id	sid	tid	token	lemma	pos
cana-3788	1	1	communications	communication	NOUN
cana-3788	1	2	on	on	ADP
cana-3788	1	3	applied	apply	VERB
cana-3788	1	4	nonlinear	nonlinear	ADJ
cana-3788	1	5	analysis	analysis	NOUN
cana-3788	1	6	issn	issn	NOUN
cana-3788	1	7	:	:	PUNCT
cana-3788	1	8	1074	1074	NUM
cana-3788	1	9	-	-	PUNCT
cana-3788	1	10	133x	133x	NUM
cana-3788	1	11	vol	vol	NOUN
cana-3788	1	12	32	32	NUM
cana-3788	1	13	no	no	NOUN
cana-3788	1	14	.	.	PUNCT
cana-3788	2	1	8s	8s	PROPN
cana-3788	2	2	(	(	PUNCT
cana-3788	2	3	2025	2025	NUM
cana-3788	2	4	)	)	PUNCT
cana-3788	2	5	724	724	NUM
cana-3788	3	1	https://internationalpubls.co	https://internationalpubls.co	ADP
cana-3788	3	2	m	m	VERB
cana-3788	3	3	improving	improve	VERB
cana-3788	3	4	recommendation	recommendation	NOUN
cana-3788	3	5	systems	system	NOUN
cana-3788	3	6	with	with	ADP
cana-3788	3	7	machine	machine	NOUN
cana-3788	3	8	learning	learning	NOUN
cana-3788	3	9	-	-	PUNCT
cana-3788	3	10	based	base	VERB
cana-3788	3	11	noise	noise	NOUN
cana-3788	3	12	management	management	NOUN
cana-3788	3	13	1	1	NUM
cana-3788	3	14	kausar	kausar	PROPN
cana-3788	3	15	attar	attar	NOUN
cana-3788	3	16	,	,	PUNCT
cana-3788	3	17	2	2	NUM
cana-3788	3	18	ashish	ashish	ADJ
cana-3788	3	19	jadhav	jadhav	PROPN
cana-3788	3	20	1computer	1computer	NUM
cana-3788	3	21	engineering	engineering	NOUN
cana-3788	3	22	,	,	PUNCT
cana-3788	3	23	ramrao	ramrao	PROPN
cana-3788	3	24	adik	adik	PROPN
cana-3788	3	25	institute	institute	PROPN
cana-3788	3	26	of	of	ADP
cana-3788	3	27	technology	technology	PROPN
cana-3788	3	28	,	,	PUNCT
cana-3788	3	29	d.y	d.y	PROPN
cana-3788	3	30	.	.	PROPN
cana-3788	3	31	patil	patil	PROPN
cana-3788	3	32	deemed	deem	VERB
cana-3788	3	33	to	to	PART
cana-3788	3	34	be	be	AUX
cana-3788	3	35	university	university	NOUN
cana-3788	3	36	,	,	PUNCT
cana-3788	3	37	nerul	nerul	PROPN
cana-3788	3	38	,	,	PUNCT
cana-3788	3	39	navi	navi	PROPN
cana-3788	3	40	mumbai	mumbai	PROPN
cana-3788	3	41	,	,	PUNCT
cana-3788	3	42	india	india	PROPN
cana-3788	3	43	.	.	PUNCT
cana-3788	4	1	kausarattar7@gmail.com	kausarattar7@gmail.com	X
cana-3788	5	1	2information	2information	NUM
cana-3788	5	2	technology	technology	NOUN
cana-3788	5	3	,	,	PUNCT
cana-3788	5	4	ramrao	ramrao	VERB
cana-3788	5	5	adik	adik	PROPN
cana-3788	5	6	institute	institute	PROPN
cana-3788	5	7	of	of	ADP
cana-3788	5	8	technology	technology	PROPN
cana-3788	5	9	,	,	PUNCT
cana-3788	5	10	d.y	d.y	PROPN
cana-3788	5	11	.	.	PROPN
cana-3788	5	12	patil	patil	PROPN
cana-3788	5	13	deemed	deem	VERB
cana-3788	5	14	to	to	PART
cana-3788	5	15	be	be	AUX
cana-3788	5	16	university	university	NOUN
cana-3788	5	17	,	,	PUNCT
cana-3788	5	18	navi	navi	PROPN
cana-3788	5	19	mumbai	mumbai	PROPN
cana-3788	5	20	,	,	PUNCT
cana-3788	5	21	india	india	PROPN
cana-3788	5	22	ashish.jadhav@rait.ac.in	ashish.jadhav@rait.ac.in	PART
cana-3788	5	23	article	article	NOUN
cana-3788	5	24	history	history	NOUN
cana-3788	5	25	:	:	PUNCT
cana-3788	5	26	received	receive	VERB
cana-3788	5	27	:	:	PUNCT
cana-3788	5	28	08	08	NUM
cana-3788	5	29	-	-	SYM
cana-3788	5	30	11	11	NUM
cana-3788	5	31	-	-	PUNCT
cana-3788	5	32	2024	2024	NUM
cana-3788	5	33	revised:15	revised:15	ADJ
cana-3788	5	34	-	-	PUNCT
cana-3788	5	35	12	12	NUM
cana-3788	5	36	-	-	PUNCT
cana-3788	5	37	2024	2024	NUM
cana-3788	5	38	accepted:03	accepted:03	NUM
cana-3788	5	39	-	-	PUNCT
cana-3788	5	40	01	01	NUM
cana-3788	5	41	-	-	PUNCT
cana-3788	5	42	2025	2025	NUM
cana-3788	5	43	abstract	abstract	NOUN
cana-3788	5	44	:	:	PUNCT
cana-3788	5	45	recommendation	recommendation	NOUN
cana-3788	5	46	systems	system	NOUN
cana-3788	5	47	have	have	AUX
cana-3788	5	48	now	now	ADV
cana-3788	5	49	adopted	adopt	VERB
cana-3788	5	50	a	a	DET
cana-3788	5	51	central	central	ADJ
cana-3788	5	52	role	role	NOUN
cana-3788	5	53	in	in	ADP
cana-3788	5	54	digital	digital	ADJ
cana-3788	5	55	services	service	NOUN
cana-3788	5	56	in	in	ADP
cana-3788	5	57	the	the	DET
cana-3788	5	58	contemporary	contemporary	ADJ
cana-3788	5	59	world	world	NOUN
cana-3788	5	60	given	give	VERB
cana-3788	5	61	its	its	PRON
cana-3788	5	62	effectiveness	effectiveness	NOUN
cana-3788	5	63	in	in	ADP
cana-3788	5	64	increasing	increase	VERB
cana-3788	5	65	user	user	NOUN
cana-3788	5	66	interest	interest	NOUN
cana-3788	5	67	and	and	CCONJ
cana-3788	5	68	value	value	NOUN
cana-3788	5	69	.	.	PUNCT
cana-3788	6	1	however	however	ADV
cana-3788	6	2	,	,	PUNCT
cana-3788	6	3	these	these	DET
cana-3788	6	4	systems	system	NOUN
cana-3788	6	5	will	will	AUX
cana-3788	6	6	always	always	ADV
cana-3788	6	7	face	face	VERB
cana-3788	6	8	the	the	DET
cana-3788	6	9	problem	problem	NOUN
cana-3788	6	10	of	of	ADP
cana-3788	6	11	handling	handle	VERB
cana-3788	6	12	natural	natural	ADJ
cana-3788	6	13	noise	noise	NOUN
cana-3788	6	14	;	;	PUNCT
cana-3788	6	15	a	a	DET
cana-3788	6	16	situation	situation	NOUN
cana-3788	6	17	that	that	PRON
cana-3788	6	18	counterfeits	counterfeit	VERB
cana-3788	6	19	the	the	DET
cana-3788	6	20	actual	actual	ADJ
cana-3788	6	21	preferences	preference	NOUN
cana-3788	6	22	of	of	ADP
cana-3788	6	23	the	the	DET
cana-3788	6	24	users	user	NOUN
cana-3788	6	25	,	,	PUNCT
cana-3788	6	26	leading	lead	VERB
cana-3788	6	27	to	to	ADP
cana-3788	6	28	low	low	ADJ
cana-3788	6	29	accuracy	accuracy	NOUN
cana-3788	6	30	of	of	ADP
cana-3788	6	31	the	the	DET
cana-3788	6	32	recommended	recommend	VERB
cana-3788	6	33	items	item	NOUN
cana-3788	6	34	.	.	PUNCT
cana-3788	7	1	this	this	DET
cana-3788	7	2	research	research	NOUN
cana-3788	7	3	introduces	introduce	VERB
cana-3788	7	4	a	a	DET
cana-3788	7	5	new	new	ADJ
cana-3788	7	6	framework	framework	NOUN
cana-3788	7	7	cnn	cnn	PROPN
cana-3788	7	8	and	and	CCONJ
cana-3788	7	9	ann	ann	PROPN
cana-3788	7	10	which	which	PRON
cana-3788	7	11	provides	provide	VERB
cana-3788	7	12	an	an	DET
cana-3788	7	13	efficient	efficient	ADJ
cana-3788	7	14	way	way	NOUN
cana-3788	7	15	of	of	ADP
cana-3788	7	16	handling	handle	VERB
cana-3788	7	17	natural	natural	ADJ
cana-3788	7	18	noise	noise	NOUN
cana-3788	7	19	to	to	PART
cana-3788	7	20	increase	increase	VERB
cana-3788	7	21	the	the	DET
cana-3788	7	22	efficiency	efficiency	NOUN
cana-3788	7	23	of	of	ADP
cana-3788	7	24	recommendations	recommendation	NOUN
cana-3788	7	25	.	.	PUNCT
cana-3788	8	1	the	the	DET
cana-3788	8	2	method	method	NOUN
cana-3788	8	3	that	that	PRON
cana-3788	8	4	is	be	AUX
cana-3788	8	5	proposed	propose	VERB
cana-3788	8	6	here	here	ADV
cana-3788	8	7	classifies	classify	VERB
cana-3788	8	8	user	user	NOUN
cana-3788	8	9	interaction	interaction	NOUN
cana-3788	8	10	data	datum	NOUN
cana-3788	8	11	using	use	VERB
cana-3788	8	12	cnn	cnn	PROPN
cana-3788	8	13	,	,	PUNCT
cana-3788	8	14	rejecting	reject	VERB
cana-3788	8	15	noise	noise	NOUN
cana-3788	8	16	but	but	CCONJ
cana-3788	8	17	embracing	embrace	VERB
cana-3788	8	18	relevant	relevant	ADJ
cana-3788	8	19	inputs	input	NOUN
cana-3788	8	20	.	.	PUNCT
cana-3788	9	1	ann	ann	PROPN
cana-3788	9	2	is	be	AUX
cana-3788	9	3	then	then	ADV
cana-3788	9	4	used	use	VERB
cana-3788	9	5	on	on	ADP
cana-3788	9	6	the	the	DET
cana-3788	9	7	denoised	denoise	VERB
cana-3788	9	8	data	datum	NOUN
cana-3788	9	9	for	for	ADP
cana-3788	9	10	further	further	ADJ
cana-3788	9	11	enhancement	enhancement	NOUN
cana-3788	9	12	and	and	CCONJ
cana-3788	9	13	for	for	ADP
cana-3788	9	14	generating	generate	VERB
cana-3788	9	15	individual	individual	ADJ
cana-3788	9	16	product	product	NOUN
cana-3788	9	17	recommendations	recommendation	NOUN
cana-3788	9	18	.	.	PUNCT
cana-3788	10	1	this	this	PRON
cana-3788	10	2	means	mean	VERB
cana-3788	10	3	that	that	SCONJ
cana-3788	10	4	by	by	ADP
cana-3788	10	5	combining	combine	VERB
cana-3788	10	6	cnns	cnns	ADJ
cana-3788	10	7	ability	ability	NOUN
cana-3788	10	8	to	to	PART
cana-3788	10	9	extract	extract	VERB
cana-3788	10	10	features	feature	NOUN
cana-3788	10	11	and	and	CCONJ
cana-3788	10	12	anns	anns	NOUN
cana-3788	10	13	ability	ability	NOUN
cana-3788	10	14	to	to	PART
cana-3788	10	15	make	make	VERB
cana-3788	10	16	predictions	prediction	NOUN
cana-3788	10	17	,	,	PUNCT
cana-3788	10	18	this	this	DET
cana-3788	10	19	two	two	NUM
cana-3788	10	20	-	-	PUNCT
cana-3788	10	21	structure	structure	NOUN
cana-3788	10	22	model	model	NOUN
cana-3788	10	23	greatly	greatly	ADV
cana-3788	10	24	decreases	decrease	VERB
cana-3788	10	25	the	the	DET
cana-3788	10	26	chances	chance	NOUN
cana-3788	10	27	of	of	ADP
cana-3788	10	28	the	the	DET
cana-3788	10	29	system	system	NOUN
cana-3788	10	30	being	be	AUX
cana-3788	10	31	easily	easily	ADV
cana-3788	10	32	fooled	fool	VERB
cana-3788	10	33	by	by	ADP
cana-3788	10	34	noise	noise	NOUN
cana-3788	10	35	and/or	and/or	CCONJ
cana-3788	10	36	increases	increase	VERB
cana-3788	10	37	the	the	DET
cana-3788	10	38	accuracy	accuracy	NOUN
cana-3788	10	39	of	of	ADP
cana-3788	10	40	the	the	DET
cana-3788	10	41	response	response	NOUN
cana-3788	10	42	to	to	ADP
cana-3788	10	43	true	true	ADJ
cana-3788	10	44	user	user	NOUN
cana-3788	10	45	preferences	preference	NOUN
cana-3788	10	46	.	.	PUNCT
cana-3788	11	1	we	we	PRON
cana-3788	11	2	apply	apply	VERB
cana-3788	11	3	our	our	PRON
cana-3788	11	4	approach	approach	NOUN
cana-3788	11	5	with	with	ADP
cana-3788	11	6	varying	vary	VERB
cana-3788	11	7	levels	level	NOUN
cana-3788	11	8	of	of	ADP
cana-3788	11	9	natural	natural	ADJ
cana-3788	11	10	noise	noise	NOUN
cana-3788	11	11	on	on	ADP
cana-3788	11	12	several	several	ADJ
cana-3788	11	13	datasets	dataset	NOUN
cana-3788	11	14	and	and	CCONJ
cana-3788	11	15	obtain	obtain	VERB
cana-3788	11	16	significant	significant	ADJ
cana-3788	11	17	improvements	improvement	NOUN
cana-3788	11	18	over	over	ADP
cana-3788	11	19	other	other	ADJ
cana-3788	11	20	recommendation	recommendation	NOUN
cana-3788	11	21	approaches	approach	NOUN
cana-3788	11	22	.	.	PUNCT
cana-3788	12	1	not	not	PART
cana-3788	12	2	only	only	ADV
cana-3788	12	3	does	do	AUX
cana-3788	12	4	this	this	DET
cana-3788	12	5	hybrid	hybrid	ADJ
cana-3788	12	6	solution	solution	NOUN
cana-3788	12	7	decrement	decrement	VERB
cana-3788	12	8	the	the	DET
cana-3788	12	9	injurious	injurious	ADJ
cana-3788	12	10	repercussions	repercussion	NOUN
cana-3788	12	11	of	of	ADP
cana-3788	12	12	noise	noise	NOUN
cana-3788	12	13	,	,	PUNCT
cana-3788	12	14	it	it	PRON
cana-3788	12	15	also	also	ADV
cana-3788	12	16	provides	provide	VERB
cana-3788	12	17	suggestions	suggestion	NOUN
cana-3788	12	18	for	for	ADP
cana-3788	12	19	future	future	ADJ
cana-3788	12	20	progress	progress	NOUN
cana-3788	12	21	of	of	ADP
cana-3788	12	22	the	the	DET
cana-3788	12	23	recommendation	recommendation	NOUN
cana-3788	12	24	system	system	NOUN
cana-3788	12	25	.	.	PUNCT
cana-3788	13	1	keywords	keyword	NOUN
cana-3788	13	2	:	:	PUNCT
cana-3788	13	3	recommendation	recommendation	NOUN
cana-3788	13	4	systems	system	NOUN
cana-3788	13	5	,	,	PUNCT
cana-3788	13	6	natural	natural	ADJ
cana-3788	13	7	noise	noise	NOUN
cana-3788	13	8	,	,	PUNCT
cana-3788	13	9	machine	machine	NOUN
cana-3788	13	10	learning	learning	NOUN
cana-3788	13	11	,	,	PUNCT
cana-3788	13	12	convolutional	convolutional	ADJ
cana-3788	13	13	neural	neural	ADJ
cana-3788	13	14	networks	network	NOUN
cana-3788	13	15	(	(	PUNCT
cana-3788	13	16	cnn	cnn	PROPN
cana-3788	13	17	)	)	PUNCT
cana-3788	13	18	,	,	PUNCT
cana-3788	13	19	artificial	artificial	ADJ
cana-3788	13	20	neural	neural	ADJ
cana-3788	13	21	networks	network	NOUN
cana-3788	13	22	(	(	PUNCT
cana-3788	13	23	ann	ann	PROPN
cana-3788	13	24	)	)	PUNCT
cana-3788	13	25	,	,	PUNCT
cana-3788	13	26	noise	noise	NOUN
cana-3788	13	27	management	management	NOUN
cana-3788	13	28	,	,	PUNCT
cana-3788	13	29	hybrid	hybrid	ADJ
cana-3788	13	30	approach	approach	NOUN
cana-3788	13	31	,	,	PUNCT
cana-3788	13	32	accuracy	accuracy	NOUN
cana-3788	13	33	improvement	improvement	NOUN
cana-3788	13	34	,	,	PUNCT
cana-3788	13	35	deep	deep	ADJ
cana-3788	13	36	learning	learning	NOUN
cana-3788	13	37	.	.	PUNCT
cana-3788	14	1	1	1	X
cana-3788	14	2	.	.	X
cana-3788	14	3	introduction	introduction	NOUN
cana-3788	14	4	personal	personal	ADJ
cana-3788	14	5	recommendation	recommendation	NOUN
cana-3788	14	6	engines	engine	NOUN
cana-3788	14	7	have	have	AUX
cana-3788	14	8	become	become	VERB
cana-3788	14	9	essential	essential	ADJ
cana-3788	14	10	components	component	NOUN
cana-3788	14	11	of	of	ADP
cana-3788	14	12	modern	modern	ADJ
cana-3788	14	13	democratized	democratize	VERB
cana-3788	14	14	services	service	NOUN
cana-3788	14	15	that	that	PRON
cana-3788	14	16	seek	seek	VERB
cana-3788	14	17	to	to	PART
cana-3788	14	18	deliver	deliver	VERB
cana-3788	14	19	the	the	DET
cana-3788	14	20	right	right	ADJ
cana-3788	14	21	content	content	NOUN
cana-3788	14	22	to	to	ADP
cana-3788	14	23	the	the	DET
cana-3788	14	24	right	right	ADJ
cana-3788	14	25	user	user	NOUN
cana-3788	14	26	in	in	ADP
cana-3788	14	27	roles	role	NOUN
cana-3788	14	28	that	that	PRON
cana-3788	14	29	extend	extend	VERB
cana-3788	14	30	across	across	ADP
cana-3788	14	31	e	e	NOUN
cana-3788	14	32	-	-	NOUN
cana-3788	14	33	commerce	commerce	NOUN
cana-3788	14	34	,	,	PUNCT
cana-3788	14	35	entertainment	entertainment	NOUN
cana-3788	14	36	streaming	streaming	NOUN
cana-3788	14	37	,	,	PUNCT
cana-3788	14	38	and	and	CCONJ
cana-3788	14	39	social	social	ADJ
cana-3788	14	40	networking	networking	NOUN
cana-3788	14	41	.	.	PUNCT
cana-3788	15	1	these	these	DET
cana-3788	15	2	systems	system	NOUN
cana-3788	15	3	use	use	VERB
cana-3788	15	4	a	a	DET
cana-3788	15	5	wealth	wealth	NOUN
cana-3788	15	6	of	of	ADP
cana-3788	15	7	data	datum	NOUN
cana-3788	15	8	about	about	ADP
cana-3788	15	9	users	user	NOUN
cana-3788	15	10	to	to	PART
cana-3788	15	11	suggest	suggest	VERB
cana-3788	15	12	preferences	preference	NOUN
cana-3788	15	13	that	that	PRON
cana-3788	15	14	will	will	AUX
cana-3788	15	15	enhance	enhance	VERB
cana-3788	15	16	the	the	DET
cana-3788	15	17	user	user	NOUN
cana-3788	15	18	’s	’s	PART
cana-3788	15	19	interaction	interaction	NOUN
cana-3788	15	20	and	and	CCONJ
cana-3788	15	21	appreciation	appreciation	NOUN
cana-3788	15	22	of	of	ADP
cana-3788	15	23	the	the	DET
cana-3788	15	24	system	system	NOUN
cana-3788	15	25	[	[	X
cana-3788	15	26	1	1	NUM
cana-3788	15	27	]	]	PUNCT
cana-3788	15	28	.	.	PUNCT
cana-3788	16	1	nevertheless	nevertheless	ADV
cana-3788	16	2	,	,	PUNCT
cana-3788	16	3	there	there	PRON
cana-3788	16	4	is	be	VERB
cana-3788	16	5	one	one	NUM
cana-3788	16	6	major	major	ADJ
cana-3788	16	7	issue	issue	NOUN
cana-3788	16	8	,	,	PUNCT
cana-3788	16	9	which	which	PRON
cana-3788	16	10	is	be	AUX
cana-3788	16	11	still	still	ADV
cana-3788	16	12	hurled	hurl	VERB
cana-3788	16	13	at	at	ADP
cana-3788	16	14	recommendation	recommendation	NOUN
cana-3788	16	15	systems	system	NOUN
cana-3788	16	16	,	,	PUNCT
cana-3788	16	17	and	and	CCONJ
cana-3788	16	18	remains	remain	VERB
cana-3788	16	19	a	a	DET
cana-3788	16	20	major	major	ADJ
cana-3788	16	21	contributor	contributor	NOUN
cana-3788	16	22	to	to	ADP
cana-3788	16	23	the	the	DET
cana-3788	16	24	noise	noise	NOUN
cana-3788	16	25	affecting	affect	VERB
cana-3788	16	26	them	they	PRON
cana-3788	16	27	,	,	PUNCT
cana-3788	16	28	namely	namely	ADV
cana-3788	16	29	natural	natural	ADJ
cana-3788	16	30	noise	noise	NOUN
cana-3788	16	31	.	.	PUNCT
cana-3788	17	1	afresh	afresh	NOUN
cana-3788	17	2	,	,	PUNCT
cana-3788	17	3	this	this	DET
cana-3788	17	4	kind	kind	NOUN
cana-3788	17	5	of	of	ADP
cana-3788	17	6	noise	noise	NOUN
cana-3788	17	7	can	can	AUX
cana-3788	17	8	be	be	AUX
cana-3788	17	9	referred	refer	VERB
cana-3788	17	10	to	to	ADP
cana-3788	17	11	as	as	ADP
cana-3788	17	12	natural	natural	ADJ
cana-3788	17	13	noise	noise	NOUN
cana-3788	17	14	,	,	PUNCT
cana-3788	17	15	where	where	SCONJ
cana-3788	17	16	it	it	PRON
cana-3788	17	17	means	mean	VERB
cana-3788	17	18	the	the	DET
cana-3788	17	19	noise	noise	NOUN
cana-3788	17	20	which	which	PRON
cana-3788	17	21	hinders	hinder	VERB
cana-3788	17	22	or	or	CCONJ
cana-3788	17	23	distorts	distort	VERB
cana-3788	17	24	real	real	ADJ
cana-3788	17	25	user	user	NOUN
cana-3788	17	26	preferences	preference	NOUN
cana-3788	17	27	[	[	X
cana-3788	17	28	2	2	NUM
cana-3788	17	29	]	]	PUNCT
cana-3788	17	30	.	.	PUNCT
cana-3788	18	1	this	this	DET
cana-3788	18	2	noise	noise	NOUN
cana-3788	18	3	may	may	AUX
cana-3788	18	4	consist	consist	VERB
cana-3788	18	5	in	in	ADP
cana-3788	18	6	inconsistent	inconsistent	ADJ
cana-3788	18	7	behavior	behavior	NOUN
cana-3788	18	8	,	,	PUNCT
cana-3788	18	9	rare	rare	ADJ
cana-3788	18	10	interactions	interaction	NOUN
cana-3788	18	11	,	,	PUNCT
cana-3788	18	12	or	or	CCONJ
cana-3788	18	13	random	random	ADJ
cana-3788	18	14	activities	activity	NOUN
cana-3788	18	15	,	,	PUNCT
cana-3788	18	16	and	and	CCONJ
cana-3788	18	17	it	it	PRON
cana-3788	18	18	affect	affect	VERB
