
cet-3928	121	19	subsets	subset	NOUN
cet-3928	121	20	of	of	ADP
cet-3928	121	21	the	the	DET
cet-3928	121	22	classifier	classifier	NOUN
cet-3928	121	23	were	be	AUX
cet-3928	121	24	used	use	VERB
cet-3928	121	25	for	for	ADP
cet-3928	121	26	training	training	NOUN
cet-3928	121	27	.	.	PUNCT
cet-3928	122	1	five	five	NUM
cet-3928	122	2	iterations	iteration	NOUN
cet-3928	122	3	were	be	AUX
cet-3928	122	4	taken	take	VERB
cet-3928	122	5	with	with	ADP
cet-3928	122	6	correct	correct	ADJ
cet-3928	122	7	classification	classification	NOUN
cet-3928	122	8	numbers	number	NOUN
cet-3928	122	9	and	and	CCONJ
cet-3928	122	10	divided	divide	VERB
cet-3928	122	11	by	by	ADP
cet-3928	122	12	the	the	DET
cet-3928	122	13	total	total	ADJ
cet-3928	122	14	number	number	NOUN
cet-3928	122	15	of	of	ADP
cet-3928	122	16	samples	sample	NOUN
cet-3928	122	17	in	in	ADP
cet-3928	122	18	the	the	DET
cet-3928	122	19	initial	initial	ADJ
cet-3928	122	20	data	datum	NOUN
cet-3928	122	21	of	of	ADP
cet-3928	122	22	average	average	ADJ
cet-3928	122	23	accuracy	accuracy	NOUN
cet-3928	122	24	.	.	PUNCT
cet-3928	123	1	the	the	DET
cet-3928	123	2	final	final	ADJ
cet-3928	123	3	assessment	assessment	NOUN
cet-3928	123	4	results	result	NOUN
cet-3928	123	5	showed	show	VERB
cet-3928	123	6	89	89	NUM
cet-3928	123	7	%	%	NOUN
cet-3928	123	8	accuracy	accuracy	NOUN
cet-3928	123	9	.	.	PUNCT
cet-3928	124	1	this	this	PRON
cet-3928	124	2	shows	show	VERB
cet-3928	124	3	that	that	SCONJ
cet-3928	124	4	the	the	DET
cet-3928	124	5	method	method	NOUN
cet-3928	124	6	of	of	ADP
cet-3928	124	7	this	this	DET
cet-3928	124	8	experiment	experiment	NOUN
cet-3928	124	9	is	be	AUX
cet-3928	124	10	quite	quite	ADV
cet-3928	124	11	successful	successful	ADJ
cet-3928	124	12	in	in	ADP
cet-3928	124	13	the	the	DET
cet-3928	124	14	practical	practical	ADJ
cet-3928	124	15	application	application	NOUN
cet-3928	124	16	of	of	ADP
cet-3928	124	17	data	datum	NOUN
cet-3928	124	18	sets	set	NOUN
cet-3928	124	19	,	,	PUNCT
cet-3928	124	20	which	which	PRON
cet-3928	124	21	mainly	mainly	ADV
cet-3928	124	22	has	have	VERB
cet-3928	124	23	the	the	DET
cet-3928	124	24	following	follow	VERB
cet-3928	124	25	three	three	NUM
cet-3928	124	26	aspects	aspect	NOUN
cet-3928	124	27	:	:	PUNCT
cet-3928	124	28	1	1	X
cet-3928	124	29	.	.	X
cet-3928	124	30	data	datum	NOUN
cet-3928	124	31	pre	pre	ADJ
cet-3928	124	32	-	-	ADJ
cet-3928	124	33	processing	processing	ADJ
cet-3928	124	34	stage	stage	NOUN
cet-3928	124	35	obtains	obtain	VERB
cet-3928	124	36	a	a	DET
cet-3928	124	37	high	high	ADJ
cet-3928	124	38	quality	quality	NOUN
cet-3928	124	39	of	of	ADP
cet-3928	124	40	the	the	DET
cet-3928	124	41	sample	sample	NOUN
cet-3928	124	42	data	datum	NOUN
cet-3928	124	43	.	.	PUNCT
cet-3928	125	1	2	2	X
cet-3928	125	2	.	.	X
cet-3928	125	3	the	the	DET
cet-3928	125	4	dimension	dimension	NOUN
cet-3928	125	5	independence	independence	NOUN
cet-3928	125	6	is	be	AUX
cet-3928	125	7	higher	high	ADJ
cet-3928	125	8	after	after	SCONJ
cet-3928	125	9	fisher	fisher	PROPN
cet-3928	125	10	discriminant	discriminant	PROPN
cet-3928	125	11	analysis	analysis	NOUN
cet-3928	125	12	.	.	PUNCT
cet-3928	126	1	3	3	X
cet-3928	126	2	.	.	X
cet-3928	126	3	accumulation	accumulation	NOUN
cet-3928	126	4	of	of	ADP
cet-3928	126	5	a	a	DET
cet-3928	126	6	priori	priori	ADJ
cet-3928	126	7	knowledge	knowledge	NOUN
cet-3928	126	8	is	be	AUX
cet-3928	126	9	more	more	ADV
cet-3928	126	10	comprehensive	comprehensive	ADJ
cet-3928	126	11	and	and	CCONJ
cet-3928	126	12	accurate	accurate	ADJ
cet-3928	126	13	,	,	PUNCT
cet-3928	126	14	so	so	SCONJ
cet-3928	126	15	the	the	DET
cet-3928	126	16	selection	selection	NOUN
cet-3928	126	17	of	of	ADP
cet-3928	126	18	network	network	NOUN
cet-3928	126	19	nodes	node	NOUN
cet-3928	126	20	is	be	AUX
cet-3928	126	21	more	more	ADV
cet-3928	126	22	reasonable	reasonable	ADJ
cet-3928	126	23	.	.	PUNCT
cet-3928	127	1	the	the	DET
cet-3928	127	2	bp	bp	PROPN
cet-3928	127	3	artificial	artificial	ADJ
cet-3928	127	4	neural	neural	ADJ
cet-3928	127	5	network	network	NOUN
cet-3928	127	6	has	have	VERB
cet-3928	127	7	a	a	DET
cet-3928	127	8	strong	strong	ADJ
cet-3928	127	9	capability	capability	NOUN
cet-3928	127	10	to	to	PART
cet-3928	127	11	handle	handle	VERB
cet-3928	127	12	and	and	CCONJ
cet-3928	127	13	deal	deal	VERB
cet-3928	127	14	with	with	ADP
cet-3928	127	15	nonlinear	nonlinear	ADJ
cet-3928	127	16	problems	problem	NOUN
cet-3928	127	17	.	.	PUNCT
cet-3928	128	1	the	the	DET
cet-3928	128	2	upper	upper	ADJ
cet-3928	128	3	and	and	CCONJ
cet-3928	128	4	lower	low	ADJ
cet-3928	128	5	layers	layer	NOUN
cet-3928	128	6	of	of	ADP
cet-3928	128	7	each	each	DET
cet-3928	128	8	neuron	neuron	NOUN
cet-3928	128	9	are	be	AUX
cet-3928	128	10	completely	completely	ADV
cet-3928	128	11	connected	connect	VERB
cet-3928	128	12	,	,	PUNCT
cet-3928	128	13	and	and	CCONJ
cet-3928	128	14	the	the	DET
cet-3928	128	15	algorithm	algorithm	NOUN
cet-3928	128	16	uses	use	VERB
cet-3928	128	17	forward	forward	ADJ
cet-3928	128	18	transfer	transfer	NOUN
cet-3928	128	19	of	of	ADP
cet-3928	128	20	information	information	NOUN
cet-3928	128	21	and	and	CCONJ
cet-3928	128	22	error	error	NOUN
cet-3928	128	23	return	return	NOUN
cet-3928	128	24	propagation	propagation	NOUN
cet-3928	128	25	of	of	ADP
cet-3928	128	26	the	the	DET
cet-3928	128	27	two	two	NUM
cet-3928	128	28	parts	part	NOUN
cet-3928	128	29	.	.	PUNCT
cet-3928	129	1	after	after	SCONJ
cet-3928	129	2	a	a	DET
cet-3928	129	3	pair	pair	NOUN
cet-3928	129	4	of	of	ADP
cet-3928	129	5	samples	sample	NOUN
cet-3928	129	6	provides	provide	VERB
cet-3928	129	7	network	network	NOUN
cet-3928	129	8	learning	learning	NOUN
