id	sid	tid	token	lemma	pos
fcis-11135	1	1	frontiers	frontier	NOUN
fcis-11135	1	2	in	in	ADP
fcis-11135	1	3	computing	computing	NOUN
fcis-11135	1	4	and	and	CCONJ
fcis-11135	1	5	intelligent	intelligent	ADJ
fcis-11135	1	6	systems	system	NOUN
fcis-11135	1	7	issn	issn	VERB
fcis-11135	1	8	:	:	PUNCT
fcis-11135	1	9	2832	2832	NUM
fcis-11135	1	10	-	-	SYM
fcis-11135	1	11	6024	6024	NUM
fcis-11135	1	12	|	|	NOUN
fcis-11135	1	13	vol	vol	NOUN
fcis-11135	1	14	.	.	PROPN
fcis-11135	2	1	4	4	NUM
fcis-11135	2	2	,	,	PUNCT
fcis-11135	2	3	no	no	INTJ
fcis-11135	2	4	.	.	NOUN
fcis-11135	2	5	3	3	NUM
fcis-11135	2	6	,	,	PUNCT
fcis-11135	2	7	2023	2023	NUM
fcis-11135	2	8	62	62	NUM
fcis-11135	2	9	design	design	NOUN
fcis-11135	2	10	and	and	CCONJ
fcis-11135	2	11	implementation	implementation	NOUN
fcis-11135	2	12	of	of	ADP
fcis-11135	2	13	a	a	DET
fcis-11135	2	14	learning	learn	VERB
fcis-11135	2	15	resource	resource	NOUN
fcis-11135	2	16	recommendation	recommendation	NOUN
fcis-11135	2	17	system	system	NOUN
fcis-11135	2	18	based	base	VERB
fcis-11135	2	19	on	on	ADP
fcis-11135	2	20	user	user	NOUN
fcis-11135	2	21	habits	habit	NOUN
fcis-11135	2	22	based	base	VERB
fcis-11135	2	23	on	on	ADP
fcis-11135	2	24	gnn	gnn	PROPN
fcis-11135	2	25	jingxuan	jingxuan	PROPN
fcis-11135	2	26	lu	lu	PROPN
fcis-11135	2	27	1	1	NUM
fcis-11135	2	28	,	,	PUNCT
fcis-11135	2	29	a	a	DET
fcis-11135	2	30	,	,	PUNCT
fcis-11135	2	31	yangkwon	yangkwon	PROPN
fcis-11135	2	32	jeong	jeong	PROPN
fcis-11135	2	33	1	1	NUM
fcis-11135	2	34	,	,	PUNCT
fcis-11135	2	35	b	b	NOUN
fcis-11135	2	36	,	,	PUNCT
fcis-11135	2	37	*	*	PROPN
fcis-11135	2	38	,	,	PUNCT
fcis-11135	2	39	jiaqi	jiaqi	PROPN
fcis-11135	2	40	xue	xue	PROPN
fcis-11135	2	41	2	2	NUM
fcis-11135	2	42	,	,	PUNCT
fcis-11135	2	43	c	c	NOUN
fcis-11135	2	44	1	1	NUM
fcis-11135	2	45	computer	computer	NOUN
fcis-11135	2	46	science	science	NOUN
fcis-11135	2	47	,	,	PUNCT
fcis-11135	2	48	dongshin	dongshin	ADJ
fcis-11135	2	49	university	university	NOUN
fcis-11135	2	50	,	,	PUNCT
fcis-11135	2	51	naju	naju	PROPN
fcis-11135	2	52	,	,	PUNCT
fcis-11135	2	53	korea	korea	PROPN
fcis-11135	2	54	2	2	NUM
fcis-11135	2	55	computer	computer	NOUN
fcis-11135	2	56	science	science	NOUN
fcis-11135	2	57	,	,	PUNCT
fcis-11135	2	58	beihua	beihua	PROPN
fcis-11135	2	59	university	university	PROPN
fcis-11135	2	60	,	,	PUNCT
fcis-11135	2	61	jilin	jilin	PROPN
fcis-11135	2	62	,	,	PUNCT
fcis-11135	2	63	china	china	PROPN
fcis-11135	2	64	a	a	DET
fcis-11135	2	65	bh_ljx@163.com	bh_ljx@163.com	PROPN
fcis-11135	2	66	,	,	PUNCT
fcis-11135	2	67	b	b	NOUN
fcis-11135	2	68	,	,	PUNCT
fcis-11135	2	69	*	*	VERB
fcis-11135	2	70	81262657@qq.com	81262657@qq.com	NUM
fcis-11135	2	71	,	,	PUNCT
fcis-11135	2	72	c	c	X
fcis-11135	2	73	2466879100@qq.com	2466879100@qq.com	NUM
fcis-11135	2	74	*	*	PUNCT
fcis-11135	2	75	corresponding	correspond	VERB
fcis-11135	2	76	author	author	NOUN
fcis-11135	2	77	:	:	PUNCT
fcis-11135	2	78	yangkwon	yangkwon	PROPN
fcis-11135	2	79	jeong	jeong	PROPN
fcis-11135	2	80	(	(	PUNCT
fcis-11135	2	81	email	email	NOUN
fcis-11135	2	82	:	:	PUNCT
fcis-11135	2	83	81262657@qq.com	81262657@qq.com	NUM
fcis-11135	2	84	)	)	PUNCT
fcis-11135	2	85	abstract	abstract	NOUN
fcis-11135	2	86	:	:	PUNCT
fcis-11135	2	87	this	this	DET
fcis-11135	2	88	project	project	NOUN
fcis-11135	2	89	aims	aim	VERB
fcis-11135	2	90	to	to	PART
fcis-11135	2	91	design	design	VERB
fcis-11135	2	92	and	and	CCONJ
fcis-11135	2	93	implement	implement	VERB
fcis-11135	2	94	a	a	DET
fcis-11135	2	95	learning	learn	VERB
fcis-11135	2	96	resource	resource	NOUN
fcis-11135	2	97	recommendation	recommendation	NOUN
fcis-11135	2	98	system	system	NOUN
fcis-11135	2	99	based	base	VERB
fcis-11135	2	100	on	on	ADP
fcis-11135	2	101	graph	graph	NOUN
fcis-11135	2	102	neural	neural	ADJ
fcis-11135	2	103	networks	network	NOUN
fcis-11135	2	104	(	(	PUNCT
fcis-11135	2	105	gnn	gnn	PROPN
fcis-11135	2	106	)	)	PUNCT
fcis-11135	2	107	.	.	PUNCT
fcis-11135	3	1	the	the	DET
fcis-11135	3	2	system	system	NOUN
fcis-11135	3	3	utilizes	utilize	VERB
fcis-11135	3	4	user	user	NOUN
fcis-11135	3	5	learning	learning	NOUN
fcis-11135	3	6	habits	habit	NOUN
fcis-11135	3	7	as	as	ADP
fcis-11135	3	8	a	a	DET
fcis-11135	3	9	foundation	foundation	NOUN
fcis-11135	3	10	to	to	PART
fcis-11135	3	11	provide	provide	VERB
fcis-11135	3	12	personalized	personalized	ADJ
fcis-11135	3	13	learning	learn	VERB
fcis-11135	3	14	resource	resource	NOUN
fcis-11135	3	15	recommendations	recommendation	NOUN
fcis-11135	3	16	.	.	PUNCT
fcis-11135	4	1	by	by	ADP
fcis-11135	4	2	collecting	collect	VERB
fcis-11135	4	3	and	and	CCONJ
fcis-11135	4	4	preprocessing	preprocesse	VERB
fcis-11135	4	5	user	user	NOUN
fcis-11135	4	6	learning	learn	VERB
fcis-11135	4	7	history	history	NOUN
fcis-11135	4	8	data	datum	NOUN
fcis-11135	4	9	,	,	PUNCT
fcis-11135	4	10	and	and	CCONJ
fcis-11135	4	11	constructing	construct	VERB
fcis-11135	4	12	a	a	DET
fcis-11135	4	13	user	user	NOUN
fcis-11135	4	14	-	-	PUNCT
fcis-11135	4	15	resource	resource	NOUN
fcis-11135	4	16	relationship	relationship	NOUN
fcis-11135	4	17	graph	graph	NOUN
fcis-11135	4	18	,	,	PUNCT
fcis-11135	4	19	the	the	DET
fcis-11135	4	20	gnn	gnn	PROPN
fcis-11135	4	21	model	model	NOUN
fcis-11135	4	22	is	be	AUX
fcis-11135	4	23	used	use	VERB
fcis-11135	4	24	to	to	PART
fcis-11135	4	25	learn	learn	VERB
fcis-11135	4	26	the	the	DET
fcis-11135	4	27	representation	representation	NOUN
fcis-11135	4	28	vectors	vector	NOUN
fcis-11135	4	29	of	of	ADP
fcis-11135	4	30	users	user	NOUN
fcis-11135	4	31	and	and	CCONJ
fcis-11135	4	32	resources	resource	NOUN
fcis-11135	4	33	.	.	PUNCT
fcis-11135	5	1	combined	combine	VERB
fcis-11135	5	2	with	with	ADP
fcis-11135	5	3	user	user	NOUN
fcis-11135	5	4	habit	habit	NOUN
fcis-11135	5	5	features	feature	NOUN
fcis-11135	5	6	,	,	PUNCT
fcis-11135	5	7	appropriate	appropriate	ADJ
fcis-11135	5	8	recommendation	recommendation	NOUN
fcis-11135	5	9	algorithms	algorithm	NOUN
fcis-11135	5	10	are	be	AUX
fcis-11135	5	11	employed	employ	VERB
fcis-11135	5	12	to	to	PART
fcis-11135	5	13	recommend	recommend	VERB
fcis-11135	5	14	learning	learn	VERB
fcis-11135	5	15	resources	resource	NOUN
fcis-11135	5	16	that	that	PRON
fcis-11135	5	17	align	align	VERB
fcis-11135	5	18	with	with	ADP
fcis-11135	5	19	their	their	PRON
fcis-11135	5	20	interests	interest	NOUN
fcis-11135	5	21	and	and	CCONJ
fcis-11135	5	22	habits	habit	NOUN
fcis-11135	5	23	.	.	PUNCT
fcis-11135	6	1	keywords	keyword	NOUN
fcis-11135	6	2	:	:	PUNCT
fcis-11135	6	3	graph	graph	VERB
fcis-11135	6	4	neural	neural	ADJ
fcis-11135	6	5	networks	network	NOUN
fcis-11135	6	6	;	;	PUNCT
fcis-11135	6	7	personalized	personalized	ADJ
fcis-11135	6	8	recommendation	recommendation	NOUN
fcis-11135	6	9	;	;	PUNCT
fcis-11135	6	10	data	datum	NOUN
fcis-11135	6	11	sparsity	sparsity	NOUN
fcis-11135	6	12	.	.	PUNCT
fcis-11135	7	1	1	1	X
fcis-11135	7	2	.	.	X
fcis-11135	7	3	introduction	introduction	NOUN
fcis-11135	7	4	with	with	ADP
fcis-11135	7	5	the	the	DET
fcis-11135	7	6	continuous	continuous	ADJ
fcis-11135	7	7	development	development	NOUN
fcis-11135	7	8	of	of	ADP
fcis-11135	7	9	information	information	NOUN
fcis-11135	7	10	technology	technology	NOUN
fcis-11135	7	11	and	and	CCONJ
fcis-11135	7	12	the	the	DET
fcis-11135	7	13	increasing	increase	VERB
fcis-11135	7	14	popularity	popularity	NOUN
fcis-11135	7	15	of	of	ADP
fcis-11135	7	16	the	the	DET
fcis-11135	7	17	internet	internet	NOUN
fcis-11135	7	18	,	,	PUNCT
fcis-11135	7	19	it	it	PRON
fcis-11135	7	20	has	have	AUX
fcis-11135	7	21	become	become	VERB
fcis-11135	7	22	a	a	DET
fcis-11135	7	23	very	very	ADV
fcis-11135	7	24	common	common	ADJ
fcis-11135	7	25	phenomenon	phenomenon	NOUN
fcis-11135	7	26	for	for	SCONJ
fcis-11135	7	27	people	people	NOUN
fcis-11135	7	28	to	to	PART
fcis-11135	7	29	obtain	obtain	VERB
fcis-11135	7	30	information	information	NOUN
fcis-11135	7	31	through	through	ADP
fcis-11135	7	32	online	online	ADJ
fcis-11135	7	33	learning	learning	NOUN
fcis-11135	7	34	.	.	PUNCT
fcis-11135	8	1	at	at	ADP
fcis-11135	8	2	the	the	DET
fcis-11135	8	3	same	same	ADJ
fcis-11135	8	4	time	time	NOUN
fcis-11135	8	5	,	,	PUNCT
fcis-11135	8	6	it	it	PRON
fcis-11135	8	7	also	also	ADV
fcis-11135	8	8	faces	face	VERB
fcis-11135	8	9	the	the	DET
fcis-11135	8	10	challenge	challenge	NOUN
fcis-11135	8	11	of	of	ADP
fcis-11135	8	12	massive	massive	ADJ
fcis-11135	8	13	online	online	ADJ
fcis-11135	8	14	resources	resource	NOUN
fcis-11135	8	15	and	and	CCONJ
fcis-11135	8	16	information	information	NOUN
fcis-11135	8	17	that	that	PRON
fcis-11135	8	18	make	make	VERB
fcis-11135	8	19	it	it	PRON
fcis-11135	8	20	difficult	difficult	ADJ
fcis-11135	8	21	for	for	SCONJ
fcis-11135	8	22	users	user	NOUN
fcis-11135	8	23	to	to	PART
fcis-11135	8	24	choose	choose	VERB
fcis-11135	8	25	and	and	CCONJ
fcis-11135	8	26	find	find	VERB
fcis-11135	8	27	information	information	NOUN
fcis-11135	8	28	that	that	PRON
fcis-11135	8	29	meets	meet	VERB
fcis-11135	8	30	their	their	PRON
fcis-11135	8	31	needs	need	NOUN
fcis-11135	8	32	.	.	PUNCT
fcis-11135	9	1	therefore	therefore	ADV
fcis-11135	9	2	,	,	PUNCT
fcis-11135	9	3	how	how	SCONJ
fcis-11135	9	4	to	to	PART
fcis-11135	9	5	provide	provide	VERB
fcis-11135	9	6	personalized	personalized	ADJ
fcis-11135	9	7	recommendations	recommendation	NOUN
fcis-11135	9	8	to	to	ADP
fcis-11135	9	9	users	user	NOUN
fcis-11135	9	10	through	through	ADP
fcis-11135	9	11	intelligent	intelligent	ADJ
fcis-11135	9	12	methods	method	NOUN
fcis-11135	9	13	to	to	PART
fcis-11135	9	14	meet	meet	VERB
fcis-11135	9	15	their	their	PRON
fcis-11135	9	16	online	online	ADJ
fcis-11135	9	17	needs	need	NOUN
fcis-11135	9	18	has	have	AUX
fcis-11135	9	19	become	become	VERB
fcis-11135	9	20	an	an	DET
fcis-11135	9	21	urgent	urgent	ADJ
fcis-11135	9	22	problem	problem	NOUN
fcis-11135	9	23	to	to	PART
fcis-11135	9	24	be	be	AUX
fcis-11135	9	25	solved	solve	VERB
fcis-11135	9	26	.	.	PUNCT
fcis-11135	10	1	so	so	ADV
fcis-11135	10	2	,	,	PUNCT
fcis-11135	10	3	we	we	PRON
fcis-11135	10	4	decided	decide	VERB
fcis-11135	10	5	to	to	PART
fcis-11135	10	6	design	design	VERB
fcis-11135	10	7	and	and	CCONJ
fcis-11135	10	8	implement	implement	VERB
fcis-11135	10	9	a	a	DET
fcis-11135	10	10	learning	learn	VERB
fcis-11135	10	11	resource	resource	NOUN
fcis-11135	10	12	recommendation	recommendation	NOUN
fcis-11135	10	13	system	system	NOUN
fcis-11135	10	14	based	base	VERB
fcis-11135	10	15	on	on	ADP
fcis-11135	10	16	user	user	NOUN
fcis-11135	10	17	habits	habit	NOUN
fcis-11135	10	18	and	and	CCONJ
fcis-11135	10	19	interests	interest	NOUN
fcis-11135	10	20	.	.	PUNCT
fcis-11135	11	1	we	we	PRON
fcis-11135	11	2	use	use	VERB
fcis-11135	11	3	graph	graph	NOUN
fcis-11135	11	4	neural	neural	ADJ
fcis-11135	11	5	network	network	NOUN
fcis-11135	11	6	deep	deep	ADJ
fcis-11135	11	7	learning	learn	VERB
fcis-11135	11	8	technology	technology	NOUN
fcis-11135	11	9	to	to	PART
fcis-11135	11	10	analyze	analyze	VERB
fcis-11135	11	11	the	the	DET
fcis-11135	11	12	big	big	ADJ
fcis-11135	11	13	data	datum	NOUN
fcis-11135	11	14	that	that	PRON
fcis-11135	11	15	users	user	NOUN
fcis-11135	11	16	browse	browse	VERB
fcis-11135	11	17	online	online	ADV
fcis-11135	11	18	,	,	PUNCT
fcis-11135	11	19	recommend	recommend	VERB
fcis-11135	11	20	to	to	ADP
fcis-11135	11	21	users	user	NOUN
fcis-11135	11	22	in	in	ADP
fcis-11135	11	23	an	an	DET
fcis-11135	11	24	intelligent	intelligent	ADJ
fcis-11135	11	25	way	way	NOUN
fcis-11135	11	26	,	,	PUNCT
fcis-11135	11	27	accurately	accurately	ADV
fcis-11135	11	28	deliver	deliver	VERB
fcis-11135	11	29	resources	resource	NOUN
fcis-11135	11	30	that	that	PRON
fcis-11135	11	31	meet	meet	VERB
fcis-11135	11	32	their	their	PRON
fcis-11135	11	33	browsing	browse	VERB
fcis-11135	11	34	habits	habit	NOUN
fcis-11135	11	35	and	and	CCONJ
fcis-11135	11	36	personalized	personalized	ADJ
fcis-11135	11	37	needs	need	NOUN
fcis-11135	11	38	,	,	PUNCT
fcis-11135	11	39	and	and	CCONJ
fcis-11135	11	40	use	use	VERB
fcis-11135	11	41	advanced	advanced	ADJ
fcis-11135	11	42	technologies	technology	NOUN
fcis-11135	11	43	such	such	ADJ
fcis-11135	11	44	as	as	ADP
fcis-11135	11	45	face	face	NOUN
fcis-11135	11	46	recognition	recognition	NOUN
fcis-11135	11	47	to	to	PART
fcis-11135	11	48	identify	identify	VERB
fcis-11135	11	49	users	user	NOUN
fcis-11135	11	50	and	and	CCONJ