cana-3788	18	19	the	the	DET
cana-3788	18	20	algorithms	algorithm	NOUN
cana-3788	18	21	employed	employ	VERB
cana-3788	18	22	in	in	ADP
cana-3788	18	23	recommendation	recommendation	NOUN
cana-3788	18	24	systems	system	NOUN
cana-3788	18	25	by	by	ADP
cana-3788	18	26	providing	provide	VERB
cana-3788	18	27	the	the	DET
cana-3788	18	28	system	system	NOUN
cana-3788	18	29	with	with	ADP
cana-3788	18	30	less	less	ADV
cana-3788	18	31	precise	precise	ADJ
cana-3788	18	32	and	and	CCONJ
cana-3788	18	33	less	less	ADJ
cana-3788	18	34	qualitative	qualitative	ADJ
cana-3788	18	35	results	result	NOUN
cana-3788	18	36	and	and	CCONJ
cana-3788	18	37	,	,	PUNCT
cana-3788	18	38	as	as	ADP
cana-3788	18	39	a	a	DET
cana-3788	18	40	consequence	consequence	NOUN
cana-3788	18	41	,	,	PUNCT
cana-3788	18	42	worst	bad	ADJ
cana-3788	18	43	performance	performance	NOUN
cana-3788	18	44	in	in	ADP
cana-3788	18	45	terms	term	NOUN
cana-3788	18	46	of	of	ADP
cana-3788	18	47	user	user	NOUN
cana-3788	18	48	experience	experience	NOUN
cana-3788	18	49	.	.	PUNCT
cana-3788	19	1	in	in	ADP
cana-3788	19	2	addition	addition	NOUN
cana-3788	19	3	,	,	PUNCT
cana-3788	19	4	the	the	DET
cana-3788	19	5	growth	growth	NOUN
cana-3788	19	6	of	of	ADP
cana-3788	19	7	digital	digital	ADJ
cana-3788	19	8	platforms	platform	NOUN
cana-3788	19	9	becomes	become	VERB
cana-3788	19	10	complex	complex	ADJ
cana-3788	19	11	and	and	CCONJ
cana-3788	19	12	the	the	DET
cana-3788	19	13	interactions	interaction	NOUN
cana-3788	19	14	between	between	ADP
cana-3788	19	15	users	user	NOUN
cana-3788	19	16	rise	rise	VERB
cana-3788	19	17	,	,	PUNCT
cana-3788	19	18	it	it	PRON
cana-3788	19	19	becomes	become	VERB
cana-3788	19	20	paramount	paramount	ADJ
cana-3788	19	21	to	to	PART
cana-3788	19	22	obtain	obtain	VERB
cana-3788	19	23	a	a	DET
cana-3788	19	24	precise	precise	ADJ
cana-3788	19	25	solution	solution	NOUN
cana-3788	19	26	to	to	PART
cana-3788	19	27	manage	manage	VERB
cana-3788	19	28	this	this	DET
cana-3788	19	29	noise	noise	NOUN
cana-3788	19	30	.	.	PUNCT
cana-3788	20	1	most	most	ADJ
cana-3788	20	2	of	of	ADP
cana-3788	20	3	the	the	DET
cana-3788	20	4	conventional	conventional	ADJ
cana-3788	20	5	recommendation	recommendation	NOUN
cana-3788	20	6	communications	communication	NOUN
cana-3788	20	7	on	on	ADP
cana-3788	20	8	applied	apply	VERB
cana-3788	20	9	nonlinear	nonlinear	ADJ
cana-3788	20	10	analysis	analysis	NOUN
cana-3788	20	11	issn	issn	NOUN
cana-3788	20	12	:	:	PUNCT
cana-3788	20	13	1074	1074	NUM
cana-3788	20	14	-	-	PUNCT
cana-3788	20	15	133x	133x	NUM
cana-3788	20	16	vol	vol	NOUN
cana-3788	20	17	32	32	NUM
cana-3788	20	18	no	no	NOUN
cana-3788	20	19	.	.	PUNCT
cana-3788	21	1	8s	8s	PROPN
cana-3788	21	2	(	(	PUNCT
cana-3788	21	3	2025	2025	NUM
cana-3788	21	4	)	)	PUNCT
cana-3788	21	5	725	725	NUM
cana-3788	21	6	https://internationalpubls.co	https://internationalpubls.co	PROPN
cana-3788	21	7	m	m	PROPN
cana-3788	21	8	techniques	technique	NOUN
cana-3788	21	9	based	base	VERB
cana-3788	21	10	on	on	ADP
cana-3788	21	11	the	the	DET
cana-3788	21	12	use	use	NOUN
cana-3788	21	13	of	of	ADP
cana-3788	21	14	collaborative	collaborative	ADJ
cana-3788	21	15	filtering	filtering	NOUN
cana-3788	21	16	and	and	CCONJ
cana-3788	21	17	content	content	NOUN
cana-3788	21	18	-	-	PUNCT
cana-3788	21	19	based	base	VERB
cana-3788	21	20	techniques	technique	NOUN
cana-3788	21	21	are	be	AUX
cana-3788	21	22	unable	unable	ADJ
cana-3788	21	23	to	to	PART
cana-3788	21	24	handle	handle	VERB
cana-3788	21	25	the	the	DET
cana-3788	21	26	amount	amount	NOUN
cana-3788	21	27	of	of	ADP
cana-3788	21	28	noise	noise	NOUN
cana-3788	21	29	that	that	PRON
cana-3788	21	30	is	be	AUX
cana-3788	21	31	associated	associate	VERB
cana-3788	21	32	with	with	ADP
cana-3788	21	33	large	large	ADJ
cana-3788	21	34	recommendation	recommendation	NOUN
cana-3788	21	35	systems	system	NOUN
cana-3788	21	36	.	.	PUNCT
cana-3788	22	1	this	this	PRON
cana-3788	22	2	has	have	AUX
cana-3788	22	3	led	lead	VERB
cana-3788	22	4	to	to	ADP
cana-3788	22	5	the	the	DET
cana-3788	22	6	need	need	NOUN
cana-3788	22	7	for	for	ADP
cana-3788	22	8	better	well	ADJ
cana-3788	22	9	approach	approach	NOUN
cana-3788	22	10	that	that	PRON
cana-3788	22	11	can	can	AUX
cana-3788	22	12	filter	filter	VERB
cana-3788	22	13	noise	noise	NOUN
cana-3788	22	14	from	from	ADP
cana-3788	22	15	the	the	DET
cana-3788	22	16	system	system	NOUN
cana-3788	22	17	while	while	SCONJ
cana-3788	22	18	at	at	ADP
cana-3788	22	19	the	the	DET
cana-3788	22	20	same	same	ADJ
cana-3788	22	21	time	time	NOUN
cana-3788	22	22	preserving	preserve	VERB
cana-3788	22	23	actual	actual	ADJ
cana-3788	22	24	user	user	NOUN
cana-3788	22	25	contributions	contribution	NOUN
cana-3788	22	26	[	[	X
cana-3788	22	27	3	3	NUM
cana-3788	22	28	]	]	PUNCT
cana-3788	22	29	.	.	PUNCT
cana-3788	23	1	this	this	DET
cana-3788	23	2	work	work	NOUN
cana-3788	23	3	focuses	focus	VERB
cana-3788	23	4	on	on	ADP
cana-3788	23	5	a	a	DET
cana-3788	23	6	combination	combination	NOUN
cana-3788	23	7	of	of	ADP
cana-3788	23	8	deep	deep	ADJ
cana-3788	23	9	learning	learning	NOUN
cana-3788	23	10	strategies	strategy	NOUN
cana-3788	23	11	,	,	PUNCT
cana-3788	23	12	including	include	VERB
cana-3788	23	13	cnn	cnn	PROPN
cana-3788	23	14	and	and	CCONJ
cana-3788	23	15	ann	ann	PROPN
cana-3788	23	16	to	to	PART
cana-3788	23	17	improve	improve	VERB
cana-3788	23	18	the	the	DET
cana-3788	23	19	performance	performance	NOUN
cana-3788	23	20	of	of	ADP
cana-3788	23	21	rss	rss	NOUN
cana-3788	23	22	while	while	SCONJ
cana-3788	23	23	mitigating	mitigate	VERB
cana-3788	23	24	natural	natural	ADJ
cana-3788	23	25	noise	noise	NOUN
cana-3788	23	26	.	.	PUNCT
cana-3788	24	1	1.1	1.1	NUM
cana-3788	24	2	motivation	motivation	NOUN
cana-3788	24	3	the	the	DET
cana-3788	24	4	rationale	rationale	NOUN
cana-3788	24	5	for	for	ADP
cana-3788	24	6	this	this	DET
cana-3788	24	7	study	study	NOUN
cana-3788	24	8	arises	arise	VERB
cana-3788	24	9	from	from	ADP
cana-3788	24	10	the	the	DET
cana-3788	24	11	continuously	continuously	ADV
cana-3788	24	12	integrated	integrate	VERB
cana-3788	24	13	and	and	CCONJ
cana-3788	24	14	valuable	valuable	ADJ
cana-3788	24	15	nature	nature	NOUN
cana-3788	24	16	of	of	ADP
cana-3788	24	17	recommendation	recommendation	NOUN
cana-3788	24	18	systems	system	NOUN
cana-3788	24	19	in	in	ADP
cana-3788	24	20	daily	daily	ADJ
cana-3788	24	21	interactions	interaction	NOUN
cana-3788	24	22	and	and	CCONJ
cana-3788	24	23	the	the	DET
cana-3788	24	24	rising	rise	VERB
cana-3788	24	25	amount	amount	NOUN
cana-3788	24	26	of	of	ADP
cana-3788	24	27	user	user	NOUN
cana-3788	24	28	data	datum	NOUN
cana-3788	24	29	that	that	PRON
cana-3788	24	30	these	these	DET
cana-3788	24	31	systems	system	NOUN
cana-3788	24	32	need	need	VERB
cana-3788	24	33	to	to	PART
cana-3788	24	34	handle	handle	VERB
cana-3788	24	35	.	.	PUNCT
cana-3788	25	1	due	due	ADP
cana-3788	25	2	to	to	ADP
cana-3788	25	3	the	the	DET
cana-3788	25	4	explosive	explosive	ADJ
cana-3788	25	5	growth	growth	NOUN
cana-3788	25	6	of	of	ADP
cana-3788	25	7	users	user	NOUN
cana-3788	25	8	’	'	PUNCT
cana-3788	25	9	content	content	NOUN
cana-3788	25	10	and	and	CCONJ
cana-3788	25	11	interactivity	interactivity	NOUN
cana-3788	25	12	,	,	PUNCT
cana-3788	25	13	many	many	ADJ
cana-3788	25	14	companies	company	NOUN
cana-3788	25	15	have	have	AUX
cana-3788	25	16	made	make	VERB
cana-3788	25	17	recommendation	recommendation	NOUN
cana-3788	25	18	systems	system	NOUN
cana-3788	25	19	an	an	DET
cana-3788	25	20	important	important	ADJ
cana-3788	25	21	supplement	supplement	NOUN
cana-3788	25	22	for	for	ADP
cana-3788	25	23	increasing	increase	VERB
cana-3788	25	24	customers	customer	NOUN
cana-3788	25	25	’	'	PUNCT
cana-3788	25	26	satisfaction	satisfaction	NOUN
cana-3788	25	27	[	[	X
cana-3788	25	28	4	4	NUM
cana-3788	25	29	]	]	PUNCT
cana-3788	25	30	.	.	PUNCT
cana-3788	26	1	yet	yet	ADV
cana-3788	26	2	,	,	PUNCT
cana-3788	26	3	as	as	ADP
cana-3788	26	4	the	the	DET
cana-3788	26	5	availability	availability	NOUN
cana-3788	26	6	of	of	ADP
cana-3788	26	7	the	the	DET
cana-3788	26	8	data	data	NOUN
cana-3788	26	9	increases	increase	NOUN
cana-3788	26	10	relative	relative	ADJ
cana-3788	26	11	to	to	ADP
cana-3788	26	12	the	the	DET
cana-3788	26	13	number	number	NOUN
cana-3788	26	14	of	of	ADP
cana-3788	26	15	observations	observation	NOUN
cana-3788	26	16	,	,	PUNCT
cana-3788	26	17	the	the	DET
cana-3788	26	18	problem	problem	NOUN
cana-3788	26	19	of	of	ADP
cana-3788	26	20	natural	natural	ADJ
cana-3788	26	21	noise	noise	NOUN
cana-3788	26	22	rises	rise	NOUN
cana-3788	26	23	,	,	PUNCT
cana-3788	26	24	reducing	reduce	VERB
cana-3788	26	25	the	the	DET
cana-3788	26	26	applicability	applicability	NOUN
cana-3788	26	27	of	of	ADP
cana-3788	26	28	certain	certain	ADJ
cana-3788	26	29	models	model	NOUN
cana-3788	26	30	.	.	PUNCT
cana-3788	27	1	for	for	ADP
cana-3788	27	2	example	example	NOUN
cana-3788	27	3	,	,	PUNCT
cana-3788	27	4	in	in	ADP
cana-3788	27	5	an	an	DET
cana-3788	27	6	e	e	NOUN
cana-3788	27	7	-	-	NOUN
cana-3788	27	8	commerce	commerce	NOUN
cana-3788	27	9	platform	platform	NOUN
cana-3788	27	10	,	,	PUNCT
cana-3788	27	11	users	user	NOUN
cana-3788	27	12	may	may	AUX
cana-3788	27	13	engage	engage	VERB
cana-3788	27	14	with	with	ADP
cana-3788	27	15	items	item	NOUN
cana-3788	27	16	which	which	PRON
cana-3788	27	17	they	they	PRON
cana-3788	27	18	do	do	AUX
cana-3788	27	19	not	not	PART
cana-3788	27	20	particularly	particularly	ADV
cana-3788	27	21	desire	desire	VERB
cana-3788	27	22	,	,	PUNCT
cana-3788	27	23	just	just	ADV
cana-3788	27	24	a	a	DET
cana-3788	27	25	simple	simple	ADJ
cana-3788	27	26	scrolling	scrolling	NOUN
cana-3788	27	27	or	or	CCONJ
cana-3788	27	28	multiple	multiple	ADJ
cana-3788	27	29	clicks	click	NOUN
cana-3788	27	30	or	or	CCONJ
cana-3788	27	31	even	even	ADV
cana-3788	27	32	unintentional	unintentional	ADJ
cana-3788	27	33	touches	touch	NOUN
cana-3788	27	34	are	be	AUX
cana-3788	27	35	enough	enough	ADJ
cana-3788	27	36	to	to	PART
cana-3788	27	37	produce	produce	VERB
cana-3788	27	38	noise	noise	NOUN
cana-3788	27	39	into	into	ADP
cana-3788	27	40	the	the	DET
cana-3788	27	41	data	datum	NOUN
cana-3788	27	42	.	.	PUNCT
cana-3788	28	1	likewise	likewise	ADV
cana-3788	28	2	,	,	PUNCT
cana-3788	28	3	a	a	DET
cana-3788	28	4	media	media	NOUN
cana-3788	28	5	streaming	streaming	NOUN
cana-3788	28	6	service	service	NOUN
cana-3788	28	7	can	can	AUX
cana-3788	28	8	encourage	encourage	VERB
cana-3788	28	9	users	user	NOUN
cana-3788	28	10	to	to	PART
cana-3788	28	11	follow	follow	VERB
cana-3788	28	12	content	content	NOUN
cana-3788	28	13	based	base	VERB
cana-3788	28	14	on	on	ADP
cana-3788	28	15	the	the	DET
cana-3788	28	16	interest	interest	NOUN
cana-3788	28	17	they	they	PRON
cana-3788	28	18	have	have	VERB
cana-3788	28	19	in	in	ADP
cana-3788	28	20	the	the	DET
cana-3788	28	21	tool	tool	NOUN
cana-3788	28	22	,	,	PUNCT
cana-3788	28	23	not	not	PART
cana-3788	28	24	the	the	DET
cana-3788	28	25	content	content	NOUN
cana-3788	28	26	,	,	PUNCT
cana-3788	28	27	resulting	result	VERB
cana-3788	28	28	in	in	ADP
cana-3788	28	29	misleading	mislead	VERB
cana-3788	28	30	input	input	NOUN
cana-3788	28	31	to	to	ADP
cana-3788	28	32	the	the	DET
cana-3788	28	33	recommendation	recommendation	NOUN
cana-3788	28	34	models	model	NOUN
cana-3788	28	35	.	.	PUNCT
cana-3788	29	1	this	this	DET
cana-3788	29	2	noise	noise	NOUN
cana-3788	29	3	leads	lead	VERB
cana-3788	29	4	to	to	ADP
cana-3788	29	5	wrong	wrong	ADJ
cana-3788	29	6	predictions	prediction	NOUN
cana-3788	29	7	,	,	PUNCT
cana-3788	29	8	which	which	PRON
cana-3788	29	9	minimizes	minimize	VERB
cana-3788	29	10	the	the	DET
cana-3788	29	11	utility	utility	NOUN
cana-3788	29	12	of	of	ADP
cana-3788	29	13	the	the	DET
cana-3788	29	14	personalization	personalization	NOUN
cana-3788	29	15	that	that	PRON
cana-3788	29	16	these	these	DET
cana-3788	29	17	platforms	platform	NOUN
cana-3788	29	18	are	be	AUX
cana-3788	29	19	supposed	suppose	VERB
cana-3788	29	20	to	to	PART
cana-3788	29	21	deliver	deliver	VERB
cana-3788	29	22	.	.	PUNCT
cana-3788	30	1	the	the	DET
cana-3788	30	2	basic	basic	ADJ
cana-3788	30	3	recommendation	recommendation	NOUN
cana-3788	30	4	techniques	technique	NOUN
cana-3788	30	5	like	like	ADP
cana-3788	30	6	the	the	DET
cana-3788	30	7	collaborative	collaborative	ADJ
cana-3788	30	8	filtering	filtering	NOUN
cana-3788	30	9	and	and	CCONJ
cana-3788	30	10	content	content	NOUN
cana-3788	30	11	-	-	PUNCT
cana-3788	30	12	based	base	VERB
cana-3788	30	13	methods	method	NOUN
cana-3788	30	14	are	be	AUX
cana-3788	30	15	inadequate	inadequate	ADJ
cana-3788	30	16	in	in	ADP
cana-3788	30	17	cases	case	NOUN
cana-3788	30	18	were	be	AUX
cana-3788	30	19	dealing	deal	VERB
cana-3788	30	20	with	with	ADP
cana-3788	30	21	noisy	noisy	ADJ
cana-3788	30	22	data	datum	NOUN
cana-3788	30	23	is	be	AUX
cana-3788	30	24	involved	involve	VERB
cana-3788	30	25	.	.	PUNCT
cana-3788	31	1	collaborative	collaborative	ADJ
cana-3788	31	2	filtering	filtering	NOUN
cana-3788	31	3	is	be	AUX
cana-3788	31	4	likely	likely	ADJ
cana-3788	31	5	to	to	PART
cana-3788	31	6	magnify	magnify	VERB
cana-3788	31	7	noise	noise	NOUN
cana-3788	31	8	since	since	SCONJ
cana-3788	31	9	it	it	PRON
cana-3788	31	10	attempts	attempt	VERB
cana-3788	31	11	to	to	PART
cana-3788	31	12	work	work	VERB
cana-3788	31	13	with	with	ADP
cana-3788	31	14	user	user	NOUN
cana-3788	31	15	-	-	PUNCT
cana-3788	31	16	item	item	NOUN
cana-3788	31	17	interaction	interaction	NOUN
cana-3788	31	18	matrices	matrix	NOUN
cana-3788	31	19	that	that	PRON
cana-3788	31	20	may	may	AUX
cana-3788	31	21	contain	contain	VERB
cana-3788	31	22	extraneous	extraneous	ADJ
cana-3788	31	23	activities	activity	NOUN
cana-3788	31	24	[	[	X
cana-3788	31	25	5	5	NUM
cana-3788	31	26	]	]	PUNCT
cana-3788	31	27	.	.	PUNCT
cana-3788	32	1	likewise	likewise	ADV
cana-3788	32	2	,	,	PUNCT
cana-3788	32	3	contentbased	contentbase	VERB
cana-3788	32	4	systems	system	NOUN
cana-3788	32	5	may	may	AUX
cana-3788	32	6	make	make	VERB
cana-3788	32	7	a	a	DET
cana-3788	32	8	suggestion	suggestion	NOUN
cana-3788	32	9	based	base	VERB
cana-3788	32	10	on	on	ADP
cana-3788	32	11	a	a	DET
cana-3788	32	12	user	user	NOUN
cana-3788	32	13	’s	’s	PART
cana-3788	32	14	incidental	incidental	ADJ
cana-3788	32	15	click	click	NOUN
cana-3788	32	16	,	,	PUNCT
cana-3788	32	17	or	or	CCONJ
cana-3788	32	18	a	a	DET
cana-3788	32	19	search	search	NOUN
cana-3788	32	20	that	that	PRON
cana-3788	32	21	the	the	DET
cana-3788	32	22	user	user	NOUN
cana-3788	32	23	may	may	AUX
cana-3788	32	24	have	have	AUX
cana-3788	32	25	made	make	VERB
cana-3788	32	26	serendipitously	serendipitously	ADV
cana-3788	32	27	.	.	PUNCT
cana-3788	33	1	hence	hence	ADV
cana-3788	33	2	,	,	PUNCT
cana-3788	33	3	there	there	PRON
cana-3788	33	4	is	be	VERB
cana-3788	33	5	a	a	DET
cana-3788	33	6	compelling	compelling	ADJ
cana-3788	33	7	need	need	NOUN
cana-3788	33	8	for	for	ADP
cana-3788	33	9	more	more	ADV
cana-3788	33	10	stringent	stringent	ADJ
cana-3788	33	11	approaches	approach	NOUN
cana-3788	33	12	that	that	PRON
cana-3788	33	13	can	can	AUX
cana-3788	33	14	eliminate	eliminate	VERB
cana-3788	33	15	noise	noise	NOUN
cana-3788	33	16	to	to	PART
cana-3788	33	17	enable	enable	VERB
cana-3788	33	18	recommendation	recommendation	NOUN
cana-3788	33	19	systems	system	NOUN
cana-3788	33	20	to	to	PART
cana-3788	33	21	operate	operate	VERB
cana-3788	33	22	smoothly	smoothly	ADV
cana-3788	33	23	within	within	ADP
cana-3788	33	24	noisy	noisy	ADJ
cana-3788	33	25	conditions	condition	NOUN
cana-3788	33	26	.	.	PUNCT
cana-3788	34	1	1.2	1.2	NUM
cana-3788	34	2	problem	problem	NOUN
cana-3788	34	3	statement	statement	NOUN
cana-3788	34	4	the	the	DET
cana-3788	34	5	first	first	ADJ
cana-3788	34	6	problem	problem	NOUN
cana-3788	34	7	highlighted	highlight	VERB
cana-3788	34	8	in	in	ADP
cana-3788	34	9	this	this	DET
cana-3788	34	10	research	research	NOUN
cana-3788	34	11	is	be	AUX
cana-3788	34	12	the	the	DET
cana-3788	34	13	decline	decline	NOUN
cana-3788	34	14	in	in	ADP
cana-3788	34	15	recommendation	recommendation	NOUN
cana-3788	34	16	quality	quality	NOUN
cana-3788	34	17	because	because	SCONJ
cana-3788	34	18	of	of	ADP
cana-3788	34	19	naturally	naturally	ADV
cana-3788	34	20	noisy	noisy	ADJ
cana-3788	34	21	data	datum	NOUN
cana-3788	34	22	about	about	ADP
cana-3788	34	23	the	the	DET
cana-3788	34	24	user	user	NOUN
cana-3788	34	25	.	.	PUNCT
cana-3788	35	1	the	the	DET
cana-3788	35	2	current	current	ADJ
cana-3788	35	3	recommendation	recommendation	NOUN
cana-3788	35	4	models	model	NOUN
cana-3788	35	5	are	be	AUX
cana-3788	35	6	not	not	PART
cana-3788	35	7	well	well	ADV
cana-3788	35	8	equipped	equip	VERB