cet-3928	129	9	mode	mode	NOUN
cet-3928	129	10	,	,	PUNCT
cet-3928	129	11	the	the	DET
cet-3928	129	12	input	input	NOUN
cet-3928	129	13	information	information	NOUN
cet-3928	129	14	from	from	ADP
cet-3928	129	15	the	the	DET
cet-3928	129	16	input	input	NOUN
cet-3928	129	17	goes	go	VERB
cet-3928	129	18	layer	layer	NOUN
cet-3928	129	19	by	by	ADP
cet-3928	129	20	layer	layer	NOUN
cet-3928	129	21	to	to	ADP
cet-3928	129	22	the	the	DET
cet-3928	129	23	output	output	NOUN
cet-3928	129	24	layer	layer	NOUN
cet-3928	129	25	,	,	PUNCT
cet-3928	129	26	and	and	CCONJ
cet-3928	129	27	neurons	neuron	NOUN
cet-3928	129	28	in	in	ADP
cet-3928	129	29	the	the	DET
cet-3928	129	30	output	output	NOUN
cet-3928	129	31	layer	layer	NOUN
cet-3928	129	32	of	of	ADP
cet-3928	129	33	the	the	DET
cet-3928	129	34	network	network	NOUN
cet-3928	129	35	input	input	NOUN
cet-3928	129	36	respond	respond	NOUN
cet-3928	129	37	.	.	PUNCT
cet-3928	130	1	then	then	ADV
cet-3928	130	2	,	,	PUNCT
cet-3928	130	3	in	in	ADP
cet-3928	130	4	the	the	DET
cet-3928	130	5	tending	tending	NOUN
cet-3928	130	6	toward	toward	ADP
cet-3928	130	7	reducing	reduce	VERB
cet-3928	130	8	the	the	DET
cet-3928	130	9	expected	expect	VERB
cet-3928	130	10	output	output	NOUN
cet-3928	130	11	and	and	CCONJ
cet-3928	130	12	the	the	DET
cet-3928	130	13	actual	actual	ADJ
cet-3928	130	14	output	output	NOUN
cet-3928	130	15	error	error	NOUN
cet-3928	130	16	,	,	PUNCT
cet-3928	130	17	the	the	DET
cet-3928	130	18	connection	connection	NOUN
cet-3928	130	19	weights	weight	NOUN
cet-3928	130	20	are	be	AUX
cet-3928	130	21	corrected	correct	VERB
cet-3928	130	22	by	by	ADP
cet-3928	130	23	each	each	DET
cet-3928	130	24	middle	middle	ADJ
cet-3928	130	25	layer	layer	NOUN
cet-3928	130	26	,	,	PUNCT
cet-3928	130	27	layer	layer	NOUN
cet-3928	130	28	by	by	ADP
cet-3928	130	29	layer	layer	NOUN
cet-3928	130	30	,	,	PUNCT
cet-3928	130	31	from	from	ADP
cet-3928	130	32	the	the	DET
cet-3928	130	33	output	output	NOUN
cet-3928	130	34	layer	layer	NOUN
cet-3928	130	35	and	and	CCONJ
cet-3928	130	36	finally	finally	ADV
cet-3928	130	37	to	to	ADP
cet-3928	130	38	the	the	DET
cet-3928	130	39	input	input	NOUN
cet-3928	130	40	layer	layer	NOUN
cet-3928	130	41	.	.	PUNCT
cet-3928	131	1	with	with	ADP
cet-3928	131	2	the	the	DET
cet-3928	131	3	error	error	NOUN
cet-3928	131	4	return	return	NOUN
cet-3928	131	5	propagation	propagation	NOUN
cet-3928	131	6	modified	modify	VERB
cet-3928	131	7	continuously	continuously	ADV
cet-3928	131	8	,	,	PUNCT
cet-3928	131	9	the	the	DET
cet-3928	131	10	network	network	NOUN
cet-3928	131	11	of	of	ADP
cet-3928	131	12	correct	correct	ADJ
cet-3928	131	13	input	input	NOUN
cet-3928	131	14	mode	mode	NOUN
cet-3928	131	15	response	response	NOUN
cet-3928	131	16	rate	rate	NOUN
cet-3928	131	17	is	be	AUX
cet-3928	131	18	rising	rise	VERB
cet-3928	131	19	.	.	PUNCT
cet-3928	132	1	the	the	DET
cet-3928	132	2	shortcoming	shortcoming	NOUN
cet-3928	132	3	of	of	ADP
cet-3928	132	4	bp	bp	PROPN
cet-3928	132	5	model	model	NOUN
cet-3928	132	6	is	be	AUX
cet-3928	132	7	slow	slow	ADJ
cet-3928	132	8	convergence	convergence	NOUN
cet-3928	132	9	speed	speed	NOUN
cet-3928	132	10	of	of	ADP
cet-3928	132	11	learning	learn	VERB
cet-3928	132	12	algorithm	algorithm	NOUN
cet-3928	132	13	,	,	PUNCT
cet-3928	132	14	having	having	AUX
cet-3928	132	15	been	be	AUX
cet-3928	132	16	limited	limit	VERB
cet-3928	132	17	to	to	ADP
cet-3928	132	18	local	local	ADJ
cet-3928	132	19	minimum	minimum	NOUN
cet-3928	132	20	rather	rather	ADV
cet-3928	132	21	than	than	ADP
cet-3928	132	22	the	the	DET
cet-3928	132	23	state	state	NOUN
cet-3928	132	24	of	of	ADP
cet-3928	132	25	the	the	DET
cet-3928	132	26	global	global	ADJ
cet-3928	132	27	convergence	convergence	NOUN
cet-3928	132	28	.	.	PUNCT
cet-3928	133	1	with	with	ADP
cet-3928	133	2	the	the	DET
cet-3928	133	3	same	same	ADJ
cet-3928	133	4	data	datum	NOUN
cet-3928	133	5	being	be	AUX
cet-3928	133	6	calculated	calculate	VERB
cet-3928	133	7	by	by	ADP
cet-3928	133	8	matlab	matlab	PROPN
cet-3928	133	9	programming	programming	NOUN
cet-3928	133	10	,	,	PUNCT
cet-3928	133	11	the	the	DET
cet-3928	133	12	prediction	prediction	NOUN
cet-3928	133	13	effect	effect	NOUN
cet-3928	133	14	of	of	ADP
cet-3928	133	15	the	the	DET
cet-3928	133	16	hybrid	hybrid	ADJ
cet-3928	133	17	algorithm	algorithm	NOUN
cet-3928	133	18	is	be	AUX
cet-3928	133	19	better	well	ADJ
cet-3928	133	20	than	than	ADP
cet-3928	133	21	that	that	PRON
cet-3928	133	22	of	of	ADP
cet-3928	133	23	both	both	CCONJ
cet-3928	133	24	the	the	DET
cet-3928	133	25	pure	pure	ADJ
cet-3928	133	26	bias	bias	NOUN
cet-3928	133	27	classification	classification	NOUN
cet-3928	133	28	algorithm	algorithm	NOUN
cet-3928	133	29	and	and	CCONJ
cet-3928	133	30	neural	neural	ADJ
cet-3928	133	31	network	network	NOUN
cet-3928	133	32	algorithm	algorithm	NOUN
cet-3928	133	33	.	.	PUNCT
cet-3928	134	1	table	table	NOUN
cet-3928	134	2	1	1	NUM
cet-3928	134	3	:	:	PUNCT
cet-3928	134	4	comparison	comparison	NOUN
cet-3928	134	5	of	of	ADP
cet-3928	134	6	classification	classification	NOUN
cet-3928	134	7	accuracy	accuracy	NOUN
cet-3928	134	8	of	of	ADP
cet-3928	134	9	different	different	ADJ
cet-3928	134	10	algorithms	algorithm	NOUN
cet-3928	134	11	algorithm	algorithm	NOUN
cet-3928	134	12	number	number	NOUN
cet-3928	134	13	of	of	ADP
cet-3928	134	14	samples	sample	NOUN
cet-3928	134	15	classification	classification	NOUN
cet-3928	134	16	accuracy	accuracy	NOUN
cet-3928	134	17	bayesian	bayesian	NOUN
cet-3928	134	18	and	and	CCONJ
cet-3928	134	19	fisher	fisher	PROPN
cet-3928	134	20	hybrid	hybrid	ADJ
cet-3928	134	21	algorithm	algorithm	NOUN