fcis-11135	11	51	make	make	VERB
fcis-11135	11	52	personalized	personalized	ADJ
fcis-11135	11	53	recommendations	recommendation	NOUN
fcis-11135	11	54	.	.	PUNCT
fcis-11135	12	1	this	this	DET
fcis-11135	12	2	learning	learn	VERB
fcis-11135	12	3	resource	resource	NOUN
fcis-11135	12	4	recommendation	recommendation	NOUN
fcis-11135	12	5	system	system	NOUN
fcis-11135	12	6	based	base	VERB
fcis-11135	12	7	on	on	ADP
fcis-11135	12	8	user	user	NOUN
fcis-11135	12	9	habits	habit	NOUN
fcis-11135	12	10	is	be	AUX
fcis-11135	12	11	an	an	DET
fcis-11135	12	12	effective	effective	ADJ
fcis-11135	12	13	solution	solution	NOUN
fcis-11135	12	14	proposed	propose	VERB
fcis-11135	12	15	to	to	PART
fcis-11135	12	16	address	address	VERB
fcis-11135	12	17	the	the	DET
fcis-11135	12	18	above	above	ADJ
fcis-11135	12	19	issues	issue	NOUN
fcis-11135	12	20	.	.	PUNCT
fcis-11135	13	1	graph	graph	VERB
fcis-11135	13	2	neural	neural	ADJ
fcis-11135	13	3	network	network	NOUN
fcis-11135	13	4	(	(	PUNCT
fcis-11135	13	5	gnn	gnn	PROPN
fcis-11135	13	6	)	)	PUNCT
fcis-11135	13	7	is	be	AUX
fcis-11135	13	8	one	one	NUM
fcis-11135	13	9	of	of	ADP
fcis-11135	13	10	the	the	DET
fcis-11135	13	11	most	most	ADV
fcis-11135	13	12	attractive	attractive	ADJ
fcis-11135	13	13	recommendation	recommendation	NOUN
fcis-11135	13	14	algorithms	algorithm	NOUN
fcis-11135	13	15	.	.	PUNCT
fcis-11135	14	1	it	it	PRON
fcis-11135	14	2	is	be	AUX
fcis-11135	14	3	a	a	DET
fcis-11135	14	4	new	new	ADJ
fcis-11135	14	5	type	type	NOUN
fcis-11135	14	6	of	of	ADP
fcis-11135	14	7	neural	neural	ADJ
fcis-11135	14	8	network	network	NOUN
fcis-11135	14	9	,	,	PUNCT
fcis-11135	14	10	which	which	PRON
fcis-11135	14	11	originates	originate	VERB
fcis-11135	14	12	from	from	ADP
fcis-11135	14	13	the	the	DET
fcis-11135	14	14	development	development	NOUN
fcis-11135	14	15	of	of	ADP
fcis-11135	14	16	convolutional	convolutional	ADJ
fcis-11135	14	17	neural	neural	ADJ
fcis-11135	14	18	network	network	NOUN
fcis-11135	14	19	(	(	PUNCT
fcis-11135	14	20	cnn	cnn	PROPN
fcis-11135	14	21	)	)	PUNCT
fcis-11135	14	22	.	.	PUNCT
fcis-11135	15	1	gnn	gnn	PROPN
fcis-11135	15	2	contains	contain	VERB
fcis-11135	15	3	rich	rich	ADJ
fcis-11135	15	4	relational	relational	ADJ
fcis-11135	15	5	information	information	NOUN
fcis-11135	15	6	,	,	PUNCT
fcis-11135	15	7	which	which	PRON
fcis-11135	15	8	can	can	AUX
fcis-11135	15	9	effectively	effectively	ADV
fcis-11135	15	10	extract	extract	VERB
fcis-11135	15	11	data	datum	NOUN
fcis-11135	15	12	features	feature	NOUN
fcis-11135	15	13	in	in	ADP
fcis-11135	15	14	the	the	DET
fcis-11135	15	15	graph	graph	NOUN
fcis-11135	15	16	field	field	NOUN
fcis-11135	15	17	and	and	CCONJ
fcis-11135	15	18	provide	provide	VERB
fcis-11135	15	19	powerful	powerful	ADJ
fcis-11135	15	20	functions	function	NOUN
fcis-11135	15	21	for	for	ADP
fcis-11135	15	22	learning	learn	VERB
fcis-11135	15	23	graph	graph	NOUN
fcis-11135	15	24	related	related	ADJ
fcis-11135	15	25	data	datum	NOUN
fcis-11135	15	26	.	.	PUNCT
fcis-11135	16	1	compared	compare	VERB
fcis-11135	16	2	to	to	ADP
fcis-11135	16	3	traditional	traditional	ADJ
fcis-11135	16	4	deep	deep	ADJ
fcis-11135	16	5	learning	learning	NOUN
fcis-11135	16	6	methods	method	NOUN
fcis-11135	16	7	,	,	PUNCT
fcis-11135	16	8	gnn	gnn	PROPN
fcis-11135	16	9	places	place	VERB
fcis-11135	16	10	more	more	ADJ
fcis-11135	16	11	emphasis	emphasis	NOUN
fcis-11135	16	12	on	on	ADP
fcis-11135	16	13	the	the	DET
fcis-11135	16	14	connections	connection	NOUN
fcis-11135	16	15	between	between	ADP
fcis-11135	16	16	nodes	node	NOUN
fcis-11135	16	17	,	,	PUNCT
fcis-11135	16	18	effectively	effectively	ADV
fcis-11135	16	19	avoiding	avoid	VERB
fcis-11135	16	20	the	the	DET
fcis-11135	16	21	problem	problem	NOUN
fcis-11135	16	22	of	of	ADP
fcis-11135	16	23	overlooked	overlook	VERB
fcis-11135	16	24	associations	association	NOUN
fcis-11135	16	25	between	between	ADP
fcis-11135	16	26	users	user	NOUN
fcis-11135	16	27	and	and	CCONJ
fcis-11135	16	28	items	item	NOUN
fcis-11135	16	29	themselves	themselves	PRON
fcis-11135	16	30	.	.	PUNCT
fcis-11135	17	1	by	by	ADP
fcis-11135	17	2	iterating	iterate	VERB
fcis-11135	17	3	on	on	ADP
fcis-11135	17	4	nodes	node	NOUN
fcis-11135	17	5	,	,	PUNCT
fcis-11135	17	6	gnn	gnn	PROPN
fcis-11135	17	7	can	can	AUX
fcis-11135	17	8	more	more	ADV
fcis-11135	17	9	accurately	accurately	ADV
fcis-11135	17	10	describe	describe	VERB
fcis-11135	17	11	the	the	DET
fcis-11135	17	12	relationships	relationship	NOUN
fcis-11135	17	13	between	between	ADP
fcis-11135	17	14	entities	entity	NOUN
fcis-11135	17	15	in	in	ADP
fcis-11135	17	16	the	the	DET
fcis-11135	17	17	graph	graph	NOUN
fcis-11135	17	18	model	model	NOUN
fcis-11135	17	19	,	,	PUNCT
fcis-11135	17	20	providing	provide	VERB
fcis-11135	17	21	a	a	DET
fcis-11135	17	22	new	new	ADJ
fcis-11135	17	23	approach	approach	NOUN
fcis-11135	17	24	for	for	ADP
fcis-11135	17	25	recommendation	recommendation	NOUN
fcis-11135	17	26	system	system	NOUN
fcis-11135	17	27	analysis	analysis	NOUN
fcis-11135	17	28	and	and	CCONJ
fcis-11135	17	29	helping	help	VERB
fcis-11135	17	30	to	to	PART
fcis-11135	17	31	mine	mine	VERB
fcis-11135	17	32	deeper	deep	ADJ
fcis-11135	17	33	information	information	NOUN
fcis-11135	17	34	.	.	PUNCT
fcis-11135	18	1	this	this	DET
fcis-11135	18	2	article	article	NOUN
fcis-11135	18	3	provides	provide	VERB
fcis-11135	18	4	an	an	DET
fcis-11135	18	5	overview	overview	NOUN
fcis-11135	18	6	of	of	ADP
fcis-11135	18	7	the	the	DET
fcis-11135	18	8	application	application	NOUN
fcis-11135	18	9	of	of	ADP
fcis-11135	18	10	gnn	gnn	PROPN
fcis-11135	18	11	in	in	ADP
fcis-11135	18	12	recommendation	recommendation	NOUN
fcis-11135	18	13	systems	system	NOUN
fcis-11135	18	14	,	,	PUNCT
fcis-11135	18	15	showcasing	showcase	VERB
fcis-11135	18	16	its	its	PRON
fcis-11135	18	17	advantages	advantage	NOUN
fcis-11135	18	18	of	of	ADP
fcis-11135	18	19	scalability	scalability	NOUN
fcis-11135	18	20	and	and	CCONJ
fcis-11135	18	21	efficiency	efficiency	NOUN
fcis-11135	18	22	,	,	PUNCT
fcis-11135	18	23	and	and	CCONJ
fcis-11135	18	24	exploring	explore	VERB
fcis-11135	18	25	its	its	PRON
fcis-11135	18	26	potential	potential	NOUN
fcis-11135	18	27	in	in	ADP
fcis-11135	18	28	improving	improve	VERB
fcis-11135	18	29	recommendation	recommendation	NOUN
fcis-11135	18	30	system	system	NOUN
fcis-11135	18	31	performance	performance	NOUN
fcis-11135	18	32	.	.	PUNCT
fcis-11135	19	1	this	this	DET
fcis-11135	19	2	paper	paper	NOUN
fcis-11135	19	3	introduces	introduce	VERB
fcis-11135	19	4	a	a	DET
fcis-11135	19	5	personalized	personalized	ADJ
fcis-11135	19	6	recommendation	recommendation	NOUN
fcis-11135	19	7	system	system	NOUN
fcis-11135	19	8	based	base	VERB
fcis-11135	19	9	on	on	ADP
fcis-11135	19	10	graph	graph	NOUN
fcis-11135	19	11	neural	neural	ADJ
fcis-11135	19	12	network	network	NOUN
fcis-11135	19	13	and	and	CCONJ
fcis-11135	19	14	advanced	advanced	ADJ
fcis-11135	19	15	technology	technology	NOUN
fcis-11135	19	16	,	,	PUNCT
fcis-11135	19	17	which	which	PRON
fcis-11135	19	18	can	can	AUX
fcis-11135	19	19	collect	collect	VERB
fcis-11135	19	20	and	and	CCONJ
fcis-11135	19	21	analyze	analyze	VERB
fcis-11135	19	22	big	big	ADJ
fcis-11135	19	23	data	datum	NOUN
fcis-11135	19	24	that	that	PRON
fcis-11135	19	25	users	user	NOUN
fcis-11135	19	26	browse	browse	VERB
fcis-11135	19	27	on	on	ADP
fcis-11135	19	28	the	the	DET
fcis-11135	19	29	internet	internet	NOUN
fcis-11135	19	30	.	.	PUNCT
fcis-11135	20	1	by	by	ADP
fcis-11135	20	2	conducting	conduct	VERB
fcis-11135	20	3	a	a	DET
fcis-11135	20	4	detailed	detailed	ADJ
fcis-11135	20	5	analysis	analysis	NOUN
fcis-11135	20	6	of	of	ADP
fcis-11135	20	7	users	user	NOUN
fcis-11135	20	8	'	'	PART
fcis-11135	20	9	internet	internet	NOUN
fcis-11135	20	10	browsing	browse	VERB
fcis-11135	20	11	records	record	NOUN
fcis-11135	20	12	,	,	PUNCT
fcis-11135	20	13	application	application	NOUN
fcis-11135	20	14	usage	usage	NOUN
fcis-11135	20	15	,	,	PUNCT
fcis-11135	20	16	and	and	CCONJ
fcis-11135	20	17	browsing	browse	VERB
fcis-11135	20	18	content	content	NOUN
fcis-11135	20	19	,	,	PUNCT
fcis-11135	20	20	the	the	DET
fcis-11135	20	21	system	system	NOUN
fcis-11135	20	22	can	can	AUX
fcis-11135	20	23	capture	capture	VERB
fcis-11135	20	24	their	their	PRON
fcis-11135	20	25	browsing	browse	VERB
fcis-11135	20	26	interests	interest	NOUN
fcis-11135	20	27	and	and	CCONJ
fcis-11135	20	28	habits	habit	NOUN
fcis-11135	20	29	,	,	PUNCT
fcis-11135	20	30	providing	provide	VERB
fcis-11135	20	31	strong	strong	ADJ
fcis-11135	20	32	data	datum	NOUN
fcis-11135	20	33	support	support	NOUN
fcis-11135	20	34	for	for	ADP
fcis-11135	20	35	subsequent	subsequent	ADJ
fcis-11135	20	36	recommendations	recommendation	NOUN
fcis-11135	20	37	.	.	PUNCT
fcis-11135	21	1	in	in	ADP
fcis-11135	21	2	this	this	DET
fcis-11135	21	3	process	process	NOUN
fcis-11135	21	4	,	,	PUNCT
fcis-11135	21	5	we	we	PRON
fcis-11135	21	6	consider	consider	VERB
fcis-11135	21	7	users	user	NOUN
fcis-11135	21	8	and	and	CCONJ
fcis-11135	21	9	browsing	browse	VERB
fcis-11135	21	10	resources	resource	NOUN
fcis-11135	21	11	as	as	ADP
fcis-11135	21	12	nodes	node	NOUN
fcis-11135	21	13	in	in	ADP
fcis-11135	21	14	the	the	DET
fcis-11135	21	15	graph	graph	NOUN
fcis-11135	21	16	and	and	CCONJ
fcis-11135	21	17	establish	establish	VERB
fcis-11135	21	18	corresponding	corresponding	ADJ
fcis-11135	21	19	graph	graph	NOUN
fcis-11135	21	20	models	model	NOUN
fcis-11135	21	21	based	base	VERB
fcis-11135	21	22	on	on	ADP
fcis-11135	21	23	their	their	PRON
fcis-11135	21	24	interrelationships	interrelationship	NOUN
fcis-11135	21	25	.	.	PUNCT
fcis-11135	22	1	by	by	ADP
fcis-11135	22	2	applying	apply	VERB
fcis-11135	22	3	deep	deep	ADJ
fcis-11135	22	4	learning	learning	NOUN
fcis-11135	22	5	techniques	technique	NOUN
fcis-11135	22	6	of	of	ADP
fcis-11135	22	7	graph	graph	NOUN
fcis-11135	22	8	neural	neural	ADJ
fcis-11135	22	9	networks	network	NOUN
fcis-11135	22	10	,	,	PUNCT
fcis-11135	22	11	user	user	NOUN
fcis-11135	22	12	data	datum	NOUN
fcis-11135	22	13	is	be	AUX
fcis-11135	22	14	modeled	model	VERB
fcis-11135	22	15	and	and	CCONJ
fcis-11135	22	16	predicted	predict	VERB
fcis-11135	22	17	to	to	PART
fcis-11135	22	18	achieve	achieve	VERB
fcis-11135	22	19	accurate	accurate	ADJ
fcis-11135	22	20	prediction	prediction	NOUN
fcis-11135	22	21	of	of	ADP
fcis-11135	22	22	user	user	NOUN
fcis-11135	22	23	needs	need	NOUN
fcis-11135	22	24	and	and	CCONJ
fcis-11135	22	25	behaviors	behavior	NOUN
fcis-11135	22	26	.	.	PUNCT
fcis-11135	23	1	in	in	ADP
fcis-11135	23	2	order	order	NOUN
fcis-11135	23	3	to	to	PART
fcis-11135	23	4	further	far	ADV
fcis-11135	23	5	improve	improve	VERB
fcis-11135	23	6	the	the	DET
fcis-11135	23	7	personalization	personalization	NOUN
fcis-11135	23	8	of	of	ADP
fcis-11135	23	9	recommendations	recommendation	NOUN
fcis-11135	23	10	,	,	PUNCT
fcis-11135	23	11	we	we	PRON
fcis-11135	23	12	have	have	AUX
fcis-11135	23	13	adopted	adopt	VERB
fcis-11135	23	14	advanced	advanced	ADJ
fcis-11135	23	15	technologies	technology	NOUN
fcis-11135	23	16	such	such	ADJ
fcis-11135	23	17	as	as	ADP
fcis-11135	23	18	facial	facial	ADJ
fcis-11135	23	19	recognition	recognition	NOUN
fcis-11135	23	20	to	to	PART
fcis-11135	23	21	identify	identify	VERB
fcis-11135	23	22	users	user	NOUN
fcis-11135	23	23	.	.	PUNCT
fcis-11135	24	1	by	by	ADP
fcis-11135	24	2	recognizing	recognize	VERB
fcis-11135	24	3	users	user	NOUN
fcis-11135	24	4	'	'	PART
fcis-11135	24	5	facial	facial	ADJ
fcis-11135	24	6	features	feature	NOUN
fcis-11135	24	7	,	,	PUNCT
fcis-11135	24	8	the	the	DET
fcis-11135	24	9	system	system	NOUN
fcis-11135	24	10	can	can	AUX
fcis-11135	24	11	more	more	ADV
fcis-11135	24	12	accurately	accurately	ADV
fcis-11135	24	13	determine	determine	VERB
fcis-11135	24	14	their	their	PRON
fcis-11135	24	15	usage	usage	NOUN
fcis-11135	24	16	needs	need	NOUN
fcis-11135	24	17	and	and	CCONJ
fcis-11135	24	18	interests	interest	NOUN
fcis-11135	24	19	,	,	PUNCT
fcis-11135	24	20	and	and	CCONJ
fcis-11135	24	21	recommend	recommend	VERB
fcis-11135	24	22	online	online	ADJ
fcis-11135	24	23	resources	resource	NOUN
fcis-11135	24	24	that	that	PRON
fcis-11135	24	25	better	well	ADV
fcis-11135	24	26	meet	meet	VERB
fcis-11135	24	27	personalized	personalized	ADJ
fcis-11135	24	28	needs	need	NOUN