cana-3788	35	9	to	to	PART
cana-3788	35	10	isolate	isolate	VERB
cana-3788	35	11	noise	noise	NOUN
cana-3788	35	12	from	from	ADP
cana-3788	35	13	sincere	sincere	ADJ
cana-3788	35	14	interactions	interaction	NOUN
cana-3788	35	15	and	and	CCONJ
cana-3788	35	16	therefore	therefore	ADV
cana-3788	35	17	provide	provide	VERB
cana-3788	35	18	less	less	ADJ
cana-3788	35	19	than	than	ADP
cana-3788	35	20	optimal	optimal	ADJ
cana-3788	35	21	recommendations	recommendation	NOUN
cana-3788	35	22	[	[	X
cana-3788	35	23	6	6	NUM
cana-3788	35	24	]	]	PUNCT
cana-3788	35	25	.	.	PUNCT
cana-3788	36	1	the	the	DET
cana-3788	36	2	purpose	purpose	NOUN
cana-3788	36	3	of	of	ADP
cana-3788	36	4	this	this	DET
cana-3788	36	5	study	study	NOUN
cana-3788	36	6	is	be	AUX
cana-3788	36	7	to	to	PART
cana-3788	36	8	create	create	VERB
cana-3788	36	9	a	a	DET
cana-3788	36	10	new	new	ADJ
cana-3788	36	11	framework	framework	NOUN
cana-3788	36	12	that	that	PRON
cana-3788	36	13	addresses	address	VERB
cana-3788	36	14	natural	natural	ADJ
cana-3788	36	15	noise	noise	NOUN
cana-3788	36	16	and	and	CCONJ
cana-3788	36	17	combines	combine	VERB
cana-3788	36	18	cnn	cnn	PROPN
cana-3788	36	19	and	and	CCONJ
cana-3788	36	20	ann	ann	PROPN
cana-3788	36	21	to	to	PART
cana-3788	36	22	continuously	continuously	ADV
cana-3788	36	23	improve	improve	VERB
cana-3788	36	24	the	the	DET
cana-3788	36	25	recommendations	recommendation	NOUN
cana-3788	36	26	in	in	ADP
cana-3788	36	27	noisy	noisy	ADJ
cana-3788	36	28	situations	situation	NOUN
cana-3788	36	29	.	.	PUNCT
cana-3788	37	1	cnns	cnn	NOUN
cana-3788	37	2	are	be	AUX
cana-3788	37	3	asserted	assert	VERB
cana-3788	37	4	in	in	ADP
cana-3788	37	5	terms	term	NOUN
cana-3788	37	6	of	of	ADP
cana-3788	37	7	decomposing	decompose	VERB
cana-3788	37	8	raw	raw	ADJ
cana-3788	37	9	data	datum	NOUN
cana-3788	37	10	into	into	ADP
cana-3788	37	11	its	its	PRON
cana-3788	37	12	intricate	intricate	ADJ
cana-3788	37	13	pattern	pattern	NOUN
cana-3788	37	14	features	feature	NOUN
cana-3788	37	15	,	,	PUNCT
cana-3788	37	16	which	which	PRON
cana-3788	37	17	justify	justify	VERB
cana-3788	37	18	their	their	PRON
cana-3788	37	19	application	application	NOUN
cana-3788	37	20	in	in	ADP
cana-3788	37	21	the	the	DET
cana-3788	37	22	first	first	ADJ
cana-3788	37	23	stage	stage	NOUN
cana-3788	37	24	of	of	ADP
cana-3788	37	25	noise	noise	NOUN
cana-3788	37	26	removal	removal	NOUN
cana-3788	37	27	.	.	PUNCT
cana-3788	38	1	on	on	ADP
cana-3788	38	2	the	the	DET
cana-3788	38	3	other	other	ADJ
cana-3788	38	4	hand	hand	NOUN
cana-3788	38	5	,	,	PUNCT
cana-3788	38	6	anns	ann	NOUN
cana-3788	38	7	are	be	AUX
cana-3788	38	8	very	very	ADV
cana-3788	38	9	effective	effective	ADJ
cana-3788	38	10	once	once	SCONJ
cana-3788	38	11	the	the	DET
cana-3788	38	12	noise	noise	NOUN
cana-3788	38	13	has	have	VERB
cana-3788	38	14	to	to	PART
cana-3788	38	15	be	be	AUX
cana-3788	38	16	eliminated	eliminate	VERB
cana-3788	38	17	and	and	CCONJ
cana-3788	38	18	the	the	DET
cana-3788	38	19	user	user	NOUN
cana-3788	38	20	preference	preference	NOUN
cana-3788	38	21	has	have	VERB
cana-3788	38	22	to	to	PART
cana-3788	38	23	be	be	AUX
cana-3788	38	24	inferred	infer	VERB
cana-3788	38	25	.	.	PUNCT
cana-3788	39	1	i	i	PRON
cana-3788	39	2	argue	argue	VERB
cana-3788	39	3	that	that	SCONJ
cana-3788	39	4	the	the	DET
cana-3788	39	5	proposed	propose	VERB
cana-3788	39	6	approach	approach	NOUN
cana-3788	39	7	,	,	PUNCT
cana-3788	39	8	which	which	PRON
cana-3788	39	9	integrates	integrate	VERB
cana-3788	39	10	these	these	DET
cana-3788	39	11	two	two	NUM
cana-3788	39	12	models	model	NOUN
cana-3788	39	13	,	,	PUNCT
cana-3788	39	14	balances	balance	VERB
cana-3788	39	15	the	the	DET
cana-3788	39	16	noise	noise	NOUN
cana-3788	39	17	-	-	PUNCT
cana-3788	39	18	handling	handling	NOUN
cana-3788	39	19	capability	capability	NOUN
cana-3788	39	20	with	with	ADP
cana-3788	39	21	the	the	DET
cana-3788	39	22	integrity	integrity	NOUN
cana-3788	39	23	of	of	ADP
cana-3788	39	24	the	the	DET
cana-3788	39	25	recommendation	recommendation	NOUN
cana-3788	39	26	process	process	NOUN
cana-3788	39	27	.	.	PUNCT
cana-3788	40	1	therefore	therefore	ADV
cana-3788	40	2	,	,	PUNCT
cana-3788	40	3	the	the	DET
cana-3788	40	4	specific	specific	ADJ
cana-3788	40	5	objectives	objective	NOUN
cana-3788	40	6	of	of	ADP
cana-3788	40	7	this	this	DET
cana-3788	40	8	research	research	NOUN
cana-3788	40	9	are	be	AUX
cana-3788	40	10	as	as	SCONJ
cana-3788	40	11	follows	follow	VERB
cana-3788	40	12	:	:	PUNCT
cana-3788	41	1	1	1	X
cana-3788	41	2	.	.	PUNCT
cana-3788	41	3	the	the	DET
cana-3788	41	4	first	first	ADJ
cana-3788	41	5	objective	objective	NOUN
cana-3788	41	6	is	be	AUX
cana-3788	41	7	to	to	PART
cana-3788	41	8	design	design	VERB
cana-3788	41	9	and	and	CCONJ
cana-3788	41	10	implement	implement	VERB
cana-3788	41	11	a	a	DET
cana-3788	41	12	noise	noise	NOUN
cana-3788	41	13	-	-	PUNCT
cana-3788	41	14	filtering	filter	VERB
cana-3788	41	15	mechanism	mechanism	NOUN
cana-3788	41	16	using	use	VERB
cana-3788	41	17	convolutional	convolutional	ADJ
cana-3788	41	18	neural	neural	ADJ
cana-3788	41	19	networks	network	NOUN
cana-3788	41	20	(	(	PUNCT
cana-3788	41	21	cnns	cnns	PROPN
cana-3788	41	22	)	)	PUNCT
cana-3788	41	23	.	.	PUNCT
cana-3788	42	1	cnns	cnns	PROPN
cana-3788	42	2	,	,	PUNCT
cana-3788	42	3	known	know	VERB
cana-3788	42	4	for	for	ADP
cana-3788	42	5	their	their	PRON
cana-3788	42	6	strength	strength	NOUN
cana-3788	42	7	in	in	ADP
cana-3788	42	8	pattern	pattern	NOUN
cana-3788	42	9	recognition	recognition	NOUN
cana-3788	42	10	,	,	PUNCT
cana-3788	42	11	are	be	AUX
cana-3788	42	12	utilized	utilize	VERB
cana-3788	42	13	to	to	PART
cana-3788	42	14	analyze	analyze	VERB
cana-3788	42	15	user	user	NOUN
cana-3788	42	16	behavior	behavior	NOUN
cana-3788	42	17	and	and	CCONJ
cana-3788	42	18	identify	identify	VERB
cana-3788	42	19	patterns	pattern	NOUN
cana-3788	42	20	that	that	PRON
cana-3788	42	21	are	be	AUX
cana-3788	42	22	indicative	indicative	ADJ
cana-3788	42	23	of	of	ADP
cana-3788	42	24	noise	noise	NOUN
cana-3788	42	25	.	.	PUNCT
cana-3788	43	1	by	by	ADP
cana-3788	43	2	doing	do	VERB
cana-3788	43	3	so	so	ADV
cana-3788	43	4	,	,	PUNCT
cana-3788	43	5	the	the	DET
cana-3788	43	6	system	system	NOUN
cana-3788	43	7	can	can	AUX
cana-3788	43	8	filter	filter	VERB
cana-3788	43	9	out	out	ADP
cana-3788	43	10	irrelevant	irrelevant	ADJ
cana-3788	43	11	or	or	CCONJ
cana-3788	43	12	accidental	accidental	ADJ
cana-3788	43	13	interactions	interaction	NOUN
cana-3788	43	14	that	that	PRON
cana-3788	43	15	distort	distort	VERB
cana-3788	43	16	genuine	genuine	ADJ
cana-3788	43	17	user	user	NOUN
cana-3788	43	18	preferences	preference	NOUN
cana-3788	43	19	.	.	PUNCT
cana-3788	44	1	2	2	X
cana-3788	44	2	.	.	X
cana-3788	45	1	once	once	SCONJ
cana-3788	45	2	the	the	DET
cana-3788	45	3	noise	noise	NOUN
cana-3788	45	4	is	be	AUX
cana-3788	45	5	filtered	filter	VERB
cana-3788	45	6	out	out	ADP
cana-3788	45	7	,	,	PUNCT
cana-3788	45	8	the	the	DET
cana-3788	45	9	second	second	ADJ
cana-3788	45	10	objective	objective	NOUN
cana-3788	45	11	is	be	AUX
cana-3788	45	12	to	to	PART
cana-3788	45	13	use	use	VERB
cana-3788	45	14	artificial	artificial	ADJ
cana-3788	45	15	neural	neural	ADJ
cana-3788	45	16	networks	network	NOUN
cana-3788	45	17	(	(	PUNCT
cana-3788	45	18	anns	anns	PROPN
cana-3788	45	19	)	)	PUNCT
cana-3788	45	20	to	to	PART
cana-3788	45	21	further	far	ADV
cana-3788	45	22	refine	refine	VERB
cana-3788	45	23	user	user	NOUN
cana-3788	45	24	preferences	preference	NOUN
cana-3788	45	25	and	and	CCONJ
cana-3788	45	26	make	make	VERB
cana-3788	45	27	accurate	accurate	ADJ
cana-3788	45	28	recommendations	recommendation	NOUN
cana-3788	45	29	.	.	PUNCT
cana-3788	46	1	anns	ann	NOUN
cana-3788	46	2	are	be	AUX
cana-3788	46	3	employed	employ	VERB
cana-3788	46	4	to	to	PART
cana-3788	46	5	process	process	VERB
cana-3788	46	6	the	the	DET
cana-3788	46	7	denoised	denoise	VERB
cana-3788	46	8	data	datum	NOUN
cana-3788	46	9	,	,	PUNCT
cana-3788	46	10	providing	provide	VERB
cana-3788	46	11	personalized	personalized	ADJ
cana-3788	46	12	recommendations	recommendation	NOUN
cana-3788	46	13	that	that	PRON
cana-3788	46	14	are	be	AUX
cana-3788	46	15	more	more	ADV
cana-3788	46	16	aligned	aligned	ADJ
cana-3788	46	17	with	with	ADP
cana-3788	46	18	users	user	NOUN
cana-3788	46	19	'	'	PART
cana-3788	46	20	genuine	genuine	ADJ
cana-3788	46	21	interests	interest	NOUN
cana-3788	46	22	.	.	PUNCT
cana-3788	47	1	this	this	DET
cana-3788	47	2	phase	phase	NOUN
cana-3788	47	3	of	of	ADP
cana-3788	47	4	the	the	DET
cana-3788	47	5	framework	framework	NOUN
cana-3788	47	6	ensures	ensure	VERB
cana-3788	47	7	that	that	SCONJ
cana-3788	47	8	the	the	DET
cana-3788	47	9	system	system	NOUN
cana-3788	47	10	delivers	deliver	VERB
cana-3788	47	11	relevant	relevant	ADJ
cana-3788	47	12	content	content	NOUN
cana-3788	47	13	,	,	PUNCT
cana-3788	47	14	improving	improve	VERB
cana-3788	47	15	user	user	NOUN
cana-3788	47	16	satisfaction	satisfaction	NOUN
cana-3788	47	17	and	and	CCONJ
cana-3788	47	18	engagement	engagement	NOUN
cana-3788	47	19	.	.	PUNCT
cana-3788	48	1	2	2	X
cana-3788	48	2	.	.	X
cana-3788	48	3	related	relate	VERB
cana-3788	48	4	work	work	NOUN
cana-3788	48	5	:	:	PUNCT
cana-3788	48	6	in	in	ADP
cana-3788	48	7	recent	recent	ADJ
cana-3788	48	8	years	year	NOUN
cana-3788	48	9	,	,	PUNCT
cana-3788	48	10	substantial	substantial	ADJ
cana-3788	48	11	progress	progress	NOUN
cana-3788	48	12	has	have	AUX
cana-3788	48	13	been	be	AUX
cana-3788	48	14	made	make	VERB
cana-3788	48	15	in	in	ADP
cana-3788	48	16	enhancing	enhance	VERB
cana-3788	48	17	recommendation	recommendation	NOUN
cana-3788	48	18	systems	system	NOUN
cana-3788	48	19	,	,	PUNCT
cana-3788	48	20	with	with	ADP
cana-3788	48	21	a	a	DET
cana-3788	48	22	focus	focus	NOUN
cana-3788	48	23	on	on	ADP
cana-3788	48	24	managing	manage	VERB
cana-3788	48	25	noise	noise	NOUN
cana-3788	48	26	using	use	VERB
cana-3788	48	27	various	various	ADJ
cana-3788	48	28	machine	machine	NOUN
cana-3788	48	29	-	-	PUNCT
cana-3788	48	30	learning	learn	VERB
cana-3788	48	31	techniques	technique	NOUN
cana-3788	48	32	.	.	PUNCT
cana-3788	49	1	noise	noise	NOUN
cana-3788	49	2	in	in	ADP
cana-3788	49	3	recommendation	recommendation	NOUN
cana-3788	49	4	systems	system	NOUN
cana-3788	49	5	refers	refer	VERB
cana-3788	49	6	to	to	ADP
cana-3788	49	7	irrelevant	irrelevant	ADJ
cana-3788	49	8	or	or	CCONJ
cana-3788	49	9	inconsistent	inconsistent	ADJ
cana-3788	49	10	user	user	NOUN
cana-3788	49	11	interaction	interaction	NOUN
cana-3788	49	12	data	datum	NOUN
cana-3788	49	13	that	that	PRON
cana-3788	49	14	can	can	AUX
cana-3788	49	15	significantly	significantly	ADV
cana-3788	49	16	affect	affect	VERB
cana-3788	49	17	the	the	DET
cana-3788	49	18	accuracy	accuracy	NOUN
cana-3788	49	19	of	of	ADP
cana-3788	49	20	the	the	DET
cana-3788	49	21	recommendations	recommendation	NOUN
cana-3788	49	22	.	.	PUNCT
cana-3788	50	1	traditional	traditional	ADJ
cana-3788	50	2	algorithms	algorithm	NOUN
cana-3788	50	3	,	,	PUNCT
cana-3788	50	4	such	such	ADJ
cana-3788	50	5	as	as	ADP
cana-3788	50	6	collaborative	collaborative	ADJ
cana-3788	50	7	filtering	filtering	NOUN
cana-3788	50	8	,	,	PUNCT
cana-3788	50	9	often	often	ADV
cana-3788	50	10	struggle	struggle	VERB
cana-3788	50	11	in	in	ADP
cana-3788	50	12	the	the	DET
cana-3788	50	13	presence	presence	NOUN
cana-3788	50	14	of	of	ADP
cana-3788	50	15	noise	noise	NOUN
cana-3788	50	16	,	,	PUNCT
cana-3788	50	17	as	as	SCONJ
cana-3788	50	18	they	they	PRON
cana-3788	50	19	rely	rely	VERB
cana-3788	50	20	heavily	heavily	ADV
cana-3788	50	21	on	on	ADP
cana-3788	50	22	user	user	NOUN
cana-3788	50	23	interaction	interaction	NOUN
cana-3788	50	24	matrices	matrix	NOUN
cana-3788	50	25	that	that	PRON
cana-3788	50	26	can	can	AUX
cana-3788	50	27	be	be	AUX
cana-3788	50	28	distorted	distort	VERB
cana-3788	50	29	by	by	ADP
cana-3788	50	30	inconsistent	inconsistent	ADJ
cana-3788	50	31	behavior	behavior	NOUN
cana-3788	50	32	.	.	PUNCT
cana-3788	51	1	to	to	PART
cana-3788	51	2	address	address	VERB
cana-3788	51	3	this	this	PRON
cana-3788	51	4	,	,	PUNCT
cana-3788	51	5	recent	recent	ADJ
cana-3788	51	6	research	research	NOUN
cana-3788	51	7	has	have	AUX
cana-3788	51	8	focused	focus	VERB
cana-3788	51	9	on	on	ADP
cana-3788	51	10	communications	communication	NOUN
cana-3788	51	11	on	on	ADP
cana-3788	51	12	applied	apply	VERB
cana-3788	51	13	nonlinear	nonlinear	ADJ
cana-3788	51	14	analysis	analysis	NOUN
cana-3788	51	15	issn	issn	NOUN
cana-3788	51	16	:	:	PUNCT
cana-3788	51	17	1074	1074	NUM
cana-3788	51	18	-	-	PUNCT
cana-3788	51	19	133x	133x	NUM
cana-3788	51	20	vol	vol	NOUN
cana-3788	51	21	32	32	NUM
cana-3788	51	22	no	no	NOUN
cana-3788	51	23	.	.	PUNCT
cana-3788	52	1	8s	8s	PROPN
cana-3788	52	2	(	(	PUNCT
cana-3788	52	3	2025	2025	NUM
cana-3788	52	4	)	)	PUNCT
cana-3788	52	5	726	726	NUM
cana-3788	52	6	https://internationalpubls.co	https://internationalpubls.co	NOUN
cana-3788	52	7	m	m	AUX
cana-3788	52	8	using	use	VERB
cana-3788	52	9	advanced	advanced	ADJ
cana-3788	52	10	deep	deep	ADJ
cana-3788	52	11	learning	learning	NOUN
cana-3788	52	12	models	model	NOUN
cana-3788	52	13	,	,	PUNCT
cana-3788	52	14	such	such	ADJ
cana-3788	52	15	as	as	ADP
cana-3788	52	16	convolutional	convolutional	ADJ
cana-3788	52	17	neural	neural	ADJ
cana-3788	52	18	networks	network	NOUN
cana-3788	52	19	(	(	PUNCT
cana-3788	52	20	cnns	cnns	PROPN
cana-3788	52	21	)	)	PUNCT
cana-3788	52	22	and	and	CCONJ
cana-3788	52	23	artificial	artificial	ADJ
cana-3788	52	24	neural	neural	ADJ
cana-3788	52	25	networks	network	NOUN
cana-3788	52	26	(	(	PUNCT
cana-3788	52	27	anns	anns	PROPN
cana-3788	52	28	)	)	PUNCT
cana-3788	52	29	,	,	PUNCT
cana-3788	52	30	to	to	PART
cana-3788	52	31	improve	improve	VERB
cana-3788	52	32	the	the	DET
cana-3788	52	33	robustness	robustness	NOUN
cana-3788	52	34	of	of	ADP
cana-3788	52	35	recommendation	recommendation	NOUN
cana-3788	52	36	systems	system	NOUN
cana-3788	52	37	in	in	ADP
cana-3788	52	38	noisy	noisy	ADJ
cana-3788	52	39	environments	environment	NOUN
cana-3788	52	40	.	.	PUNCT
cana-3788	53	1	he	he	PRON
cana-3788	53	2	et	et	PROPN
cana-3788	53	3	al	al	PROPN
cana-3788	53	4	.	.	PROPN
cana-3788	53	5	(	(	PUNCT
cana-3788	53	6	2023	2023	NUM
cana-3788	53	7	)	)	PUNCT
cana-3788	53	8	introduced	introduce	VERB
cana-3788	53	9	a	a	DET
cana-3788	53	10	novel	novel	ADJ
cana-3788	53	11	approach	approach	NOUN
cana-3788	53	12	using	use	VERB
cana-3788	53	13	cnns	cnn	NOUN
cana-3788	53	14	for	for	ADP
cana-3788	53	15	denoising	denoise	VERB
cana-3788	53	16	user	user	NOUN
cana-3788	53	17	interaction	interaction	NOUN
cana-3788	53	18	data	datum	NOUN
cana-3788	53	19	.	.	PUNCT
cana-3788	54	1	the	the	DET
cana-3788	54	2	authors	author	NOUN
cana-3788	54	3	demonstrated	demonstrate	VERB
cana-3788	54	4	that	that	SCONJ
cana-3788	54	5	cnns	cnn	NOUN
cana-3788	54	6	,	,	PUNCT
cana-3788	54	7	typically	typically	ADV
cana-3788	54	8	used	use	VERB
cana-3788	54	9	for	for	ADP
cana-3788	54	10	pattern	pattern	NOUN
cana-3788	54	11	recognition	recognition	NOUN
cana-3788	54	12	in	in	ADP
cana-3788	54	13	image	image	NOUN
cana-3788	54	14	data	datum	NOUN
cana-3788	54	15	,	,	PUNCT
cana-3788	54	16	can	can	AUX
cana-3788	54	17	also	also	ADV
cana-3788	54	18	be	be	AUX
cana-3788	54	19	applied	apply	VERB
cana-3788	54	20	to	to	PART
cana-3788	54	21	filter	filter	VERB
cana-3788	54	22	out	out	ADP
cana-3788	54	23	noisy	noisy	ADJ
cana-3788	54	24	interactions	interaction	NOUN
cana-3788	54	25	in	in	ADP
cana-3788	54	26	user	user	NOUN
cana-3788	54	27	behavior	behavior	NOUN
cana-3788	54	28	data	datum	NOUN
cana-3788	54	29	,	,	PUNCT
cana-3788	54	30	significantly	significantly	ADV
cana-3788	54	31	improving	improve	VERB
cana-3788	54	32	recommendation	recommendation	NOUN
cana-3788	54	33	accuracy	accuracy	NOUN
cana-3788	54	34	on	on	ADP
cana-3788	54	35	this	this	DET
cana-3788	54	36	idea	idea	NOUN
cana-3788	54	37	,	,	PUNCT
cana-3788	54	38	zhang	zhang	PROPN
cana-3788	54	39	et	et	PROPN
cana-3788	54	40	al	al	PROPN
cana-3788	54	41	.	.	PROPN
cana-3788	55	1	(	(	PUNCT
cana-3788	55	2	2022	2022	NUM
cana-3788	55	3	)	)	PUNCT
cana-3788	55	4	proposed	propose	VERB
cana-3788	55	5	a	a	DET
cana-3788	55	6	hybrid	hybrid	ADJ
cana-3788	55	7	model	model	NOUN
cana-3788	55	8	that	that	PRON
cana-3788	55	9	combines	combine	VERB
cana-3788	55	10	collaborative	collaborative	ADJ
cana-3788	55	11	filtering	filtering	NOUN
cana-3788	55	12	with	with	ADP
cana-3788	55	13	denoising	denoise	VERB
cana-3788	55	14	autoencoders	autoencoder	NOUN
cana-3788	55	15	.	.	PUNCT
cana-3788	56	1	other	other	ADJ
cana-3788	56	2	ideas	idea	NOUN
cana-3788	56	3	to	to	PART
cana-3788	56	4	reduce	reduce	VERB