cet-3928	134	22	2000	2000	NUM
cet-3928	134	23	training	training	NOUN
cet-3928	134	24	,	,	PUNCT
cet-3928	134	25	2000	2000	NUM
cet-3928	134	26	test	test	NOUN
cet-3928	134	27	89	89	NUM
cet-3928	134	28	pure	pure	ADJ
cet-3928	134	29	bayesian	bayesian	NOUN
cet-3928	134	30	algorithm	algorithm	NOUN
cet-3928	134	31	2000	2000	NUM
cet-3928	134	32	training	training	NOUN
cet-3928	134	33	,	,	PUNCT
cet-3928	134	34	2000	2000	NUM
cet-3928	134	35	test	test	NOUN
cet-3928	134	36	73	73	NUM
cet-3928	134	37	neural	neural	ADJ
cet-3928	134	38	network	network	NOUN
cet-3928	134	39	algorithm	algorithm	NOUN
cet-3928	134	40	2000	2000	NUM
cet-3928	134	41	training	training	NOUN
cet-3928	134	42	,	,	PUNCT
cet-3928	134	43	2000	2000	NUM
cet-3928	134	44	test	test	NOUN
cet-3928	134	45	70	70	NUM
cet-3928	134	46	4	4	NUM
cet-3928	134	47	.	.	PUNCT
cet-3928	135	1	conclusion	conclusion	NOUN
cet-3928	135	2	it	it	PRON
cet-3928	135	3	can	can	AUX
cet-3928	135	4	be	be	AUX
cet-3928	135	5	seen	see	VERB
cet-3928	135	6	from	from	ADP
cet-3928	135	7	the	the	DET
cet-3928	135	8	experimental	experimental	ADJ
cet-3928	135	9	results	result	NOUN
cet-3928	135	10	obtained	obtain	VERB
cet-3928	135	11	that	that	SCONJ
cet-3928	135	12	the	the	DET
cet-3928	135	13	combination	combination	NOUN
cet-3928	135	14	of	of	ADP
cet-3928	135	15	fisher	fisher	NOUN
cet-3928	135	16	based	base	VERB
cet-3928	135	17	on	on	ADP
cet-3928	135	18	bayesian	bayesian	NOUN
cet-3928	135	19	classification	classification	NOUN
cet-3928	135	20	algorithms	algorithm	NOUN
cet-3928	135	21	performs	perform	VERB
cet-3928	135	22	better	well	ADJ
cet-3928	135	23	than	than	ADP
cet-3928	135	24	only	only	ADV
cet-3928	135	25	the	the	DET
cet-3928	135	26	bayesian	bayesian	NOUN
cet-3928	135	27	algorithm	algorithm	NOUN
cet-3928	135	28	alone	alone	ADV
cet-3928	135	29	,	,	PUNCT
cet-3928	135	30	with	with	ADP
cet-3928	135	31	an	an	DET
cet-3928	135	32	increased	increase	VERB
cet-3928	135	33	accuracy	accuracy	NOUN
cet-3928	135	34	of	of	ADP
cet-3928	135	35	approximately	approximately	ADV
cet-3928	135	36	15	15	NUM
cet-3928	135	37	%	%	NOUN
cet-3928	135	38	.	.	PUNCT
cet-3928	136	1	the	the	DET
cet-3928	136	2	traditional	traditional	ADJ
cet-3928	136	3	bayes	bayes	NOUN
cet-3928	136	4	algorithm	algorithm	PROPN
cet-3928	136	5	considers	consider	VERB
cet-3928	136	6	the	the	DET
cet-3928	136	7	connection	connection	NOUN
cet-3928	136	8	between	between	ADP
cet-3928	136	9	the	the	DET
cet-3928	136	10	properties	property	NOUN
cet-3928	136	11	of	of	ADP
cet-3928	136	12	each	each	DET
cet-3928	136	13	dimension	dimension	NOUN
cet-3928	136	14	,	,	PUNCT
cet-3928	136	15	and	and	CCONJ
cet-3928	136	16	by	by	ADP
cet-3928	136	17	adding	add	VERB
cet-3928	136	18	the	the	DET
cet-3928	136	19	fisher	fisher	PROPN
cet-3928	136	20	classification	classification	NOUN
cet-3928	136	21	algorithm	algorithm	NOUN
cet-3928	136	22	and	and	CCONJ
cet-3928	136	23	projection	projection	NOUN
cet-3928	136	24	of	of	ADP
cet-3928	136	25	each	each	DET
cet-3928	136	26	attribute	attribute	NOUN
cet-3928	136	27	correlation	correlation	NOUN
cet-3928	136	28	between	between	ADP
cet-3928	136	29	is	be	AUX
cet-3928	136	30	greatly	greatly	ADV
cet-3928	136	31	reduced	reduce	VERB
cet-3928	136	32	,	,	PUNCT
cet-3928	136	33	thus	thus	ADV
cet-3928	136	34	fully	fully	ADV
cet-3928	136	35	improving	improve	VERB
cet-3928	136	36	the	the	DET
cet-3928	136	37	classification	classification	NOUN
cet-3928	136	38	accuracy	accuracy	NOUN
cet-3928	136	39	.	.	PUNCT
cet-3928	137	1	the	the	DET
cet-3928	137	2	classical	classical	ADJ
cet-3928	137	3	bayesian	bayesian	NOUN
cet-3928	137	4	classifier	classifier	NOUN
cet-3928	137	5	is	be	AUX
cet-3928	137	6	a	a	DET
cet-3928	137	7	simple	simple	ADJ
cet-3928	137	8	and	and	CCONJ
cet-3928	137	9	effective	effective	ADJ
cet-3928	137	10	classification	classification	NOUN
cet-3928	137	11	algorithm	algorithm	NOUN
cet-3928	137	12	,	,	PUNCT
cet-3928	137	13	but	but	CCONJ
cet-3928	137	14	its	its	PRON
cet-3928	137	15	independence	independence	NOUN
cet-3928	137	16	assumption	assumption	NOUN
cet-3928	137	17	makes	make	VERB
cet-3928	137	18	it	it	PRON
cet-3928	137	19	unable	unable	ADJ
cet-3928	137	20	to	to	PART
cet-3928	137	21	express	express	VERB
cet-3928	137	22	any	any	DET
cet-3928	137	23	attribute	attribute	NOUN
cet-3928	137	24	dependency	dependency	NOUN
cet-3928	137	25	relationship	relationship	NOUN
cet-3928	137	26	between	between	ADP
cet-3928	137	27	the	the	DET
cet-3928	137	28	actual	actual	ADJ
cet-3928	137	29	data	datum	NOUN
cet-3928	137	30	.	.	PUNCT
cet-3928	138	1	without	without	ADP
cet-3928	138	2	the	the	DET
cet-3928	138	3	use	use	NOUN
cet-3928	138	4	of	of	ADP
cet-3928	138	5	class	class	NOUN
cet-3928	138	6	information	information	NOUN
cet-3928	138	7	,	,	PUNCT
cet-3928	138	8	it	it	PRON
cet-3928	138	9	is	be	AUX
cet-3928	138	10	only	only	ADV
cet-3928	138	11	an	an	DET
cet-3928	138	12	approximate	approximate	ADJ
cet-3928	138	13	expression	expression	NOUN
cet-3928	138	14	of	of	ADP
cet-3928	138	15	the	the	DET
cet-3928	138	16	parameters	parameter	NOUN
cet-3928	138	17	of	of	ADP
cet-3928	138	18	the	the	DET
cet-3928	138	19	distribution	distribution	NOUN
cet-3928	138	20	of	of	ADP
cet-3928	138	21	the	the	DET
cet-3928	138	22	training	training	NOUN
cet-3928	138	23	sample	sample	NOUN
cet-3928	138	24	set	set	VERB
cet-3928	138	25	for	for	ADP
cet-3928	138	26	each	each	DET
cet-3928	138	27	class	class	NOUN
cet-3928	138	28	.	.	PUNCT
cet-3928	139	1	in	in	ADP
cet-3928	139	2	this	this	DET
cet-3928	139	3	paper	paper	NOUN
cet-3928	139	4	,	,	PUNCT
cet-3928	139	5	an	an	DET
cet-3928	139	6	improved	improved	ADJ