fcis-11135	24	29	for	for	ADP
fcis-11135	24	30	users	user	NOUN
fcis-11135	24	31	.	.	PUNCT
fcis-11135	25	1	this	this	DET
fcis-11135	25	2	personalized	personalized	ADJ
fcis-11135	25	3	recommendation	recommendation	NOUN
fcis-11135	25	4	method	method	NOUN
fcis-11135	25	5	enables	enable	VERB
fcis-11135	25	6	users	user	NOUN
fcis-11135	25	7	to	to	PART
fcis-11135	25	8	obtain	obtain	VERB
fcis-11135	25	9	content	content	NOUN
fcis-11135	25	10	and	and	CCONJ
fcis-11135	25	11	services	service	NOUN
fcis-11135	25	12	that	that	PRON
fcis-11135	25	13	suit	suit	VERB
fcis-11135	25	14	their	their	PRON
fcis-11135	25	15	interests	interest	NOUN
fcis-11135	25	16	more	more	ADV
fcis-11135	25	17	satisfactorily	satisfactorily	ADV
fcis-11135	25	18	,	,	PUNCT
fcis-11135	25	19	thereby	thereby	ADV
fcis-11135	25	20	improving	improve	VERB
fcis-11135	25	21	the	the	DET
fcis-11135	25	22	effectiveness	effectiveness	NOUN
fcis-11135	25	23	and	and	CCONJ
fcis-11135	25	24	user	user	NOUN
fcis-11135	25	25	experience	experience	NOUN
fcis-11135	25	26	of	of	ADP
fcis-11135	25	27	the	the	DET
fcis-11135	25	28	recommendation	recommendation	NOUN
fcis-11135	25	29	system	system	NOUN
fcis-11135	25	30	.	.	PUNCT
fcis-11135	26	1	2	2	X
fcis-11135	26	2	.	.	X
fcis-11135	26	3	related	relate	VERB
fcis-11135	26	4	work	work	NOUN
fcis-11135	26	5	2.1	2.1	NUM
fcis-11135	26	6	.	.	PUNCT
fcis-11135	27	1	research	research	NOUN
fcis-11135	27	2	content	content	NOUN
fcis-11135	27	3	a	a	DET
fcis-11135	27	4	learning	learn	VERB
fcis-11135	27	5	resource	resource	NOUN
fcis-11135	27	6	recommendation	recommendation	NOUN
fcis-11135	27	7	system	system	NOUN
fcis-11135	27	8	is	be	AUX
fcis-11135	27	9	a	a	DET
fcis-11135	27	10	system	system	NOUN
fcis-11135	27	11	that	that	PRON
fcis-11135	27	12	intelligently	intelligently	ADV
fcis-11135	27	13	recommends	recommend	VERB
fcis-11135	27	14	learning	learn	VERB
fcis-11135	27	15	resources	resource	NOUN
fcis-11135	27	16	that	that	PRON
fcis-11135	27	17	meet	meet	VERB
fcis-11135	27	18	users	user	NOUN
fcis-11135	27	19	'	'	PART
fcis-11135	27	20	interests	interest	NOUN
fcis-11135	27	21	and	and	CCONJ
fcis-11135	27	22	needs	need	NOUN
fcis-11135	27	23	.	.	PUNCT
fcis-11135	28	1	the	the	DET
fcis-11135	28	2	system	system	NOUN
fcis-11135	28	3	aims	aim	VERB
fcis-11135	28	4	to	to	PART
fcis-11135	28	5	provide	provide	VERB
fcis-11135	28	6	more	more	ADV
fcis-11135	28	7	personalized	personalized	ADJ
fcis-11135	28	8	and	and	CCONJ
fcis-11135	28	9	accurate	accurate	ADJ
fcis-11135	28	10	recommendation	recommendation	NOUN
fcis-11135	28	11	of	of	ADP
fcis-11135	28	12	learning	learn	VERB
fcis-11135	28	13	resources	resource	NOUN
fcis-11135	28	14	,	,	PUNCT
fcis-11135	28	15	improving	improve	VERB
fcis-11135	28	16	the	the	DET
fcis-11135	28	17	effectiveness	effectiveness	NOUN
fcis-11135	28	18	and	and	CCONJ
fcis-11135	28	19	efficiency	efficiency	NOUN
fcis-11135	28	20	of	of	ADP
fcis-11135	28	21	network	network	NOUN
fcis-11135	28	22	usage	usage	NOUN
fcis-11135	28	23	.	.	PUNCT
fcis-11135	29	1	the	the	DET
fcis-11135	29	2	system	system	NOUN
fcis-11135	29	3	should	should	AUX
fcis-11135	29	4	be	be	AUX
fcis-11135	29	5	able	able	ADJ
fcis-11135	29	6	to	to	PART
fcis-11135	29	7	recommend	recommend	VERB
fcis-11135	29	8	usage	usage	NOUN
fcis-11135	29	9	resources	resource	NOUN
fcis-11135	29	10	that	that	PRON
fcis-11135	29	11	meet	meet	VERB
fcis-11135	29	12	users	user	NOUN
fcis-11135	29	13	'	'	PART
fcis-11135	29	14	needs	need	NOUN
fcis-11135	29	15	based	base	VERB
fcis-11135	29	16	on	on	ADP
fcis-11135	29	17	factors	factor	NOUN
fcis-11135	29	18	such	such	ADJ
fcis-11135	29	19	as	as	ADP
fcis-11135	29	20	their	their	PRON
fcis-11135	29	21	historical	historical	ADJ
fcis-11135	29	22	usage	usage	NOUN
fcis-11135	29	23	records	record	NOUN
fcis-11135	29	24	,	,	PUNCT
fcis-11135	29	25	interests	interest	NOUN
fcis-11135	29	26	,	,	PUNCT
fcis-11135	29	27	and	and	CCONJ
fcis-11135	29	28	usage	usage	NOUN
fcis-11135	29	29	goals	goal	NOUN
fcis-11135	29	30	.	.	PUNCT
fcis-11135	30	1	continuously	continuously	ADV
fcis-11135	30	2	optimize	optimize	VERB
fcis-11135	30	3	recommendation	recommendation	NOUN
fcis-11135	30	4	algorithms	algorithm	NOUN
fcis-11135	30	5	through	through	ADP
fcis-11135	30	6	algorithm	algorithm	NOUN
fcis-11135	30	7	and	and	CCONJ
fcis-11135	30	8	data	datum	NOUN
fcis-11135	30	9	analysis	analysis	NOUN
fcis-11135	30	10	to	to	PART
fcis-11135	30	11	improve	improve	VERB
fcis-11135	30	12	the	the	DET
fcis-11135	30	13	accuracy	accuracy	NOUN
fcis-11135	30	14	and	and	CCONJ
fcis-11135	30	15	precision	precision	NOUN
fcis-11135	30	16	of	of	ADP
fcis-11135	30	17	recommendations	recommendation	NOUN
fcis-11135	30	18	.	.	PUNCT
fcis-11135	31	1	and	and	CCONJ
fcis-11135	31	2	recommend	recommend	VERB
fcis-11135	31	3	various	various	ADJ
fcis-11135	31	4	types	type	NOUN
fcis-11135	31	5	of	of	ADP
fcis-11135	31	6	learning	learn	VERB
fcis-11135	31	7	resources	resource	NOUN
fcis-11135	31	8	,	,	PUNCT
fcis-11135	31	9	including	include	VERB
fcis-11135	31	10	videos	video	NOUN
fcis-11135	31	11	,	,	PUNCT
fcis-11135	31	12	articles	article	NOUN
fcis-11135	31	13	,	,	PUNCT
fcis-11135	31	14	books	book	NOUN
fcis-11135	31	15	,	,	PUNCT
fcis-11135	31	16	63	63	NUM
fcis-11135	31	17	courses	course	NOUN
fcis-11135	31	18	,	,	PUNCT
fcis-11135	31	19	etc	etc	X
fcis-11135	31	20	.	.	X
fcis-11135	31	21	,	,	PUNCT
fcis-11135	31	22	to	to	PART
fcis-11135	31	23	meet	meet	VERB
fcis-11135	31	24	the	the	DET
fcis-11135	31	25	needs	need	NOUN
fcis-11135	31	26	of	of	ADP
fcis-11135	31	27	different	different	ADJ
fcis-11135	31	28	users	user	NOUN
fcis-11135	31	29	.	.	PUNCT
fcis-11135	32	1	finally	finally	ADV
fcis-11135	32	2	,	,	PUNCT
fcis-11135	32	3	the	the	DET
fcis-11135	32	4	system	system	NOUN
fcis-11135	32	5	should	should	AUX
fcis-11135	32	6	ensure	ensure	VERB
fcis-11135	32	7	the	the	DET
fcis-11135	32	8	security	security	NOUN
fcis-11135	32	9	and	and	CCONJ
fcis-11135	32	10	privacy	privacy	NOUN
fcis-11135	32	11	of	of	ADP
fcis-11135	32	12	user	user	NOUN
fcis-11135	32	13	data	datum	NOUN
fcis-11135	32	14	to	to	PART
fcis-11135	32	15	avoid	avoid	VERB
fcis-11135	32	16	the	the	DET
fcis-11135	32	17	leakage	leakage	NOUN
fcis-11135	32	18	or	or	CCONJ
fcis-11135	32	19	abuse	abuse	NOUN
fcis-11135	32	20	of	of	ADP
fcis-11135	32	21	user	user	NOUN
fcis-11135	32	22	information	information	NOUN
fcis-11135	32	23	.	.	PUNCT
fcis-11135	33	1	2.2	2.2	NUM
fcis-11135	33	2	.	.	PUNCT
fcis-11135	34	1	research	research	NOUN
fcis-11135	34	2	background	background	NOUN
fcis-11135	34	3	with	with	ADP
fcis-11135	34	4	the	the	DET
fcis-11135	34	5	continuous	continuous	ADJ
fcis-11135	34	6	development	development	NOUN
fcis-11135	34	7	of	of	ADP
fcis-11135	34	8	information	information	NOUN
fcis-11135	34	9	technology	technology	NOUN
fcis-11135	34	10	and	and	CCONJ
fcis-11135	34	11	the	the	DET
fcis-11135	34	12	increasing	increase	VERB
fcis-11135	34	13	popularity	popularity	NOUN
fcis-11135	34	14	of	of	ADP
fcis-11135	34	15	the	the	DET
fcis-11135	34	16	internet	internet	NOUN
fcis-11135	34	17	,	,	PUNCT
fcis-11135	34	18	it	it	PRON
fcis-11135	34	19	has	have	AUX
fcis-11135	34	20	become	become	VERB
fcis-11135	34	21	a	a	DET
fcis-11135	34	22	very	very	ADV
fcis-11135	34	23	common	common	ADJ
fcis-11135	34	24	phenomenon	phenomenon	NOUN
fcis-11135	34	25	for	for	SCONJ
fcis-11135	34	26	people	people	NOUN
fcis-11135	34	27	to	to	PART
fcis-11135	34	28	obtain	obtain	VERB
fcis-11135	34	29	information	information	NOUN
fcis-11135	34	30	through	through	ADP
fcis-11135	34	31	online	online	ADJ
fcis-11135	34	32	learning	learning	NOUN
fcis-11135	34	33	.	.	PUNCT
fcis-11135	35	1	at	at	ADP
fcis-11135	35	2	the	the	DET
fcis-11135	35	3	same	same	ADJ
fcis-11135	35	4	time	time	NOUN
fcis-11135	35	5	,	,	PUNCT
fcis-11135	35	6	it	it	PRON
fcis-11135	35	7	also	also	ADV
fcis-11135	35	8	faces	face	VERB
fcis-11135	35	9	the	the	DET
fcis-11135	35	10	challenge	challenge	NOUN
fcis-11135	35	11	of	of	ADP
fcis-11135	35	12	massive	massive	ADJ
fcis-11135	35	13	online	online	ADJ
fcis-11135	35	14	resources	resource	NOUN
fcis-11135	35	15	and	and	CCONJ
fcis-11135	35	16	information	information	NOUN
fcis-11135	35	17	that	that	PRON
fcis-11135	35	18	make	make	VERB
fcis-11135	35	19	it	it	PRON
fcis-11135	35	20	difficult	difficult	ADJ
fcis-11135	35	21	for	for	SCONJ
fcis-11135	35	22	users	user	NOUN
fcis-11135	35	23	to	to	PART
fcis-11135	35	24	choose	choose	VERB
fcis-11135	35	25	and	and	CCONJ
fcis-11135	35	26	find	find	VERB
fcis-11135	35	27	information	information	NOUN
fcis-11135	35	28	that	that	PRON
fcis-11135	35	29	meets	meet	VERB
fcis-11135	35	30	their	their	PRON
fcis-11135	35	31	needs	need	NOUN
fcis-11135	35	32	.	.	PUNCT
fcis-11135	36	1	therefore	therefore	ADV
fcis-11135	36	2	,	,	PUNCT
fcis-11135	36	3	how	how	SCONJ
fcis-11135	36	4	to	to	PART
fcis-11135	36	5	provide	provide	VERB
fcis-11135	36	6	personalized	personalized	ADJ
fcis-11135	36	7	recommendations	recommendation	NOUN
fcis-11135	36	8	to	to	ADP
fcis-11135	36	9	users	user	NOUN
fcis-11135	36	10	through	through	ADP
fcis-11135	36	11	intelligent	intelligent	ADJ
fcis-11135	36	12	methods	method	NOUN
fcis-11135	36	13	to	to	PART
fcis-11135	36	14	meet	meet	VERB
fcis-11135	36	15	their	their	PRON
fcis-11135	36	16	online	online	ADJ
fcis-11135	36	17	needs	need	NOUN
fcis-11135	36	18	has	have	AUX
fcis-11135	36	19	become	become	VERB
fcis-11135	36	20	an	an	DET
fcis-11135	36	21	urgent	urgent	ADJ
fcis-11135	36	22	problem	problem	NOUN
fcis-11135	36	23	to	to	PART
fcis-11135	36	24	be	be	AUX
fcis-11135	36	25	solved	solve	VERB
fcis-11135	36	26	.	.	PUNCT
fcis-11135	37	1	so	so	ADV
fcis-11135	37	2	,	,	PUNCT
fcis-11135	37	3	we	we	PRON
fcis-11135	37	4	decided	decide	VERB
fcis-11135	37	5	to	to	PART
fcis-11135	37	6	design	design	VERB
fcis-11135	37	7	and	and	CCONJ
fcis-11135	37	8	implement	implement	VERB
fcis-11135	37	9	a	a	DET
fcis-11135	37	10	learning	learn	VERB
fcis-11135	37	11	resource	resource	NOUN
fcis-11135	37	12	recommendation	recommendation	NOUN
fcis-11135	37	13	system	system	NOUN
fcis-11135	37	14	based	base	VERB
fcis-11135	37	15	on	on	ADP
fcis-11135	37	16	user	user	NOUN
fcis-11135	37	17	habits	habit	NOUN
fcis-11135	37	18	and	and	CCONJ
fcis-11135	37	19	interests	interest	NOUN
fcis-11135	37	20	.	.	PUNCT
fcis-11135	38	1	we	we	PRON
fcis-11135	38	2	use	use	VERB
fcis-11135	38	3	graph	graph	NOUN
fcis-11135	38	4	neural	neural	ADJ
fcis-11135	38	5	network	network	NOUN
fcis-11135	38	6	deep	deep	ADJ
fcis-11135	38	7	learning	learn	VERB
fcis-11135	38	8	technology	technology	NOUN
fcis-11135	38	9	to	to	PART
fcis-11135	38	10	analyze	analyze	VERB
fcis-11135	38	11	the	the	DET
fcis-11135	38	12	big	big	ADJ
fcis-11135	38	13	data	datum	NOUN
fcis-11135	38	14	that	that	PRON
fcis-11135	38	15	users	user	NOUN
fcis-11135	38	16	browse	browse	VERB
fcis-11135	38	17	online	online	ADV
fcis-11135	38	18	,	,	PUNCT
fcis-11135	38	19	recommend	recommend	VERB
fcis-11135	38	20	to	to	ADP
fcis-11135	38	21	users	user	NOUN
fcis-11135	38	22	in	in	ADP
fcis-11135	38	23	an	an	DET
fcis-11135	38	24	intelligent	intelligent	ADJ
fcis-11135	38	25	way	way	NOUN
fcis-11135	38	26	,	,	PUNCT
fcis-11135	38	27	accurately	accurately	ADV
fcis-11135	38	28	deliver	deliver	VERB
fcis-11135	38	29	resources	resource	NOUN
fcis-11135	38	30	that	that	PRON
fcis-11135	38	31	meet	meet	VERB
fcis-11135	38	32	their	their	PRON
fcis-11135	38	33	browsing	browse	VERB
fcis-11135	38	34	habits	habit	NOUN
fcis-11135	38	35	and	and	CCONJ
fcis-11135	38	36	personalized	personalized	ADJ
fcis-11135	38	37	needs	need	NOUN
fcis-11135	38	38	,	,	PUNCT
fcis-11135	38	39	and	and	CCONJ
fcis-11135	38	40	use	use	VERB
fcis-11135	38	41	advanced	advanced	ADJ
fcis-11135	38	42	technologies	technology	NOUN
fcis-11135	38	43	such	such	ADJ
fcis-11135	38	44	as	as	ADP
fcis-11135	38	45	face	face	NOUN
fcis-11135	38	46	recognition	recognition	NOUN
fcis-11135	38	47	to	to	PART
fcis-11135	38	48	identify	identify	VERB
fcis-11135	38	49	users	user	NOUN
fcis-11135	38	50	and	and	CCONJ
fcis-11135	38	51	make	make	VERB
fcis-11135	38	52	personalized	personalized	ADJ
fcis-11135	38	53	recommendations	recommendation	NOUN
fcis-11135	38	54	.	.	PUNCT
fcis-11135	39	1	3	3	X
fcis-11135	39	2	.	.	X
fcis-11135	39	3	gnn	gnn	PROPN