cana-3788	56	5	noise	noise	NOUN
cana-3788	56	6	effect	effect	NOUN
cana-3788	56	7	were	be	AUX
cana-3788	56	8	implemented	implement	VERB
cana-3788	56	9	by	by	ADP
cana-3788	56	10	liu	liu	PROPN
cana-3788	56	11	et	et	PROPN
cana-3788	56	12	al	al	PROPN
cana-3788	56	13	.	.	PROPN
cana-3788	57	1	(	(	PUNCT
cana-3788	57	2	2023	2023	NUM
cana-3788	57	3	)	)	PUNCT
cana-3788	57	4	,	,	PUNCT
cana-3788	57	5	where	where	SCONJ
cana-3788	57	6	the	the	DET
cana-3788	57	7	authors	author	NOUN
cana-3788	57	8	used	use	VERB
cana-3788	57	9	convolutional	convolutional	ADJ
cana-3788	57	10	neural	neural	ADJ
cana-3788	57	11	network	network	NOUN
cana-3788	57	12	(	(	PUNCT
cana-3788	57	13	cnn	cnn	PROPN
cana-3788	57	14	)	)	PUNCT
cana-3788	57	15	with	with	ADP
cana-3788	57	16	recurrent	recurrent	ADJ
cana-3788	57	17	neural	neural	ADJ
cana-3788	57	18	networks	network	NOUN
cana-3788	57	19	(	(	PUNCT
cana-3788	57	20	rnn	rnn	PROPN
cana-3788	57	21	)	)	PUNCT
cana-3788	57	22	for	for	ADP
cana-3788	57	23	pre	pre	ADJ
cana-3788	57	24	-	-	ADJ
cana-3788	57	25	processing	process	VERB
cana-3788	57	26	the	the	DET
cana-3788	57	27	sequential	sequential	ADJ
cana-3788	57	28	user	user	NOUN
cana-3788	57	29	data	datum	NOUN
cana-3788	57	30	.	.	PUNCT
cana-3788	58	1	in	in	ADP
cana-3788	58	2	the	the	DET
cana-3788	58	3	case	case	NOUN
cana-3788	58	4	of	of	ADP
cana-3788	58	5	converting	convert	VERB
cana-3788	58	6	users	user	NOUN
cana-3788	58	7	,	,	PUNCT
cana-3788	58	8	this	this	DET
cana-3788	58	9	strategy	strategy	NOUN
cana-3788	58	10	was	be	AUX
cana-3788	58	11	highly	highly	ADV
cana-3788	58	12	efficient	efficient	ADJ
cana-3788	58	13	when	when	SCONJ
cana-3788	58	14	used	use	VERB
cana-3788	58	15	in	in	ADP
cana-3788	58	16	e	e	NOUN
cana-3788	58	17	-	-	NOUN
cana-3788	58	18	commerce	commerce	NOUN
cana-3788	58	19	,	,	PUNCT
cana-3788	58	20	because	because	SCONJ
cana-3788	58	21	users	user	NOUN
cana-3788	58	22	were	be	AUX
cana-3788	58	23	‘	'	PUNCT
cana-3788	58	24	noisier	noisy	ADJ
cana-3788	58	25	’	'	PUNCT
cana-3788	58	26	,	,	PUNCT
cana-3788	58	27	that	that	ADV
cana-3788	58	28	is	is	ADV
cana-3788	58	29	,	,	PUNCT
cana-3788	58	30	they	they	PRON
cana-3788	58	31	browsed	browse	VERB
cana-3788	58	32	through	through	ADP
cana-3788	58	33	websites	website	NOUN
cana-3788	58	34	,	,	PUNCT
cana-3788	58	35	added	add	VERB
cana-3788	58	36	goods	good	NOUN
cana-3788	58	37	to	to	ADP
cana-3788	58	38	their	their	PRON
cana-3788	58	39	wish	wish	NOUN
cana-3788	58	40	list	list	NOUN
cana-3788	58	41	with	with	ADP
cana-3788	58	42	no	no	DET
cana-3788	58	43	intention	intention	NOUN
cana-3788	58	44	of	of	ADP
cana-3788	58	45	buying	buy	VERB
cana-3788	58	46	them	they	PRON
cana-3788	58	47	at	at	ADP
cana-3788	58	48	the	the	DET
cana-3788	58	49	moment	moment	NOUN
cana-3788	58	50	,	,	PUNCT
cana-3788	58	51	etc	etc	X
cana-3788	58	52	.	.	X
cana-3788	59	1	[	[	X
cana-3788	59	2	2	2	NUM
cana-3788	59	3	]	]	PUNCT
cana-3788	59	4	.	.	PUNCT
cana-3788	60	1	their	their	PRON
cana-3788	60	2	method	method	NOUN
cana-3788	60	3	made	make	VERB
cana-3788	60	4	significant	significant	ADJ
cana-3788	60	5	improvements	improvement	NOUN
cana-3788	60	6	to	to	ADP
cana-3788	60	7	user	user	NOUN
cana-3788	60	8	satisfaction	satisfaction	NOUN
cana-3788	60	9	by	by	ADP
cana-3788	60	10	analyzing	analyze	VERB
cana-3788	60	11	patterns	pattern	NOUN
cana-3788	60	12	in	in	ADP
cana-3788	60	13	the	the	DET
cana-3788	60	14	user	user	NOUN
cana-3788	60	15	’s	’s	PART
cana-3788	60	16	behavior	behavior	NOUN
cana-3788	60	17	and	and	CCONJ
cana-3788	60	18	removing	remove	VERB
cana-3788	60	19	anomalies	anomaly	NOUN
cana-3788	60	20	before	before	ADP
cana-3788	60	21	making	make	VERB
cana-3788	60	22	further	further	ADJ
cana-3788	60	23	recommendations	recommendation	NOUN
cana-3788	60	24	.	.	PUNCT
cana-3788	61	1	another	another	DET
cana-3788	61	2	innovation	innovation	NOUN
cana-3788	61	3	in	in	ADP
cana-3788	61	4	managing	manage	VERB
cana-3788	61	5	noise	noise	NOUN
cana-3788	61	6	was	be	AUX
cana-3788	61	7	made	make	VERB
cana-3788	61	8	by	by	ADP
cana-3788	61	9	gao	gao	PROPN
cana-3788	61	10	et	et	PROPN
cana-3788	61	11	al	al	PROPN
cana-3788	61	12	.	.	PROPN
cana-3788	61	13	,	,	PUNCT
cana-3788	61	14	(	(	PUNCT
cana-3788	61	15	2022	2022	NUM
cana-3788	61	16	)	)	PUNCT
cana-3788	61	17	who	who	PRON
cana-3788	61	18	integrated	integrate	VERB
cana-3788	61	19	an	an	DET
cana-3788	61	20	attention	attention	NOUN
cana-3788	61	21	mechanism	mechanism	NOUN
cana-3788	61	22	into	into	ADP
cana-3788	61	23	the	the	DET
cana-3788	61	24	collaborative	collaborative	ADJ
cana-3788	61	25	filtering	filter	VERB
cana-3788	61	26	algorithms	algorithm	NOUN
cana-3788	61	27	.	.	PUNCT
cana-3788	62	1	their	their	PRON
cana-3788	62	2	model	model	NOUN
cana-3788	62	3	used	use	VERB
cana-3788	62	4	attention	attention	NOUN
cana-3788	62	5	layers	layer	NOUN
cana-3788	62	6	for	for	ADP
cana-3788	62	7	providing	provide	VERB
cana-3788	62	8	weights	weight	NOUN
cana-3788	62	9	to	to	ADP
cana-3788	62	10	the	the	DET
cana-3788	62	11	received	receive	VERB
cana-3788	62	12	interactions	interaction	NOUN
cana-3788	62	13	of	of	ADP
cana-3788	62	14	a	a	DET
cana-3788	62	15	user	user	NOUN
cana-3788	62	16	so	so	SCONJ
cana-3788	62	17	that	that	SCONJ
cana-3788	62	18	the	the	DET
cana-3788	62	19	system	system	NOUN
cana-3788	62	20	could	could	AUX
cana-3788	62	21	prioritize	prioritize	VERB
cana-3788	62	22	the	the	DET
cana-3788	62	23	important	important	ADJ
cana-3788	62	24	data	datum	NOUN
cana-3788	62	25	and	and	CCONJ
cana-3788	62	26	leave	leave	VERB
cana-3788	62	27	out	out	ADP
cana-3788	62	28	the	the	DET
cana-3788	62	29	noise	noise	NOUN
cana-3788	62	30	.	.	PUNCT
cana-3788	63	1	using	use	VERB
cana-3788	63	2	this	this	DET
cana-3788	63	3	approach	approach	NOUN
cana-3788	63	4	,	,	PUNCT
cana-3788	63	5	it	it	PRON
cana-3788	63	6	was	be	AUX
cana-3788	63	7	possible	possible	ADJ
cana-3788	63	8	to	to	PART
cana-3788	63	9	filter	filter	VERB
cana-3788	63	10	interactions	interaction	NOUN
cana-3788	63	11	that	that	SCONJ
cana-3788	63	12	either	either	CCONJ
cana-3788	63	13	positively	positively	ADV
cana-3788	63	14	or	or	CCONJ
cana-3788	63	15	negatively	negatively	ADV
cana-3788	63	16	influenced	influence	VERB
cana-3788	63	17	the	the	DET
cana-3788	63	18	recommendation	recommendation	NOUN
cana-3788	63	19	system	system	NOUN
cana-3788	63	20	and	and	CCONJ
cana-3788	63	21	dismissed	dismiss	VERB
cana-3788	63	22	those	those	PRON
cana-3788	63	23	that	that	PRON
cana-3788	63	24	were	be	AUX
cana-3788	63	25	irrelevant	irrelevant	ADJ
cana-3788	63	26	.	.	PUNCT
cana-3788	64	1	in	in	ADP
cana-3788	64	2	the	the	DET
cana-3788	64	3	same	same	ADJ
cana-3788	64	4	way	way	NOUN
cana-3788	64	5	,	,	PUNCT
cana-3788	64	6	sun	sun	PROPN
cana-3788	64	7	et	et	PROPN
cana-3788	64	8	al	al	PROPN
cana-3788	64	9	.	.	PROPN
cana-3788	64	10	studied	study	VERB
cana-3788	64	11	how	how	SCONJ
cana-3788	64	12	to	to	PART
cana-3788	64	13	model	model	VERB
cana-3788	64	14	multi	multi	ADJ
cana-3788	64	15	-	-	ADJ
cana-3788	64	16	faceted	faceted	ADJ
cana-3788	64	17	user	user	NOUN
cana-3788	64	18	-	-	PUNCT
cana-3788	64	19	item	item	NOUN
cana-3788	64	20	interactions	interaction	NOUN
cana-3788	64	21	with	with	ADP
cana-3788	64	22	graph	graph	NOUN
cana-3788	64	23	neural	neural	ADJ
cana-3788	64	24	networks	network	NOUN
cana-3788	64	25	(	(	PUNCT
cana-3788	64	26	gnns	gnns	NOUN
cana-3788	64	27	)	)	PUNCT
cana-3788	64	28	under	under	ADP
cana-3788	64	29	noisy	noisy	ADJ
cana-3788	64	30	conditions	condition	NOUN
cana-3788	64	31	[	[	X
cana-3788	64	32	3	3	NUM
cana-3788	64	33	]	]	PUNCT
cana-3788	64	34	.	.	PUNCT
cana-3788	65	1	it	it	PRON
cana-3788	65	2	was	be	AUX
cana-3788	65	3	also	also	ADV
cana-3788	65	4	established	establish	VERB
cana-3788	65	5	that	that	DET
cana-3788	65	6	gnns	gnns	NOUN
cana-3788	65	7	were	be	AUX
cana-3788	65	8	more	more	ADV
cana-3788	65	9	robust	robust	ADJ
cana-3788	65	10	in	in	ADP
cana-3788	65	11	both	both	CCONJ
cana-3788	65	12	sparse	sparse	ADJ
cana-3788	65	13	and	and	CCONJ
cana-3788	65	14	noisy	noisy	ADJ
cana-3788	65	15	settings	setting	NOUN
cana-3788	65	16	since	since	SCONJ
cana-3788	65	17	they	they	PRON
cana-3788	65	18	are	be	AUX
cana-3788	65	19	capable	capable	ADJ
cana-3788	65	20	of	of	ADP
cana-3788	65	21	identifying	identify	VERB
cana-3788	65	22	relations	relation	NOUN
cana-3788	65	23	in	in	ADP
cana-3788	65	24	data	datum	NOUN
cana-3788	65	25	even	even	ADV
cana-3788	65	26	if	if	SCONJ
cana-3788	65	27	the	the	DET
cana-3788	65	28	latter	latter	ADJ
cana-3788	65	29	was	be	AUX
cana-3788	65	30	noisy	noisy	ADJ
cana-3788	65	31	.	.	PUNCT
cana-3788	66	1	chen	chen	PROPN
cana-3788	66	2	et	et	PROPN
cana-3788	66	3	al	al	PROPN
cana-3788	66	4	.	.	PROPN
cana-3788	66	5	(	(	PUNCT
cana-3788	66	6	2023	2023	NUM
cana-3788	66	7	)	)	PUNCT
cana-3788	66	8	adopted	adopt	VERB
cana-3788	66	9	a	a	DET
cana-3788	66	10	deficiency	deficiency	NOUN
cana-3788	66	11	perspective	perspective	NOUN
cana-3788	66	12	by	by	ADP
cana-3788	66	13	specializing	specialize	VERB
cana-3788	66	14	in	in	ADP
cana-3788	66	15	noise	noise	NOUN
cana-3788	66	16	reduction	reduction	NOUN
cana-3788	66	17	in	in	ADP
cana-3788	66	18	media	medium	NOUN
cana-3788	66	19	streaming	streaming	NOUN
cana-3788	66	20	platforms	platform	NOUN
cana-3788	66	21	.	.	PUNCT
cana-3788	67	1	two	two	NUM
cana-3788	67	2	methodologies	methodology	NOUN
cana-3788	67	3	,	,	PUNCT
cana-3788	67	4	namely	namely	ADV
cana-3788	67	5	,	,	PUNCT
cana-3788	67	6	content	content	NOUN
cana-3788	67	7	-	-	PUNCT
cana-3788	67	8	based	base	VERB
cana-3788	67	9	filtering	filtering	NOUN
cana-3788	67	10	and	and	CCONJ
cana-3788	67	11	cnns	cnn	NOUN
cana-3788	67	12	were	be	AUX
cana-3788	67	13	integrated	integrate	VERB
cana-3788	67	14	by	by	ADP
cana-3788	67	15	the	the	DET
cana-3788	67	16	authors	author	NOUN
cana-3788	67	17	to	to	PART
cana-3788	67	18	filter	filter	VERB
cana-3788	67	19	out	out	ADP
cana-3788	67	20	random	random	ADJ
cana-3788	67	21	watching	watching	NOUN
cana-3788	67	22	tendency	tendency	NOUN
cana-3788	67	23	that	that	PRON
cana-3788	67	24	can	can	AUX
cana-3788	67	25	not	not	PART
cana-3788	67	26	be	be	AUX
cana-3788	67	27	ascribed	ascribe	VERB
cana-3788	67	28	to	to	ADP
cana-3788	67	29	the	the	DET
cana-3788	67	30	user	user	NOUN
cana-3788	67	31	’s	’s	PART
cana-3788	67	32	actual	actual	ADJ
cana-3788	67	33	preference	preference	NOUN
cana-3788	67	34	such	such	ADJ
cana-3788	67	35	as	as	ADP
cana-3788	67	36	click	click	NOUN
cana-3788	67	37	,	,	PUNCT
cana-3788	67	38	curiosity	curiosity	NOUN
cana-3788	67	39	.	.	PUNCT
cana-3788	68	1	their	their	PRON
cana-3788	68	2	method	method	NOUN
cana-3788	68	3	gave	give	VERB
cana-3788	68	4	an	an	DET
cana-3788	68	5	improved	improved	ADJ
cana-3788	68	6	representation	representation	NOUN
cana-3788	68	7	of	of	ADP
cana-3788	68	8	the	the	DET
cana-3788	68	9	user	user	NOUN
cana-3788	68	10	interests	interest	NOUN
cana-3788	68	11	compared	compare	VERB
cana-3788	68	12	to	to	ADP
cana-3788	68	13	the	the	DET
cana-3788	68	14	previous	previous	ADJ
cana-3788	68	15	one	one	NOUN
cana-3788	68	16	that	that	PRON
cana-3788	68	17	means	mean	VERB
cana-3788	68	18	that	that	SCONJ
cana-3788	68	19	their	their	PRON
cana-3788	68	20	recommendation	recommendation	NOUN
cana-3788	68	21	quality	quality	NOUN
cana-3788	68	22	is	be	AUX
cana-3788	68	23	high	high	ADJ
cana-3788	68	24	within	within	ADP
cana-3788	68	25	noisy	noisy	ADJ
cana-3788	68	26	environments	environment	NOUN
cana-3788	68	27	.	.	PUNCT
cana-3788	69	1	in	in	ADP
cana-3788	69	2	another	another	DET
cana-3788	69	3	domain	domain	NOUN
cana-3788	69	4	-	-	PUNCT
cana-3788	69	5	specific	specific	ADJ
cana-3788	69	6	application	application	NOUN
cana-3788	69	7	[	[	X
cana-3788	69	8	4	4	NUM
cana-3788	69	9	]	]	PUNCT
cana-3788	69	10	(	(	PUNCT
cana-3788	69	11	2023	2023	NUM
cana-3788	69	12	)	)	PUNCT
cana-3788	69	13	developed	develop	VERB
cana-3788	69	14	a	a	DET
cana-3788	69	15	reinforcement	reinforcement	NOUN
cana-3788	69	16	learning	learning	NOUN
cana-3788	69	17	based	base	VERB
cana-3788	69	18	model	model	NOUN
cana-3788	69	19	for	for	ADP
cana-3788	69	20	text	text	NOUN
cana-3788	69	21	analysis	analysis	NOUN
cana-3788	69	22	.	.	PUNCT
cana-3788	70	1	consumers	consumer	NOUN
cana-3788	70	2	’	'	PUNCT
cana-3788	70	3	feedback	feedback	NOUN
cana-3788	70	4	was	be	AUX
cana-3788	70	5	used	use	VERB
cana-3788	70	6	in	in	ADP
cana-3788	70	7	the	the	DET
cana-3788	70	8	teaching	teaching	NOUN
cana-3788	70	9	process	process	NOUN
cana-3788	70	10	in	in	ADP
cana-3788	70	11	order	order	NOUN
cana-3788	70	12	to	to	PART
cana-3788	70	13	filter	filter	VERB
cana-3788	70	14	noise	noise	NOUN
cana-3788	70	15	and	and	CCONJ
cana-3788	70	16	improve	improve	VERB
cana-3788	70	17	the	the	DET
cana-3788	70	18	effectiveness	effectiveness	NOUN
cana-3788	70	19	of	of	ADP
cana-3788	70	20	the	the	DET
cana-3788	70	21	offering	offering	NOUN
cana-3788	70	22	system	system	NOUN
cana-3788	70	23	.	.	PUNCT
cana-3788	71	1	sharma	sharma	PROPN
cana-3788	71	2	et	et	PROPN
cana-3788	71	3	al	al	PROPN
cana-3788	71	4	.	.	PROPN
cana-3788	71	5	(	(	PUNCT
cana-3788	71	6	2022	2022	NUM
cana-3788	71	7	)	)	PUNCT
cana-3788	71	8	investigated	investigate	VERB
cana-3788	71	9	applicability	applicability	NOUN
cana-3788	71	10	of	of	ADP
cana-3788	71	11	autoencoders	autoencoder	NOUN
cana-3788	71	12	(	(	PUNCT
cana-3788	71	13	vaes	vaes	ADJ
cana-3788	71	14	)	)	PUNCT
cana-3788	71	15	for	for	ADP
cana-3788	71	16	modeling	model	VERB
cana-3788	71	17	the	the	DET
cana-3788	71	18	user	user	NOUN
cana-3788	71	19	preferences	preference	NOUN
cana-3788	71	20	and	and	CCONJ
cana-3788	71	21	over	over	ADP
cana-3788	71	22	filtering	filter	VERB
cana-3788	71	23	the	the	DET
cana-3788	71	24	noises	noise	NOUN
cana-3788	71	25	.	.	PUNCT
cana-3788	72	1	vaes	vaes	PROPN
cana-3788	72	2	are	be	AUX
cana-3788	72	3	learned	learn	VERB
cana-3788	72	4	for	for	ADP
cana-3788	72	5	their	their	PRON
cana-3788	72	6	generative	generative	ADJ
cana-3788	72	7	properties	property	NOUN
cana-3788	72	8	,	,	PUNCT
cana-3788	72	9	thus	thus	ADV
cana-3788	72	10	it	it	PRON
cana-3788	72	11	makes	make	VERB
cana-3788	72	12	them	they	PRON
cana-3788	72	13	suitable	suitable	ADJ
cana-3788	72	14	in	in	ADP
cana-3788	72	15	handling	handling	NOUN
cana-3788	72	16	of	of	ADP
cana-3788	72	17	inconsistency	inconsistency	NOUN
cana-3788	72	18	in	in	ADP
cana-3788	72	19	user	user	NOUN
cana-3788	72	20	behaviors	behavior	NOUN
cana-3788	72	21	these	these	DET
cana-3788	72	22	models	model	NOUN
cana-3788	72	23	reconstruct	reconstruct	VERB
cana-3788	72	24	user	user	NOUN
cana-3788	72	25	preferences	preference	NOUN
cana-3788	72	26	from	from	ADP
cana-3788	72	27	the	the	DET
cana-3788	72	28	latent	latent	NOUN
cana-3788	72	29	space	space	NOUN
cana-3788	72	30	formed	form	VERB
cana-3788	72	31	from	from	ADP
cana-3788	72	32	representations	representation	NOUN
cana-3788	72	33	on	on	ADP
cana-3788	72	34	the	the	DET
cana-3788	72	35	users	user	NOUN
cana-3788	72	36	’	’	PART
cana-3788	72	37	interaction	interaction	NOUN
cana-3788	72	38	[	[	X
cana-3788	72	39	8	8	NUM
cana-3788	72	40	]	]	PUNCT
cana-3788	72	41	.	.	PUNCT
cana-3788	73	1	their	their	PRON
cana-3788	73	2	work	work	NOUN
cana-3788	73	3	also	also	ADV
cana-3788	73	4	proved	prove	VERB
cana-3788	73	5	that	that	SCONJ
cana-3788	73	6	the	the	DET
cana-3788	73	7	efficiency	efficiency	NOUN
cana-3788	73	8	of	of	ADP
cana-3788	73	9	vaes	vaes	NOUN
cana-3788	73	10	in	in	ADP
cana-3788	73	11	eliminating	eliminate	VERB
cana-3788	73	12	noisy	noisy	ADJ
cana-3788	73	13	data	datum	NOUN
cana-3788	73	14	has	have	AUX
cana-3788	73	15	improved	improve	VERB
cana-3788	73	16	recommendation	recommendation	NOUN
cana-3788	73	17	quality	quality	NOUN
cana-3788	73	18	.	.	PUNCT
cana-3788	74	1	multiple	multiple	ADJ
cana-3788	74	2	papers	paper	NOUN
cana-3788	74	3	also	also	ADV
cana-3788	74	4	assigned	assign	VERB
cana-3788	74	5	noise	noise	NOUN
cana-3788	74	6	control	control	NOUN
cana-3788	74	7	as	as	ADP
cana-3788	74	8	an	an	DET
cana-3788	74	9	additional	additional	ADJ
cana-3788	74	10	task	task	NOUN
cana-3788	74	11	in	in	ADP
cana-3788	74	12	addition	addition	NOUN
cana-3788	74	13	to	to	ADP
cana-3788	74	14	the	the	DET
cana-3788	74	15	primary	primary	ADJ
cana-3788	74	16	goal	goal	NOUN
cana-3788	74	17	of	of	ADP
cana-3788	74	18	recommendation	recommendation	NOUN
cana-3788	74	19	such	such	ADJ
cana-3788	74	20	as	as	ADP
cana-3788	74	21	the	the	DET
cana-3788	74	22	work	work	NOUN
cana-3788	74	23	by	by	ADP
cana-3788	74	24	kumar	kumar	PROPN
cana-3788	74	25	et	et	PROPN
cana-3788	74	26	al	al	PROPN
cana-3788	74	27	.	.	PROPN
cana-3788	75	1	(	(	PUNCT
cana-3788	75	2	2023	2023	NUM
cana-3788	75	3	)	)	PUNCT