cet-3928	139	7	classifier	classifier	NOUN
cet-3928	139	8	is	be	AUX
cet-3928	139	9	proposed	propose	VERB
cet-3928	139	10	,	,	PUNCT
cet-3928	139	11	from	from	ADP
cet-3928	139	12	another	another	DET
cet-3928	139	13	point	point	NOUN
cet-3928	139	14	of	of	ADP
cet-3928	139	15	view	view	NOUN
cet-3928	139	16	,	,	PUNCT
cet-3928	139	17	to	to	PART
cet-3928	139	18	solve	solve	VERB
cet-3928	139	19	the	the	DET
cet-3928	139	20	problem	problem	NOUN
cet-3928	139	21	of	of	ADP
cet-3928	139	22	the	the	DET
cet-3928	139	23	classical	classical	ADJ
cet-3928	139	24	bias	bias	NOUN
cet-3928	139	25	classifier	classifier	NOUN
cet-3928	139	26	not	not	PART
cet-3928	139	27	being	be	AUX
cet-3928	139	28	able	able	ADJ
cet-3928	139	29	to	to	PART
cet-3928	139	30	extract	extract	VERB
cet-3928	139	31	class	class	NOUN
cet-3928	139	32	information	information	NOUN
cet-3928	139	33	.	.	PUNCT
cet-3928	140	1	this	this	PRON
cet-3928	140	2	is	be	AUX
cet-3928	140	3	accomplished	accomplish	VERB
cet-3928	140	4	through	through	ADP
cet-3928	140	5	the	the	DET
cet-3928	140	6	use	use	NOUN
cet-3928	140	7	of	of	ADP
cet-3928	140	8	fisher	fisher	PROPN
cet-3928	140	9	's	's	PART
cet-3928	140	10	discriminant	discriminant	ADJ
cet-3928	140	11	analysis	analysis	NOUN
cet-3928	140	12	method	method	NOUN
cet-3928	140	13	for	for	ADP
cet-3928	140	14	the	the	DET
cet-3928	140	15	separation	separation	NOUN
cet-3928	140	16	of	of	ADP
cet-3928	140	17	class	class	NOUN
cet-3928	140	18	and	and	CCONJ
cet-3928	140	19	class	class	NOUN
cet-3928	140	20	largest	large	ADJ
cet-3928	140	21	projection	projection	NOUN
cet-3928	140	22	space	space	NOUN
cet-3928	140	23	.	.	PUNCT
cet-3928	141	1	then	then	ADV
cet-3928	141	2	the	the	DET
cet-3928	141	3	original	original	ADJ
cet-3928	141	4	samples	sample	NOUN
cet-3928	141	5	are	be	AUX
cet-3928	141	6	projected	project	VERB
cet-3928	141	7	to	to	ADP
cet-3928	141	8	the	the	DET
cet-3928	141	9	maximum	maximum	ADJ
cet-3928	141	10	separable	separable	ADJ
cet-3928	141	11	space	space	NOUN
cet-3928	141	12	,	,	PUNCT
cet-3928	141	13	and	and	CCONJ
cet-3928	141	14	the	the	DET
cet-3928	141	15	new	new	ADJ
cet-3928	141	16	samples	sample	NOUN
cet-3928	141	17	are	be	AUX
cet-3928	141	18	obtained	obtain	VERB
cet-3928	141	19	.	.	PUNCT
cet-3928	142	1	using	use	VERB
cet-3928	142	2	the	the	DET
cet-3928	142	3	discriminant	discriminant	NOUN
cet-3928	142	4	for	for	ADP
cet-3928	142	5	the	the	DET
cet-3928	142	6	new	new	ADJ
cet-3928	142	7	attributes	attribute	NOUN
cet-3928	142	8	,	,	PUNCT
cet-3928	142	9	then	then	ADV
cet-3928	142	10	the	the	DET
cet-3928	142	11	classical	classical	ADJ
cet-3928	142	12	bias	bias	NOUN
cet-3928	142	13	classification	classification	NOUN
cet-3928	142	14	algorithm	algorithm	NOUN
cet-3928	142	15	is	be	AUX
cet-3928	142	16	used	use	VERB
cet-3928	142	17	to	to	PART
cet-3928	142	18	classify	classify	VERB
cet-3928	142	19	the	the	DET
cet-3928	142	20	samples	sample	NOUN
cet-3928	142	21	.	.	PUNCT
cet-3928	143	1	experiments	experiment	NOUN
cet-3928	143	2	show	show	VERB
cet-3928	143	3	that	that	SCONJ
cet-3928	143	4	integrating	integrate	VERB
cet-3928	143	5	the	the	DET
cet-3928	143	6	classical	classical	ADJ
cet-3928	143	7	bias	bias	NOUN
cet-3928	143	8	classifier	classifier	NOUN
cet-3928	143	9	and	and	CCONJ
cet-3928	143	10	fisher	fisher	PROPN
cet-3928	143	11	linear	linear	PROPN
cet-3928	143	12	discriminant	discriminant	ADJ
cet-3928	143	13	analysis	analysis	NOUN
cet-3928	143	14	method	method	NOUN
cet-3928	143	15	,	,	PUNCT
cet-3928	143	16	can	can	AUX
cet-3928	143	17	achieve	achieve	VERB
cet-3928	143	18	a	a	DET
cet-3928	143	19	better	well	ADJ
cet-3928	143	20	classification	classification	NOUN
cet-3928	143	21	effect	effect	NOUN
cet-3928	143	22	.	.	PUNCT
cet-3928	144	1	383	383	NUM
cet-3928	144	2	this	this	DET
cet-3928	144	3	paper	paper	NOUN
cet-3928	144	4	,	,	PUNCT
cet-3928	144	5	on	on	ADP
cet-3928	144	6	the	the	DET
cet-3928	144	7	basis	basis	NOUN
cet-3928	144	8	of	of	ADP
cet-3928	144	9	analyzing	analyze	VERB
cet-3928	144	10	the	the	DET
cet-3928	144	11	characteristics	characteristic	NOUN
cet-3928	144	12	of	of	ADP
cet-3928	144	13	the	the	DET
cet-3928	144	14	bayesian	bayesian	NOUN
cet-3928	144	15	model	model	NOUN
cet-3928	144	16	,	,	PUNCT
cet-3928	144	17	combined	combine	VERB
cet-3928	144	18	with	with	ADP
cet-3928	144	19	the	the	DET
cet-3928	144	20	fisher	fisher	PROPN
cet-3928	144	21	linear	linear	PROPN
cet-3928	144	22	discriminant	discriminant	ADJ
cet-3928	144	23	analysis	analysis	NOUN
cet-3928	144	24	,	,	PUNCT
cet-3928	144	25	gives	give	VERB
cet-3928	144	26	a	a	DET
cet-3928	144	27	combined	combine	VERB
cet-3928	144	28	bayesian	bayesian	NOUN
cet-3928	144	29	and	and	CCONJ
cet-3928	144	30	fisher	fisher	PROPN
cet-3928	144	31	algorithm	algorithm	NOUN
cet-3928	144	32	of	of	ADP
cet-3928	144	33	a	a	DET
cet-3928	144	34	multi	multi	ADJ
cet-3928	144	35	-	-	ADJ
cet-3928	144	36	dimensional	dimensional	ADJ
cet-3928	144	37	customer	customer	NOUN
cet-3928	144	38	behavior	behavior	NOUN
cet-3928	144	39	analysis	analysis	NOUN
cet-3928	144	40	model	model	NOUN
cet-3928	144	41	.	.	PUNCT
cet-3928	145	1	results	result	NOUN
cet-3928	145	2	show	show	VERB
cet-3928	145	3	that	that	SCONJ
cet-3928	145	4	the	the	DET
cet-3928	145	5	model	model	NOUN
cet-3928	145	6	can	can	AUX
cet-3928	145	7	effectively	effectively	ADV
cet-3928	145	8	improve	improve	VERB
cet-3928	145	9	classification	classification	NOUN
cet-3928	145	10	accuracy	accuracy	NOUN
cet-3928	145	11	and	and	CCONJ
cet-3928	145	12	reduce	reduce	VERB
cet-3928	145	13	labor	labor	NOUN
cet-3928	145	14	cost	cost	NOUN
cet-3928	145	15	.	.	PUNCT