fcis-11135	39	4	algorithm	algorithm	NOUN
fcis-11135	39	5	in	in	ADP
fcis-11135	39	6	random	random	ADJ
fcis-11135	39	7	initialization	initialization	NOUN
fcis-11135	40	1	,	,	PUNCT
fcis-11135	40	2	we	we	PRON
fcis-11135	40	3	only	only	ADV
fcis-11135	40	4	need	need	VERB
fcis-11135	40	5	to	to	PART
fcis-11135	40	6	determine	determine	VERB
fcis-11135	40	7	the	the	DET
fcis-11135	40	8	range	range	NOUN
fcis-11135	40	9	and	and	CCONJ
fcis-11135	40	10	distribution	distribution	NOUN
fcis-11135	40	11	of	of	ADP
fcis-11135	40	12	initialization	initialization	NOUN
fcis-11135	40	13	,	,	PUNCT
fcis-11135	40	14	and	and	CCONJ
fcis-11135	40	15	common	common	ADJ
fcis-11135	40	16	methods	method	NOUN
fcis-11135	40	17	include	include	VERB
fcis-11135	40	18	using	use	VERB
fcis-11135	40	19	uniform	uniform	NOUN
fcis-11135	40	20	or	or	CCONJ
fcis-11135	40	21	gaussian	gaussian	ADJ
fcis-11135	40	22	distributions	distribution	NOUN
fcis-11135	40	23	to	to	PART
fcis-11135	40	24	generate	generate	VERB
fcis-11135	40	25	random	random	ADJ
fcis-11135	40	26	values	value	NOUN
fcis-11135	40	27	.	.	PUNCT
fcis-11135	41	1	for	for	ADP
fcis-11135	41	2	the	the	DET
fcis-11135	41	3	random	random	ADJ
fcis-11135	41	4	initialization	initialization	NOUN
fcis-11135	41	5	of	of	ADP
fcis-11135	41	6	features	feature	NOUN
fcis-11135	41	7	of	of	ADP
fcis-11135	41	8	nodes	node	NOUN
fcis-11135	41	9	and	and	CCONJ
fcis-11135	41	10	edges	edge	NOUN
fcis-11135	41	11	,	,	PUNCT
fcis-11135	41	12	set	set	VERB
fcis-11135	41	13	a	a	DET
fcis-11135	41	14	range	range	NOUN
fcis-11135	41	15	to	to	PART
fcis-11135	41	16	randomly	randomly	ADV
fcis-11135	41	17	generate	generate	VERB
fcis-11135	41	18	corresponding	corresponding	ADJ
fcis-11135	41	19	numerical	numerical	ADJ
fcis-11135	41	20	values	value	NOUN
fcis-11135	41	21	from	from	ADP
fcis-11135	41	22	the	the	DET
fcis-11135	41	23	specified	specified	ADJ
fcis-11135	41	24	distribution	distribution	NOUN
fcis-11135	41	25	.	.	PUNCT
fcis-11135	42	1	3.1	3.1	NUM
fcis-11135	42	2	.	.	PUNCT
fcis-11135	42	3	graph	graph	NOUN
fcis-11135	42	4	convolution	convolution	NOUN
fcis-11135	42	5	among	among	ADP
fcis-11135	42	6	them	they	PRON
fcis-11135	42	7	,	,	PUNCT
fcis-11135	42	8	hi	hi	INTJ
fcis-11135	42	9	(	(	PUNCT
fcis-11135	42	10	l+1	l+1	X
fcis-11135	42	11	)	)	PUNCT
fcis-11135	42	12	is	be	AUX
fcis-11135	42	13	the	the	DET
fcis-11135	42	14	new	new	ADJ
fcis-11135	42	15	feature	feature	NOUN
fcis-11135	42	16	representation	representation	NOUN
fcis-11135	42	17	of	of	ADP
fcis-11135	42	18	node	node	ADJ
fcis-11135	42	19	i	i	PRON
fcis-11135	42	20	in	in	ADP
fcis-11135	42	21	the	the	DET
fcis-11135	42	22	l+1	l+1	PART
fcis-11135	42	23	layer	layer	NOUN
fcis-11135	42	24	,	,	PUNCT
fcis-11135	42	25	hj	hj	X
fcis-11135	42	26	(	(	PUNCT
fcis-11135	42	27	l	l	NOUN
fcis-11135	42	28	)	)	PUNCT
fcis-11135	42	29	is	be	AUX
fcis-11135	42	30	the	the	DET
fcis-11135	42	31	feature	feature	NOUN
fcis-11135	42	32	representation	representation	NOUN
fcis-11135	42	33	of	of	ADP
fcis-11135	42	34	node	node	PROPN
fcis-11135	42	35	j	j	PROPN
fcis-11135	42	36	in	in	ADP
fcis-11135	42	37	the	the	DET
fcis-11135	42	38	l	l	NOUN
fcis-11135	42	39	layer	layer	NOUN
fcis-11135	42	40	,	,	PUNCT
fcis-11135	42	41	n	n	CCONJ
fcis-11135	42	42	(	(	PUNCT
fcis-11135	42	43	i	i	NOUN
fcis-11135	42	44	)	)	PUNCT
fcis-11135	42	45	is	be	AUX
fcis-11135	42	46	the	the	DET
fcis-11135	42	47	set	set	NOUN
fcis-11135	42	48	of	of	ADP
fcis-11135	42	49	neighboring	neighboring	NOUN
fcis-11135	42	50	nodes	node	NOUN
fcis-11135	42	51	of	of	ADP
fcis-11135	42	52	node	node	PROPN
fcis-11135	42	53	i	i	PROPN
fcis-11135	42	54	,	,	PUNCT
fcis-11135	42	55	cij	cij	PROPN
fcis-11135	42	56	is	be	AUX
fcis-11135	42	57	the	the	DET
fcis-11135	42	58	normalization	normalization	NOUN
fcis-11135	42	59	coefficient	coefficient	NOUN
fcis-11135	42	60	of	of	ADP
fcis-11135	42	61	the	the	DET
fcis-11135	42	62	number	number	NOUN
fcis-11135	42	63	of	of	ADP
fcis-11135	42	64	edges	edge	NOUN
fcis-11135	42	65	between	between	ADP
fcis-11135	42	66	node	node	NOUN
fcis-11135	42	67	i	i	PROPN
fcis-11135	42	68	and	and	CCONJ
fcis-11135	42	69	node	node	PROPN
fcis-11135	42	70	j	j	PROPN
fcis-11135	42	71	,	,	PUNCT
fcis-11135	42	72	and	and	CCONJ
fcis-11135	42	73	w	w	PROPN
fcis-11135	42	74	(	(	PUNCT
fcis-11135	42	75	l	l	NOUN
fcis-11135	42	76	)	)	PUNCT
fcis-11135	42	77	is	be	AUX
fcis-11135	42	78	the	the	DET
fcis-11135	42	79	weight	weight	NOUN
fcis-11135	42	80	parameter	parameter	NOUN
fcis-11135	42	81	of	of	ADP
fcis-11135	42	82	the	the	DET
fcis-11135	42	83	l	l	NOUN
fcis-11135	42	84	layer	layer	NOUN
fcis-11135	42	85	,	,	PUNCT
fcis-11135	42	86	σ	σ	PROPN
fcis-11135	42	87	is	be	AUX
fcis-11135	42	88	the	the	DET
fcis-11135	42	89	activation	activation	NOUN
fcis-11135	42	90	function	function	NOUN
fcis-11135	42	91	.	.	PUNCT
fcis-11135	43	1	by	by	ADP
fcis-11135	43	2	performing	perform	VERB
fcis-11135	43	3	convolution	convolution	NOUN
fcis-11135	43	4	operations	operation	NOUN
fcis-11135	43	5	between	between	ADP
fcis-11135	43	6	node	node	NOUN
fcis-11135	43	7	features	feature	NOUN
fcis-11135	43	8	and	and	CCONJ
fcis-11135	43	9	neighboring	neighboring	NOUN
fcis-11135	43	10	node	node	NOUN
fcis-11135	43	11	features	feature	NOUN
fcis-11135	43	12	,	,	PUNCT
fcis-11135	43	13	utilizing	utilize	VERB
fcis-11135	43	14	the	the	DET
fcis-11135	43	15	connectivity	connectivity	NOUN
fcis-11135	43	16	between	between	ADP
fcis-11135	43	17	nodes	node	NOUN
fcis-11135	43	18	for	for	ADP
fcis-11135	43	19	feature	feature	NOUN
fcis-11135	43	20	updates	update	NOUN
fcis-11135	43	21	and	and	CCONJ
fcis-11135	43	22	propagation	propagation	NOUN
fcis-11135	43	23	3.2	3.2	NUM
fcis-11135	43	24	.	.	PUNCT
fcis-11135	44	1	graph	graph	NOUN
fcis-11135	44	2	pooling	pool	VERB
fcis-11135	44	3	hg	hg	ADP
fcis-11135	44	4	=	=	NOUN
fcis-11135	44	5	i	i	PROPN
fcis-11135	44	6	∈	∈	PROPN
fcis-11135	44	7	v	v	ADP
fcis-11135	44	8	max	max	PROPN
fcis-11135	44	9	(	(	PUNCT
fcis-11135	44	10	uhi	uhi	INTJ
fcis-11135	44	11	)	)	PUNCT
fcis-11135	44	12	among	among	ADP
fcis-11135	44	13	them	they	PRON
fcis-11135	44	14	,	,	PUNCT
fcis-11135	44	15	hg	hg	PROPN
fcis-11135	44	16	is	be	AUX
fcis-11135	44	17	the	the	DET
fcis-11135	44	18	graph	graph	NOUN
fcis-11135	44	19	level	level	NOUN
fcis-11135	44	20	feature	feature	NOUN
fcis-11135	44	21	vector	vector	NOUN
fcis-11135	44	22	,	,	PUNCT
fcis-11135	44	23	hi	hi	INTJ
fcis-11135	44	24	is	be	AUX
fcis-11135	44	25	the	the	DET
fcis-11135	44	26	feature	feature	NOUN
fcis-11135	44	27	vector	vector	NOUN
fcis-11135	44	28	of	of	ADP
fcis-11135	44	29	node	node	PROPN
fcis-11135	44	30	i	i	PROPN
fcis-11135	44	31	,	,	PUNCT
fcis-11135	44	32	and	and	CCONJ
fcis-11135	44	33	u	u	NOUN
fcis-11135	44	34	is	be	AUX
fcis-11135	44	35	the	the	DET
fcis-11135	44	36	channel	channel	NOUN
fcis-11135	44	37	transformation	transformation	NOUN
fcis-11135	44	38	parameter	parameter	NOUN
fcis-11135	44	39	.	.	PUNCT
fcis-11135	45	1	by	by	ADP
fcis-11135	45	2	selecting	select	VERB
fcis-11135	45	3	important	important	ADJ
fcis-11135	45	4	nodes	node	NOUN
fcis-11135	45	5	and	and	CCONJ
fcis-11135	45	6	edges	edge	NOUN
fcis-11135	45	7	,	,	PUNCT
fcis-11135	45	8	or	or	CCONJ
fcis-11135	45	9	segmenting	segment	VERB
fcis-11135	45	10	and	and	CCONJ
fcis-11135	45	11	sampling	sample	VERB
fcis-11135	45	12	the	the	DET
fcis-11135	45	13	graph	graph	NOUN
fcis-11135	45	14	,	,	PUNCT
fcis-11135	45	15	subgraphs	subgraph	NOUN
fcis-11135	45	16	can	can	AUX
fcis-11135	45	17	be	be	AUX
fcis-11135	45	18	generated	generate	VERB
fcis-11135	45	19	that	that	PRON
fcis-11135	45	20	represent	represent	VERB
fcis-11135	45	21	the	the	DET
fcis-11135	45	22	entire	entire	ADJ
fcis-11135	45	23	graph	graph	NOUN
fcis-11135	45	24	structure	structure	NOUN
fcis-11135	45	25	information	information	NOUN
fcis-11135	45	26	.	.	PUNCT
fcis-11135	46	1	this	this	DET
fcis-11135	46	2	subgraph	subgraph	NOUN
fcis-11135	46	3	can	can	AUX
fcis-11135	46	4	be	be	AUX
fcis-11135	46	5	used	use	VERB
fcis-11135	46	6	as	as	ADP
fcis-11135	46	7	input	input	NOUN
fcis-11135	46	8	to	to	ADP
fcis-11135	46	9	the	the	DET
fcis-11135	46	10	model	model	NOUN
fcis-11135	46	11	for	for	ADP
fcis-11135	46	12	feature	feature	NOUN
fcis-11135	46	13	transfer	transfer	NOUN
fcis-11135	46	14	and	and	CCONJ
fcis-11135	46	15	aggregation	aggregation	NOUN
fcis-11135	46	16	calculations	calculation	NOUN
fcis-11135	46	17	.	.	PUNCT
fcis-11135	47	1	3.3	3.3	NUM
fcis-11135	47	2	.	.	PUNCT
fcis-11135	48	1	graph	graph	VERB
fcis-11135	48	2	attention	attention	NOUN
fcis-11135	48	3	eij	eij	PROPN
fcis-11135	48	4	=	=	SYM
fcis-11135	48	5	leakyrelu(at[w1hi∣∣w2hj	leakyrelu(at[w1hi∣∣w2hj	PROPN
fcis-11135	48	6	]	]	X
fcis-11135	48	7	)	)	PUNCT
fcis-11135	49	1	αij=	αij=	NUM
fcis-11135	49	2	exp(eij)/(∑k∈n(i)exp(eik	exp(eij)/(∑k∈n(i)exp(eik	NOUN
fcis-11135	49	3	)	)	PUNCT
fcis-11135	49	4	)	)	PUNCT
fcis-11135	50	1	hi′=σ(j∈n(i	hi′=σ(j∈n(i	ADJ
fcis-11135	50	2	)	)	PUNCT
fcis-11135	50	3	∑(αij	∑(αij	PROPN
fcis-11135	50	4	)	)	PUNCT
fcis-11135	50	5	w3(hj	w3(hj	PROPN
fcis-11135	50	6	)	)	PUNCT
fcis-11135	50	7	)	)	PUNCT
fcis-11135	50	8	among	among	ADP
fcis-11135	50	9	them	they	PRON
fcis-11135	50	10	,	,	PUNCT
fcis-11135	50	11	eij	eij	PROPN
fcis-11135	50	12	is	be	AUX
fcis-11135	50	13	the	the	DET
fcis-11135	50	14	edge	edge	NOUN
fcis-11135	50	15	weight	weight	NOUN
fcis-11135	50	16	calculated	calculate	VERB
fcis-11135	50	17	through	through	ADP
fcis-11135	50	18	the	the	DET
fcis-11135	50	19	attention	attention	NOUN
fcis-11135	50	20	mechanism	mechanism	NOUN
fcis-11135	50	21	,	,	PUNCT
fcis-11135	50	22	a	a	PRON
fcis-11135	50	23	is	be	AUX
fcis-11135	50	24	the	the	DET
fcis-11135	50	25	weight	weight	NOUN
fcis-11135	50	26	vector	vector	NOUN
fcis-11135	50	27	of	of	ADP
fcis-11135	50	28	the	the	DET
fcis-11135	50	29	attention	attention	NOUN
fcis-11135	50	30	mechanism	mechanism	NOUN
fcis-11135	50	31	,	,	PUNCT
fcis-11135	50	32	and	and	CCONJ
fcis-11135	50	33	|	|	ADV
fcis-11135	50	34	|represents	|represent	VERB
fcis-11135	50	35	the	the	DET
fcis-11135	50	36	vector	vector	NOUN
fcis-11135	50	37	concatenation	concatenation	NOUN
fcis-11135	50	38	operation	operation	NOUN
fcis-11135	50	39	,	,	PUNCT
fcis-11135	50	40	α	α	PROPN
fcis-11135	50	41	ij	ij	NOUN
fcis-11135	50	42	is	be	AUX
fcis-11135	50	43	the	the	DET
fcis-11135	50	44	attention	attention	NOUN
fcis-11135	50	45	coefficient	coefficient	NOUN
fcis-11135	50	46	between	between	ADP
fcis-11135	50	47	node	node	PROPN
fcis-11135	50	48	i	i	PROPN
fcis-11135	50	49	and	and	CCONJ
fcis-11135	50	50	neighboring	neighbor	VERB
fcis-11135	50	51	node	node	PROPN
fcis-11135	50	52	j	j	PROPN
fcis-11135	50	53	,	,	PUNCT
fcis-11135	50	54	and	and	CCONJ
fcis-11135	50	55	hi	hi	INTJ
fcis-11135	50	56	'	'	PUNCT
fcis-11135	50	57	is	be	AUX
fcis-11135	50	58	the	the	DET
fcis-11135	50	59	updated	update	VERB
fcis-11135	50	60	feature	feature	NOUN
fcis-11135	50	61	representation	representation	NOUN
fcis-11135	50	62	of	of	ADP
fcis-11135	50	63	node	node	PROPN
fcis-11135	50	64	i.	i.	NOUN
fcis-11135	50	65	the	the	DET
fcis-11135	50	66	specific	specific	ADJ
fcis-11135	50	67	algorithm	algorithm	NOUN
fcis-11135	50	68	for	for	ADP
fcis-11135	50	69	adaptive	adaptive	ADJ
fcis-11135	50	70	initialization	initialization	NOUN
fcis-11135	50	71	can	can	AUX
fcis-11135	50	72	be	be	AUX
fcis-11135	50	73	selected	select	VERB
fcis-11135	50	74	or	or	CCONJ
fcis-11135	50	75	designed	design	VERB
fcis-11135	50	76	based	base	VERB
fcis-11135	50	77	on	on	ADP
fcis-11135	50	78	the	the	DET
fcis-11135	50	79	needs	need	NOUN
fcis-11135	50	80	of	of	ADP
fcis-11135	50	81	the	the	DET
fcis-11135	50	82	problem	problem	NOUN
fcis-11135	50	83	and	and	CCONJ
fcis-11135	50	84	the	the	DET
fcis-11135	50	85	design	design	NOUN
fcis-11135	50	86	of	of	ADP
fcis-11135	50	87	the	the	DET
fcis-11135	50	88	network	network	NOUN
fcis-11135	50	89	.	.	PUNCT
fcis-11135	51	1	it	it	PRON
fcis-11135	51	2	can	can	AUX
fcis-11135	51	3	be	be	AUX
fcis-11135	51	4	used	use	VERB
fcis-11135	51	5	in	in	ADP
fcis-11135	51	6	conjunction	conjunction	NOUN
fcis-11135	51	7	with	with	ADP
fcis-11135	51	8	different	different	ADJ
fcis-11135	51	9	gnn	gnn	NOUN
fcis-11135	51	10	models	model	NOUN
fcis-11135	51	11	,	,	PUNCT
fcis-11135	51	12	aggregation	aggregation	NOUN
fcis-11135	51	13	methods	method	NOUN
fcis-11135	51	14	,	,	PUNCT