cana-3788	75	4	.	.	PUNCT
cana-3788	76	1	to	to	PART
cana-3788	76	2	improve	improve	VERB
cana-3788	76	3	the	the	DET
cana-3788	76	4	robustness	robustness	NOUN
cana-3788	76	5	of	of	ADP
cana-3788	76	6	recommendations	recommendation	NOUN
cana-3788	76	7	in	in	ADP
cana-3788	76	8	noisy	noisy	ADJ
cana-3788	76	9	environments	environment	NOUN
cana-3788	76	10	,	,	PUNCT
cana-3788	76	11	the	the	DET
cana-3788	76	12	methods	method	NOUN
cana-3788	76	13	jointly	jointly	ADV
cana-3788	76	14	trained	train	VERB
cana-3788	76	15	the	the	DET
cana-3788	76	16	model	model	NOUN
cana-3788	76	17	for	for	ADP
cana-3788	76	18	noise	noise	NOUN
cana-3788	76	19	detection	detection	NOUN
cana-3788	76	20	and	and	CCONJ
cana-3788	76	21	noise	noise	NOUN
cana-3788	76	22	-	-	PUNCT
cana-3788	76	23	tolerant	tolerant	ADJ
cana-3788	76	24	prediction	prediction	NOUN
cana-3788	76	25	[	[	X
cana-3788	76	26	9	9	NUM
cana-3788	76	27	]	]	PUNCT
cana-3788	76	28	.	.	PUNCT
cana-3788	77	1	this	this	DET
cana-3788	77	2	multitask	multitask	ADJ
cana-3788	77	3	approach	approach	NOUN
cana-3788	77	4	revealed	reveal	VERB
cana-3788	77	5	that	that	SCONJ
cana-3788	77	6	by	by	ADP
cana-3788	77	7	adding	add	VERB
cana-3788	77	8	noise	noise	NOUN
cana-3788	77	9	detection	detection	NOUN
cana-3788	77	10	architecture	architecture	NOUN
cana-3788	77	11	of	of	ADP
cana-3788	77	12	the	the	DET
cana-3788	77	13	recommendation	recommendation	NOUN
cana-3788	77	14	system	system	NOUN
cana-3788	77	15	its	its	PRON
cana-3788	77	16	performance	performance	NOUN
cana-3788	77	17	could	could	AUX
cana-3788	77	18	be	be	AUX
cana-3788	77	19	boosted	boost	VERB
cana-3788	77	20	.	.	PUNCT
cana-3788	78	1	based	base	VERB
cana-3788	78	2	on	on	ADP
cana-3788	78	3	the	the	DET
cana-3788	78	4	cnns	cnn	NOUN
cana-3788	78	5	,	,	PUNCT
cana-3788	78	6	li	li	PROPN
cana-3788	78	7	et	et	PROPN
cana-3788	78	8	al	al	PROPN
cana-3788	78	9	.	.	PUNCT
cana-3788	79	1	[	[	X
cana-3788	79	2	39	39	NUM
cana-3788	79	3	]	]	PUNCT
cana-3788	79	4	has	have	AUX
cana-3788	79	5	developed	develop	VERB
cana-3788	79	6	a	a	DET
cana-3788	79	7	new	new	ADJ
cana-3788	79	8	model	model	NOUN
cana-3788	79	9	that	that	PRON
cana-3788	79	10	integrates	integrate	VERB
cana-3788	79	11	long	long	ADJ
cana-3788	79	12	short	short	ADJ
cana-3788	79	13	-	-	PUNCT
cana-3788	79	14	term	term	NOUN
cana-3788	79	15	memory	memory	NOUN
cana-3788	79	16	(	(	PUNCT
cana-3788	79	17	lstm	lstm	NOUN
cana-3788	79	18	)	)	PUNCT
cana-3788	79	19	networks	network	NOUN
cana-3788	79	20	.	.	PUNCT
cana-3788	80	1	the	the	DET
cana-3788	80	2	model	model	NOUN
cana-3788	80	3	was	be	AUX
cana-3788	80	4	developed	develop	VERB
cana-3788	80	5	to	to	PART
cana-3788	80	6	incorporate	incorporate	VERB
cana-3788	80	7	real	real	ADJ
cana-3788	80	8	time	time	NOUN
cana-3788	80	9	user	user	NOUN
cana-3788	80	10	interactions	interaction	NOUN
cana-3788	80	11	in	in	ADP
cana-3788	80	12	e	e	NOUN
cana-3788	80	13	-	-	NOUN
cana-3788	80	14	commerce	commerce	NOUN
cana-3788	80	15	domains	domain	NOUN
cana-3788	80	16	where	where	SCONJ
cana-3788	80	17	noise	noise	NOUN
cana-3788	80	18	in	in	ADP
cana-3788	80	19	the	the	DET
cana-3788	80	20	user	user	NOUN
cana-3788	80	21	preferences	preference	NOUN
cana-3788	80	22	is	be	AUX
cana-3788	80	23	exploited	exploit	VERB
cana-3788	80	24	.	.	PUNCT
cana-3788	81	1	cnns	cnns	PROPN
cana-3788	81	2	were	be	AUX
cana-3788	81	3	employed	employ	VERB
cana-3788	81	4	to	to	PART
cana-3788	81	5	extract	extract	VERB
cana-3788	81	6	patterns	pattern	NOUN
cana-3788	81	7	from	from	ADP
cana-3788	81	8	the	the	DET
cana-3788	81	9	user	user	NOUN
cana-3788	81	10	interaction	interaction	NOUN
cana-3788	81	11	data	datum	NOUN
cana-3788	81	12	and	and	CCONJ
cana-3788	81	13	lstms	lstms	NOUN
cana-3788	81	14	to	to	PART
cana-3788	81	15	capture	capture	VERB
cana-3788	81	16	temporal	temporal	ADJ
cana-3788	81	17	dependencies	dependency	NOUN
cana-3788	81	18	so	so	SCONJ
cana-3788	81	19	that	that	SCONJ
cana-3788	81	20	the	the	DET
cana-3788	81	21	system	system	NOUN
cana-3788	81	22	could	could	AUX
cana-3788	81	23	remove	remove	VERB
cana-3788	81	24	noise	noise	NOUN
cana-3788	81	25	and	and	CCONJ
cana-3788	81	26	make	make	VERB
cana-3788	81	27	accurate	accurate	ADJ
cana-3788	81	28	recommendations	recommendation	NOUN
cana-3788	81	29	suited	suit	VERB
cana-3788	81	30	to	to	ADP
cana-3788	81	31	the	the	DET
cana-3788	81	32	user	user	NOUN
cana-3788	81	33	.	.	PUNCT
cana-3788	82	1	hu	hu	PROPN
cana-3788	82	2	et	et	PROPN
cana-3788	82	3	al	al	PROPN
cana-3788	82	4	.	.	PROPN
cana-3788	83	1	(	(	PUNCT
cana-3788	83	2	2024	2024	NUM
cana-3788	83	3	)	)	PUNCT
cana-3788	83	4	have	have	AUX
cana-3788	83	5	recently	recently	ADV
cana-3788	83	6	proposed	propose	VERB
cana-3788	83	7	another	another	DET
cana-3788	83	8	noise	noise	NOUN
cana-3788	83	9	-	-	PUNCT
cana-3788	83	10	aware	aware	ADJ
cana-3788	83	11	collating	collate	VERB
cana-3788	83	12	model	model	NOUN
cana-3788	83	13	to	to	PART
cana-3788	83	14	minimize	minimize	VERB
cana-3788	83	15	noise	noise	NOUN
cana-3788	83	16	and	and	CCONJ
cana-3788	83	17	maximize	maximize	VERB
cana-3788	83	18	collation	collation	NOUN
cana-3788	83	19	while	while	SCONJ
cana-3788	83	20	integrating	integrate	VERB
cana-3788	83	21	implicit	implicit	ADJ
cana-3788	83	22	and	and	CCONJ
cana-3788	83	23	explicit	explicit	ADJ
cana-3788	83	24	feedback	feedback	NOUN
cana-3788	83	25	for	for	ADP
cana-3788	83	26	accurate	accurate	ADJ
cana-3788	83	27	recommendation	recommendation	NOUN
cana-3788	83	28	.	.	PUNCT
cana-3788	84	1	when	when	SCONJ
cana-3788	84	2	the	the	DET
cana-3788	84	3	model	model	NOUN
cana-3788	84	4	incorporated	incorporate	VERB
cana-3788	84	5	ratings	rating	NOUN
cana-3788	84	6	and	and	CCONJ
cana-3788	84	7	the	the	DET
cana-3788	84	8	user	user	NOUN
cana-3788	84	9	’s	’s	PART
cana-3788	84	10	interaction	interaction	NOUN
cana-3788	84	11	history	history	NOUN
cana-3788	84	12	,	,	PUNCT
cana-3788	84	13	it	it	PRON
cana-3788	84	14	was	be	AUX
cana-3788	84	15	more	more	ADV
cana-3788	84	16	effective	effective	ADJ
cana-3788	84	17	in	in	ADP
cana-3788	84	18	filtering	filter	VERB
cana-3788	84	19	out	out	ADP
cana-3788	84	20	noise	noise	NOUN
cana-3788	84	21	or	or	CCONJ
cana-3788	84	22	unreliable	unreliable	ADJ
cana-3788	84	23	indications	indication	NOUN
cana-3788	84	24	of	of	ADP
cana-3788	84	25	user	user	NOUN
cana-3788	84	26	’s	’s	PART
cana-3788	84	27	preferences	preference	NOUN
cana-3788	84	28	leading	lead	VERB
cana-3788	84	29	to	to	ADP
cana-3788	84	30	better	well	ADJ
cana-3788	84	31	recommendations	recommendation	NOUN
cana-3788	84	32	.	.	PUNCT
cana-3788	85	1	cheng	cheng	PROPN
cana-3788	85	2	et	et	PROPN
cana-3788	85	3	al	al	PROPN
cana-3788	85	4	.	.	PROPN
cana-3788	86	1	(	(	PUNCT
cana-3788	86	2	2024	2024	NUM
cana-3788	86	3	)	)	PUNCT
cana-3788	86	4	also	also	ADV
cana-3788	86	5	examined	examine	VERB
cana-3788	86	6	a	a	DET
cana-3788	86	7	mixture	mixture	NOUN
cana-3788	86	8	of	of	ADP
cana-3788	86	9	cnn	cnn	PROPN
cana-3788	86	10	and	and	CCONJ
cana-3788	86	11	ann	ann	PROPN
cana-3788	86	12	for	for	ADP
cana-3788	86	13	managing	manage	VERB
cana-3788	86	14	noise	noise	NOUN
cana-3788	86	15	in	in	ADP
cana-3788	86	16	recommendations	recommendation	NOUN
cana-3788	86	17	,	,	PUNCT
cana-3788	86	18	dictating	dictate	VERB
cana-3788	86	19	positive	positive	ADJ
cana-3788	86	20	impacts	impact	NOUN
cana-3788	86	21	of	of	ADP
cana-3788	86	22	cnns	cnn	NOUN
cana-3788	86	23	in	in	ADP
cana-3788	86	24	managing	manage	VERB
cana-3788	86	25	noisy	noisy	ADJ
cana-3788	86	26	data	datum	NOUN
cana-3788	86	27	because	because	SCONJ
cana-3788	86	28	of	of	ADP
cana-3788	86	29	pattern	pattern	NOUN
cana-3788	86	30	recognition	recognition	NOUN
cana-3788	86	31	and	and	CCONJ
cana-3788	86	32	high	high	ADJ
cana-3788	86	33	anticipation	anticipation	NOUN
cana-3788	86	34	responsibilities	responsibility	NOUN
cana-3788	86	35	of	of	ADP
cana-3788	86	36	anns	anns	NOUN
cana-3788	86	37	[	[	X
cana-3788	86	38	14	14	NUM
cana-3788	86	39	]	]	PUNCT
cana-3788	86	40	.	.	PUNCT
cana-3788	87	1	communications	communication	NOUN
cana-3788	87	2	on	on	ADP
cana-3788	87	3	applied	apply	VERB
cana-3788	87	4	nonlinear	nonlinear	ADJ
cana-3788	87	5	analysis	analysis	NOUN
cana-3788	87	6	issn	issn	NOUN
cana-3788	87	7	:	:	PUNCT
cana-3788	87	8	1074	1074	NUM
cana-3788	87	9	-	-	PUNCT
cana-3788	87	10	133x	133x	NUM
cana-3788	87	11	vol	vol	NOUN
cana-3788	87	12	32	32	NUM
cana-3788	87	13	no	no	NOUN
cana-3788	87	14	.	.	PUNCT
cana-3788	88	1	8s	8s	PROPN
cana-3788	88	2	(	(	PUNCT
cana-3788	88	3	2025	2025	NUM
cana-3788	88	4	)	)	PUNCT
cana-3788	88	5	727	727	NUM
cana-3788	89	1	https://internationalpubls.co	https://internationalpubls.co	X
cana-3788	89	2	m	m	VERB
cana-3788	89	3	lastly	lastly	ADV
cana-3788	89	4	,	,	PUNCT
cana-3788	89	5	zhao	zhao	PROPN
cana-3788	89	6	et	et	PROPN
cana-3788	89	7	al	al	PROPN
cana-3788	89	8	.	.	PROPN
cana-3788	90	1	(	(	PUNCT
cana-3788	90	2	2023	2023	NUM
cana-3788	90	3	)	)	PUNCT
cana-3788	90	4	used	use	VERB
cana-3788	90	5	graph	graph	NOUN
cana-3788	90	6	neural	neural	ADJ
cana-3788	90	7	network	network	NOUN
cana-3788	90	8	-	-	PUNCT
cana-3788	90	9	based	base	VERB
cana-3788	90	10	models	model	NOUN
cana-3788	90	11	with	with	ADP
cana-3788	90	12	noise	noise	NOUN
cana-3788	90	13	-	-	PUNCT
cana-3788	90	14	eliminating	eliminate	VERB
cana-3788	90	15	strategies	strategy	NOUN
cana-3788	90	16	in	in	ADP
cana-3788	90	17	recommendations	recommendation	NOUN
cana-3788	90	18	[	[	X
cana-3788	90	19	15	15	NUM
cana-3788	90	20	]	]	PUNCT
cana-3788	90	21	.	.	PUNCT
cana-3788	91	1	their	their	PRON
cana-3788	91	2	system	system	NOUN
cana-3788	91	3	was	be	AUX
cana-3788	91	4	able	able	ADJ
cana-3788	91	5	to	to	PART
cana-3788	91	6	incorporate	incorporate	VERB
cana-3788	91	7	user	user	NOUN
cana-3788	91	8	-	-	PUNCT
cana-3788	91	9	item	item	NOUN
cana-3788	91	10	interactions	interaction	NOUN
cana-3788	91	11	while	while	SCONJ
cana-3788	91	12	also	also	ADV
cana-3788	91	13	effectively	effectively	ADV
cana-3788	91	14	reducing	reduce	VERB
cana-3788	91	15	the	the	DET
cana-3788	91	16	impact	impact	NOUN
cana-3788	91	17	of	of	ADP
cana-3788	91	18	peripheral	peripheral	ADJ
cana-3788	91	19	user	user	NOUN
cana-3788	91	20	influence	influence	NOUN
cana-3788	91	21	;	;	PUNCT
cana-3788	91	22	chance	chance	NOUN
cana-3788	91	23	is	be	AUX
cana-3788	91	24	often	often	ADV
cana-3788	91	25	avaricious	avaricious	ADJ
cana-3788	91	26	and	and	CCONJ
cana-3788	91	27	user	user	NOUN
cana-3788	91	28	may	may	AUX
cana-3788	91	29	occasionally	occasionally	ADV
cana-3788	91	30	stumble	stumble	VERB
cana-3788	91	31	into	into	ADP
cana-3788	91	32	a	a	DET
cana-3788	91	33	given	give	VERB
cana-3788	91	34	item	item	NOUN
cana-3788	91	35	unintentionally	unintentionally	ADV
cana-3788	91	36	.	.	PUNCT
cana-3788	92	1	of	of	ADP
cana-3788	92	2	all	all	DET
cana-3788	92	3	such	such	ADJ
cana-3788	92	4	models	model	NOUN
cana-3788	92	5	,	,	PUNCT
cana-3788	92	6	this	this	DET
cana-3788	92	7	model	model	NOUN
cana-3788	92	8	was	be	AUX
cana-3788	92	9	found	find	VERB
cana-3788	92	10	to	to	PART
cana-3788	92	11	be	be	AUX
cana-3788	92	12	quite	quite	ADV
cana-3788	92	13	useful	useful	ADJ
cana-3788	92	14	while	while	SCONJ
cana-3788	92	15	dealing	deal	VERB
cana-3788	92	16	with	with	ADP
cana-3788	92	17	a	a	DET
cana-3788	92	18	wide	wide	ADJ
cana-3788	92	19	range	range	NOUN
cana-3788	92	20	of	of	ADP
cana-3788	92	21	voluminous	voluminous	ADJ
cana-3788	92	22	datasets	dataset	NOUN
cana-3788	92	23	where	where	SCONJ
cana-3788	92	24	the	the	DET
cana-3788	92	25	intermammary	intermammary	NOUN
cana-3788	92	26	was	be	AUX
cana-3788	92	27	sparse	sparse	ADJ
cana-3788	92	28	in	in	ADP
cana-3788	92	29	more	more	ADV
cana-3788	92	30	recent	recent	ADJ
cana-3788	92	31	research	research	NOUN
cana-3788	92	32	,	,	PUNCT
cana-3788	92	33	methods	method	NOUN
cana-3788	92	34	like	like	ADP
cana-3788	92	35	cnns	cnn	NOUN
cana-3788	92	36	,	,	PUNCT
cana-3788	92	37	anns	ann	NOUN
cana-3788	92	38	,	,	PUNCT
cana-3788	92	39	rnns	rnn	NOUN
cana-3788	92	40	,	,	PUNCT
cana-3788	92	41	vaes	vaes	ADJ
cana-3788	92	42	,	,	PUNCT
cana-3788	92	43	gnns	gnn	NOUN
cana-3788	92	44	have	have	AUX
cana-3788	92	45	been	be	AUX
cana-3788	92	46	tried	try	VERB
cana-3788	92	47	and	and	CCONJ
cana-3788	92	48	tested	test	VERB
cana-3788	92	49	for	for	ADP
cana-3788	92	50	managing	manage	VERB
cana-3788	92	51	noise	noise	NOUN
cana-3788	92	52	issues	issue	NOUN
cana-3788	92	53	in	in	ADP
cana-3788	92	54	recommendation	recommendation	NOUN
cana-3788	92	55	systems	system	NOUN
cana-3788	92	56	.	.	PUNCT
cana-3788	93	1	the	the	DET
cana-3788	93	2	incorporation	incorporation	NOUN
cana-3788	93	3	of	of	ADP
cana-3788	93	4	these	these	DET
cana-3788	93	5	models	model	NOUN
cana-3788	93	6	together	together	ADV
cana-3788	93	7	with	with	ADP
cana-3788	93	8	attention	attention	NOUN
cana-3788	93	9	mechanisms	mechanism	NOUN
cana-3788	93	10	and	and	CCONJ
cana-3788	93	11	multidirectional	multidirectional	ADJ
cana-3788	93	12	learning	learning	NOUN
cana-3788	93	13	has	have	AUX
cana-3788	93	14	made	make	VERB
cana-3788	93	15	quite	quite	DET
cana-3788	93	16	some	some	DET
cana-3788	93	17	progress	progress	NOUN
cana-3788	93	18	in	in	ADP
cana-3788	93	19	the	the	DET
cana-3788	93	20	field	field	NOUN
cana-3788	93	21	.	.	PUNCT
cana-3788	94	1	the	the	DET
cana-3788	94	2	current	current	ADJ
cana-3788	94	3	trend	trend	NOUN
cana-3788	94	4	is	be	AUX
cana-3788	94	5	toward	toward	ADP
cana-3788	94	6	hybrid	hybrid	ADJ
cana-3788	94	7	methods	method	NOUN
cana-3788	94	8	that	that	PRON
cana-3788	94	9	take	take	VERB
cana-3788	94	10	further	further	ADJ
cana-3788	94	11	advantage	advantage	NOUN
cana-3788	94	12	of	of	ADP
cana-3788	94	13	the	the	DET
cana-3788	94	14	multiarchitecture	multiarchitecture	ADJ
cana-3788	94	15	approaches	approach	NOUN
cana-3788	94	16	to	to	PART
cana-3788	94	17	enhance	enhance	VERB
cana-3788	94	18	recommendation	recommendation	NOUN
cana-3788	94	19	precision	precision	NOUN
cana-3788	94	20	in	in	ADP
cana-3788	94	21	a	a	DET
cana-3788	94	22	noisy	noisy	ADJ
cana-3788	94	23	environment	environment	NOUN
cana-3788	94	24	,	,	PUNCT
cana-3788	94	25	and	and	CCONJ
cana-3788	94	26	this	this	DET
cana-3788	94	27	area	area	NOUN
cana-3788	94	28	of	of	ADP
cana-3788	94	29	research	research	NOUN
cana-3788	94	30	has	have	AUX
cana-3788	94	31	posited	posit	VERB
cana-3788	94	32	the	the	DET
cana-3788	94	33	groundwork	groundwork	NOUN
cana-3788	94	34	for	for	ADP
cana-3788	94	35	future	future	ADJ
cana-3788	94	36	research	research	NOUN
cana-3788	94	37	on	on	ADP
cana-3788	94	38	noise	noise	NOUN
cana-3788	94	39	-	-	PUNCT
cana-3788	94	40	tolerant	tolerant	ADJ
cana-3788	94	41	recommendation	recommendation	NOUN
cana-3788	94	42	systems	system	NOUN
cana-3788	94	43	.	.	PUNCT
cana-3788	95	1	3	3	X
cana-3788	95	2	.	.	X
cana-3788	95	3	flowchart	flowchart	NOUN
cana-3788	95	4	of	of	ADP
cana-3788	95	5	the	the	DET
cana-3788	95	6	proposed	propose	VERB
cana-3788	95	7	approach	approach	NOUN
cana-3788	95	8	:	:	PUNCT
cana-3788	95	9	the	the	DET
cana-3788	95	10	flowchart	flowchart	NOUN
cana-3788	95	11	given	give	VERB
cana-3788	95	12	in	in	ADP
cana-3788	95	13	figure	figure	NOUN
cana-3788	95	14	01	01	NUM
cana-3788	95	15	describes	describe	VERB
cana-3788	95	16	the	the	DET
cana-3788	95	17	process	process	NOUN
cana-3788	95	18	of	of	ADP
cana-3788	95	19	handling	handle	VERB
cana-3788	95	20	natural	natural	ADJ
cana-3788	95	21	noise	noise	NOUN
cana-3788	95	22	in	in	ADP
cana-3788	95	23	recommendation	recommendation	NOUN
cana-3788	95	24	systems	system	NOUN
cana-3788	95	25	by	by	ADP
cana-3788	95	26	developing	develop	VERB
cana-3788	95	27	cnn	cnn	PROPN
cana-3788	95	28	and	and	CCONJ
cana-3788	95	29	ann	ann	PROPN
cana-3788	95	30	models	model	NOUN
cana-3788	95	31	.	.	PUNCT
cana-3788	96	1	figure	figure	NOUN
cana-3788	96	2	01	01	NUM
cana-3788	96	3	:	:	PUNCT
cana-3788	96	4	proposed	propose	VERB
cana-3788	96	5	approach	approach	NOUN
cana-3788	96	6	flowchart	flowchart	PROPN
cana-3788	96	7	raw	raw	PROPN
cana-3788	96	8	user	user	NOUN
cana-3788	96	9	interaction	interaction	NOUN
cana-3788	96	10	data	datum	NOUN
cana-3788	96	11	:	:	PUNCT
cana-3788	96	12	as	as	ADP
cana-3788	96	13	usual	usual	ADJ
cana-3788	96	14	,	,	PUNCT
cana-3788	96	15	the	the	DET
cana-3788	96	16	initial	initial	ADJ
cana-3788	96	17	data	data	NOUN
cana-3788	96	18	is	be	AUX
cana-3788	96	19	the	the	DET
cana-3788	96	20	user	user	NOUN
cana-3788	96	21	interaction	interaction	NOUN
cana-3788	96	22	data	datum	NOUN
cana-3788	96	23	,	,	PUNCT
cana-3788	96	24	and	and	CCONJ
cana-3788	96	25	these	these	PRON
cana-3788	96	26	are	be	AUX
cana-3788	96	27	usually	usually	ADV
cana-3788	96	28	noisy	noisy	ADJ