cet-3928	146	1	at	at	ADP
cet-3928	146	2	the	the	DET
cet-3928	146	3	same	same	ADJ
cet-3928	146	4	time	time	NOUN
cet-3928	146	5	to	to	ADP
cet-3928	146	6	it	it	PRON
cet-3928	146	7	can	can	AUX
cet-3928	146	8	provide	provide	VERB
cet-3928	146	9	customers	customer	NOUN
cet-3928	146	10	with	with	ADP
cet-3928	146	11	good	good	ADJ
cet-3928	146	12	quality	quality	NOUN
cet-3928	146	13	products	product	NOUN
cet-3928	146	14	,	,	PUNCT
cet-3928	146	15	which	which	PRON
cet-3928	146	16	is	be	AUX
cet-3928	146	17	the	the	DET
cet-3928	146	18	cornerstone	cornerstone	NOUN
cet-3928	146	19	of	of	ADP
cet-3928	146	20	the	the	DET
cet-3928	146	21	market	market	NOUN
cet-3928	146	22	,	,	PUNCT
cet-3928	146	23	and	and	CCONJ
cet-3928	146	24	is	be	AUX
cet-3928	146	25	the	the	DET
cet-3928	146	26	key	key	NOUN
cet-3928	146	27	to	to	PART
cet-3928	146	28	win	win	VERB
cet-3928	146	29	over	over	ADP
cet-3928	146	30	the	the	DET
cet-3928	146	31	trust	trust	NOUN
cet-3928	146	32	of	of	ADP
cet-3928	146	33	users	user	NOUN
cet-3928	146	34	.	.	PUNCT
cet-3928	147	1	acknowledgments	acknowledgment	NOUN
cet-3928	147	2	heilongjiang	heilongjiang	PROPN
cet-3928	147	3	province	province	PROPN
cet-3928	147	4	natural	natural	PROPN
cet-3928	147	5	science	science	PROPN
cet-3928	147	6	foundation	foundation	PROPN
cet-3928	147	7	of	of	ADP
cet-3928	147	8	china	china	PROPN
cet-3928	147	9	(	(	PUNCT
cet-3928	147	10	f201436	f201436	NOUN
cet-3928	147	11	)	)	PUNCT
cet-3928	147	12	.	.	PUNCT
cet-3928	148	1	references	reference	NOUN
cet-3928	148	2	abdelfattah	abdelfattah	PROPN
cet-3928	148	3	i.m	i.m	PROPN
cet-3928	148	4	.	.	PROPN
cet-3928	148	5	,	,	PUNCT
cet-3928	148	6	khedr	khedr	PROPN
cet-3928	148	7	w.i	w.i	PROPN
cet-3928	148	8	.	.	PROPN
cet-3928	148	9	,	,	PUNCT
cet-3928	148	10	sallam	sallam	PROPN
cet-3928	148	11	k.m	k.m	PROPN
cet-3928	148	12	.	.	PROPN
cet-3928	148	13	,	,	PUNCT
cet-3928	148	14	2013	2013	NUM
cet-3928	148	15	,	,	PUNCT
cet-3928	148	16	a	a	DET
cet-3928	148	17	topsis	topsis	NOUN
cet-3928	148	18	based	base	VERB
cet-3928	148	19	method	method	NOUN
cet-3928	148	20	for	for	ADP
cet-3928	148	21	gene	gene	NOUN
cet-3928	148	22	selection	selection	NOUN
cet-3928	148	23	for	for	ADP
cet-3928	148	24	cancer	cancer	NOUN
cet-3928	148	25	classification	classification	NOUN
cet-3928	148	26	j	j	PROPN
cet-3928	148	27	]	]	X
cet-3928	148	28	.	.	PUNCT
cet-3928	149	1	international	international	ADJ
cet-3928	149	2	journal	journal	PROPN
cet-3928	149	3	of	of	ADP
cet-3928	149	4	computer	computer	NOUN
cet-3928	149	5	applications	application	NOUN
cet-3928	149	6	,	,	PUNCT
cet-3928	149	7	67(17	67(17	NUM
cet-3928	149	8	):	):	PUNCT
cet-3928	149	9	39	39	NUM
cet-3928	149	10	-	-	SYM
cet-3928	149	11	44	44	NUM
cet-3928	149	12	.	.	PUNCT
cet-3928	150	1	doi:10.5120/11490	doi:10.5120/11490	PROPN
cet-3928	150	2	-	-	PUNCT
cet-3928	150	3	7195	7195	NUM
cet-3928	150	4	.	.	PUNCT
cet-3928	151	1	aquaro	aquaro	PROPN
cet-3928	151	2	v.	v.	PROPN
cet-3928	151	3	,	,	PUNCT
cet-3928	151	4	bardoscia	bardoscia	NOUN
cet-3928	151	5	m.	m.	NOUN
cet-3928	151	6	,	,	PUNCT
cet-3928	151	7	bellotti	bellotti	PROPN
cet-3928	151	8	r.	r.	PROPN
cet-3928	151	9	,	,	PUNCT
cet-3928	151	10	2009	2009	NUM
cet-3928	151	11	,	,	PUNCT
cet-3928	151	12	a	a	DET
cet-3928	151	13	bayesian	bayesian	NOUN
cet-3928	151	14	networks	network	NOUN
cet-3928	151	15	approach	approach	VERB
cet-3928	151	16	to	to	ADP
cet-3928	151	17	operational	operational	ADJ
cet-3928	151	18	risk[j	risk[j	NOUN
cet-3928	151	19	]	]	PUNCT
cet-3928	151	20	.	.	PUNCT
cet-3928	152	1	physicall	physicall	VERB
cet-3928	152	2	a	a	DET
cet-3928	152	3	statistical	statistical	ADJ
cet-3928	152	4	mechanics	mechanic	NOUN
cet-3928	152	5	&	&	CCONJ
cet-3928	152	6	its	its	PRON
cet-3928	152	7	applications	application	NOUN
cet-3928	152	8	,	,	PUNCT
cet-3928	152	9	389(906.3968	389(906.3968	NUM
cet-3928	152	10	):	):	PUNCT
cet-3928	152	11	1721–1728	1721–1728	NUM
cet-3928	152	12	.	.	PUNCT
cet-3928	153	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	153	2	/	/	SYM
cet-3928	153	3	j.physa.2009.12.043	j.physa.2009.12.043	PROPN
cet-3928	153	4	.	.	PUNCT
cet-3928	153	5	bouchaala	bouchaala	PROPN
cet-3928	153	6	l.	l.	PROPN
cet-3928	153	7	,	,	PUNCT
cet-3928	153	8	masmoudi	masmoudi	PROPN
cet-3928	153	9	a.	a.	PROPN
cet-3928	153	10	,	,	PUNCT
cet-3928	153	11	gargouri	gargouri	PROPN
cet-3928	153	12	f.	f.	PROPN
cet-3928	153	13	,	,	PUNCT
cet-3928	153	14	2010	2010	NUM
cet-3928	153	15	,	,	PUNCT
cet-3928	153	16	improving	improve	VERB
cet-3928	153	17	algorithms	algorithm	NOUN
cet-3928	153	18	for	for	ADP
cet-3928	153	19	structure	structure	NOUN
cet-3928	153	20	learning	learning	NOUN
cet-3928	153	21	in	in	ADP
cet-3928	153	22	bayesian	bayesian	NOUN
cet-3928	153	23	networks	network	NOUN
cet-3928	153	24	using	use	VERB
cet-3928	153	25	a	a	DET
cet-3928	153	26	new	new	ADJ
cet-3928	153	27	implicit	implicit	ADJ
cet-3928	153	28	score[j	score[j	NOUN
cet-3928	153	29	]	]	PUNCT
cet-3928	153	30	.	.	PUNCT
cet-3928	154	1	expert	expert	NOUN
cet-3928	154	2	systems	system	NOUN
cet-3928	154	3	with	with	ADP
cet-3928	154	4	applications	application	NOUN
cet-3928	154	5	,	,	PUNCT
cet-3928	154	6	37(7):5470	37(7):5470	NUM
cet-3928	154	7	-	-	SYM
cet-3928	154	8	5475	5475	NUM
cet-3928	154	9	.	.	PUNCT
cet-3928	155	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	155	2	/	/	SYM
cet-3928	155	3	j.eswa.2010.02.065	j.eswa.2010.02.065	PROPN
cet-3928	155	4	.	.	PUNCT
cet-3928	156	1	cook	cook	PROPN
cet-3928	156	2	d.f	d.f	PROPN
cet-3928	156	3	.	.	PROPN
cet-3928	156	4	,	,	PUNCT
cet-3928	156	5	ragsdale	ragsdale	PROPN
cet-3928	156	6	c.t	c.t	PROPN
cet-3928	156	7	.	.	PROPN