fcis-11135	51	15	and	and	CCONJ
fcis-11135	51	16	feature	feature	NOUN
fcis-11135	51	17	update	update	NOUN
fcis-11135	51	18	rules	rule	NOUN
fcis-11135	51	19	to	to	PART
fcis-11135	51	20	improve	improve	VERB
fcis-11135	51	21	the	the	DET
fcis-11135	51	22	performance	performance	NOUN
fcis-11135	51	23	and	and	CCONJ
fcis-11135	51	24	adaptability	adaptability	NOUN
fcis-11135	51	25	of	of	ADP
fcis-11135	51	26	the	the	DET
fcis-11135	51	27	model	model	NOUN
fcis-11135	51	28	(	(	PUNCT
fcis-11135	51	29	figure	figure	NOUN
fcis-11135	51	30	1	1	NUM
fcis-11135	51	31	)	)	PUNCT
fcis-11135	51	32	.	.	PUNCT
fcis-11135	52	1	figure	figure	VERB
fcis-11135	52	2	1	1	NUM
fcis-11135	52	3	.	.	PUNCT
fcis-11135	52	4	initialization	initialization	PROPN
fcis-11135	52	5	model	model	PROPN
fcis-11135	52	6	diagram	diagram	PROPN
fcis-11135	52	7	3.4	3.4	NUM
fcis-11135	52	8	.	.	PUNCT
fcis-11135	53	1	linear	linear	ADJ
fcis-11135	53	2	transformation	transformation	NOUN
fcis-11135	53	3	for	for	ADP
fcis-11135	53	4	each	each	DET
fcis-11135	53	5	layer	layer	NOUN
fcis-11135	53	6	of	of	ADP
fcis-11135	53	7	nodes	node	NOUN
fcis-11135	53	8	,	,	PUNCT
fcis-11135	53	9	linear	linear	ADJ
fcis-11135	53	10	transformation	transformation	NOUN
fcis-11135	53	11	is	be	AUX
fcis-11135	53	12	a	a	DET
fcis-11135	53	13	basic	basic	ADJ
fcis-11135	53	14	computational	computational	ADJ
fcis-11135	53	15	operation	operation	NOUN
fcis-11135	53	16	.	.	PUNCT
fcis-11135	54	1	its	its	PRON
fcis-11135	54	2	purpose	purpose	NOUN
fcis-11135	54	3	is	be	AUX
fcis-11135	54	4	to	to	PART
fcis-11135	54	5	multiply	multiply	VERB
fcis-11135	54	6	the	the	DET
fcis-11135	54	7	input	input	NOUN
fcis-11135	54	8	data	datum	NOUN
fcis-11135	54	9	by	by	ADP
fcis-11135	54	10	the	the	DET
fcis-11135	54	11	weight	weight	NOUN
fcis-11135	54	12	matrix	matrix	NOUN
fcis-11135	54	13	and	and	CCONJ
fcis-11135	54	14	add	add	VERB
fcis-11135	54	15	a	a	DET
fcis-11135	54	16	bias	bias	NOUN
fcis-11135	54	17	vector	vector	NOUN
fcis-11135	54	18	to	to	PART
fcis-11135	54	19	obtain	obtain	VERB
fcis-11135	54	20	an	an	DET
fcis-11135	54	21	intermediate	intermediate	ADJ
fcis-11135	54	22	linear	linear	ADJ
fcis-11135	54	23	output	output	NOUN
fcis-11135	54	24	.	.	PUNCT
fcis-11135	55	1	perform	perform	VERB
fcis-11135	55	2	nonlinear	nonlinear	ADJ
fcis-11135	55	3	conversion	conversion	NOUN
fcis-11135	55	4	on	on	ADP
fcis-11135	55	5	linear	linear	ADJ
fcis-11135	55	6	output	output	NOUN
fcis-11135	55	7	and	and	CCONJ
fcis-11135	55	8	introduce	introduce	VERB
fcis-11135	55	9	nonlinear	nonlinear	ADJ
fcis-11135	55	10	factors	factor	NOUN
fcis-11135	55	11	(	(	PUNCT
fcis-11135	55	12	figure	figure	NOUN
fcis-11135	55	13	2	2	NUM
fcis-11135	55	14	)	)	PUNCT
fcis-11135	55	15	.	.	PUNCT
fcis-11135	56	1	normalize	normalize	VERB
fcis-11135	56	2	the	the	DET
fcis-11135	56	3	input	input	NOUN
fcis-11135	56	4	data	datum	NOUN
fcis-11135	56	5	of	of	ADP
fcis-11135	56	6	each	each	DET
fcis-11135	56	7	layer	layer	NOUN
fcis-11135	56	8	to	to	ADP
fcis-11135	56	9	a	a	DET
fcis-11135	56	10	mean	mean	NOUN
fcis-11135	56	11	of	of	ADP
fcis-11135	56	12	0	0	NUM
fcis-11135	56	13	and	and	CCONJ
fcis-11135	56	14	a	a	DET
fcis-11135	56	15	variance	variance	NOUN
fcis-11135	56	16	of	of	ADP
fcis-11135	56	17	1	1	NUM
fcis-11135	56	18	.	.	PUNCT
fcis-11135	56	19	by	by	ADP
fcis-11135	56	20	reducing	reduce	VERB
fcis-11135	56	21	the	the	DET
fcis-11135	56	22	distribution	distribution	NOUN
fcis-11135	56	23	changes	change	NOUN
fcis-11135	56	24	of	of	ADP
fcis-11135	56	25	input	input	NOUN
fcis-11135	56	26	data	datum	NOUN
fcis-11135	56	27	and	and	CCONJ
fcis-11135	56	28	providing	provide	VERB
fcis-11135	56	29	reliable	reliable	ADJ
fcis-11135	56	30	gradient	gradient	NOUN
fcis-11135	56	31	signals	signal	NOUN
fcis-11135	56	32	,	,	PUNCT
fcis-11135	56	33	the	the	DET
fcis-11135	56	34	network	network	NOUN
fcis-11135	56	35	is	be	AUX
fcis-11135	56	36	easy	easy	ADJ
fcis-11135	56	37	to	to	PART
fcis-11135	56	38	train	train	VERB
fcis-11135	56	39	.	.	PUNCT
fcis-11135	57	1	the	the	DET
fcis-11135	57	2	pooling	pool	VERB
fcis-11135	57	3	operation	operation	NOUN
fcis-11135	57	4	reduces	reduce	VERB
fcis-11135	57	5	the	the	DET
fcis-11135	57	6	size	size	NOUN
fcis-11135	57	7	of	of	ADP
fcis-11135	57	8	feature	feature	NOUN
fcis-11135	57	9	maps	map	NOUN
fcis-11135	57	10	and	and	CCONJ
fcis-11135	57	11	extracts	extract	VERB
fcis-11135	57	12	spatial	spatial	ADJ
fcis-11135	57	13	hierarchical	hierarchical	ADJ
fcis-11135	57	14	information	information	NOUN
fcis-11135	57	15	of	of	ADP
fcis-11135	57	16	features	feature	NOUN
fcis-11135	57	17	.	.	PUNCT
fcis-11135	58	1	reduce	reduce	VERB
fcis-11135	58	2	the	the	DET
fcis-11135	58	3	number	number	NOUN
fcis-11135	58	4	of	of	ADP
fcis-11135	58	5	parameters	parameter	NOUN
fcis-11135	58	6	and	and	CCONJ
fcis-11135	58	7	improve	improve	VERB
fcis-11135	58	8	the	the	DET
fcis-11135	58	9	computational	computational	ADJ
fcis-11135	58	10	efficiency	efficiency	NOUN
fcis-11135	58	11	of	of	ADP
fcis-11135	58	12	the	the	DET
fcis-11135	58	13	network	network	NOUN
fcis-11135	58	14	.	.	PUNCT
fcis-11135	59	1	randomly	randomly	ADV
fcis-11135	59	2	discard	discard	VERB
fcis-11135	59	3	a	a	DET
fcis-11135	59	4	portion	portion	NOUN
fcis-11135	59	5	of	of	ADP
fcis-11135	59	6	the	the	DET
fcis-11135	59	7	node	node	NOUN
fcis-11135	59	8	's	's	PART
fcis-11135	59	9	output	output	NOUN
fcis-11135	59	10	.	.	PUNCT
fcis-11135	60	1	by	by	ADP
fcis-11135	60	2	randomly	randomly	ADV
fcis-11135	60	3	deactivating	deactivate	VERB
fcis-11135	60	4	a	a	DET
fcis-11135	60	5	portion	portion	NOUN
fcis-11135	60	6	of	of	ADP
fcis-11135	60	7	nodes	node	NOUN
fcis-11135	60	8	,	,	PUNCT
fcis-11135	60	9	the	the	DET
fcis-11135	60	10	interdependence	interdependence	NOUN
fcis-11135	60	11	between	between	ADP
fcis-11135	60	12	each	each	DET
fcis-11135	60	13	node	node	NOUN
fcis-11135	60	14	can	can	AUX
fcis-11135	60	15	be	be	AUX
fcis-11135	60	16	limited	limit	VERB
fcis-11135	60	17	,	,	PUNCT
fcis-11135	60	18	enhancing	enhance	VERB
fcis-11135	60	19	the	the	DET
fcis-11135	60	20	model	model	NOUN
fcis-11135	60	21	's	's	PART
fcis-11135	60	22	generalization	generalization	NOUN
fcis-11135	60	23	ability	ability	NOUN
fcis-11135	60	24	.	.	PUNCT
fcis-11135	61	1	figure	figure	NOUN
fcis-11135	61	2	2	2	NUM
fcis-11135	61	3	.	.	NOUN
fcis-11135	61	4	number	number	NOUN
fcis-11135	61	5	linear	linear	PROPN
fcis-11135	61	6	transformation	transformation	NOUN
fcis-11135	61	7	model	model	NOUN
fcis-11135	61	8	.	.	PUNCT
fcis-11135	62	1	4	4	X
fcis-11135	62	2	.	.	NUM
fcis-11135	62	3	proposed	propose	VERB
fcis-11135	62	4	solutions	solution	NOUN
fcis-11135	62	5	and	and	CCONJ
fcis-11135	62	6	solutions	solution	NOUN
fcis-11135	62	7	4.1	4.1	NUM
fcis-11135	62	8	.	.	PUNCT
fcis-11135	62	9	proposed	propose	VERB
fcis-11135	62	10	problem	problem	NOUN
fcis-11135	62	11	solving	solve	VERB
fcis-11135	62	12	when	when	SCONJ
fcis-11135	62	13	using	use	VERB
fcis-11135	62	14	gnn	gnn	NOUN
fcis-11135	62	15	to	to	PART
fcis-11135	62	16	solve	solve	VERB
fcis-11135	62	17	learning	learn	VERB
fcis-11135	62	18	resource	resource	NOUN
fcis-11135	62	19	recommendation	recommendation	NOUN
fcis-11135	62	20	systems	system	NOUN
fcis-11135	62	21	based	base	VERB
fcis-11135	62	22	on	on	ADP
fcis-11135	62	23	user	user	NOUN
fcis-11135	62	24	habits	habit	NOUN
fcis-11135	62	25	,	,	PUNCT
fcis-11135	62	26	the	the	DET
fcis-11135	62	27	following	follow	VERB
fcis-11135	62	28	issues	issue	NOUN
fcis-11135	62	29	related	relate	VERB
fcis-11135	62	30	to	to	ADP
fcis-11135	62	31	gnn	gnn	PROPN
fcis-11135	62	32	are	be	AUX
fcis-11135	62	33	involved	involve	VERB
fcis-11135	62	34	:	:	PUNCT
fcis-11135	62	35	model	model	NOUN
fcis-11135	62	36	complexity	complexity	NOUN
fcis-11135	62	37	and	and	CCONJ
fcis-11135	62	38	training	training	NOUN
fcis-11135	62	39	efficiency	efficiency	NOUN
fcis-11135	62	40	:	:	PUNCT
fcis-11135	62	41	complex	complex	ADJ
fcis-11135	62	42	gnn	gnn	NOUN
fcis-11135	62	43	models	model	NOUN
fcis-11135	62	44	may	may	AUX
fcis-11135	62	45	lead	lead	VERB
fcis-11135	62	46	to	to	PART
fcis-11135	62	47	slow	slow	VERB
fcis-11135	62	48	training	training	NOUN
fcis-11135	62	49	and	and	CCONJ
fcis-11135	62	50	require	require	VERB
fcis-11135	62	51	significant	significant	ADJ
fcis-11135	62	52	computational	computational	ADJ
fcis-11135	62	53	resources	resource	NOUN
fcis-11135	62	54	.	.	PUNCT
fcis-11135	63	1	data	datum	NOUN
fcis-11135	63	2	sparsity	sparsity	NOUN
fcis-11135	63	3	:	:	PUNCT
fcis-11135	63	4	users	user	NOUN
fcis-11135	63	5	tend	tend	VERB
fcis-11135	63	6	to	to	PART
fcis-11135	63	7	have	have	VERB
fcis-11135	63	8	very	very	ADV
fcis-11135	63	9	sparse	sparse	ADJ
fcis-11135	63	10	data	datum	NOUN
fcis-11135	63	11	,	,	PUNCT
fcis-11135	63	12	which	which	PRON
fcis-11135	63	13	may	may	AUX
fcis-11135	63	14	affect	affect	VERB
fcis-11135	63	15	the	the	DET
fcis-11135	63	16	performance	performance	NOUN
fcis-11135	63	17	and	and	CCONJ
fcis-11135	63	18	recommendation	recommendation	NOUN
fcis-11135	63	19	accuracy	accuracy	NOUN
fcis-11135	63	20	of	of	ADP
fcis-11135	63	21	gnn	gnn	NOUN
fcis-11135	63	22	models	model	NOUN
fcis-11135	63	23	.	.	PUNCT
fcis-11135	64	1	hierarchical	hierarchical	ADJ
fcis-11135	64	2	diversity	diversity	NOUN
fcis-11135	64	3	:	:	PUNCT
fcis-11135	64	4	user	user	NOUN
fcis-11135	64	5	habits	habit	NOUN
fcis-11135	64	6	data	datum	NOUN
fcis-11135	64	7	may	may	AUX
fcis-11135	64	8	have	have	VERB
fcis-11135	64	9	multiple	multiple	ADJ
fcis-11135	64	10	64	64	NUM
fcis-11135	64	11	hierarchical	hierarchical	ADJ
fcis-11135	64	12	structures	structure	NOUN
fcis-11135	64	13	,	,	PUNCT
fcis-11135	64	14	and	and	CCONJ
fcis-11135	64	15	how	how	SCONJ
fcis-11135	64	16	to	to	PART
fcis-11135	64	17	flexibly	flexibly	ADV
fcis-11135	64	18	model	model	VERB
fcis-11135	64	19	this	this	DET
fcis-11135	64	20	structure	structure	NOUN
fcis-11135	64	21	is	be	AUX
fcis-11135	64	22	a	a	DET
fcis-11135	64	23	challenge	challenge	NOUN
fcis-11135	64	24	.	.	PUNCT
fcis-11135	65	1	information	information	NOUN
fcis-11135	65	2	dissemination	dissemination	NOUN
fcis-11135	65	3	and	and	CCONJ
fcis-11135	65	4	long	long	ADJ
fcis-11135	65	5	-	-	PUNCT
fcis-11135	65	6	distance	distance	NOUN
fcis-11135	65	7	dependence	dependence	NOUN
fcis-11135	65	8	:	:	PUNCT
fcis-11135	65	9	information	information	NOUN
fcis-11135	65	10	dissemination	dissemination	NOUN
fcis-11135	65	11	in	in	ADP
fcis-11135	65	12	gnn	gnn	PROPN
fcis-11135	65	13	is	be	AUX
fcis-11135	65	14	usually	usually	ADV
fcis-11135	65	15	local	local	ADJ
fcis-11135	65	16	,	,	PUNCT
fcis-11135	65	17	and	and	CCONJ
fcis-11135	65	18	information	information	NOUN
fcis-11135	65	19	transmission	transmission	NOUN
fcis-11135	65	20	between	between	ADP
fcis-11135	65	21	distant	distant	ADJ
fcis-11135	65	22	nodes	node	NOUN
fcis-11135	65	23	may	may	AUX
fcis-11135	65	24	not	not	PART
fcis-11135	65	25	be	be	AUX
fcis-11135	65	26	effective	effective	ADJ
fcis-11135	65	27	enough	enough	ADV
fcis-11135	65	28	.	.	PUNCT
fcis-11135	66	1	context	context	NOUN
fcis-11135	66	2	and	and	CCONJ
fcis-11135	66	3	temporal	temporal	ADJ
fcis-11135	66	4	modeling	modeling	NOUN
fcis-11135	66	5	:	:	PUNCT
fcis-11135	66	6	learning	learn	VERB
fcis-11135	66	7	resource	resource	NOUN
fcis-11135	66	8	recommendation	recommendation	NOUN
fcis-11135	66	9	needs	need	VERB
fcis-11135	66	10	to	to	PART
fcis-11135	66	11	consider	consider	VERB
fcis-11135	66	12	context	context	NOUN
fcis-11135	66	13	and	and	CCONJ
fcis-11135	66	14	temporal	temporal	ADJ
fcis-11135	66	15	relationships	relationship	NOUN
fcis-11135	66	16	,	,	PUNCT
fcis-11135	66	17	and	and	CCONJ
fcis-11135	66	18	how	how	SCONJ
fcis-11135	66	19	to	to	PART
fcis-11135	66	20	introduce	introduce	VERB
fcis-11135	66	21	them	they	PRON
fcis-11135	66	22	into	into	ADP
fcis-11135	66	23	the	the	DET
fcis-11135	66	24	gnn	gnn	PROPN
fcis-11135	66	25	model	model	NOUN
fcis-11135	66	26	is	be	AUX
fcis-11135	66	27	an	an	DET
fcis-11135	66	28	important	important	ADJ
fcis-11135	66	29	issue	issue	NOUN
fcis-11135	66	30	.	.	PUNCT
fcis-11135	67	1	model	model	NOUN
fcis-11135	67	2	interpretability	interpretability	NOUN
fcis-11135	67	3	:	:	PUNCT
fcis-11135	67	4	gnn	gnn	NOUN
fcis-11135	67	5	models	model	NOUN
fcis-11135	67	6	are	be	AUX
fcis-11135	67	7	usually	usually	ADV