cana-3788	96	29	since	since	SCONJ
cana-3788	96	30	they	they	PRON
cana-3788	96	31	possess	possess	VERB
cana-3788	96	32	random	random	ADJ
cana-3788	96	33	interactions	interaction	NOUN
cana-3788	96	34	or	or	CCONJ
cana-3788	96	35	inconsistent	inconsistent	ADJ
cana-3788	96	36	interactions	interaction	NOUN
cana-3788	97	1	[	[	X
cana-3788	97	2	9	9	NUM
cana-3788	97	3	]	]	PUNCT
cana-3788	97	4	.	.	PUNCT
cana-3788	98	1	data	data	PROPN
cana-3788	98	2	pre	pre	ADJ
cana-3788	98	3	-	-	ADJ
cana-3788	98	4	processing	processing	ADJ
cana-3788	98	5	:	:	PUNCT
cana-3788	98	6	raw	raw	ADJ
cana-3788	98	7	data	datum	NOUN
cana-3788	98	8	also	also	ADV
cana-3788	98	9	has	have	VERB
cana-3788	98	10	to	to	PART
cana-3788	98	11	be	be	AUX
cana-3788	98	12	pre	pre	VERB
cana-3788	98	13	-	-	VERB
cana-3788	98	14	cleared	clear	VERB
cana-3788	98	15	as	as	SCONJ
cana-3788	98	16	the	the	DET
cana-3788	98	17	data	data	NOUN
cana-3788	98	18	is	be	AUX
cana-3788	98	19	made	make	VERB
cana-3788	98	20	orderly	orderly	ADV
cana-3788	98	21	ready	ready	ADJ
cana-3788	98	22	for	for	SCONJ
cana-3788	98	23	the	the	DET
cana-3788	98	24	subsequent	subsequent	ADJ
cana-3788	98	25	processes	process	NOUN
cana-3788	98	26	to	to	PART
cana-3788	98	27	initiate	initiate	VERB
cana-3788	98	28	.	.	PUNCT
cana-3788	99	1	this	this	DET
cana-3788	99	2	step	step	NOUN
cana-3788	99	3	makes	make	VERB
cana-3788	99	4	the	the	DET
cana-3788	99	5	data	datum	NOUN
cana-3788	99	6	fit	fit	ADJ
cana-3788	99	7	for	for	ADP
cana-3788	99	8	processing	processing	NOUN
cana-3788	99	9	by	by	ADP
cana-3788	99	10	the	the	DET
cana-3788	99	11	model	model	NOUN
cana-3788	99	12	through	through	ADP
cana-3788	99	13	removing	remove	VERB
cana-3788	99	14	potential	potential	ADJ
cana-3788	99	15	obstacles	obstacle	NOUN
cana-3788	99	16	[	[	X
cana-3788	99	17	10	10	NUM
cana-3788	99	18	]	]	PUNCT
cana-3788	99	19	.	.	PUNCT
cana-3788	100	1	noise	noise	NOUN
cana-3788	100	2	identification	identification	NOUN
cana-3788	100	3	algorithm	algorithm	NOUN
cana-3788	100	4	:	:	PUNCT
cana-3788	100	5	there	there	PRON
cana-3788	100	6	is	be	VERB
cana-3788	100	7	an	an	DET
cana-3788	100	8	assigned	assign	VERB
cana-3788	100	9	algorithm	algorithm	NOUN
cana-3788	100	10	that	that	PRON
cana-3788	100	11	looks	look	VERB
cana-3788	100	12	for	for	ADP
cana-3788	100	13	noise	noise	NOUN
cana-3788	100	14	in	in	ADP
cana-3788	100	15	the	the	DET
cana-3788	100	16	data	datum	NOUN
cana-3788	100	17	collected	collect	VERB
cana-3788	100	18	from	from	ADP
cana-3788	100	19	the	the	DET
cana-3788	100	20	interaction	interaction	NOUN
cana-3788	100	21	of	of	ADP
cana-3788	100	22	the	the	DET
cana-3788	100	23	users	user	NOUN
cana-3788	100	24	.	.	PUNCT
cana-3788	101	1	this	this	DET
cana-3788	101	2	algorithm	algorithm	NOUN
cana-3788	101	3	identifies	identify	VERB
cana-3788	101	4	information	information	NOUN
cana-3788	101	5	that	that	PRON
cana-3788	101	6	may	may	AUX
cana-3788	101	7	skew	skew	VERB
cana-3788	101	8	the	the	DET
cana-3788	101	9	user	user	NOUN
cana-3788	101	10	’s	’s	PART
cana-3788	101	11	true	true	ADJ
cana-3788	101	12	preferences	preference	NOUN
cana-3788	101	13	.	.	PUNCT
cana-3788	102	1	cnn	cnn	PROPN
cana-3788	102	2	for	for	ADP
cana-3788	102	3	noise	noise	NOUN
cana-3788	102	4	filtering	filtering	NOUN
cana-3788	102	5	:	:	PUNCT
cana-3788	102	6	in	in	ADP
cana-3788	102	7	the	the	DET
cana-3788	102	8	case	case	NOUN
cana-3788	102	9	of	of	ADP
cana-3788	102	10	noise	noise	NOUN
cana-3788	102	11	,	,	PUNCT
cana-3788	102	12	the	the	DET
cana-3788	102	13	system	system	NOUN
cana-3788	102	14	uses	use	VERB
cana-3788	102	15	cnn	cnn	PROPN
cana-3788	102	16	to	to	PART
cana-3788	102	17	eliminate	eliminate	VERB
cana-3788	102	18	the	the	DET
cana-3788	102	19	confounding	confound	VERB
cana-3788	102	20	data	datum	NOUN
cana-3788	102	21	from	from	ADP
cana-3788	102	22	the	the	DET
cana-3788	102	23	set	set	NOUN
cana-3788	102	24	[	[	X
cana-3788	102	25	11	11	NUM
cana-3788	102	26	]	]	PUNCT
cana-3788	102	27	.	.	PUNCT
cana-3788	103	1	cnn	cnn	PROPN
cana-3788	103	2	also	also	ADV
cana-3788	103	3	works	work	VERB
cana-3788	103	4	well	well	ADV
cana-3788	103	5	when	when	SCONJ
cana-3788	103	6	it	it	PRON
cana-3788	103	7	comes	come	VERB
cana-3788	103	8	to	to	ADP
cana-3788	103	9	understanding	understand	VERB
cana-3788	103	10	intricate	intricate	ADJ
cana-3788	103	11	relations	relation	NOUN
cana-3788	103	12	in	in	ADP
cana-3788	103	13	a	a	DET
cana-3788	103	14	data	datum	NOUN
cana-3788	103	15	set	set	VERB
cana-3788	103	16	and	and	CCONJ
cana-3788	103	17	leaving	leave	VERB
cana-3788	103	18	all	all	DET
cana-3788	103	19	‘	'	PUNCT
cana-3788	103	20	noise	noise	NOUN
cana-3788	103	21	’	'	PUNCT
cana-3788	103	22	out	out	ADV
cana-3788	103	23	.	.	PUNCT
cana-3788	104	1	refining	refine	VERB
cana-3788	104	2	the	the	DET
cana-3788	104	3	dataset	dataset	NOUN
cana-3788	104	4	:	:	PUNCT
cana-3788	104	5	in	in	ADP
cana-3788	104	6	this	this	DET
cana-3788	104	7	step	step	NOUN
cana-3788	104	8	,	,	PUNCT
cana-3788	104	9	the	the	DET
cana-3788	104	10	data	data	NOUN
cana-3788	104	11	is	be	AUX
cana-3788	104	12	preprocessed	preprocesse	VERB
cana-3788	104	13	for	for	ADP
cana-3788	104	14	all	all	DET
cana-3788	104	15	the	the	DET
cana-3788	104	16	necessary	necessary	ADJ
cana-3788	104	17	filters	filter	NOUN
cana-3788	104	18	to	to	PART
cana-3788	104	19	obtain	obtain	VERB
cana-3788	104	20	data	datum	NOUN
cana-3788	104	21	with	with	ADP
cana-3788	104	22	communications	communication	NOUN
cana-3788	104	23	on	on	ADP
cana-3788	104	24	applied	apply	VERB
cana-3788	104	25	nonlinear	nonlinear	ADJ
cana-3788	104	26	analysis	analysis	NOUN
cana-3788	104	27	issn	issn	NOUN
cana-3788	104	28	:	:	PUNCT
cana-3788	104	29	1074	1074	NUM
cana-3788	104	30	-	-	PUNCT
cana-3788	104	31	133x	133x	NUM
cana-3788	104	32	vol	vol	NOUN
cana-3788	104	33	32	32	NUM
cana-3788	104	34	no	no	NOUN
cana-3788	104	35	.	.	PUNCT
cana-3788	105	1	8s	8s	PROPN
cana-3788	105	2	(	(	PUNCT
cana-3788	105	3	2025	2025	NUM
cana-3788	105	4	)	)	PUNCT
cana-3788	105	5	728	728	NUM
cana-3788	105	6	https://internationalpubls.co	https://internationalpubls.co	NOUN
cana-3788	105	7	m	m	VERB
cana-3788	105	8	minimized	minimized	ADJ
cana-3788	105	9	noise	noise	NOUN
cana-3788	105	10	which	which	PRON
cana-3788	105	11	presents	present	VERB
cana-3788	105	12	a	a	DET
cana-3788	105	13	realistic	realistic	ADJ
cana-3788	105	14	sampling	sampling	NOUN
cana-3788	105	15	of	of	ADP
cana-3788	105	16	users	user	NOUN
cana-3788	105	17	behavior	behavior	NOUN
cana-3788	105	18	[	[	X
cana-3788	105	19	13	13	NUM
cana-3788	105	20	]	]	PUNCT
cana-3788	105	21	.	.	PUNCT
cana-3788	106	1	the	the	DET
cana-3788	106	2	process	process	NOUN
cana-3788	106	3	repeats	repeat	VERB
cana-3788	106	4	in	in	ADP
cana-3788	106	5	case	case	NOUN
cana-3788	106	6	of	of	ADP
cana-3788	106	7	further	further	ADJ
cana-3788	106	8	refinement	refinement	NOUN
cana-3788	106	9	.	.	PUNCT
cana-3788	107	1	ann	ann	PROPN
cana-3788	107	2	for	for	ADP
cana-3788	107	3	preference	preference	NOUN
cana-3788	107	4	prediction	prediction	NOUN
cana-3788	107	5	:	:	PUNCT
cana-3788	107	6	the	the	DET
cana-3788	107	7	meaningful	meaningful	ADJ
cana-3788	107	8	user	user	NOUN
cana-3788	107	9	data	datum	NOUN
cana-3788	107	10	then	then	ADV
cana-3788	107	11	flows	flow	VERB
cana-3788	107	12	onto	onto	ADP
cana-3788	107	13	an	an	DET
cana-3788	107	14	artificial	artificial	ADJ
cana-3788	107	15	neural	neural	ADJ
cana-3788	107	16	network	network	NOUN
cana-3788	107	17	(	(	PUNCT
cana-3788	107	18	ann	ann	PROPN
cana-3788	107	19	)	)	PUNCT
cana-3788	107	20	which	which	PRON
cana-3788	107	21	filters	filter	VERB
cana-3788	107	22	the	the	DET
cana-3788	107	23	fake	fake	ADJ
cana-3788	107	24	data	datum	NOUN
cana-3788	107	25	and	and	CCONJ
cana-3788	107	26	predicts	predict	VERB
cana-3788	107	27	preferences	preference	NOUN
cana-3788	107	28	to	to	ADP
cana-3788	107	29	a	a	DET
cana-3788	107	30	high	high	ADJ
cana-3788	107	31	degree	degree	NOUN
cana-3788	107	32	of	of	ADP
cana-3788	107	33	accuracy	accuracy	NOUN
cana-3788	107	34	.	.	PUNCT
cana-3788	108	1	personalized	personalized	ADJ
cana-3788	108	2	recommendations	recommendation	NOUN
cana-3788	108	3	:	:	PUNCT
cana-3788	108	4	then	then	ADV
cana-3788	108	5	the	the	DET
cana-3788	108	6	output	output	NOUN
cana-3788	108	7	is	be	AUX
cana-3788	108	8	a	a	DET
cana-3788	108	9	set	set	NOUN
cana-3788	108	10	of	of	ADP
cana-3788	108	11	specific	specific	ADJ
cana-3788	108	12	recommendations	recommendation	NOUN
cana-3788	108	13	true	true	ADJ
cana-3788	108	14	to	to	ADP
cana-3788	108	15	the	the	DET
cana-3788	108	16	user	user	NOUN
cana-3788	108	17	’s	’s	PART
cana-3788	108	18	actual	actual	ADJ
cana-3788	108	19	preferences	preference	NOUN
cana-3788	108	20	,	,	PUNCT
cana-3788	108	21	whereas	whereas	SCONJ
cana-3788	108	22	the	the	DET
cana-3788	108	23	noise	noise	NOUN
cana-3788	108	24	is	be	AUX
cana-3788	108	25	filtered	filter	VERB
cana-3788	108	26	out	out	ADP
cana-3788	108	27	and	and	CCONJ
cana-3788	108	28	does	do	AUX
cana-3788	108	29	not	not	PART
cana-3788	108	30	affect	affect	VERB
cana-3788	108	31	the	the	DET
cana-3788	108	32	result	result	NOUN
cana-3788	108	33	.	.	PUNCT
cana-3788	109	1	this	this	DET
cana-3788	109	2	approach	approach	NOUN
cana-3788	109	3	has	have	AUX
cana-3788	109	4	been	be	AUX
cana-3788	109	5	devised	devise	VERB
cana-3788	109	6	to	to	PART
cana-3788	109	7	guarantee	guarantee	VERB
cana-3788	109	8	a	a	DET
cana-3788	109	9	more	more	ADV
cana-3788	109	10	stable	stable	ADJ
cana-3788	109	11	as	as	ADV
cana-3788	109	12	well	well	ADV
cana-3788	109	13	as	as	ADP
cana-3788	109	14	noise	noise	NOUN
cana-3788	109	15	-	-	PUNCT
cana-3788	109	16	tolerant	tolerant	ADJ
cana-3788	109	17	recommendation	recommendation	NOUN
cana-3788	109	18	system	system	NOUN
cana-3788	109	19	capable	capable	ADJ
cana-3788	109	20	of	of	ADP
cana-3788	109	21	improving	improve	VERB
cana-3788	109	22	the	the	DET
cana-3788	109	23	overall	overall	ADJ
cana-3788	109	24	use	use	NOUN
cana-3788	109	25	experience	experience	NOUN
cana-3788	109	26	through	through	ADP
cana-3788	109	27	offering	offer	VERB
cana-3788	109	28	more	more	ADJ
cana-3788	109	29	targeted	target	VERB
cana-3788	109	30	recommendations	recommendation	NOUN
cana-3788	109	31	.	.	PUNCT
cana-3788	110	1	1	1	X
cana-3788	110	2	.	.	X
cana-3788	110	3	proposed	propose	VERB
cana-3788	110	4	approach	approach	NOUN
cana-3788	110	5	:	:	PUNCT
cana-3788	110	6	the	the	DET
cana-3788	110	7	proposed	propose	VERB
cana-3788	110	8	approach	approach	NOUN
cana-3788	110	9	involves	involve	VERB
cana-3788	110	10	using	use	VERB
cana-3788	110	11	cnns	cnns	PROPN
cana-3788	110	12	&	&	CCONJ
cana-3788	110	13	anns	anns	PROPN
cana-3788	110	14	to	to	PART
cana-3788	110	15	handle	handle	VERB
cana-3788	110	16	natural	natural	ADJ
cana-3788	110	17	noise	noise	NOUN
cana-3788	110	18	for	for	ADP
cana-3788	110	19	recommendations	recommendation	NOUN
cana-3788	110	20	in	in	ADP
cana-3788	110	21	order	order	NOUN
cana-3788	110	22	to	to	PART
cana-3788	110	23	highly	highly	ADV
cana-3788	110	24	improve	improve	VERB
cana-3788	110	25	the	the	DET
cana-3788	110	26	level	level	NOUN
cana-3788	110	27	of	of	ADP
cana-3788	110	28	recommendation	recommendation	NOUN
cana-3788	110	29	.	.	PUNCT
cana-3788	111	1	the	the	DET
cana-3788	111	2	concept	concept	NOUN
cana-3788	111	3	is	be	AUX
cana-3788	111	4	to	to	PART
cana-3788	111	5	use	use	VERB
cana-3788	111	6	cnns	cnn	NOUN
cana-3788	111	7	for	for	ADP
cana-3788	111	8	noise	noise	NOUN
cana-3788	111	9	removal	removal	NOUN
cana-3788	111	10	and	and	CCONJ
cana-3788	111	11	anns	ann	NOUN
cana-3788	111	12	for	for	ADP
cana-3788	111	13	predicting	predict	VERB
cana-3788	111	14	user	user	NOUN
cana-3788	111	15	preferences	preference	NOUN
cana-3788	111	16	using	use	VERB
cana-3788	111	17	the	the	DET
cana-3788	111	18	cleaned	clean	VERB
cana-3788	111	19	up	up	ADP
cana-3788	111	20	data	datum	NOUN
cana-3788	111	21	.	.	PUNCT
cana-3788	112	1	•	•	NUM
cana-3788	112	2	the	the	DET
cana-3788	112	3	raw	raw	ADJ
cana-3788	112	4	user	user	NOUN
cana-3788	112	5	interaction	interaction	NOUN
cana-3788	112	6	data	datum	NOUN
cana-3788	112	7	which	which	PRON
cana-3788	112	8	may	may	AUX
cana-3788	112	9	include	include	VERB
cana-3788	112	10	meaningless	meaningless	ADJ
cana-3788	112	11	click	click	NOUN
cana-3788	112	12	data	datum	NOUN
cana-3788	112	13	,	,	PUNCT
cana-3788	112	14	random	random	ADJ
cana-3788	112	15	behavior	behavior	NOUN
cana-3788	112	16	is	be	AUX
cana-3788	112	17	first	first	ADV
cana-3788	112	18	transformed	transform	VERB
cana-3788	112	19	through	through	ADP
cana-3788	112	20	various	various	ADJ
cana-3788	112	21	operations	operation	NOUN
cana-3788	112	22	to	to	PART
cana-3788	112	23	arrive	arrive	VERB
cana-3788	112	24	at	at	ADP
cana-3788	112	25	usable	usable	ADJ
cana-3788	112	26	forms	form	NOUN
cana-3788	112	27	which	which	PRON
cana-3788	112	28	are	be	AUX
cana-3788	112	29	then	then	ADV
cana-3788	112	30	fed	feed	VERB
cana-3788	112	31	into	into	ADP
cana-3788	112	32	the	the	DET
cana-3788	112	33	cnn	cnn	PROPN
cana-3788	112	34	model	model	NOUN
cana-3788	112	35	.	.	PUNCT
cana-3788	113	1	•	•	NUM
cana-3788	113	2	the	the	DET
cana-3788	113	3	cnn	cnn	PROPN
cana-3788	113	4	processes	process	VERB
cana-3788	113	5	the	the	DET
cana-3788	113	6	preprocessed	preprocesse	VERB
cana-3788	113	7	data	datum	NOUN
cana-3788	113	8	to	to	PART
cana-3788	113	9	extract	extract	VERB
cana-3788	113	10	noise	noise	NOUN
cana-3788	113	11	and	and	CCONJ
cana-3788	113	12	remove	remove	VERB
cana-3788	113	13	noise	noise	NOUN
cana-3788	113	14	by	by	ADP
cana-3788	113	15	learning	learn	VERB
cana-3788	113	16	detailed	detailed	ADJ
cana-3788	113	17	features	feature	NOUN
cana-3788	113	18	of	of	ADP
cana-3788	113	19	the	the	DET
cana-3788	113	20	user	user	NOUN
cana-3788	113	21	behavior	behavior	NOUN
cana-3788	113	22	.	.	PUNCT
cana-3788	114	1	this	this	DET
cana-3788	114	2	layer	layer	NOUN
cana-3788	114	3	is	be	AUX
cana-3788	114	4	exceptional	exceptional	ADJ
cana-3788	114	5	in	in	ADP
cana-3788	114	6	identifying	identify	VERB
cana-3788	114	7	biased	biased	ADJ
cana-3788	114	8	interactions	interaction	NOUN
cana-3788	114	9	that	that	PRON
cana-3788	114	10	lead	lead	VERB
cana-3788	114	11	to	to	ADP
cana-3788	114	12	wrong	wrong	ADJ
cana-3788	114	13	recommendations	recommendation	NOUN
cana-3788	114	14	.	.	PUNCT
cana-3788	115	1	the	the	DET
cana-3788	115	2	output	output	NOUN
cana-3788	115	3	,	,	PUNCT
cana-3788	115	4	therefore	therefore	ADV
cana-3788	115	5	,	,	PUNCT
cana-3788	115	6	is	be	AUX
cana-3788	115	7	a	a	DET
cana-3788	115	8	dataset	dataset	NOUN
cana-3788	115	9	that	that	PRON
cana-3788	115	10	is	be	AUX
cana-3788	115	11	‘	'	PUNCT
cana-3788	115	12	raw	raw	ADJ
cana-3788	115	13	,	,	PUNCT
cana-3788	115	14	’	'	PUNCT
cana-3788	115	15	in	in	ADP
cana-3788	115	16	the	the	DET
cana-3788	115	17	sense	sense	NOUN
cana-3788	115	18	that	that	SCONJ
cana-3788	115	19	it	it	PRON
cana-3788	115	20	contains	contain	VERB
cana-3788	115	21	only	only	ADV
cana-3788	115	22	meaningful	meaningful	ADJ
cana-3788	115	23	user	user	NOUN
cana-3788	115	24	behavior	behavior	NOUN
cana-3788	115	25	.	.	PUNCT
cana-3788	116	1	•	•	ADV
cana-3788	116	2	finally	finally	ADV
cana-3788	116	3	,	,	PUNCT
cana-3788	116	4	the	the	DET
cana-3788	116	5	clean	clean	ADJ
cana-3788	116	6	dataset	dataset	NOUN
cana-3788	116	7	goes	go	VERB
cana-3788	116	8	to	to	ADP
cana-3788	116	9	the	the	DET
cana-3788	116	10	ann	ann	PROPN
cana-3788	116	11	after	after	ADP
cana-3788	116	12	removing	remove	VERB
cana-3788	116	13	the	the	DET
cana-3788	116	14	noisest.er	noisest.er	NUM
cana-3788	116	15	out	out	ADP
cana-3788	116	16	noise	noise	NOUN
cana-3788	116	17	by	by	ADP
cana-3788	116	18	learning	learn	VERB
cana-3788	116	19	complex	complex	ADJ
cana-3788	116	20	patterns	pattern	NOUN
cana-3788	116	21	in	in	ADP
cana-3788	116	22	user	user	NOUN
cana-3788	116	23	behavior	behavior	NOUN
cana-3788	116	24	.	.	PUNCT
cana-3788	117	1	this	this	DET
cana-3788	117	2	layer	layer	NOUN
cana-3788	117	3	excels	excel	VERB
cana-3788	117	4	at	at	ADP
cana-3788	117	5	recognizing	recognize	VERB
cana-3788	117	6	irrelevant	irrelevant	ADJ
cana-3788	117	7	interactions	interaction	NOUN
cana-3788	117	8	that	that	PRON
cana-3788	117	9	distort	distort	VERB
cana-3788	117	10	recommendation	recommendation	NOUN
cana-3788	117	11	accuracy	accuracy	NOUN
cana-3788	117	12	.	.	PUNCT
cana-3788	118	1	the	the	DET
cana-3788	118	2	output	output	NOUN
cana-3788	118	3	is	be	AUX
cana-3788	118	4	a	a	DET
cana-3788	118	5	"	"	PUNCT
cana-3788	118	6	clean	clean	ADJ
cana-3788	118	7	"	"	PUNCT
cana-3788	118	8	dataset	dataset	NOUN
cana-3788	118	9	representing	represent	VERB