cet-3928	156	8	,	,	PUNCT
cet-3928	156	9	major	major	PROPN
cet-3928	156	10	r.l	r.l	PROPN
cet-3928	156	11	.	.	PROPN
cet-3928	156	12	,	,	PUNCT
cet-3928	156	13	2000	2000	NUM
cet-3928	156	14	,	,	PUNCT
cet-3928	156	15	combining	combine	VERB
cet-3928	156	16	a	a	DET
cet-3928	156	17	neural	neural	ADJ
cet-3928	156	18	network	network	NOUN
cet-3928	156	19	with	with	ADP
cet-3928	156	20	a	a	DET
cet-3928	156	21	genetic	genetic	ADJ
cet-3928	156	22	algorithm	algorithm	NOUN
cet-3928	156	23	for	for	ADP
cet-3928	156	24	process	process	NOUN
cet-3928	156	25	parameter	parameter	NOUN
cet-3928	156	26	optimization[j	optimization[j	PROPN
cet-3928	156	27	]	]	PUNCT
cet-3928	156	28	.	.	PUNCT
cet-3928	157	1	engineering	engineering	NOUN
cet-3928	157	2	applications	application	NOUN
cet-3928	157	3	of	of	ADP
cet-3928	157	4	artificial	artificial	ADJ
cet-3928	157	5	intelligence	intelligence	NOUN
cet-3928	157	6	,	,	PUNCT
cet-3928	157	7	13(4):391	13(4):391	NUM
cet-3928	157	8	-	-	SYM
cet-3928	157	9	396	396	NUM
cet-3928	157	10	.	.	PUNCT
cet-3928	158	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	158	2	/	/	SYM
cet-3928	158	3	s0952	s0952	PROPN
cet-3928	158	4	-	-	PUNCT
cet-3928	158	5	1976(00)00021	1976(00)00021	NUM
cet-3928	158	6	-	-	PUNCT
cet-3928	158	7	x	x	PROPN
cet-3928	158	8	duan	duan	PROPN
cet-3928	158	9	j.	j.	PROPN
cet-3928	158	10	,	,	PUNCT
cet-3928	158	11	wang	wang	PROPN
cet-3928	158	12	w.	w.	PROPN
cet-3928	158	13	,	,	PUNCT
cet-3928	158	14	zeng	zeng	PROPN
cet-3928	158	15	j.	j.	PROPN
cet-3928	158	16	,	,	PUNCT
cet-3928	158	17	2009	2009	NUM
cet-3928	158	18	,	,	PUNCT
cet-3928	158	19	a	a	DET
cet-3928	158	20	prediction	prediction	NOUN
cet-3928	158	21	algorithm	algorithm	NOUN
cet-3928	158	22	for	for	ADP
cet-3928	158	23	time	time	NOUN
cet-3928	158	24	series	series	NOUN
cet-3928	158	25	based	base	VERB
cet-3928	158	26	on	on	ADP
cet-3928	158	27	adaptive	adaptive	ADJ
cet-3928	158	28	model	model	NOUN
cet-3928	158	29	selection[j	selection[j	PROPN
cet-3928	158	30	]	]	PUNCT
cet-3928	158	31	.	.	PUNCT
cet-3928	159	1	expert	expert	NOUN
cet-3928	159	2	systems	system	NOUN
cet-3928	159	3	with	with	ADP
cet-3928	159	4	applications	application	NOUN
cet-3928	159	5	,	,	PUNCT
cet-3928	159	6	36(2):1308	36(2):1308	NUM
cet-3928	159	7	-	-	SYM
cet-3928	159	8	1314	1314	NUM
cet-3928	159	9	.	.	PUNCT
cet-3928	160	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	160	2	/	/	SYM
cet-3928	160	3	j.eswa.2007.11.021	j.eswa.2007.11.021	PROPN
cet-3928	160	4	.	.	PUNCT
cet-3928	161	1	guo	guo	PROPN
cet-3928	161	2	x.	x.	PROPN
cet-3928	161	3	,	,	PUNCT
cet-3928	161	4	li	li	PROPN
cet-3928	161	5	d.c	d.c	PROPN
cet-3928	161	6	.	.	PROPN
cet-3928	161	7	,	,	PUNCT
cet-3928	161	8	zhang	zhang	PROPN
cet-3928	161	9	a.	a.	PROPN
cet-3928	161	10	,	,	PUNCT
cet-3928	161	11	2012	2012	NUM
cet-3928	161	12	,	,	PUNCT
cet-3928	161	13	improved	improve	VERB
cet-3928	161	14	support	support	NOUN
cet-3928	161	15	vector	vector	NOUN
cet-3928	161	16	machine	machine	NOUN
cet-3928	161	17	oil	oil	NOUN
cet-3928	161	18	price	price	NOUN
cet-3928	161	19	forecast	forecast	NOUN
cet-3928	161	20	model	model	NOUN
cet-3928	161	21	based	base	VERB
cet-3928	161	22	on	on	ADP
cet-3928	161	23	genetic	genetic	ADJ
cet-3928	161	24	algorithm	algorithm	NOUN
cet-3928	161	25	optimization	optimization	NOUN
cet-3928	161	26	parameters	parameter	NOUN
cet-3928	161	27	[	[	X
cet-3928	161	28	j	j	X
cet-3928	161	29	]	]	X
cet-3928	161	30	.	.	PUNCT
cet-3928	162	1	aasri	aasri	PROPN
cet-3928	162	2	procedia	procedia	PROPN
cet-3928	162	3	,	,	PUNCT
cet-3928	162	4	1(4):525	1(4):525	NUM
cet-3928	162	5	-	-	SYM
cet-3928	162	6	530	530	NUM
cet-3928	162	7	.	.	PUNCT
cet-3928	163	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	163	2	/	/	SYM
cet-3928	163	3	j.aasri.2012.06.082	j.aasri.2012.06.082	PROPN
cet-3928	163	4	.	.	PUNCT
cet-3928	164	1	hao	hao	PROPN
cet-3928	164	2	h.n	h.n	PROPN
cet-3928	164	3	.	.	PROPN
cet-3928	164	4	,	,	PUNCT
cet-3928	164	5	2010	2010	NUM
cet-3928	164	6	,	,	PUNCT
cet-3928	164	7	notice	notice	NOUN
cet-3928	164	8	of	of	ADP
cet-3928	164	9	retraction	retraction	NOUN
cet-3928	164	10	short	short	ADJ
cet-3928	164	11	-	-	PUNCT
cet-3928	164	12	term	term	NOUN
cet-3928	164	13	forecasting	forecasting	NOUN
cet-3928	164	14	of	of	ADP
cet-3928	164	15	stock	stock	NOUN
cet-3928	164	16	price	price	NOUN
cet-3928	164	17	based	base	VERB
cet-3928	164	18	on	on	ADP
cet-3928	164	19	genetic	genetic	ADJ
cet-3928	164	20	-	-	PUNCT
cet-3928	164	21	neural	neural	ADJ
cet-3928	164	22	network[c]//	network[c]//	PROPN
cet-3928	164	23	natural	natural	ADJ
cet-3928	164	24	computation	computation	NOUN
cet-3928	164	25	(	(	PUNCT
cet-3928	164	26	icnc	icnc	PROPN
cet-3928	164	27	)	)	PUNCT
cet-3928	164	28	,	,	PUNCT
cet-3928	164	29	2010	2010	NUM
cet-3928	164	30	sixth	sixth	ADJ
cet-3928	164	31	international	international	ADJ
cet-3928	164	32	conference	conference	NOUN
cet-3928	164	33	on	on	ADP
cet-3928	164	34	.	.	PUNCT
cet-3928	165	1	ieee	ieee	PROPN
cet-3928	165	2	,	,	PUNCT
cet-3928	165	3	1838	1838	NUM
cet-3928	165	4	-	-	SYM
cet-3928	165	5	1841	1841	NUM
cet-3928	165	6	.	.	PUNCT
cet-3928	166	1	doi:10.1109	doi:10.1109	VERB
cet-3928	166	2	/	/	SYM
cet-3928	166	3	icnc.2010.5584528	icnc.2010.5584528	PROPN
cet-3928	166	4	.	.	PUNCT
cet-3928	167	1	liu	liu	PROPN
cet-3928	167	2	c.	c.	PROPN
cet-3928	167	3	,	,	PUNCT
cet-3928	167	4	2014	2014	NUM
cet-3928	167	5	,	,	PUNCT
cet-3928	167	6	network	network	NOUN
cet-3928	167	7	intrusion	intrusion	NOUN
cet-3928	167	8	detection	detection	NOUN
cet-3928	167	9	model	model	NOUN
cet-3928	167	10	based	base	VERB
cet-3928	167	11	on	on	ADP
cet-3928	167	12	genetic	genetic	ADJ