fcis-11135	67	8	black	black	ADJ
fcis-11135	67	9	box	box	NOUN
fcis-11135	67	10	models	model	NOUN
fcis-11135	67	11	,	,	PUNCT
fcis-11135	67	12	making	make	VERB
fcis-11135	67	13	it	it	PRON
fcis-11135	67	14	difficult	difficult	ADJ
fcis-11135	67	15	to	to	PART
fcis-11135	67	16	explain	explain	VERB
fcis-11135	67	17	their	their	PRON
fcis-11135	67	18	internal	internal	ADJ
fcis-11135	67	19	information	information	NOUN
fcis-11135	67	20	transmission	transmission	NOUN
fcis-11135	67	21	and	and	CCONJ
fcis-11135	67	22	decision	decision	NOUN
fcis-11135	67	23	-	-	PUNCT
fcis-11135	67	24	making	make	VERB
fcis-11135	67	25	processes	process	NOUN
fcis-11135	67	26	.	.	PUNCT
fcis-11135	68	1	4.2	4.2	NUM
fcis-11135	68	2	.	.	PUNCT
fcis-11135	68	3	solution	solution	NOUN
fcis-11135	68	4	to	to	PART
fcis-11135	68	5	address	address	VERB
fcis-11135	68	6	the	the	DET
fcis-11135	68	7	above	above	ADJ
fcis-11135	68	8	issues	issue	NOUN
fcis-11135	68	9	,	,	PUNCT
fcis-11135	68	10	we	we	PRON
fcis-11135	68	11	have	have	VERB
fcis-11135	68	12	the	the	DET
fcis-11135	68	13	following	follow	VERB
fcis-11135	68	14	solution	solution	NOUN
fcis-11135	68	15	process	process	NOUN
fcis-11135	68	16	to	to	PART
fcis-11135	68	17	incorporate	incorporate	VERB
fcis-11135	68	18	the	the	DET
fcis-11135	68	19	user	user	NOUN
fcis-11135	68	20	's	's	PART
fcis-11135	68	21	node	node	PROPN
fcis-11135	68	22	zi	zi	PROPN
fcis-11135	68	23	and	and	CCONJ
fcis-11135	68	24	its	its	PRON
fcis-11135	68	25	weight	weight	NOUN
fcis-11135	68	26	wi	wi	PROPN
fcis-11135	68	27	into	into	ADP
fcis-11135	68	28	the	the	DET
fcis-11135	68	29	model	model	NOUN
fcis-11135	68	30	.	.	PUNCT
fcis-11135	69	1	firstly	firstly	ADV
fcis-11135	69	2	,	,	PUNCT
fcis-11135	69	3	we	we	PRON
fcis-11135	69	4	need	need	VERB
fcis-11135	69	5	to	to	PART
fcis-11135	69	6	convert	convert	VERB
fcis-11135	69	7	the	the	DET
fcis-11135	69	8	nodes	node	NOUN
fcis-11135	69	9	and	and	CCONJ
fcis-11135	69	10	edges	edge	NOUN
fcis-11135	69	11	in	in	ADP
fcis-11135	69	12	the	the	DET
fcis-11135	69	13	graph	graph	NOUN
fcis-11135	69	14	into	into	ADP
fcis-11135	69	15	representations	representation	NOUN
fcis-11135	69	16	that	that	PRON
fcis-11135	69	17	can	can	AUX
fcis-11135	69	18	be	be	AUX
fcis-11135	69	19	processed	process	VERB
fcis-11135	69	20	by	by	ADP
fcis-11135	69	21	the	the	DET
fcis-11135	69	22	computer	computer	NOUN
fcis-11135	69	23	.	.	PUNCT
fcis-11135	70	1	nodes	node	NOUN
fcis-11135	70	2	will	will	AUX
fcis-11135	70	3	be	be	AUX
fcis-11135	70	4	represented	represent	VERB
fcis-11135	70	5	as	as	ADP
fcis-11135	70	6	vectors	vector	NOUN
fcis-11135	70	7	or	or	CCONJ
fcis-11135	70	8	matrices	matrix	NOUN
fcis-11135	70	9	,	,	PUNCT
fcis-11135	70	10	and	and	CCONJ
fcis-11135	70	11	edges	edge	NOUN
fcis-11135	70	12	will	will	AUX
fcis-11135	70	13	be	be	AUX
fcis-11135	70	14	represented	represent	VERB
fcis-11135	70	15	in	in	ADP
fcis-11135	70	16	the	the	DET
fcis-11135	70	17	form	form	NOUN
fcis-11135	70	18	of	of	ADP
fcis-11135	70	19	adjacency	adjacency	NOUN
fcis-11135	70	20	matrix	matrix	NOUN
fcis-11135	70	21	or	or	CCONJ
fcis-11135	70	22	adjacency	adjacency	NOUN
fcis-11135	70	23	list	list	NOUN
fcis-11135	70	24	.	.	PUNCT
fcis-11135	71	1	the	the	DET
fcis-11135	71	2	characteristics	characteristic	NOUN
fcis-11135	71	3	of	of	ADP
fcis-11135	71	4	each	each	DET
fcis-11135	71	5	node	node	NOUN
fcis-11135	71	6	and	and	CCONJ
fcis-11135	71	7	the	the	DET
fcis-11135	71	8	characteristics	characteristic	NOUN
fcis-11135	71	9	of	of	ADP
fcis-11135	71	10	its	its	PRON
fcis-11135	71	11	neighbor	neighbor	NOUN
fcis-11135	71	12	nodes	node	NOUN
fcis-11135	71	13	are	be	AUX
fcis-11135	71	14	aggregated	aggregate	VERB
fcis-11135	71	15	,	,	PUNCT
fcis-11135	71	16	and	and	CCONJ
fcis-11135	71	17	the	the	DET
fcis-11135	71	18	connection	connection	NOUN
fcis-11135	71	19	relationship	relationship	NOUN
fcis-11135	71	20	and	and	CCONJ
fcis-11135	71	21	weight	weight	NOUN
fcis-11135	71	22	between	between	ADP
fcis-11135	71	23	nodes	node	NOUN
fcis-11135	71	24	are	be	AUX
fcis-11135	71	25	determined	determine	VERB
fcis-11135	71	26	according	accord	VERB
fcis-11135	71	27	to	to	ADP
fcis-11135	71	28	the	the	DET
fcis-11135	71	29	adjacency	adjacency	NOUN
fcis-11135	71	30	matrix	matrix	NOUN
fcis-11135	71	31	or	or	CCONJ
fcis-11135	71	32	adjacency	adjacency	NOUN
fcis-11135	71	33	list	list	NOUN
fcis-11135	71	34	to	to	PART
fcis-11135	71	35	calculate	calculate	VERB
fcis-11135	71	36	the	the	DET
fcis-11135	71	37	aggregated	aggregate	VERB
fcis-11135	71	38	neighbor	neighbor	NOUN
fcis-11135	71	39	feature	feature	NOUN
fcis-11135	71	40	representation	representation	NOUN
fcis-11135	71	41	.	.	PUNCT
fcis-11135	72	1	perform	perform	VERB
fcis-11135	72	2	a	a	DET
fcis-11135	72	3	linear	linear	ADJ
fcis-11135	72	4	transformation	transformation	NOUN
fcis-11135	72	5	on	on	ADP
fcis-11135	72	6	the	the	DET
fcis-11135	72	7	aggregated	aggregate	VERB
fcis-11135	72	8	neighbor	neighbor	NOUN
fcis-11135	72	9	features	feature	VERB
fcis-11135	72	10	,	,	PUNCT
fcis-11135	72	11	multiplying	multiply	VERB
fcis-11135	72	12	them	they	PRON
fcis-11135	72	13	by	by	ADP
fcis-11135	72	14	the	the	DET
fcis-11135	72	15	weight	weight	NOUN
fcis-11135	72	16	matrix	matrix	NOUN
fcis-11135	72	17	and	and	CCONJ
fcis-11135	72	18	adding	add	VERB
fcis-11135	72	19	a	a	DET
fcis-11135	72	20	bias	bias	NOUN
fcis-11135	72	21	vector	vector	NOUN
fcis-11135	72	22	.	.	PUNCT
fcis-11135	73	1	the	the	DET
fcis-11135	73	2	activation	activation	NOUN
fcis-11135	73	3	function	function	NOUN
fcis-11135	73	4	is	be	AUX
fcis-11135	73	5	used	use	VERB
fcis-11135	73	6	for	for	ADP
fcis-11135	73	7	nonlinear	nonlinear	ADJ
fcis-11135	73	8	conversion	conversion	NOUN
fcis-11135	73	9	of	of	ADP
fcis-11135	73	10	the	the	DET
fcis-11135	73	11	features	feature	NOUN
fcis-11135	73	12	after	after	ADP
fcis-11135	73	13	linear	linear	PROPN
fcis-11135	73	14	transformation	transformation	NOUN
fcis-11135	73	15	.	.	PUNCT
fcis-11135	74	1	use	use	VERB
fcis-11135	74	2	the	the	DET
fcis-11135	74	3	nonlinear	nonlinear	NOUN
fcis-11135	74	4	transformed	transform	VERB
fcis-11135	74	5	features	feature	NOUN
fcis-11135	74	6	as	as	ADP
fcis-11135	74	7	new	new	ADJ
fcis-11135	74	8	features	feature	NOUN
fcis-11135	74	9	for	for	ADP
fcis-11135	74	10	node	node	ADJ
fcis-11135	74	11	transfer	transfer	NOUN
fcis-11135	74	12	in	in	ADP
fcis-11135	74	13	subsequent	subsequent	ADJ
fcis-11135	74	14	layers	layer	NOUN
fcis-11135	74	15	.	.	PUNCT
fcis-11135	75	1	repeat	repeat	VERB
fcis-11135	75	2	the	the	DET
fcis-11135	75	3	feature	feature	NOUN
fcis-11135	75	4	transfer	transfer	NOUN
fcis-11135	75	5	process	process	NOUN
fcis-11135	75	6	until	until	SCONJ
fcis-11135	75	7	the	the	DET
fcis-11135	75	8	set	set	ADJ
fcis-11135	75	9	number	number	NOUN
fcis-11135	75	10	of	of	ADP
fcis-11135	75	11	convolutional	convolutional	ADJ
fcis-11135	75	12	layers	layer	NOUN
fcis-11135	75	13	is	be	AUX
fcis-11135	75	14	reached	reach	VERB
fcis-11135	75	15	.	.	PUNCT
fcis-11135	76	1	based	base	VERB
fcis-11135	76	2	on	on	ADP
fcis-11135	76	3	the	the	DET
fcis-11135	76	4	features	feature	NOUN
fcis-11135	76	5	transmitted	transmit	VERB
fcis-11135	76	6	through	through	ADP
fcis-11135	76	7	a	a	DET
fcis-11135	76	8	series	series	NOUN
fcis-11135	76	9	of	of	ADP
fcis-11135	76	10	graph	graph	NOUN
fcis-11135	76	11	convolutional	convolutional	ADJ
fcis-11135	76	12	layers	layer	NOUN
fcis-11135	76	13	,	,	PUNCT
fcis-11135	76	14	corresponding	correspond	VERB
fcis-11135	76	15	prediction	prediction	NOUN
fcis-11135	76	16	tasks	task	NOUN
fcis-11135	76	17	are	be	AUX
fcis-11135	76	18	performed	perform	VERB
fcis-11135	76	19	in	in	ADP
fcis-11135	76	20	the	the	DET
fcis-11135	76	21	output	output	NOUN
fcis-11135	76	22	layer	layer	NOUN
fcis-11135	76	23	and	and	CCONJ
fcis-11135	76	24	the	the	DET
fcis-11135	76	25	final	final	ADJ
fcis-11135	76	26	results	result	NOUN
fcis-11135	76	27	are	be	AUX
fcis-11135	76	28	obtained	obtain	VERB
fcis-11135	76	29	.	.	PUNCT
fcis-11135	77	1	through	through	ADP
fcis-11135	77	2	the	the	DET
fcis-11135	77	3	above	above	ADJ
fcis-11135	77	4	process	process	NOUN
fcis-11135	77	5	,	,	PUNCT
fcis-11135	77	6	gnn	gnn	PROPN
fcis-11135	77	7	can	can	AUX
fcis-11135	77	8	transfer	transfer	VERB
fcis-11135	77	9	and	and	CCONJ
fcis-11135	77	10	aggregate	aggregate	VERB
fcis-11135	77	11	the	the	DET
fcis-11135	77	12	input	input	NOUN
fcis-11135	77	13	graph	graph	NOUN
fcis-11135	77	14	data	datum	NOUN
fcis-11135	77	15	through	through	ADP
fcis-11135	77	16	a	a	DET
fcis-11135	77	17	series	series	NOUN
fcis-11135	77	18	of	of	ADP
fcis-11135	77	19	graph	graph	NOUN
fcis-11135	77	20	convolutional	convolutional	ADJ
fcis-11135	77	21	layer	layer	NOUN
fcis-11135	77	22	features	feature	NOUN
fcis-11135	77	23	,	,	PUNCT
fcis-11135	77	24	and	and	CCONJ
fcis-11135	77	25	ultimately	ultimately	ADV
fcis-11135	77	26	obtain	obtain	VERB
fcis-11135	77	27	the	the	DET
fcis-11135	77	28	predicted	predict	VERB
fcis-11135	77	29	results	result	NOUN
fcis-11135	77	30	of	of	ADP
fcis-11135	77	31	the	the	DET
fcis-11135	77	32	graph	graph	NOUN
fcis-11135	77	33	or	or	CCONJ
fcis-11135	77	34	node	node	NOUN
fcis-11135	77	35	.	.	PUNCT
fcis-11135	78	1	this	this	DET
fcis-11135	78	2	forward	forward	ADJ
fcis-11135	78	3	propagation	propagation	NOUN
fcis-11135	78	4	process	process	NOUN
fcis-11135	78	5	enables	enable	VERB
fcis-11135	78	6	gnn	gnn	PROPN
fcis-11135	78	7	to	to	PART
fcis-11135	78	8	fully	fully	ADV
fcis-11135	78	9	utilize	utilize	VERB
fcis-11135	78	10	the	the	DET
fcis-11135	78	11	topology	topology	NOUN
fcis-11135	78	12	information	information	NOUN
fcis-11135	78	13	between	between	ADP
fcis-11135	78	14	nodes	node	NOUN
fcis-11135	78	15	and	and	CCONJ
fcis-11135	78	16	perform	perform	VERB
fcis-11135	78	17	features	feature	NOUN
fcis-11135	78	18	between	between	ADP
fcis-11135	78	19	layers	layer	NOUN
fcis-11135	78	20	when	when	SCONJ
fcis-11135	78	21	processing	processing	NOUN
fcis-11135	78	22	graph	graph	NOUN
fcis-11135	78	23	structure	structure	NOUN
fcis-11135	78	24	data	datum	NOUN
fcis-11135	78	25	transfer	transfer	NOUN
fcis-11135	78	26	and	and	CCONJ
fcis-11135	78	27	aggregate	aggregate	VERB
fcis-11135	78	28	to	to	PART
fcis-11135	78	29	extract	extract	VERB
fcis-11135	78	30	meaningful	meaningful	ADJ
fcis-11135	78	31	representations	representation	NOUN
fcis-11135	78	32	and	and	CCONJ
fcis-11135	78	33	make	make	VERB
fcis-11135	78	34	predictions	prediction	NOUN
fcis-11135	78	35	(	(	PUNCT
fcis-11135	78	36	figure	figure	NOUN
fcis-11135	78	37	3	3	NUM
fcis-11135	78	38	)	)	PUNCT
fcis-11135	78	39	.	.	PUNCT
fcis-11135	79	1	figure	figure	VERB
fcis-11135	79	2	3	3	NUM
fcis-11135	79	3	.	.	PUNCT
fcis-11135	80	1	gnn	gnn	PROPN
fcis-11135	80	2	flowchart	flowchart	PROPN
fcis-11135	80	3	.	.	PUNCT
fcis-11135	81	1	5	5	NUM
fcis-11135	81	2	.	.	X
fcis-11135	81	3	experiments	experiment	NOUN
fcis-11135	81	4	5.1	5.1	NUM
fcis-11135	81	5	.	.	PUNCT
fcis-11135	82	1	datasets	dataset	NOUN
fcis-11135	82	2	build	build	VERB
fcis-11135	82	3	a	a	DET
fcis-11135	82	4	learning	learn	VERB
fcis-11135	82	5	resource	resource	NOUN
fcis-11135	82	6	recommendation	recommendation	NOUN
fcis-11135	82	7	system	system	NOUN
fcis-11135	82	8	based	base	VERB
fcis-11135	82	9	on	on	ADP
fcis-11135	82	10	user	user	NOUN
fcis-11135	82	11	habits	habit	NOUN
fcis-11135	82	12	,	,	PUNCT
fcis-11135	82	13	including	include	VERB
fcis-11135	82	14	modules	module	NOUN
fcis-11135	82	15	such	such	ADJ
fcis-11135	82	16	as	as	ADP
fcis-11135	82	17	user	user	NOUN
fcis-11135	82	18	information	information	NOUN
fcis-11135	82	19	collection	collection	NOUN
fcis-11135	82	20	,	,	PUNCT
fcis-11135	82	21	data	datum	NOUN
fcis-11135	82	22	analysis	analysis	NOUN
fcis-11135	82	23	,	,	PUNCT
fcis-11135	82	24	recommendation	recommendation	NOUN
fcis-11135	82	25	algorithms	algorithm	NOUN
fcis-11135	82	26	,	,	PUNCT
fcis-11135	82	27	and	and	CCONJ
fcis-11135	82	28	user	user	NOUN
fcis-11135	82	29	feedback	feedback	NOUN
fcis-11135	82	30	(	(	PUNCT
fcis-11135	82	31	figure	figure	NOUN
fcis-11135	82	32	4	4	NUM
fcis-11135	82	33	)	)	PUNCT
fcis-11135	82	34	.	.	PUNCT
fcis-11135	83	1	the	the	DET
fcis-11135	83	2	results	result	NOUN
fcis-11135	83	3	shown	show	VERB
fcis-11135	83	4	in	in	ADP
fcis-11135	83	5	the	the	DET