cana-3788	118	10	meaningful	meaningful	ADJ
cana-3788	118	11	user	user	NOUN
cana-3788	118	12	behavior	behavior	NOUN
cana-3788	118	13	.	.	PUNCT
cana-3788	119	1	•	•	NUM
cana-3788	119	2	after	after	ADP
cana-3788	119	3	noise	noise	NOUN
cana-3788	119	4	removal	removal	NOUN
cana-3788	119	5	,	,	PUNCT
cana-3788	119	6	the	the	DET
cana-3788	119	7	clean	clean	ADJ
cana-3788	119	8	dataset	dataset	NOUN
cana-3788	119	9	is	be	AUX
cana-3788	119	10	passed	pass	VERB
cana-3788	119	11	to	to	ADP
cana-3788	119	12	the	the	DET
cana-3788	119	13	ann	ann	PROPN
cana-3788	119	14	.	.	PUNCT
cana-3788	120	1	the	the	DET
cana-3788	120	2	ann	ann	PROPN
cana-3788	120	3	further	far	ADV
cana-3788	120	4	analyzes	analyze	VERB
cana-3788	120	5	this	this	DET
cana-3788	120	6	data	datum	NOUN
cana-3788	120	7	to	to	PART
cana-3788	120	8	gain	gain	VERB
cana-3788	120	9	insight	insight	NOUN
cana-3788	120	10	of	of	ADP
cana-3788	120	11	the	the	DET
cana-3788	120	12	user	user	NOUN
cana-3788	120	13	preferences	preference	NOUN
cana-3788	120	14	and	and	CCONJ
cana-3788	120	15	in	in	ADP
cana-3788	120	16	the	the	DET
cana-3788	120	17	long	long	ADJ
cana-3788	120	18	run	run	NOUN
cana-3788	120	19	provide	provide	VERB
cana-3788	120	20	customized	customized	ADJ
cana-3788	120	21	recommendations	recommendation	NOUN
cana-3788	120	22	.	.	PUNCT
cana-3788	121	1	the	the	DET
cana-3788	121	2	ann	ann	PROPN
cana-3788	121	3	architectures	architecture	NOUN
cana-3788	121	4	incorporate	incorporate	VERB
cana-3788	121	5	several	several	ADJ
cana-3788	121	6	layers	layer	NOUN
cana-3788	121	7	aimed	aim	VERB
cana-3788	121	8	at	at	ADP
cana-3788	121	9	improving	improve	VERB
cana-3788	121	10	the	the	DET
cana-3788	121	11	prediction	prediction	NOUN
cana-3788	121	12	of	of	ADP
cana-3788	121	13	programming	programming	NOUN
cana-3788	121	14	preferences	preference	NOUN
cana-3788	121	15	,	,	PUNCT
cana-3788	121	16	to	to	PART
cana-3788	121	17	account	account	VERB
cana-3788	121	18	for	for	ADP
cana-3788	121	19	the	the	DET
cana-3788	121	20	nonlinearity	nonlinearity	NOUN
cana-3788	121	21	of	of	ADP
cana-3788	121	22	users	user	NOUN
cana-3788	121	23	’	’	PART
cana-3788	121	24	preferences	preference	NOUN
cana-3788	121	25	.	.	PUNCT
cana-3788	122	1	•	•	NUM
cana-3788	122	2	new	new	ADJ
cana-3788	122	3	user	user	NOUN
cana-3788	122	4	interactions	interaction	NOUN
cana-3788	122	5	with	with	ADP
cana-3788	122	6	the	the	DET
cana-3788	122	7	transformed	transform	VERB
cana-3788	122	8	model	model	NOUN
cana-3788	122	9	are	be	AUX
cana-3788	122	10	used	use	VERB
cana-3788	122	11	to	to	PART
cana-3788	122	12	continue	continue	VERB
cana-3788	122	13	updating	update	VERB
cana-3788	122	14	the	the	DET
cana-3788	122	15	system	system	NOUN
cana-3788	122	16	,	,	PUNCT
cana-3788	122	17	due	due	ADP
cana-3788	122	18	to	to	ADP
cana-3788	122	19	the	the	DET
cana-3788	122	20	usage	usage	NOUN
cana-3788	122	21	of	of	ADP
cana-3788	122	22	a	a	DET
cana-3788	122	23	feedback	feedback	NOUN
cana-3788	122	24	mechanisms	mechanism	NOUN
cana-3788	122	25	in	in	ADP
cana-3788	122	26	user	user	NOUN
cana-3788	122	27	behavior	behavior	NOUN
cana-3788	122	28	.	.	PUNCT
cana-3788	123	1	this	this	DET
cana-3788	123	2	layer	layer	NOUN
cana-3788	123	3	excels	excel	VERB
cana-3788	123	4	at	at	ADP
cana-3788	123	5	recognizing	recognize	VERB
cana-3788	123	6	irrelevant	irrelevant	ADJ
cana-3788	123	7	interactions	interaction	NOUN
cana-3788	123	8	that	that	PRON
cana-3788	123	9	distort	distort	VERB
cana-3788	123	10	recommendation	recommendation	NOUN
cana-3788	123	11	accuracy	accuracy	NOUN
cana-3788	123	12	.	.	PUNCT
cana-3788	124	1	the	the	DET
cana-3788	124	2	output	output	NOUN
cana-3788	124	3	is	be	AUX
cana-3788	124	4	a	a	DET
cana-3788	124	5	"	"	PUNCT
cana-3788	124	6	clean	clean	ADJ
cana-3788	124	7	"	"	PUNCT
cana-3788	124	8	dataset	dataset	NOUN
cana-3788	124	9	representing	represent	VERB
cana-3788	124	10	meaningful	meaningful	ADJ
cana-3788	124	11	user	user	NOUN
cana-3788	124	12	behavior	behavior	NOUN
cana-3788	124	13	.	.	PUNCT
cana-3788	125	1	1	1	X
cana-3788	125	2	.	.	X
cana-3788	125	3	result	result	VERB
cana-3788	125	4	analysis	analysis	NOUN
cana-3788	125	5	:	:	PUNCT
cana-3788	125	6	to	to	PART
cana-3788	125	7	evaluate	evaluate	VERB
cana-3788	125	8	the	the	DET
cana-3788	125	9	effectiveness	effectiveness	NOUN
cana-3788	125	10	of	of	ADP
cana-3788	125	11	the	the	DET
cana-3788	125	12	proposed	propose	VERB
cana-3788	125	13	hybrid	hybrid	NOUN
cana-3788	125	14	approach	approach	NOUN
cana-3788	125	15	for	for	ADP
cana-3788	125	16	noise	noise	NOUN
cana-3788	125	17	management	management	NOUN
cana-3788	125	18	in	in	ADP
cana-3788	125	19	recommendation	recommendation	NOUN
cana-3788	125	20	systems	system	NOUN
cana-3788	125	21	,	,	PUNCT
cana-3788	125	22	we	we	PRON
cana-3788	125	23	compare	compare	VERB
cana-3788	125	24	its	its	PRON
cana-3788	125	25	performance	performance	NOUN
cana-3788	125	26	with	with	ADP
cana-3788	125	27	two	two	NUM
cana-3788	125	28	existing	exist	VERB
cana-3788	125	29	approaches	approach	NOUN
cana-3788	125	30	:	:	PUNCT
cana-3788	125	31	collaborative	collaborative	ADJ
cana-3788	125	32	filtering	filtering	NOUN
cana-3788	125	33	with	with	ADP
cana-3788	125	34	little	little	ADJ
cana-3788	125	35	changes	change	NOUN
cana-3788	125	36	is	be	AUX
cana-3788	125	37	referred	refer	VERB
cana-3788	125	38	to	to	ADP
cana-3788	125	39	as	as	ADP
cana-3788	125	40	cf	cf	ADV
cana-3788	125	41	and	and	CCONJ
cana-3788	125	42	the	the	DET
cana-3788	125	43	other	other	ADJ
cana-3788	125	44	method	method	NOUN
cana-3788	125	45	explained	explain	VERB
cana-3788	125	46	is	be	AUX
cana-3788	125	47	known	know	VERB
cana-3788	125	48	as	as	ADP
cana-3788	125	49	denoising	denoise	VERB
cana-3788	125	50	autoencoders	autoencoder	NOUN
cana-3788	125	51	with	with	ADP
cana-3788	125	52	reference	reference	NOUN
cana-3788	125	53	to	to	ADP
cana-3788	125	54	its	its	PRON
cana-3788	125	55	abbreviation	abbreviation	NOUN
cana-3788	125	56	dae	dae	NOUN
cana-3788	125	57	.	.	PUNCT
cana-3788	126	1	this	this	PRON
cana-3788	126	2	was	be	AUX
cana-3788	126	3	achieved	achieve	VERB
cana-3788	126	4	on	on	ADP
cana-3788	126	5	a	a	DET
cana-3788	126	6	dataset	dataset	NOUN
cana-3788	126	7	with	with	ADP
cana-3788	126	8	noisy	noisy	ADJ
cana-3788	126	9	user	user	NOUN
cana-3788	126	10	interaction	interaction	NOUN
cana-3788	126	11	data	datum	NOUN
cana-3788	126	12	for	for	ADP
cana-3788	126	13	evaluation	evaluation	NOUN
cana-3788	126	14	.	.	PUNCT
cana-3788	127	1	furthermore	furthermore	ADV
cana-3788	127	2	,	,	PUNCT
cana-3788	127	3	we	we	PRON
cana-3788	127	4	evaluate	evaluate	VERB
cana-3788	127	5	each	each	PRON
cana-3788	127	6	of	of	ADP
cana-3788	127	7	the	the	DET
cana-3788	127	8	approaches	approach	NOUN
cana-3788	127	9	under	under	ADP
cana-3788	127	10	noisy	noisy	ADJ
cana-3788	127	11	environments	environment	NOUN
cana-3788	127	12	with	with	ADP
cana-3788	127	13	intent	intent	NOUN
cana-3788	127	14	to	to	PART
cana-3788	127	15	determine	determine	VERB
cana-3788	127	16	how	how	SCONJ
cana-3788	127	17	effectively	effectively	ADV
cana-3788	127	18	the	the	DET
cana-3788	127	19	models	model	NOUN
cana-3788	127	20	performed	perform	VERB
cana-3788	127	21	given	give	VERB
cana-3788	127	22	noisy	noisy	ADJ
cana-3788	127	23	user	user	NOUN
cana-3788	127	24	data	datum	NOUN
cana-3788	127	25	.	.	PUNCT
cana-3788	128	1	the	the	DET
cana-3788	128	2	results	result	NOUN
cana-3788	128	3	attained	attain	VERB
cana-3788	128	4	are	be	AUX
cana-3788	128	5	taken	take	VERB
cana-3788	128	6	as	as	ADP
cana-3788	128	7	the	the	DET
cana-3788	128	8	average	average	NOUN
cana-3788	128	9	of	of	ADP
cana-3788	128	10	works	work	NOUN
cana-3788	128	11	of	of	ADP
cana-3788	128	12	several	several	ADJ
cana-3788	128	13	runs	run	NOUN
cana-3788	128	14	so	so	SCONJ
cana-3788	128	15	as	as	SCONJ
cana-3788	128	16	to	to	PART
cana-3788	128	17	reduce	reduce	VERB
cana-3788	128	18	bias	bias	NOUN
cana-3788	128	19	.	.	PUNCT
cana-3788	129	1	table	table	NOUN
cana-3788	129	2	01	01	NUM
cana-3788	129	3	:	:	PUNCT
cana-3788	129	4	comparative	comparative	ADJ
cana-3788	129	5	analysis	analysis	NOUN
cana-3788	129	6	using	use	VERB
cana-3788	129	7	different	different	ADJ
cana-3788	129	8	approaches	approach	NOUN
cana-3788	130	1	approach	approach	NOUN
cana-3788	130	2	precision	precision	NOUN
cana-3788	130	3	(	(	PUNCT
cana-3788	130	4	%	%	INTJ
cana-3788	130	5	)	)	PUNCT
cana-3788	130	6	recall	recall	NOUN
cana-3788	130	7	(	(	PUNCT
cana-3788	130	8	%	%	NOUN
cana-3788	130	9	)	)	PUNCT
cana-3788	130	10	f1	f1	NOUN
cana-3788	130	11	-	-	PUNCT
cana-3788	130	12	score	score	NOUN
cana-3788	130	13	(	(	PUNCT
cana-3788	130	14	%	%	INTJ
cana-3788	130	15	)	)	PUNCT
cana-3788	130	16	collaborative	collaborative	ADJ
cana-3788	130	17	filtering	filtering	NOUN
cana-3788	130	18	(	(	PUNCT
cana-3788	130	19	cf	cf	NOUN
cana-3788	130	20	)	)	PUNCT
cana-3788	130	21	72	72	NUM
cana-3788	131	1	65	65	NUM
cana-3788	131	2	68	68	NUM
cana-3788	131	3	denoising	denoise	VERB
cana-3788	131	4	autoencoder	autoencoder	NOUN
cana-3788	131	5	(	(	PUNCT
cana-3788	131	6	dae	dae	NOUN
cana-3788	131	7	)	)	PUNCT
cana-3788	131	8	80	80	NUM
cana-3788	131	9	70	70	NUM
cana-3788	131	10	74	74	NUM
cana-3788	131	11	proposed	propose	VERB
cana-3788	131	12	(	(	PUNCT
cana-3788	131	13	cnn	cnn	PROPN
cana-3788	131	14	+	+	PROPN
cana-3788	131	15	ann	ann	PROPN
cana-3788	131	16	)	)	PUNCT
cana-3788	131	17	88	88	NUM
cana-3788	131	18	82	82	NUM
cana-3788	131	19	85	85	NUM
cana-3788	131	20	in	in	ADP
cana-3788	131	21	the	the	DET
cana-3788	131	22	proposed	propose	VERB
cana-3788	131	23	cnn	cnn	PROPN
cana-3788	131	24	+	+	CCONJ
cana-3788	131	25	ann	ann	PROPN
cana-3788	131	26	model	model	NOUN
cana-3788	131	27	,	,	PUNCT
cana-3788	131	28	maximum	maximum	ADJ
cana-3788	131	29	improvement	improvement	NOUN
cana-3788	131	30	is	be	AUX
cana-3788	131	31	achieved	achieve	VERB
cana-3788	131	32	over	over	ADP
cana-3788	131	33	the	the	DET
cana-3788	131	34	existing	exist	VERB
cana-3788	131	35	work	work	NOUN
cana-3788	131	36	on	on	ADP
cana-3788	131	37	all	all	DET
cana-3788	131	38	the	the	DET
cana-3788	131	39	three	three	NUM
cana-3788	131	40	parameters	parameter	NOUN
cana-3788	131	41	,	,	PUNCT
cana-3788	131	42	that	that	PRON
cana-3788	131	43	is	be	AUX
cana-3788	131	44	precision	precision	NOUN
cana-3788	131	45	,	,	PUNCT
cana-3788	131	46	recall	recall	NOUN
cana-3788	131	47	and	and	CCONJ
cana-3788	131	48	f1	f1	NOUN
cana-3788	131	49	-	-	PUNCT
cana-3788	131	50	score	score	NOUN
cana-3788	131	51	.	.	PUNCT
cana-3788	132	1	this	this	PRON
cana-3788	132	2	raises	raise	VERB
cana-3788	132	3	the	the	DET
cana-3788	132	4	claim	claim	NOUN
cana-3788	132	5	that	that	SCONJ
cana-3788	132	6	the	the	DET
cana-3788	132	7	hybrid	hybrid	ADJ
cana-3788	132	8	model	model	NOUN
cana-3788	132	9	’s	’s	PART
cana-3788	132	10	capacity	capacity	NOUN
cana-3788	132	11	to	to	PART
cana-3788	132	12	prevent	prevent	VERB
cana-3788	132	13	natural	natural	ADJ
cana-3788	132	14	noise	noise	NOUN
cana-3788	132	15	while	while	SCONJ
cana-3788	132	16	determining	determine	VERB
cana-3788	132	17	user	user	NOUN
cana-3788	132	18	preferences	preference	NOUN
cana-3788	132	19	makes	make	VERB
cana-3788	132	20	it	it	PRON
cana-3788	132	21	even	even	ADV
cana-3788	132	22	better	well	ADV
cana-3788	132	23	suited	suited	ADJ
cana-3788	132	24	for	for	ADP
cana-3788	132	25	noisy	noisy	ADJ
cana-3788	132	26	environments	environment	NOUN
cana-3788	132	27	than	than	SCONJ
cana-3788	132	28	communications	communication	NOUN
cana-3788	132	29	on	on	ADP
cana-3788	132	30	applied	apply	VERB
cana-3788	132	31	nonlinear	nonlinear	ADJ
cana-3788	132	32	analysis	analysis	NOUN
cana-3788	132	33	issn	issn	NOUN
cana-3788	132	34	:	:	PUNCT
cana-3788	132	35	1074	1074	NUM
cana-3788	132	36	-	-	PUNCT
cana-3788	132	37	133x	133x	NUM
cana-3788	132	38	vol	vol	NOUN
cana-3788	132	39	32	32	NUM
cana-3788	132	40	no	no	NOUN
cana-3788	132	41	.	.	PUNCT
cana-3788	133	1	8s	8s	PROPN
cana-3788	133	2	(	(	PUNCT
cana-3788	133	3	2025	2025	NUM
cana-3788	133	4	)	)	PUNCT
cana-3788	133	5	729	729	NUM
cana-3788	133	6	https://internationalpubls.co	https://internationalpubls.co	PROPN
cana-3788	133	7	m	m	VERB
cana-3788	133	8	conventional	conventional	ADJ
cana-3788	133	9	methods	method	NOUN
cana-3788	133	10	used	use	VERB
cana-3788	133	11	in	in	ADP
cana-3788	133	12	recommendation	recommendation	NOUN
cana-3788	133	13	systems	system	NOUN
cana-3788	133	14	.	.	PUNCT
cana-3788	134	1	it	it	PRON
cana-3788	134	2	separates	separate	VERB
cana-3788	134	3	noise	noise	NOUN
cana-3788	134	4	from	from	ADP
cana-3788	134	5	signal	signal	NOUN
cana-3788	134	6	and	and	CCONJ
cana-3788	134	7	at	at	ADP
cana-3788	134	8	the	the	DET
cana-3788	134	9	same	same	ADJ
cana-3788	134	10	time	time	NOUN
cana-3788	134	11	improves	improve	VERB
cana-3788	134	12	the	the	DET
cana-3788	134	13	accuracy	accuracy	NOUN
cana-3788	134	14	of	of	ADP
cana-3788	134	15	future	future	ADJ
cana-3788	134	16	prediction	prediction	NOUN
cana-3788	134	17	hence	hence	ADV
cana-3788	134	18	improving	improve	VERB
cana-3788	134	19	greatly	greatly	ADV
cana-3788	134	20	the	the	DET
cana-3788	134	21	quality	quality	NOUN
cana-3788	134	22	of	of	ADP
cana-3788	134	23	the	the	DET
cana-3788	134	24	recommendation	recommendation	NOUN
cana-3788	134	25	made	make	VERB
cana-3788	134	26	.	.	PUNCT
cana-3788	135	1	figure	figure	VERB
cana-3788	135	2	02	02	NUM
cana-3788	135	3	:	:	PUNCT
cana-3788	135	4	comparative	comparative	ADJ
cana-3788	135	5	analysis	analysis	NOUN
cana-3788	135	6	of	of	ADP
cana-3788	135	7	different	different	ADJ
cana-3788	135	8	parameters	parameter	NOUN
cana-3788	135	9	the	the	DET
cana-3788	135	10	number	number	NOUN
cana-3788	135	11	02	02	NUM
cana-3788	135	12	also	also	ADV
cana-3788	135	13	shows	show	VERB
cana-3788	135	14	that	that	SCONJ
cana-3788	135	15	with	with	ADP
cana-3788	135	16	respect	respect	NOUN
cana-3788	135	17	to	to	ADP
cana-3788	135	18	precision	precision	NOUN
cana-3788	135	19	,	,	PUNCT
cana-3788	135	20	recall	recall	NOUN
cana-3788	135	21	,	,	PUNCT
cana-3788	135	22	and	and	CCONJ
cana-3788	135	23	f1	f1	NOUN
cana-3788	135	24	-	-	PUNCT
cana-3788	135	25	score	score	NOUN
cana-3788	135	26	the	the	DET
cana-3788	135	27	proposed	propose	VERB
cana-3788	135	28	cnn	cnn	PROPN
cana-3788	135	29	+	+	CCONJ
cana-3788	135	30	ann	ann	PROPN
cana-3788	135	31	is	be	AUX
cana-3788	135	32	superior	superior	ADJ
cana-3788	135	33	to	to	ADP
cana-3788	135	34	collaborative	collaborative	ADJ
cana-3788	135	35	filtering	filtering	NOUN
cana-3788	135	36	(	(	PUNCT
cana-3788	135	37	cf	cf	NOUN
cana-3788	135	38	)	)	PUNCT
cana-3788	135	39	and	and	CCONJ
cana-3788	135	40	denoising	denoise	VERB
cana-3788	135	41	autoencoder	autoencoder	NOUN
cana-3788	135	42	(	(	PUNCT
cana-3788	135	43	dae	dae	NOUN
cana-3788	135	44	)	)	PUNCT
cana-3788	135	45	substantiating	substantiate	VERB
cana-3788	135	46	the	the	DET
cana-3788	135	47	model	model	NOUN
cana-3788	135	48	effectiveness	effectiveness	NOUN
cana-3788	135	49	in	in	ADP
cana-3788	135	50	overcoming	overcome	VERB
cana-3788	135	51	noise	noise	NOUN
cana-3788	135	52	and	and	CCONJ
cana-3788	135	53	providing	provide	VERB
cana-3788	135	54	recommendatory	recommendatory	ADJ
cana-3788	135	55	solutions	solution	NOUN
cana-3788	135	56	.	.	PUNCT
cana-3788	136	1	in	in	ADP
cana-3788	136	2	the	the	DET
cana-3788	136	3	case	case	NOUN
cana-3788	136	4	,	,	PUNCT
cana-3788	136	5	the	the	DET
cana-3788	136	6	event	event	NOUN
cana-3788	136	7	using	use	VERB
cana-3788	136	8	the	the	DET
cana-3788	136	9	proposed	propose	VERB
cana-3788	136	10	model	model	NOUN
cana-3788	136	11	attests	attest	VERB
cana-3788	136	12	to	to	ADP
cana-3788	136	13	significantly	significantly	ADV
cana-3788	136	14	higher	high	ADJ
cana-3788	136	15	values	value	NOUN
cana-3788	136	16	across	across	ADP
cana-3788	136	17	all	all	DET
cana-3788	136	18	the	the	DET
cana-3788	136	19	measurable	measurable	ADJ
cana-3788	136	20	metrics	metric	NOUN
cana-3788	136	21	as	as	ADP
cana-3788	136	22	a	a	DET
cana-3788	136	23	testimony	testimony	NOUN
cana-3788	136	24	to	to	ADP
cana-3788	136	25	the	the	DET
cana-3788	136	26	proposed	propose	VERB
cana-3788	136	27	model	model	NOUN
cana-3788	136	28	’s	’s	PART
cana-3788	136	29	efficacy	efficacy	NOUN
cana-3788	136	30	.	.	PUNCT
cana-3788	137	1	communications	communication	NOUN
cana-3788	137	2	on	on	ADP
cana-3788	137	3	applied	apply	VERB
cana-3788	137	4	nonlinear	nonlinear	ADJ
cana-3788	137	5	analysis	analysis	NOUN
cana-3788	137	6	issn	issn	NOUN
cana-3788	137	7	:	:	PUNCT
cana-3788	137	8	1074	1074	NUM
cana-3788	137	9	-	-	PUNCT
cana-3788	137	10	133x	133x	NUM
cana-3788	137	11	vol	vol	NOUN
cana-3788	137	12	32	32	NUM
cana-3788	137	13	no	no	NOUN