cet-3928	167	13	algorithm	algorithm	NOUN
cet-3928	167	14	optimizing	optimize	VERB
cet-3928	167	15	parameters	parameter	NOUN
cet-3928	167	16	of	of	ADP
cet-3928	167	17	support	support	NOUN
cet-3928	167	18	vector	vector	NOUN
cet-3928	167	19	machine	machine	NOUN
cet-3928	168	1	[	[	X
cet-3928	168	2	j	j	X
cet-3928	168	3	]	]	X
cet-3928	168	4	.	.	PUNCT
cet-3928	169	1	advanced	advanced	ADJ
cet-3928	169	2	materials	material	NOUN
cet-3928	169	3	research	research	NOUN
cet-3928	169	4	,	,	PUNCT
cet-3928	169	5	989	989	NUM
cet-3928	169	6	-	-	PUNCT
cet-3928	169	7	994:2012	994:2012	NUM
cet-3928	169	8	-	-	PUNCT
cet-3928	169	9	2015	2015	NUM
cet-3928	169	10	.	.	PUNCT
cet-3928	170	1	doi:10.4028	doi:10.4028	ADJ
cet-3928	170	2	/	/	SYM
cet-3928	170	3	www.scientific.net	www.scientific.net	NOUN
cet-3928	170	4	/	/	SYM
cet-3928	170	5	amr.989	amr.989	NOUN
cet-3928	170	6	-	-	PUNCT
cet-3928	170	7	994.2012	994.2012	NUM
cet-3928	170	8	.	.	PUNCT
cet-3928	171	1	li	li	PROPN
cet-3928	171	2	l.	l.	PROPN
cet-3928	171	3	,	,	PUNCT
cet-3928	171	4	ma	ma	PROPN
cet-3928	171	5	s.	s.	PROPN
cet-3928	171	6	,	,	PUNCT
cet-3928	171	7	zhang	zhang	PROPN
cet-3928	171	8	y.	y.	PROPN
cet-3928	171	9	,	,	PUNCT
cet-3928	171	10	2014	2014	NUM
cet-3928	171	11	,	,	PUNCT
cet-3928	171	12	optimization	optimization	NOUN
cet-3928	171	13	algorithm	algorithm	NOUN
cet-3928	171	14	based	base	VERB
cet-3928	171	15	on	on	ADP
cet-3928	171	16	genetic	genetic	ADJ
cet-3928	171	17	support	support	NOUN
cet-3928	171	18	vector	vector	NOUN
cet-3928	171	19	machine	machine	NOUN
cet-3928	171	20	model[c]//	model[c]//	PROPN
cet-3928	171	21	seventh	seventh	ADJ
cet-3928	171	22	international	international	ADJ
cet-3928	171	23	symposium	symposium	NOUN
cet-3928	171	24	on	on	ADP
cet-3928	171	25	computational	computational	ADJ
cet-3928	171	26	intelligence	intelligence	NOUN
cet-3928	171	27	and	and	CCONJ
cet-3928	171	28	design	design	NOUN
cet-3928	171	29	.	.	PUNCT
cet-3928	172	1	ieee	ieee	NOUN
cet-3928	172	2	,	,	PUNCT
cet-3928	172	3	307	307	NUM
cet-3928	172	4	310	310	NUM
cet-3928	172	5	.	.	PUNCT
cet-3928	173	1	doi:10.1109	doi:10.1109	VERB
cet-3928	173	2	/	/	SYM
cet-3928	173	3	iscid.2014.99	iscid.2014.99	NOUN
cet-3928	173	4	.	.	PUNCT
cet-3928	174	1	qu	qu	PROPN
cet-3928	174	2	h.n	h.n	PROPN
cet-3928	174	3	.	.	PROPN
cet-3928	174	4	,	,	PUNCT
cet-3928	174	5	li	li	PROPN
cet-3928	174	6	g.z	g.z	PROPN
cet-3928	174	7	.	.	PROPN
cet-3928	174	8	,	,	PUNCT
cet-3928	174	9	xu	xu	PROPN
cet-3928	175	1	w.s	w.s	PROPN
cet-3928	175	2	.	.	PROPN
cet-3928	175	3	,	,	PUNCT
cet-3928	175	4	2010	2010	NUM
cet-3928	175	5	,	,	PUNCT
cet-3928	175	6	an	an	DET
cet-3928	175	7	asymmetric	asymmetric	ADJ
cet-3928	175	8	classifier	classifier	NOUN
cet-3928	175	9	based	base	VERB
cet-3928	175	10	on	on	ADP
cet-3928	175	11	partial	partial	ADJ
cet-3928	175	12	least	least	ADJ
cet-3928	175	13	squares[j	squares[j	NOUN
cet-3928	175	14	]	]	PUNCT
cet-3928	175	15	.	.	PUNCT
cet-3928	176	1	pattern	pattern	NOUN
cet-3928	176	2	recognition	recognition	NOUN
cet-3928	176	3	,	,	PUNCT
cet-3928	176	4	43(10):3448	43(10):3448	X
cet-3928	176	5	-	-	SYM
cet-3928	176	6	3457	3457	NUM
cet-3928	176	7	.	.	PUNCT
cet-3928	177	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	177	2	/	/	SYM
cet-3928	177	3	j.	j.	PROPN
cet-3928	177	4	patcog	patcog	PROPN
cet-3928	177	5	.	.	PUNCT
cet-3928	178	1	2010.05.002	2010.05.002	NOUN
cet-3928	178	2	.	.	PUNCT
cet-3928	179	1	sun	sun	PROPN
cet-3928	179	2	y.	y.	PROPN
cet-3928	179	3	,	,	PUNCT
cet-3928	179	4	tang	tang	PROPN
cet-3928	179	5	y.	y.	PROPN
cet-3928	179	6	,	,	PUNCT
cet-3928	179	7	ding	de	VERB
cet-3928	179	8	s.l	s.l	PROPN
cet-3928	179	9	.	.	PROPN
cet-3928	179	10	,	,	PUNCT
cet-3928	179	11	2011	2011	NUM
cet-3928	179	12	,	,	PUNCT
cet-3928	179	13	diagnose	diagnose	VERB
cet-3928	179	14	the	the	DET
cet-3928	179	15	mild	mild	ADJ
cet-3928	179	16	cognitive	cognitive	ADJ
cet-3928	179	17	impairment	impairment	NOUN
cet-3928	179	18	by	by	ADP
cet-3928	179	19	constructing	construct	VERB
cet-3928	179	20	bayesian	bayesian	NOUN
cet-3928	179	21	network	network	NOUN
cet-3928	179	22	with	with	ADP
cet-3928	179	23	missing	miss	VERB
cet-3928	179	24	data[j	data[j	NOUN
cet-3928	179	25	]	]	PUNCT
cet-3928	179	26	.	.	PUNCT
cet-3928	180	1	expert	expert	NOUN
cet-3928	180	2	systems	system	NOUN
cet-3928	180	3	with	with	ADP
cet-3928	180	4	applications	application	NOUN
cet-3928	180	5	,	,	PUNCT
cet-3928	180	6	38(1):442	38(1):442	NUM
cet-3928	180	7	-	-	SYM
cet-3928	180	8	449	449	NUM
cet-3928	180	9	.	.	PUNCT
cet-3928	180	10	doi:10.1016	doi:10.1016	PROPN
cet-3928	180	11	/	/	SYM
cet-3928	180	12	j.eswa.2010.06.084	j.eswa.2010.06.084	PROPN
cet-3928	180	13	.	.	PUNCT
cet-3928	181	1	thalayasingam	thalayasingam	ADJ
cet-3928	181	2	m.	m.	NOUN
cet-3928	181	3	,	,	PUNCT
cet-3928	181	4	veerakumarasivam	veerakumarasivam	ADJ
cet-3928	181	5	a.	a.	NOUN
cet-3928	181	6	,	,	PUNCT
cet-3928	181	7	kulanthayan	kulanthayan	PROPN
cet-3928	181	8	s.	s.	PROPN
cet-3928	181	9	,	,	PUNCT
cet-3928	181	10	2012	2012	NUM
cet-3928	181	11	,	,	PUNCT
cet-3928	181	12	clinical	clinical	ADJ
cet-3928	181	13	clues	clue	NOUN
cet-3928	181	14	for	for	ADP
cet-3928	181	15	head	head	NOUN
cet-3928	181	16	injuries	injury	NOUN
cet-3928	181	17	amongst	amongst	ADP
cet-3928	181	18	malaysian	malaysian	ADJ
cet-3928	181	19	infants	infant	NOUN
cet-3928	181	20	:	:	PUNCT
cet-3928	181	21	accidental	accidental	ADJ
cet-3928	181	22	or	or	CCONJ
cet-3928	181	23	non	non	ADJ
cet-3928	181	24	-	-	ADJ
cet-3928	181	25	accidental?[j	accidental?[j	ADJ
cet-3928	181	26	]	]	PUNCT
cet-3928	181	27	.	.	PUNCT
cet-3928	182	1	injury	injury	NOUN