fcis-11135	83	6	following	follow	VERB
fcis-11135	83	7	figure	figure	NOUN
fcis-11135	83	8	show	show	VERB
fcis-11135	83	9	that	that	SCONJ
fcis-11135	83	10	as	as	SCONJ
fcis-11135	83	11	users	user	NOUN
fcis-11135	83	12	use	use	VERB
fcis-11135	83	13	the	the	DET
fcis-11135	83	14	recommendation	recommendation	NOUN
fcis-11135	83	15	system	system	NOUN
fcis-11135	83	16	,	,	PUNCT
fcis-11135	83	17	the	the	DET
fcis-11135	83	18	collection	collection	NOUN
fcis-11135	83	19	time	time	NOUN
fcis-11135	83	20	of	of	ADP
fcis-11135	83	21	the	the	DET
fcis-11135	83	22	dataset	dataset	NOUN
fcis-11135	83	23	increases	increase	NOUN
fcis-11135	83	24	,	,	PUNCT
fcis-11135	83	25	and	and	CCONJ
fcis-11135	83	26	the	the	DET
fcis-11135	83	27	browsing	browse	VERB
fcis-11135	83	28	time	time	NOUN
fcis-11135	83	29	of	of	ADP
fcis-11135	83	30	users	user	NOUN
fcis-11135	83	31	shows	show	VERB
fcis-11135	83	32	a	a	DET
fcis-11135	83	33	significant	significant	ADJ
fcis-11135	83	34	increase	increase	NOUN
fcis-11135	83	35	.	.	PUNCT
fcis-11135	84	1	one	one	NUM
fcis-11135	84	2	possible	possible	ADJ
fcis-11135	84	3	reason	reason	NOUN
fcis-11135	84	4	is	be	AUX
fcis-11135	84	5	that	that	SCONJ
fcis-11135	84	6	users	user	NOUN
fcis-11135	84	7	'	'	PART
fcis-11135	84	8	interest	interest	NOUN
fcis-11135	84	9	in	in	ADP
fcis-11135	84	10	learning	learn	VERB
fcis-11135	84	11	resources	resource	NOUN
fcis-11135	84	12	has	have	AUX
fcis-11135	84	13	increased	increase	VERB
fcis-11135	84	14	,	,	PUNCT
fcis-11135	84	15	and	and	CCONJ
fcis-11135	84	16	recommendation	recommendation	NOUN
fcis-11135	84	17	algorithms	algorithm	NOUN
fcis-11135	84	18	have	have	VERB
fcis-11135	84	19	more	more	ADV
fcis-11135	84	20	accurate	accurate	ADJ
fcis-11135	84	21	analysis	analysis	NOUN
fcis-11135	84	22	and	and	CCONJ
fcis-11135	84	23	judgment	judgment	NOUN
fcis-11135	84	24	of	of	ADP
fcis-11135	84	25	users	user	NOUN
fcis-11135	84	26	after	after	ADP
fcis-11135	84	27	collecting	collect	VERB
fcis-11135	84	28	more	more	ADJ
fcis-11135	84	29	data	datum	NOUN
fcis-11135	84	30	,	,	PUNCT
fcis-11135	84	31	thereby	thereby	ADV
fcis-11135	84	32	stimulating	stimulate	VERB
fcis-11135	84	33	their	their	PRON
fcis-11135	84	34	use	use	NOUN
fcis-11135	84	35	.	.	PUNCT
fcis-11135	85	1	figure	figure	NOUN
fcis-11135	85	2	4	4	NUM
fcis-11135	85	3	.	.	PUNCT
fcis-11135	85	4	user	user	NOUN
fcis-11135	85	5	information	information	PROPN
fcis-11135	85	6	collection	collection	PROPN
fcis-11135	85	7	diagram	diagram	PROPN
fcis-11135	85	8	5.2	5.2	NUM
fcis-11135	85	9	.	.	PUNCT
fcis-11135	86	1	testing	test	VERB
fcis-11135	86	2	the	the	DET
fcis-11135	86	3	hidden	hide	VERB
fcis-11135	86	4	layer	layer	NOUN
fcis-11135	86	5	dimension	dimension	NOUN
fcis-11135	86	6	defines	define	VERB
fcis-11135	86	7	the	the	DET
fcis-11135	86	8	dimension	dimension	NOUN
fcis-11135	86	9	of	of	ADP
fcis-11135	86	10	the	the	DET
fcis-11135	86	11	representation	representation	NOUN
fcis-11135	86	12	of	of	ADP
fcis-11135	86	13	each	each	DET
fcis-11135	86	14	node	node	NOUN
fcis-11135	86	15	in	in	ADP
fcis-11135	86	16	the	the	DET
fcis-11135	86	17	gnn	gnn	PROPN
fcis-11135	86	18	model	model	NOUN
fcis-11135	86	19	.	.	PUNCT
fcis-11135	87	1	as	as	SCONJ
fcis-11135	87	2	shown	show	VERB
fcis-11135	87	3	in	in	ADP
fcis-11135	87	4	the	the	DET
fcis-11135	87	5	above	above	ADJ
fcis-11135	87	6	figure	figure	NOUN
fcis-11135	87	7	,	,	PUNCT
fcis-11135	87	8	a	a	DET
fcis-11135	87	9	smaller	small	ADJ
fcis-11135	87	10	hidden	hide	VERB
fcis-11135	87	11	layer	layer	NOUN
fcis-11135	87	12	dimension	dimension	NOUN
fcis-11135	87	13	may	may	AUX
fcis-11135	87	14	lead	lead	VERB
fcis-11135	87	15	to	to	ADP
fcis-11135	87	16	information	information	NOUN
fcis-11135	87	17	loss	loss	NOUN
fcis-11135	87	18	,	,	PUNCT
fcis-11135	87	19	resulting	result	VERB
fcis-11135	87	20	in	in	ADP
fcis-11135	87	21	underfitting	underfitting	NOUN
fcis-11135	87	22	of	of	ADP
fcis-11135	87	23	the	the	DET
fcis-11135	87	24	model	model	NOUN
fcis-11135	87	25	.	.	PUNCT
fcis-11135	88	1	a	a	DET
fcis-11135	88	2	larger	large	ADJ
fcis-11135	88	3	hidden	hide	VERB
fcis-11135	88	4	layer	layer	NOUN
fcis-11135	88	5	dimension	dimension	NOUN
fcis-11135	88	6	may	may	AUX
fcis-11135	88	7	lead	lead	VERB
fcis-11135	88	8	to	to	ADP
fcis-11135	88	9	too	too	ADV
fcis-11135	88	10	many	many	ADJ
fcis-11135	88	11	parameters	parameter	NOUN
fcis-11135	88	12	,	,	PUNCT
fcis-11135	88	13	increasing	increase	VERB
fcis-11135	88	14	computational	computational	ADJ
fcis-11135	88	15	and	and	CCONJ
fcis-11135	88	16	storage	storage	NOUN
fcis-11135	88	17	costs	cost	NOUN
fcis-11135	88	18	,	,	PUNCT
fcis-11135	88	19	and	and	CCONJ
fcis-11135	88	20	also	also	ADV
fcis-11135	88	21	being	be	AUX
fcis-11135	88	22	prone	prone	ADJ
fcis-11135	88	23	to	to	ADP
fcis-11135	88	24	overfitting	overfitte	VERB
fcis-11135	88	25	.	.	PUNCT
fcis-11135	89	1	we	we	PRON
fcis-11135	89	2	used	use	VERB
fcis-11135	89	3	a	a	DET
fcis-11135	89	4	lot	lot	NOUN
fcis-11135	89	5	of	of	ADP
fcis-11135	89	6	data	datum	NOUN
fcis-11135	89	7	to	to	PART
fcis-11135	89	8	determine	determine	VERB
fcis-11135	89	9	which	which	DET
fcis-11135	89	10	dimension	dimension	NOUN
fcis-11135	89	11	to	to	PART
fcis-11135	89	12	choose	choose	VERB
fcis-11135	89	13	(	(	PUNCT
fcis-11135	89	14	figure	figure	NOUN
fcis-11135	89	15	5	5	NUM
fcis-11135	89	16	)	)	PUNCT
fcis-11135	89	17	figure	figure	NOUN
fcis-11135	89	18	5	5	NUM
fcis-11135	89	19	.	.	PUNCT
fcis-11135	89	20	hidden	hide	VERB
fcis-11135	89	21	layer	layer	NOUN
fcis-11135	89	22	dimension	dimension	NOUN
fcis-11135	89	23	diagram	diagram	NOUN
fcis-11135	89	24	5.3	5.3	NUM
fcis-11135	89	25	.	.	PUNCT
fcis-11135	90	1	experimental	experimental	ADJ
fcis-11135	90	2	results	result	NOUN
fcis-11135	90	3	5.3.1	5.3.1	PROPN
fcis-11135	90	4	.	.	PUNCT
fcis-11135	90	5	test	test	NOUN
fcis-11135	90	6	procedure	procedure	NOUN
fcis-11135	90	7	build	build	VERB
fcis-11135	90	8	a	a	DET
fcis-11135	90	9	learning	learn	VERB
fcis-11135	90	10	resource	resource	NOUN
fcis-11135	90	11	recommendation	recommendation	NOUN
fcis-11135	90	12	system	system	NOUN
fcis-11135	90	13	based	base	VERB
fcis-11135	90	14	on	on	ADP
fcis-11135	90	15	user	user	NOUN
fcis-11135	90	16	habits	habit	NOUN
fcis-11135	90	17	,	,	PUNCT
fcis-11135	90	18	including	include	VERB
fcis-11135	90	19	user	user	NOUN
fcis-11135	90	20	information	information	NOUN
fcis-11135	90	21	collection	collection	NOUN
fcis-11135	90	22	,	,	PUNCT
fcis-11135	90	23	and	and	CCONJ
fcis-11135	90	24	the	the	DET
fcis-11135	90	25	data	data	NOUN
fcis-11135	90	26	graph	graph	NOUN
fcis-11135	90	27	is	be	AUX
fcis-11135	90	28	the	the	DET
fcis-11135	90	29	data	data	NOUN
fcis-11135	90	30	representation	representation	NOUN
fcis-11135	90	31	of	of	ADP
fcis-11135	90	32	gnn	gnn	PROPN
fcis-11135	90	33	compared	compare	VERB
fcis-11135	90	34	with	with	ADP
fcis-11135	90	35	other	other	ADJ
fcis-11135	90	36	models	model	NOUN
fcis-11135	90	37	.	.	PUNCT
fcis-11135	91	1	from	from	ADP
fcis-11135	91	2	it	it	PRON
fcis-11135	91	3	,	,	PUNCT
fcis-11135	91	4	we	we	PRON
fcis-11135	91	5	can	can	AUX
fcis-11135	91	6	see	see	VERB
fcis-11135	91	7	that	that	SCONJ
fcis-11135	91	8	gnn	gnn	PROPN
fcis-11135	91	9	can	can	AUX
fcis-11135	91	10	generally	generally	ADV
fcis-11135	91	11	achieve	achieve	VERB
fcis-11135	91	12	better	well	ADJ
fcis-11135	91	13	performance	performance	NOUN
fcis-11135	91	14	than	than	ADP
fcis-11135	91	15	traditional	traditional	ADJ
fcis-11135	91	16	machine	machine	NOUN
fcis-11135	91	17	learning	learn	VERB
fcis-11135	91	18	algorithms	algorithm	NOUN
fcis-11135	91	19	based	base	VERB
fcis-11135	91	20	on	on	ADP
fcis-11135	91	21	feature	feature	NOUN
fcis-11135	91	22	engineering	engineering	NOUN
fcis-11135	91	23	when	when	SCONJ
fcis-11135	91	24	processing	processing	NOUN
fcis-11135	91	25	graph	graph	NOUN
fcis-11135	91	26	structure	structure	NOUN
fcis-11135	91	27	data	datum	NOUN
fcis-11135	91	28	.	.	PUNCT
fcis-11135	92	1	gnn	gnn	PROPN
fcis-11135	92	2	can	can	AUX
fcis-11135	92	3	automatically	automatically	ADV
fcis-11135	92	4	learn	learn	VERB
fcis-11135	92	5	the	the	DET
fcis-11135	92	6	representation	representation	NOUN
fcis-11135	92	7	of	of	ADP
fcis-11135	92	8	nodes	node	NOUN
fcis-11135	92	9	and	and	CCONJ
fcis-11135	92	10	edges	edge	NOUN
fcis-11135	92	11	from	from	ADP
fcis-11135	92	12	data	datum	NOUN
fcis-11135	92	13	,	,	PUNCT
fcis-11135	92	14	and	and	CCONJ
fcis-11135	92	15	capture	capture	VERB
fcis-11135	92	16	the	the	DET
fcis-11135	92	17	relationships	relationship	NOUN
fcis-11135	92	18	between	between	ADP
fcis-11135	92	19	nodes	node	NOUN
fcis-11135	92	20	through	through	ADP
fcis-11135	92	21	information	information	NOUN
fcis-11135	92	22	transmission	transmission	NOUN
fcis-11135	92	23	and	and	CCONJ
fcis-11135	92	24	aggregation	aggregation	NOUN
fcis-11135	92	25	.	.	PUNCT
fcis-11135	93	1	5.3.2	5.3.2	X
fcis-11135	93	2	.	.	PUNCT
fcis-11135	94	1	result	result	NOUN
fcis-11135	94	2	verification	verification	NOUN
fcis-11135	94	3	experimental	experimental	ADJ
fcis-11135	94	4	verification	verification	NOUN
fcis-11135	94	5	:	:	PUNCT
fcis-11135	94	6	through	through	ADP
fcis-11135	94	7	experiments	experiment	NOUN
fcis-11135	94	8	,	,	PUNCT
fcis-11135	94	9	after	after	ADP
fcis-11135	94	10	65	65	NUM
fcis-11135	94	11	continuous	continuous	ADJ
fcis-11135	94	12	iteration	iteration	NOUN
fcis-11135	94	13	and	and	CCONJ
fcis-11135	94	14	training	training	NOUN
fcis-11135	94	15	,	,	PUNCT
fcis-11135	94	16	the	the	DET
fcis-11135	94	17	recommendation	recommendation	NOUN
fcis-11135	94	18	algorithm	algorithm	NOUN
fcis-11135	94	19	is	be	AUX
fcis-11135	94	20	optimized	optimize	VERB
fcis-11135	94	21	to	to	PART
fcis-11135	94	22	improve	improve	VERB
fcis-11135	94	23	recommendation	recommendation	NOUN
fcis-11135	94	24	accuracy	accuracy	NOUN
fcis-11135	94	25	and	and	CCONJ
fcis-11135	94	26	user	user	NOUN
fcis-11135	94	27	satisfaction	satisfaction	NOUN
fcis-11135	94	28	(	(	PUNCT
fcis-11135	94	29	table	table	NOUN
fcis-11135	94	30	1	1	NUM
fcis-11135	94	31	)	)	PUNCT
fcis-11135	94	32	.	.	PUNCT
fcis-11135	95	1	table	table	NOUN
fcis-11135	95	2	1	1	NUM
fcis-11135	95	3	.	.	X
fcis-11135	95	4	comparison	comparison	NOUN
fcis-11135	95	5	between	between	ADP
fcis-11135	95	6	gnn	gnn	PROPN
fcis-11135	95	7	and	and	CCONJ
fcis-11135	95	8	other	other	ADJ
fcis-11135	95	9	models	model	NOUN
fcis-11135	95	10	data	datum	NOUN
fcis-11135	95	11	set	set	VERB
fcis-11135	95	12	model	model	NOUN
fcis-11135	95	13	accuracy	accuracy	PROPN
fcis-11135	95	14	local	local	ADJ
fcis-11135	95	15	receptive	receptive	ADJ
fcis-11135	95	16	process	process	NOUN
fcis-11135	95	17	graph	graph	NOUN
fcis-11135	95	18	data	datum	NOUN
fcis-11135	95	19	traditional	traditional	ADJ
fcis-11135	95	20	machine	machine	NOUN
fcis-11135	95	21	learning	learn	VERB
fcis-11135	95	22	algorithms	algorithm	VERB
fcis-11135	95	23	0.76823	0.76823	NUM
fcis-11135	95	24	0.5624	0.5624	NUM
fcis-11135	95	25	1.5419	1.5419	NUM
fcis-11135	95	26	cnn	cnn	NOUN
fcis-11135	95	27	0.75695	0.75695	NUM
fcis-11135	95	28	0.5495	0.5495	NUM
fcis-11135	95	29	1.5942	1.5942	NUM
fcis-11135	95	30	rnn	rnn	VERB
fcis-11135	95	31	0.75261	0.75261	NUM
fcis-11135	95	32	0.5689	0.5689	NUM
fcis-11135	95	33	1.5913	1.5913	NUM
fcis-11135	95	34	attention	attention	NOUN
fcis-11135	95	35	mechanism	mechanism	NOUN
fcis-11135	95	36	0.81656	0.81656	NUM
fcis-11135	95	37	0.5974	0.5974	NUM
fcis-11135	95	38	1.4159	1.4159	NUM
fcis-11135	95	39	gnn	gnn	NOUN
fcis-11135	95	40	0.82459	0.82459	NUM
fcis-11135	95	41	0.6912	0.6912	NUM
fcis-11135	95	42	1.6962	1.6962	NUM
fcis-11135	95	43	total	total	NOUN
fcis-11135	95	44	3.91894	3.91894	NUM
fcis-11135	95	45	2.9694	2.9694	NUM
fcis-11135	95	46	7.8395	7.8395	NUM
fcis-11135	95	47	6	6	NUM
fcis-11135	95	48	.	.	PUNCT
fcis-11135	96	1	conclusion	conclusion	VERB
fcis-11135	96	2	traditional	traditional	ADJ
fcis-11135	96	3	recommendation	recommendation	NOUN
fcis-11135	96	4	systems	system	NOUN
fcis-11135	96	5	mostly	mostly	ADV
fcis-11135	96	6	use	use	VERB
fcis-11135	96	7	convolutional	convolutional	ADJ
fcis-11135	96	8	neural	neural	ADJ
fcis-11135	96	9	network	network	NOUN
fcis-11135	96	10	(	(	PUNCT
fcis-11135	96	11	cnn	cnn	PROPN
fcis-11135	96	12	)	)	PUNCT
fcis-11135	96	13	to	to	PART
fcis-11135	96	14	achieve	achieve	VERB