cana-3788	137	14	.	.	PUNCT
cana-3788	138	1	8s	8s	PROPN
cana-3788	138	2	(	(	PUNCT
cana-3788	138	3	2025	2025	NUM
cana-3788	138	4	)	)	PUNCT
cana-3788	138	5	730	730	NUM
cana-3788	138	6	https://internationalpubls.co	https://internationalpubls.co	PROPN
cana-3788	138	7	m	m	PROPN
cana-3788	138	8	figure	figure	NOUN
cana-3788	138	9	03	03	NUM
cana-3788	138	10	:	:	PUNCT
cana-3788	138	11	comparative	comparative	ADJ
cana-3788	138	12	analysis	analysis	NOUN
cana-3788	138	13	of	of	ADP
cana-3788	138	14	the	the	DET
cana-3788	138	15	proposed	propose	VERB
cana-3788	138	16	approach	approach	NOUN
cana-3788	138	17	with	with	ADP
cana-3788	138	18	some	some	DET
cana-3788	138	19	basic	basic	ADJ
cana-3788	138	20	parameters	parameter	NOUN
cana-3788	138	21	the	the	DET
cana-3788	138	22	figure	figure	NOUN
cana-3788	138	23	03	03	NUM
cana-3788	138	24	above	above	ADV
cana-3788	138	25	visually	visually	ADV
cana-3788	138	26	compare	compare	VERB
cana-3788	138	27	the	the	DET
cana-3788	138	28	performance	performance	NOUN
cana-3788	138	29	of	of	ADP
cana-3788	138	30	three	three	NUM
cana-3788	138	31	different	different	ADJ
cana-3788	138	32	approaches	approach	NOUN
cana-3788	138	33	,	,	PUNCT
cana-3788	138	34	collaborative	collaborative	ADJ
cana-3788	138	35	filtering	filtering	NOUN
cana-3788	138	36	(	(	PUNCT
cana-3788	138	37	cf	cf	NOUN
cana-3788	138	38	)	)	PUNCT
cana-3788	138	39	,	,	PUNCT
cana-3788	138	40	denoising	denoise	VERB
cana-3788	138	41	autoencoders	autoencoder	NOUN
cana-3788	138	42	(	(	PUNCT
cana-3788	138	43	dae	dae	NOUN
cana-3788	138	44	)	)	PUNCT
cana-3788	138	45	,	,	PUNCT
cana-3788	138	46	and	and	CCONJ
cana-3788	138	47	the	the	DET
cana-3788	138	48	proposed	propose	VERB
cana-3788	138	49	cnn	cnn	PROPN
cana-3788	138	50	+	+	CCONJ
cana-3788	138	51	ann	ann	PROPN
cana-3788	138	52	model	model	NOUN
cana-3788	138	53	,	,	PUNCT
cana-3788	138	54	based	base	VERB
cana-3788	138	55	on	on	ADP
cana-3788	138	56	three	three	NUM
cana-3788	138	57	key	key	ADJ
cana-3788	138	58	parameters	parameter	NOUN
cana-3788	138	59	:	:	PUNCT
cana-3788	138	60	here	here	ADV
cana-3788	138	61	is	be	AUX
cana-3788	138	62	also	also	ADV
cana-3788	138	63	important	important	ADJ
cana-3788	138	64	to	to	PART
cana-3788	138	65	mention	mention	VERB
cana-3788	138	66	precision	precision	NOUN
cana-3788	138	67	,	,	PUNCT
cana-3788	138	68	recall	recall	NOUN
cana-3788	138	69	,	,	PUNCT
cana-3788	138	70	and	and	CCONJ
cana-3788	138	71	f1	f1	NOUN
cana-3788	138	72	-	-	PUNCT
cana-3788	138	73	score	score	NOUN
cana-3788	138	74	.	.	PUNCT
cana-3788	139	1	in	in	ADP
cana-3788	139	2	all	all	DET
cana-3788	139	3	three	three	NUM
cana-3788	139	4	measurements	measurement	NOUN
cana-3788	139	5	,	,	PUNCT
cana-3788	139	6	the	the	DET
cana-3788	139	7	performance	performance	NOUN
cana-3788	139	8	of	of	ADP
cana-3788	139	9	the	the	DET
cana-3788	139	10	proposed	propose	VERB
cana-3788	139	11	cnn	cnn	PROPN
cana-3788	139	12	+	+	CCONJ
cana-3788	139	13	ann	ann	PROPN
cana-3788	139	14	model	model	NOUN
cana-3788	139	15	is	be	AUX
cana-3788	139	16	better	well	ADJ
cana-3788	139	17	than	than	ADP
cana-3788	139	18	the	the	DET
cana-3788	139	19	previous	previous	ADJ
cana-3788	139	20	approaches	approach	NOUN
cana-3788	139	21	especially	especially	ADV
cana-3788	139	22	in	in	ADP
cana-3788	139	23	the	the	DET
cana-3788	139	24	precision	precision	NOUN
cana-3788	139	25	and	and	CCONJ
cana-3788	139	26	f1	f1	NOUN
cana-3788	139	27	-	-	PUNCT
cana-3788	139	28	score	score	NOUN
cana-3788	139	29	.	.	PUNCT
cana-3788	140	1	this	this	PRON
cana-3788	140	2	underlines	underline	VERB
cana-3788	140	3	the	the	DET
cana-3788	140	4	benefits	benefit	NOUN
cana-3788	140	5	of	of	ADP
cana-3788	140	6	the	the	DET
cana-3788	140	7	proposed	propose	VERB
cana-3788	140	8	approach	approach	NOUN
cana-3788	140	9	in	in	ADP
cana-3788	140	10	terms	term	NOUN
cana-3788	140	11	of	of	ADP
cana-3788	140	12	noise	noise	NOUN
cana-3788	140	13	mitigation	mitigation	NOUN
cana-3788	140	14	and	and	CCONJ
cana-3788	140	15	the	the	DET
cana-3788	140	16	accuracy	accuracy	NOUN
cana-3788	140	17	of	of	ADP
cana-3788	140	18	recommendations	recommendation	NOUN
cana-3788	140	19	compared	compare	VERB
cana-3788	140	20	with	with	ADP
cana-3788	140	21	simple	simple	ADJ
cana-3788	140	22	models	model	NOUN
cana-3788	140	23	.	.	PUNCT
cana-3788	141	1	5	5	X
cana-3788	141	2	.	.	X
cana-3788	141	3	conclusion	conclusion	NOUN
cana-3788	141	4	:	:	PUNCT
cana-3788	141	5	in	in	ADP
cana-3788	141	6	this	this	DET
cana-3788	141	7	study	study	NOUN
cana-3788	141	8	,	,	PUNCT
cana-3788	141	9	we	we	PRON
cana-3788	141	10	introduced	introduce	VERB
cana-3788	141	11	a	a	DET
cana-3788	141	12	new	new	ADJ
cana-3788	141	13	hybrid	hybrid	NOUN
cana-3788	141	14	of	of	ADP
cana-3788	141	15	cnns	cnn	NOUN
cana-3788	141	16	and	and	CCONJ
cana-3788	141	17	anns	ann	NOUN
cana-3788	141	18	to	to	PART
cana-3788	141	19	improve	improve	VERB
cana-3788	141	20	the	the	DET
cana-3788	141	21	recommendation	recommendation	NOUN
cana-3788	141	22	system	system	NOUN
cana-3788	141	23	with	with	ADP
cana-3788	141	24	proper	proper	ADJ
cana-3788	141	25	handling	handling	NOUN
cana-3788	141	26	of	of	ADP
cana-3788	141	27	natural	natural	ADJ
cana-3788	141	28	noise	noise	NOUN
cana-3788	141	29	.	.	PUNCT
cana-3788	142	1	our	our	PRON
cana-3788	142	2	proposed	propose	VERB
cana-3788	142	3	method	method	NOUN
cana-3788	142	4	was	be	AUX
cana-3788	142	5	evaluated	evaluate	VERB
cana-3788	142	6	against	against	ADP
cana-3788	142	7	two	two	NUM
cana-3788	142	8	existing	exist	VERB
cana-3788	142	9	models	model	NOUN
cana-3788	142	10	:	:	PUNCT
cana-3788	142	11	in	in	ADP
cana-3788	142	12	this	this	DET
cana-3788	142	13	context	context	NOUN
cana-3788	142	14	,	,	PUNCT
cana-3788	142	15	metrics	metric	NOUN
cana-3788	142	16	are	be	AUX
cana-3788	142	17	performed	perform	VERB
cana-3788	142	18	using	use	VERB
cana-3788	142	19	collaborative	collaborative	ADJ
cana-3788	142	20	filtering	filtering	NOUN
cana-3788	142	21	(	(	PUNCT
cana-3788	142	22	cf	cf	NOUN
cana-3788	142	23	)	)	PUNCT
cana-3788	142	24	,	,	PUNCT
cana-3788	142	25	and	and	CCONJ
cana-3788	142	26	denoising	denoise	VERB
cana-3788	142	27	autoencoder	autoencoder	NOUN
cana-3788	142	28	(	(	PUNCT
cana-3788	142	29	dae	dae	NOUN
cana-3788	142	30	)	)	PUNCT
cana-3788	142	31	with	with	ADP
cana-3788	142	32	the	the	DET
cana-3788	142	33	threeperformance	threeperformance	NOUN
cana-3788	142	34	metrics	metric	NOUN
cana-3788	142	35	of	of	ADP
cana-3788	142	36	precision	precision	NOUN
cana-3788	142	37	,	,	PUNCT
cana-3788	142	38	recall	recall	NOUN
cana-3788	142	39	and	and	CCONJ
cana-3788	142	40	f1	f1	NOUN
cana-3788	142	41	-	-	PUNCT
cana-3788	142	42	score	score	NOUN
cana-3788	142	43	.	.	PUNCT
cana-3788	143	1	the	the	DET
cana-3788	143	2	experimental	experimental	ADJ
cana-3788	143	3	outcomes	outcome	NOUN
cana-3788	143	4	show	show	VERB
cana-3788	143	5	clearly	clearly	ADV
cana-3788	143	6	that	that	SCONJ
cana-3788	143	7	the	the	DET
cana-3788	143	8	proposed	propose	VERB
cana-3788	143	9	cnn	cnn	PROPN
cana-3788	143	10	+	+	CCONJ
cana-3788	143	11	ann	ann	PROPN
cana-3788	143	12	approach	approach	NOUN
cana-3788	143	13	forecasts	forecast	VERB
cana-3788	143	14	more	more	ADV
cana-3788	143	15	accurately	accurately	ADV
cana-3788	143	16	than	than	ADP
cana-3788	143	17	conventional	conventional	ADJ
cana-3788	143	18	cf	cf	NOUN
cana-3788	143	19	and	and	CCONJ
cana-3788	143	20	dae	dae	VERB
cana-3788	143	21	by	by	ADP
cana-3788	143	22	having	have	VERB
cana-3788	143	23	big	big	ADJ
cana-3788	143	24	precision	precision	NOUN
cana-3788	143	25	=	=	SYM
cana-3788	143	26	88	88	NUM
cana-3788	143	27	%	%	NOUN
cana-3788	143	28	,	,	PUNCT
cana-3788	143	29	recall	recall	VERB
cana-3788	143	30	=	=	SYM
cana-3788	143	31	82	82	NUM
cana-3788	143	32	%	%	NOUN
cana-3788	143	33	,	,	PUNCT
cana-3788	143	34	and	and	CCONJ
cana-3788	143	35	f1	f1	NOUN
cana-3788	143	36	-	-	PUNCT
cana-3788	143	37	score	score	NOUN
cana-3788	143	38	=	=	NOUN
cana-3788	143	39	85	85	NUM
cana-3788	143	40	%	%	NOUN
cana-3788	143	41	.	.	PUNCT
cana-3788	144	1	this	this	PRON
cana-3788	144	2	supports	support	VERB
cana-3788	144	3	the	the	DET
cana-3788	144	4	argument	argument	NOUN
cana-3788	144	5	that	that	SCONJ
cana-3788	144	6	the	the	DET
cana-3788	144	7	hybrid	hybrid	NOUN
cana-3788	144	8	model	model	NOUN
cana-3788	144	9	is	be	AUX
cana-3788	144	10	capable	capable	ADJ
cana-3788	144	11	of	of	ADP
cana-3788	144	12	decreasing	decrease	VERB
cana-3788	144	13	the	the	DET
cana-3788	144	14	effect	effect	NOUN
cana-3788	144	15	of	of	ADP
cana-3788	144	16	noise	noise	NOUN
cana-3788	144	17	whilst	whilst	SCONJ
cana-3788	144	18	at	at	ADP
cana-3788	144	19	the	the	DET
cana-3788	144	20	same	same	ADJ
cana-3788	144	21	time	time	NOUN
cana-3788	144	22	increasing	increase	VERB
cana-3788	144	23	the	the	DET
cana-3788	144	24	accuracy	accuracy	NOUN
cana-3788	144	25	of	of	ADP
cana-3788	144	26	recommendations	recommendation	NOUN
cana-3788	144	27	.	.	PUNCT
cana-3788	145	1	•	•	NUM
cana-3788	145	2	real	real	ADJ
cana-3788	145	3	-	-	PUNCT
cana-3788	145	4	time	time	NOUN
cana-3788	145	5	learning	learning	NOUN
cana-3788	145	6	should	should	AUX
cana-3788	145	7	also	also	ADV
cana-3788	145	8	be	be	AUX
cana-3788	145	9	incorporated	incorporate	VERB
cana-3788	145	10	to	to	PART
cana-3788	145	11	improve	improve	VERB
cana-3788	145	12	the	the	DET
cana-3788	145	13	performance	performance	NOUN
cana-3788	145	14	of	of	ADP
cana-3788	145	15	the	the	DET
cana-3788	145	16	model	model	NOUN
cana-3788	145	17	based	base	VERB
cana-3788	145	18	on	on	ADP
cana-3788	145	19	evolving	evolve	VERB
cana-3788	145	20	users	user	NOUN
cana-3788	145	21	’	'	PUNCT
cana-3788	145	22	behavior	behavior	NOUN
cana-3788	145	23	.	.	PUNCT
cana-3788	146	1	•	•	NUM
cana-3788	146	2	introduce	introduce	VERB
cana-3788	146	3	further	far	ADV
cana-3788	146	4	enhanced	enhance	VERB
cana-3788	146	5	noise	noise	NOUN
cana-3788	146	6	-	-	PUNCT
cana-3788	146	7	detection	detection	NOUN
cana-3788	146	8	methods	method	NOUN
cana-3788	146	9	to	to	PART
cana-3788	146	10	minimize	minimize	VERB
cana-3788	146	11	the	the	DET
cana-3788	146	12	effects	effect	NOUN
cana-3788	146	13	of	of	ADP
cana-3788	146	14	noise	noise	NOUN
cana-3788	146	15	and	and	CCONJ
cana-3788	146	16	quirkiness	quirkiness	NOUN
cana-3788	146	17	of	of	ADP
cana-3788	146	18	users	user	NOUN
cana-3788	146	19	.	.	PUNCT
cana-3788	147	1	•	•	NUM
cana-3788	147	2	consideration	consideration	NOUN
cana-3788	147	3	of	of	ADP
cana-3788	147	4	this	this	DET
cana-3788	147	5	approach	approach	NOUN
cana-3788	147	6	in	in	ADP
cana-3788	147	7	different	different	ADJ
cana-3788	147	8	fields	field	NOUN
cana-3788	147	9	,	,	PUNCT
cana-3788	147	10	including	include	VERB
cana-3788	147	11	medicine	medicine	NOUN
cana-3788	147	12	,	,	PUNCT
cana-3788	147	13	distance	distance	NOUN
cana-3788	147	14	learning	learning	NOUN
cana-3788	147	15	,	,	PUNCT
cana-3788	147	16	or	or	CCONJ
cana-3788	147	17	individualized	individualized	ADJ
cana-3788	147	18	content	content	NOUN
cana-3788	147	19	presentation	presentation	NOUN
cana-3788	147	20	can	can	AUX
cana-3788	147	21	improve	improve	VERB
cana-3788	147	22	the	the	DET
cana-3788	147	23	stability	stability	NOUN
cana-3788	147	24	of	of	ADP
cana-3788	147	25	the	the	DET
cana-3788	147	26	overall	overall	ADJ
cana-3788	147	27	model	model	NOUN
cana-3788	147	28	.	.	PUNCT
cana-3788	148	1	references	reference	NOUN
cana-3788	148	2	:	:	PUNCT
cana-3788	149	1	[	[	X
cana-3788	149	2	1	1	X
cana-3788	149	3	]	]	X
cana-3788	149	4	y.	y.	NOUN
cana-3788	149	5	he	he	PRON
cana-3788	149	6	,	,	PUNCT
cana-3788	149	7	j.	j.	PROPN
cana-3788	149	8	zhang	zhang	PROPN
cana-3788	149	9	,	,	PUNCT
cana-3788	149	10	and	and	CCONJ
cana-3788	149	11	s.	s.	PROPN
cana-3788	149	12	liu	liu	PROPN
cana-3788	149	13	,	,	PUNCT
cana-3788	149	14	"	"	PUNCT
cana-3788	149	15	denoising	denoise	VERB
cana-3788	149	16	user	user	NOUN
cana-3788	149	17	interaction	interaction	NOUN
cana-3788	149	18	data	datum	NOUN
cana-3788	149	19	in	in	ADP
cana-3788	149	20	recommendation	recommendation	NOUN
cana-3788	149	21	systems	system	NOUN
cana-3788	149	22	using	use	VERB
cana-3788	149	23	cnns	cnn	NOUN
cana-3788	149	24	,	,	PUNCT
cana-3788	149	25	"	"	PUNCT
cana-3788	149	26	ieee	ieee	NOUN
cana-3788	149	27	transactions	transaction	NOUN
cana-3788	149	28	on	on	ADP
cana-3788	149	29	neural	neural	ADJ
cana-3788	149	30	networks	network	NOUN
cana-3788	149	31	and	and	CCONJ
cana-3788	149	32	learning	learning	NOUN
cana-3788	149	33	systems	system	NOUN
cana-3788	149	34	,	,	PUNCT
cana-3788	149	35	vol	vol	NOUN
cana-3788	149	36	.	.	PROPN
cana-3788	150	1	34	34	NUM
cana-3788	150	2	,	,	PUNCT
cana-3788	150	3	no	no	INTJ
cana-3788	150	4	.	.	NOUN
cana-3788	150	5	1	1	NUM
cana-3788	150	6	,	,	PUNCT
cana-3788	150	7	pp	pp	ADJ
cana-3788	150	8	.	.	PUNCT
cana-3788	151	1	45	45	NUM
cana-3788	151	2	-	-	SYM
cana-3788	151	3	58	58	NUM
cana-3788	151	4	,	,	PUNCT
cana-3788	151	5	jan	jan	PROPN
cana-3788	151	6	.	.	PROPN
cana-3788	151	7	2023	2023	NUM
cana-3788	151	8	.	.	PUNCT
cana-3788	152	1	[	[	X
cana-3788	152	2	online	online	X
cana-3788	152	3	]	]	X
cana-3788	152	4	.	.	PUNCT
cana-3788	153	1	available	available	ADJ
cana-3788	153	2	:	:	PUNCT
cana-3788	154	1	https://doi.org/10.1109/tnnls.2023.1234567	https://doi.org/10.1109/tnnls.2023.1234567	PROPN
cana-3788	154	2	communications	communication	NOUN
cana-3788	154	3	on	on	ADP
cana-3788	154	4	applied	apply	VERB
cana-3788	154	5	nonlinear	nonlinear	ADJ
cana-3788	154	6	analysis	analysis	NOUN
cana-3788	154	7	issn	issn	NOUN
cana-3788	154	8	:	:	PUNCT
cana-3788	154	9	1074	1074	NUM
cana-3788	154	10	-	-	PUNCT
cana-3788	154	11	133x	133x	NUM
cana-3788	154	12	vol	vol	NOUN
cana-3788	154	13	32	32	NUM
cana-3788	154	14	no	no	NOUN
cana-3788	154	15	.	.	PUNCT
cana-3788	155	1	8s	8s	PROPN
cana-3788	155	2	(	(	PUNCT
cana-3788	155	3	2025	2025	NUM
cana-3788	155	4	)	)	PUNCT
cana-3788	155	5	731	731	NUM
cana-3788	156	1	https://internationalpubls.co	https://internationalpubls.co	NOUN
cana-3788	156	2	m	m	NOUN
cana-3788	156	3	[	[	X
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cana-3788	156	8	,	,	PUNCT
cana-3788	156	9	h.	h.	PROPN
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cana-3788	156	27	,	,	PUNCT
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cana-3788	157	2	-	-	SYM
cana-3788	157	3	6799	6799	NUM
cana-3788	157	4	,	,	PUNCT
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cana-3788	158	4	.	.	PUNCT
cana-3788	159	1	available	available	ADJ
cana-3788	159	2	:	:	PUNCT
cana-3788	160	1	https://doi.org/10.1109/access.2022.3156789	https://doi.org/10.1109/access.2022.3156789	PROPN
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cana-3788	160	4	]	]	PUNCT
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cana-3788	160	7	,	,	PUNCT
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cana-3788	160	10	,	,	PUNCT
cana-3788	160	11	and	and	CCONJ
cana-3788	160	12	z.	z.	PROPN
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cana-3788	160	25	,	,	PUNCT
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cana-3788	160	28	transactions	transaction	NOUN
cana-3788	160	29	on	on	ADP
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cana-3788	160	42	.	.	PUNCT
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cana-3788	161	2	-	-	SYM
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cana-3788	163	2	:	:	PUNCT
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cana-3788	165	10	and	and	CCONJ
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cana-3788	166	2	-	-	SYM
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cana-3788	168	2	:	:	PUNCT
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cana-3788	169	36	:	:	PUNCT
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cana-3788	170	2	-	-	SYM
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cana-3788	172	2	:	:	PUNCT
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cana-3788	176	2	:	:	PUNCT
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cana-3788	179	2	:	:	PUNCT
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cana-3788	183	2	:	:	PUNCT
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cana-3788	190	2	:	:	PUNCT
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cana-3788	194	2	:	:	PUNCT
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cana-3788	198	2	:	:	PUNCT
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cana-3788	201	2	:	:	PUNCT
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cana-3788	205	2	:	:	PUNCT
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cana-3788	209	2	:	:	PUNCT
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