cet-3928	182	2	-	-	PUNCT
cet-3928	182	3	international	international	ADJ
cet-3928	182	4	journal	journal	NOUN
cet-3928	182	5	of	of	ADP
cet-3928	182	6	the	the	DET
cet-3928	182	7	care	care	NOUN
cet-3928	182	8	of	of	ADP
cet-3928	182	9	the	the	DET
cet-3928	182	10	injured	injure	VERB
cet-3928	182	11	,	,	PUNCT
cet-3928	182	12	43(12):2083	43(12):2083	NUM
cet-3928	182	13	-	-	SYM
cet-3928	182	14	2087	2087	NUM
cet-3928	182	15	.	.	PUNCT
cet-3928	183	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	183	2	/	/	SYM
cet-3928	183	3	j.injury.2012.02.010	j.injury.2012.02.010	PROPN
cet-3928	183	4	.	.	PUNCT
cet-3928	184	1	tseng	tseng	PROPN
cet-3928	184	2	p.c	p.c	PROPN
cet-3928	184	3	.	.	PROPN
cet-3928	184	4	,	,	PUNCT
cet-3928	184	5	woung	woung	PROPN
cet-3928	184	6	l.c	l.c	PROPN
cet-3928	184	7	.	.	PROPN
cet-3928	184	8	,	,	PUNCT
cet-3928	184	9	tseng	tseng	PROPN
cet-3928	184	10	g.l	g.l	PROPN
cet-3928	184	11	.	.	PROPN
cet-3928	184	12	,	,	PUNCT
cet-3928	184	13	2012	2012	NUM
cet-3928	184	14	,	,	PUNCT
cet-3928	184	15	refractive	refractive	ADJ
cet-3928	184	16	change	change	NOUN
cet-3928	184	17	after	after	SCONJ
cet-3928	184	18	pars	pars	PROPN
cet-3928	184	19	plana	plana	PROPN
cet-3928	184	20	vitrectomy[j	vitrectomy[j	PROPN
cet-3928	184	21	]	]	PROPN
cet-3928	184	22	.	.	PUNCT
cet-3928	185	1	taiwan	taiwan	PROPN
cet-3928	185	2	journal	journal	PROPN
cet-3928	185	3	of	of	ADP
cet-3928	185	4	ophthalmology	ophthalmology	NOUN
cet-3928	185	5	,	,	PUNCT
cet-3928	185	6	2(1):18–21	2(1):18–21	NUM
cet-3928	185	7	.	.	PUNCT
cet-3928	186	1	doi	doi	NOUN
cet-3928	186	2	:	:	PUNCT
cet-3928	186	3	10.1016	10.1016	NUM
cet-3928	186	4	/	/	SYM
cet-3928	186	5	j.tjo.2011.11.003	j.tjo.2011.11.003	PROPN
cet-3928	186	6	.	.	PUNCT
cet-3928	187	1	yang	yang	PROPN
cet-3928	187	2	y.	y.	PROPN
cet-3928	187	3	,	,	PUNCT
cet-3928	187	4	wu	wu	PROPN
cet-3928	187	5	y.	y.	PROPN
cet-3928	187	6	,	,	PUNCT
cet-3928	187	7	2012	2012	NUM
cet-3928	187	8	,	,	PUNCT
cet-3928	187	9	on	on	ADP
cet-3928	187	10	the	the	DET
cet-3928	187	11	properties	property	NOUN
cet-3928	187	12	of	of	ADP
cet-3928	187	13	concept	concept	NOUN
cet-3928	187	14	classes	class	NOUN
cet-3928	187	15	induced	induce	VERB
cet-3928	187	16	by	by	ADP
cet-3928	187	17	multivalued	multivalue	VERB
cet-3928	187	18	bayesian	bayesian	NOUN
cet-3928	187	19	networks	network	NOUN
cet-3928	187	20	[	[	X
cet-3928	187	21	j	j	X
cet-3928	187	22	]	]	X
cet-3928	187	23	.	.	PUNCT
cet-3928	188	1	information	information	NOUN
cet-3928	188	2	sciences	sciences	PROPN
cet-3928	188	3	,	,	PUNCT
cet-3928	188	4	184(1):155	184(1):155	NUM
cet-3928	188	5	-	-	SYM
cet-3928	188	6	165	165	NUM
cet-3928	188	7	.	.	PUNCT
cet-3928	189	1	doi:10.1016	doi:10.1016	PROPN
cet-3928	189	2	/	/	SYM
cet-3928	189	3	j.ins.2011.08.031	j.ins.2011.08.031	PROPN
cet-3928	189	4	yoon	yoon	PROPN
cet-3928	189	5	i.p.b	i.p.b	PROPN
cet-3928	189	6	.	.	PROPN
cet-3928	189	7	,	,	PUNCT
cet-3928	189	8	2014	2014	NUM
cet-3928	189	9	,	,	PUNCT
cet-3928	189	10	a	a	DET
cet-3928	189	11	semantic	semantic	ADJ
cet-3928	189	12	analysis	analysis	NOUN
cet-3928	189	13	approach	approach	NOUN
cet-3928	189	14	for	for	ADP
cet-3928	189	15	identifying	identify	VERB
cet-3928	189	16	patent	patent	NOUN
cet-3928	189	17	infringement	infringement	NOUN
cet-3928	189	18	based	base	VERB
cet-3928	189	19	on	on	ADP
cet-3928	189	20	a	a	DET
cet-3928	189	21	product	product	NOUN
cet-3928	189	22	–	–	PUNCT
cet-3928	189	23	patent	patent	NOUN
cet-3928	189	24	map[j	map[j	NOUN
cet-3928	189	25	]	]	PUNCT
cet-3928	189	26	.	.	PUNCT
cet-3928	190	1	technology	technology	NOUN
cet-3928	190	2	analysis	analysis	NOUN
cet-3928	190	3	&	&	CCONJ
cet-3928	190	4	strategic	strategic	ADJ
cet-3928	190	5	management	management	NOUN
cet-3928	190	6	,	,	PUNCT
cet-3928	190	7	26(8):855	26(8):855	PROPN
cet-3928	190	8	-	-	PUNCT
cet-3928	190	9	874	874	NUM
cet-3928	190	10	.	.	PUNCT
cet-3928	191	1	doi:10.1080/09537325.2014.909926	doi:10.1080/09537325.2014.909926	PROPN
cet-3928	191	2	.	.	PROPN
cet-3928	191	3	yu	yu	PROPN
cet-3928	191	4	f.	f.	PROPN
cet-3928	191	5	,	,	PUNCT
cet-3928	191	6	wang	wang	PROPN
cet-3928	191	7	z.q	z.q	PROPN
cet-3928	191	8	.	.	PROPN
cet-3928	191	9	,	,	PUNCT
cet-3928	191	10	xu	xu	PROPN
cet-3928	192	1	x.z	x.z	PROPN
cet-3928	192	2	.	.	PROPN
cet-3928	192	3	,	,	PUNCT
cet-3928	192	4	2014	2014	NUM
cet-3928	192	5	,	,	PUNCT
cet-3928	192	6	short	short	ADJ
cet-3928	192	7	-	-	PUNCT
cet-3928	192	8	term	term	NOUN
cet-3928	192	9	gas	gas	NOUN
cet-3928	192	10	load	load	NOUN
cet-3928	192	11	forecasting	forecasting	NOUN
cet-3928	192	12	based	base	VERB
cet-3928	192	13	on	on	ADP
cet-3928	192	14	wavelet	wavelet	PROPN
cet-3928	192	15	bp	bp	PROPN
cet-3928	192	16	neural	neural	ADJ
cet-3928	192	17	network	network	NOUN
cet-3928	192	18	optimized	optimize	VERB
cet-3928	192	19	by	by	ADP
cet-3928	192	20	genetic	genetic	ADJ
cet-3928	192	21	algorithm[j	algorithm[j	PROPN
cet-3928	192	22	]	]	PUNCT
cet-3928	192	23	.	.	PUNCT
cet-3928	193	1	applied	apply	VERB
cet-3928	193	2	mechanics	mechanic	NOUN
cet-3928	193	3	&	&	CCONJ
cet-3928	193	4	materials	material	NOUN
cet-3928	193	5	,	,	PUNCT
cet-3928	193	6	631	631	NUM
cet-3928	193	7	-	-	PUNCT
cet-3928	193	8	632(631	632(631	NUM
cet-3928	193	9	-	-	PUNCT
cet-3928	193	10	632):79	632):79	NUM
cet-3928	193	11	-	-	PUNCT
cet-3928	193	12	85	85	NUM
cet-3928	193	13	.	.	PUNCT
cet-3928	194	1	doi:10.4028	doi:10.4028	ADJ
cet-3928	194	2	/	/	SYM
cet-3928	194	3	www.scientific.net	www.scientific.net	NOUN
cet-3928	194	4	/	/	SYM
cet-3928	194	5	amm.631	amm.631	NOUN
cet-3928	194	6	-	-	PUNCT
cet-3928	194	7	632.79	632.79	NUM
cet-3928	194	8	.	.	PUNCT
cet-3928	195	1	384	384	NUM