fcis-11135	96	15	simple	simple	ADJ
fcis-11135	96	16	image	image	NOUN
fcis-11135	96	17	data	data	NOUN
fcis-11135	96	18	collection	collection	NOUN
fcis-11135	96	19	for	for	ADP
fcis-11135	96	20	recommendation	recommendation	NOUN
fcis-11135	96	21	,	,	PUNCT
fcis-11135	96	22	but	but	CCONJ
fcis-11135	96	23	we	we	PRON
fcis-11135	96	24	are	be	AUX
fcis-11135	96	25	a	a	DET
fcis-11135	96	26	gnn	gnn	NOUN
fcis-11135	96	27	based	base	VERB
fcis-11135	96	28	recommendation	recommendation	NOUN
fcis-11135	96	29	system	system	NOUN
fcis-11135	96	30	based	base	VERB
fcis-11135	96	31	on	on	ADP
fcis-11135	96	32	user	user	NOUN
fcis-11135	96	33	habits	habit	NOUN
fcis-11135	96	34	.	.	PUNCT
fcis-11135	97	1	our	our	PRON
fcis-11135	97	2	software	software	NOUN
fcis-11135	97	3	can	can	AUX
fcis-11135	97	4	handle	handle	VERB
fcis-11135	97	5	more	more	ADJ
fcis-11135	97	6	complex	complex	ADJ
fcis-11135	97	7	relationships	relationship	NOUN
fcis-11135	97	8	and	and	CCONJ
fcis-11135	97	9	images	image	NOUN
fcis-11135	97	10	using	use	VERB
fcis-11135	97	11	gnn	gnn	NOUN
fcis-11135	97	12	,	,	PUNCT
fcis-11135	97	13	and	and	CCONJ
fcis-11135	97	14	gnn	gnn	PROPN
fcis-11135	97	15	can	can	AUX
fcis-11135	97	16	carry	carry	VERB
fcis-11135	97	17	out	out	ADP
fcis-11135	97	18	end	end	NOUN
fcis-11135	97	19	-	-	PUNCT
fcis-11135	97	20	to	to	ADP
fcis-11135	97	21	-	-	PUNCT
fcis-11135	97	22	end	end	NOUN
fcis-11135	97	23	learning	learning	NOUN
fcis-11135	97	24	without	without	ADP
fcis-11135	97	25	manually	manually	ADV
fcis-11135	97	26	designing	design	VERB
fcis-11135	97	27	features	feature	NOUN
fcis-11135	97	28	,	,	PUNCT
fcis-11135	97	29	which	which	PRON
fcis-11135	97	30	makes	make	VERB
fcis-11135	97	31	us	we	PRON
fcis-11135	97	32	more	more	ADV
fcis-11135	97	33	competitive	competitive	ADJ
fcis-11135	97	34	in	in	ADP
fcis-11135	97	35	the	the	DET
fcis-11135	97	36	market	market	NOUN
fcis-11135	97	37	;	;	PUNCT
fcis-11135	97	38	traditional	traditional	ADJ
fcis-11135	97	39	recommendation	recommendation	NOUN
fcis-11135	97	40	systems	system	NOUN
fcis-11135	97	41	only	only	ADV
fcis-11135	97	42	recommend	recommend	VERB
fcis-11135	97	43	a	a	DET
fcis-11135	97	44	class	class	NOUN
fcis-11135	97	45	of	of	ADP
fcis-11135	97	46	resources	resource	NOUN
fcis-11135	97	47	that	that	PRON
fcis-11135	97	48	users	user	NOUN
fcis-11135	97	49	often	often	ADV
fcis-11135	97	50	browse	browse	VERB
fcis-11135	97	51	.	.	PUNCT
fcis-11135	98	1	the	the	DET
fcis-11135	98	2	most	most	ADV
fcis-11135	98	3	obvious	obvious	ADJ
fcis-11135	98	4	example	example	NOUN
fcis-11135	98	5	is	be	AUX
fcis-11135	98	6	the	the	DET
fcis-11135	98	7	tiktok	tiktok	ADJ
fcis-11135	98	8	recommendation	recommendation	NOUN
fcis-11135	98	9	system	system	NOUN
fcis-11135	98	10	.	.	PUNCT
fcis-11135	99	1	the	the	DET
fcis-11135	99	2	videos	video	NOUN
fcis-11135	99	3	recommended	recommend	VERB
fcis-11135	99	4	by	by	ADP
fcis-11135	99	5	it	it	PRON
fcis-11135	99	6	are	be	AUX
fcis-11135	99	7	easy	easy	ADJ
fcis-11135	99	8	to	to	PART
fcis-11135	99	9	solidify	solidify	VERB
fcis-11135	99	10	into	into	ADP
fcis-11135	99	11	a	a	DET
fcis-11135	99	12	class	class	NOUN
fcis-11135	99	13	and	and	CCONJ
fcis-11135	99	14	difficult	difficult	ADJ
fcis-11135	99	15	to	to	PART
fcis-11135	99	16	broaden	broaden	VERB
fcis-11135	99	17	,	,	PUNCT
fcis-11135	99	18	which	which	PRON
fcis-11135	99	19	will	will	AUX
fcis-11135	99	20	only	only	ADV
fcis-11135	99	21	trap	trap	VERB
fcis-11135	99	22	users	user	NOUN
fcis-11135	99	23	in	in	ADP
fcis-11135	99	24	a	a	DET
fcis-11135	99	25	single	single	ADJ
fcis-11135	99	26	interest	interest	NOUN
fcis-11135	99	27	circle	circle	NOUN
fcis-11135	99	28	.	.	PUNCT
fcis-11135	100	1	our	our	PRON
fcis-11135	100	2	recommendation	recommendation	NOUN
fcis-11135	100	3	system	system	NOUN
fcis-11135	100	4	will	will	AUX
fcis-11135	100	5	predict	predict	VERB
fcis-11135	100	6	the	the	DET
fcis-11135	100	7	learning	learning	NOUN
fcis-11135	100	8	resources	resource	NOUN
fcis-11135	100	9	that	that	SCONJ
fcis-11135	100	10	users	user	NOUN
fcis-11135	100	11	are	be	AUX
fcis-11135	100	12	interested	interested	ADJ
fcis-11135	100	13	in	in	ADP
fcis-11135	100	14	and	and	CCONJ
fcis-11135	100	15	make	make	VERB
fcis-11135	100	16	recommendations	recommendation	NOUN
fcis-11135	100	17	.	.	PUNCT
fcis-11135	101	1	if	if	SCONJ
fcis-11135	101	2	users	user	NOUN
fcis-11135	101	3	browse	browse	VERB
fcis-11135	101	4	,	,	PUNCT
fcis-11135	101	5	our	our	PRON
fcis-11135	101	6	algorithm	algorithm	NOUN
fcis-11135	101	7	will	will	AUX
fcis-11135	101	8	identify	identify	VERB
fcis-11135	101	9	,	,	PUNCT
fcis-11135	101	10	then	then	ADV
fcis-11135	101	11	add	add	VERB
fcis-11135	101	12	such	such	ADJ
fcis-11135	101	13	resources	resource	NOUN
fcis-11135	101	14	to	to	ADP
fcis-11135	101	15	the	the	DET
fcis-11135	101	16	user	user	NOUN
fcis-11135	101	17	interest	interest	NOUN
fcis-11135	101	18	library	library	NOUN
fcis-11135	101	19	and	and	CCONJ
fcis-11135	101	20	recommend	recommend	VERB
fcis-11135	101	21	this	this	DET
fcis-11135	101	22	type	type	NOUN
fcis-11135	101	23	of	of	ADP
fcis-11135	101	24	resource	resource	NOUN
fcis-11135	101	25	.	.	PUNCT
fcis-11135	102	1	and	and	CCONJ
fcis-11135	102	2	our	our	PRON
fcis-11135	102	3	system	system	NOUN
fcis-11135	102	4	will	will	AUX
fcis-11135	102	5	intelligently	intelligently	ADV
fcis-11135	102	6	identify	identify	VERB
fcis-11135	102	7	the	the	DET
fcis-11135	102	8	resources	resource	NOUN
fcis-11135	102	9	that	that	PRON
fcis-11135	102	10	users	user	NOUN
fcis-11135	102	11	are	be	AUX
fcis-11135	102	12	browsing	browse	VERB
fcis-11135	102	13	and	and	CCONJ
fcis-11135	102	14	correct	correct	VERB
fcis-11135	102	15	them	they	PRON
fcis-11135	102	16	,	,	PUNCT
fcis-11135	102	17	achieving	achieve	VERB
fcis-11135	102	18	the	the	DET
fcis-11135	102	19	effect	effect	NOUN
fcis-11135	102	20	of	of	ADP
fcis-11135	102	21	pushing	push	VERB
fcis-11135	102	22	positive	positive	ADJ
fcis-11135	102	23	energy	energy	NOUN
fcis-11135	102	24	resources	resource	NOUN
fcis-11135	102	25	to	to	ADP
fcis-11135	102	26	users	user	NOUN
fcis-11135	102	27	.	.	PUNCT
fcis-11135	103	1	references	reference	NOUN
fcis-11135	103	2	[	[	X
fcis-11135	103	3	1	1	NUM
fcis-11135	103	4	]	]	PUNCT
fcis-11135	103	5	lehman	lehman	PROPN
fcis-11135	103	6	a	a	PROPN
fcis-11135	103	7	,	,	PUNCT
fcis-11135	103	8	miller	miller	PROPN
fcis-11135	103	9	s	s	PART
fcis-11135	103	10	j.a	j.a	PROPN
fcis-11135	103	11	theoretical	theoretical	ADJ
fcis-11135	103	12	conversation	conversation	NOUN
fcis-11135	103	13	about	about	ADP
fcis-11135	103	14	responses	response	NOUN
fcis-11135	103	15	to	to	ADP
fcis-11135	103	16	information	information	NOUN
fcis-11135	103	17	overload	overload	NOUN
fcis-11135	103	18	[	[	X
fcis-11135	103	19	j].information,2020,11	j].information,2020,11	NOUN
fcis-11135	103	20	(	(	PUNCT
fcis-11135	103	21	8)	8)	NUM
fcis-11135	103	22	:	:	PUNCT
fcis-11135	103	23	379	379	NUM
fcis-11135	103	24	-	-	SYM
fcis-11135	103	25	389	389	NUM
fcis-11135	103	26	.	.	PUNCT
fcis-11135	104	1	[	[	X
fcis-11135	104	2	2	2	NUM
fcis-11135	104	3	]	]	X
fcis-11135	104	4	zhou	zhou	PROPN
fcis-11135	104	5	j	j	PROPN
fcis-11135	104	6	,	,	PUNCT
fcis-11135	104	7	cui	cui	VERB
fcis-11135	104	8	g	g	PROPN
fcis-11135	104	9	,	,	PUNCT
fcis-11135	104	10	zhang	zhang	PROPN
fcis-11135	104	11	z	z	PROPN
fcis-11135	104	12	,	,	PUNCT
fcis-11135	104	13	et	et	PROPN
fcis-11135	104	14	al.graph	al.graph	PROPN
fcis-11135	104	15	neural	neural	PROPN
fcis-11135	104	16	networks	network	NOUN
fcis-11135	104	17	a	a	DET
fcis-11135	104	18	review	review	NOUN
fcis-11135	104	19	of	of	ADP
fcis-11135	104	20	methods	method	NOUN
fcis-11135	104	21	and	and	CCONJ
fcis-11135	104	22	applications[j	applications[j	NOUN
fcis-11135	104	23	]	]	PUNCT
fcis-11135	104	24	.	.	PUNCT
fcis-11135	105	1	arxiv	arxiv	NOUN
fcis-11135	105	2	:	:	PUNCT
fcis-11135	105	3	1812	1812	NUM
fcis-11135	105	4	.	.	PUNCT
fcis-11135	106	1	08434	08434	NUM
fcis-11135	106	2	,	,	PUNCT
fcis-11135	106	3	2018	2018	NUM
fcis-11135	106	4	.	.	PUNCT
fcis-11135	107	1	[	[	X
fcis-11135	107	2	3	3	X
fcis-11135	107	3	]	]	X
fcis-11135	107	4	vaswani	vaswani	NOUN
fcis-11135	107	5	a	a	PRON
fcis-11135	107	6	,	,	PUNCT
fcis-11135	107	7	shazeer	shazeer	NOUN
fcis-11135	107	8	n	n	SYM
fcis-11135	107	9	,	,	PUNCT
fcis-11135	107	10	parmar	parmar	PROPN
fcis-11135	107	11	n	n	CCONJ
fcis-11135	107	12	,	,	PUNCT
fcis-11135	107	13	et	et	NOUN
fcis-11135	107	14	al.attention	al.attention	NOUN
fcis-11135	107	15	is	be	AUX
fcis-11135	107	16	all	all	PRON
fcis-11135	107	17	you	you	PRON
fcis-11135	107	18	need	need	VERB
fcis-11135	107	19	[	[	X
fcis-11135	107	20	c]/	c]/	NOUN
fcis-11135	107	21	/advances	/advances	PUNCT
fcis-11135	107	22	in	in	ADP
fcis-11135	107	23	neural	neural	ADJ
fcis-11135	107	24	information	information	NOUN
fcis-11135	107	25	processing	process	VERB
fcis-11135	107	26	systems.long	systems.long	PROPN
fcis-11135	107	27	beach	beach	NOUN
fcis-11135	107	28	:	:	PUNCT
fcis-11135	107	29	curran	curran	PROPN
fcis-11135	107	30	associates	associates	PROPN
fcis-11135	107	31	,	,	PUNCT
fcis-11135	107	32	inc,2017	inc,2017	NUM
fcis-11135	107	33	:	:	PUNCT
fcis-11135	107	34	6000	6000	NUM
fcis-11135	107	35	-	-	SYM
fcis-11135	107	36	6010	6010	NUM
fcis-11135	107	37	.	.	PUNCT
fcis-11135	108	1	[	[	X
fcis-11135	108	2	4	4	NUM
fcis-11135	108	3	]	]	X
fcis-11135	108	4	cheng	cheng	PROPN
fcis-11135	108	5	z	z	PROPN
fcis-11135	108	6	y	y	PROPN
fcis-11135	108	7	,	,	PUNCT
fcis-11135	108	8	ding	de	VERB
fcis-11135	108	9	y	y	PROPN
fcis-11135	108	10	,	,	PUNCT
fcis-11135	108	11	he	he	PRON
fcis-11135	108	12	x	x	SYM
fcis-11135	108	13	n	n	CCONJ
fcis-11135	108	14	,	,	PUNCT
fcis-11135	108	15	et	et	PROPN
fcis-11135	108	16	al.a^3ncf	al.a^3ncf	VERB
fcis-11135	108	17	:	:	PUNCT
fcis-11135	108	18	an	an	DET
fcis-11135	108	19	adaptive	adaptive	ADJ
fcis-11135	108	20	aspect	aspect	NOUN
fcis-11135	108	21	attention	attention	NOUN
fcis-11135	108	22	model	model	NOUN
fcis-11135	108	23	for	for	ADP
fcis-11135	108	24	rating	rating	NOUN
fcis-11135	108	25	prediction[c]/	prediction[c]/	NOUN
fcis-11135	108	26	/proceedings	/proceeding	NOUN
fcis-11135	108	27	of	of	ADP
fcis-11135	108	28	the	the	DET
fcis-11135	108	29	27th	27th	ADJ
fcis-11135	108	30	international	international	ADJ
fcis-11135	108	31	joint	joint	ADJ
fcis-11135	108	32	conference	conference	NOUN
fcis-11135	108	33	on	on	ADP
fcis-11135	108	34	artificial	artificial	ADJ
fcis-11135	108	35	intelligence	intelligence	NOUN
fcis-11135	108	36	.	.	PUNCT
fcis-11135	109	1	louisiana	louisiana	PROPN
fcis-11135	109	2	:	:	PUNCT
fcis-11135	109	3	aaai,2018	aaai,2018	NOUN
fcis-11135	109	4	:	:	PUNCT
fcis-11135	109	5	3748	3748	NUM
fcis-11135	109	6	-	-	SYM
fcis-11135	109	7	3754	3754	NUM
fcis-11135	109	8	.	.	PUNCT
fcis-11135	110	1	[	[	X
fcis-11135	110	2	5	5	X
fcis-11135	110	3	]	]	X
fcis-11135	110	4	pei	pei	PROPN
fcis-11135	110	5	w	w	PROPN
fcis-11135	110	6	j	j	PROPN
fcis-11135	110	7	,	,	PUNCT
fcis-11135	110	8	yang	yang	PROPN
fcis-11135	110	9	j	j	PROPN
fcis-11135	110	10	,	,	PUNCT
fcis-11135	110	11	sun	sun	PROPN
fcis-11135	110	12	z	z	PROPN
fcis-11135	110	13	,	,	PUNCT
fcis-11135	110	14	et	et	NOUN
fcis-11135	110	15	al.interacting	al.interacte	VERB
fcis-11135	110	16	attention	attention	NOUN
fcis-11135	110	17	-	-	PUNCT
fcis-11135	110	18	gated	gate	VERB
fcis-11135	110	19	recurrent	recurrent	ADJ
fcis-11135	110	20	networks	network	NOUN
fcis-11135	110	21	for	for	ADP
fcis-11135	110	22	recommendatio	recommendatio	NOUN
fcis-11135	110	23	[	[	X
fcis-11135	110	24	c]/	c]/	NOUN
fcis-11135	110	25	/	/	SYM
fcis-11135	110	26	proceedings	proceeding	NOUN
fcis-11135	110	27	of	of	ADP
fcis-11135	110	28	the	the	DET
fcis-11135	110	29	2017	2017	NUM
fcis-11135	110	30	acm	acm	NOUN
fcis-11135	110	31	on	on	ADP
fcis-11135	110	32	conference	conference	NOUN
fcis-11135	110	33	on	on	ADP
fcis-11135	110	34	information	information	NOUN
fcis-11135	110	35	and	and	CCONJ
fcis-11135	110	36	knowledge	knowledge	NOUN
fcis-11135	110	37	management	management	NOUN
fcis-11135	110	38	.	.	PUNCT
fcis-11135	111	1	singapore	singapore	PROPN
fcis-11135	111	2	:	:	PUNCT
fcis-11135	111	3	acm,2017	acm,2017	NUM
fcis-11135	111	4	:	:	PUNCT
fcis-11135	111	5	1459	1459	NUM
fcis-11135	111	6	-	-	SYM
fcis-11135	111	7	14	14	NUM
fcis-11135	111	8	.	.	PUNCT