id	sid	tid	token	lemma	pos
cana-660	1	1	communications	communication	NOUN
cana-660	1	2	on	on	ADP
cana-660	1	3	applied	apply	VERB
cana-660	1	4	nonlinear	nonlinear	ADJ
cana-660	1	5	analysis	analysis	NOUN
cana-660	1	6	issn	issn	NOUN
cana-660	1	7	:	:	PUNCT
cana-660	1	8	1074	1074	NUM
cana-660	1	9	-	-	PUNCT
cana-660	1	10	133x	133x	NUM
cana-660	1	11	vol	vol	NOUN
cana-660	1	12	31	31	NUM
cana-660	1	13	no	no	NOUN
cana-660	1	14	.	.	PUNCT
cana-660	2	1	2s	2s	NUM
cana-660	2	2	(	(	PUNCT
cana-660	2	3	2024	2024	NUM
cana-660	2	4	)	)	PUNCT
cana-660	2	5	454	454	NUM
cana-660	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	2	7	embedding	embed	VERB
cana-660	2	8	hybrid	hybrid	ADJ
cana-660	2	9	evolutionary	evolutionary	ADJ
cana-660	2	10	approach	approach	NOUN
cana-660	2	11	for	for	ADP
cana-660	2	12	learning	learning	NOUN
cana-660	2	13	-	-	PUNCT
cana-660	2	14	to	to	ADP
cana-660	2	15	-	-	PUNCT
cana-660	2	16	rank	rank	NOUN
cana-660	2	17	computation	computation	NOUN
cana-660	2	18	for	for	ADP
cana-660	2	19	the	the	DET
cana-660	2	20	selection	selection	NOUN
cana-660	2	21	of	of	ADP
cana-660	2	22	features	feature	NOUN
cana-660	2	23	using	use	VERB
cana-660	2	24	machine	machine	NOUN
cana-660	2	25	learning	learn	VERB
cana-660	2	26	sushilkumar	sushilkumar	PROPN
cana-660	2	27	chavhan1	chavhan1	PROPN
cana-660	2	28	*	*	PROPN
cana-660	2	29	,	,	PUNCT
cana-660	2	30	r.	r.	PROPN
cana-660	2	31	c.	c.	PROPN
cana-660	2	32	dharmik	dharmik	VERB
cana-660	2	33	2	2	NUM
cana-660	2	34	1,2	1,2	NUM
cana-660	2	35	department	department	NOUN
cana-660	2	36	of	of	ADP
cana-660	2	37	information	information	NOUN
cana-660	2	38	technology	technology	NOUN
cana-660	2	39	,	,	PUNCT
cana-660	2	40	yeshwantrao	yeshwantrao	NOUN
cana-660	2	41	chavan	chavan	PROPN
cana-660	2	42	college	college	PROPN
cana-660	2	43	of	of	ADP
cana-660	2	44	engineering	engineering	NOUN
cana-660	2	45	,	,	PUNCT
cana-660	2	46	nagpur	nagpur	PROPN
cana-660	2	47	,	,	PUNCT
cana-660	2	48	maharashtra	maharashtra	PROPN
cana-660	2	49	,	,	PUNCT
cana-660	2	50	schavhansushil@gmail.com1,raj_dharmik@yahoo.com2	schavhansushil@gmail.com1,raj_dharmik@yahoo.com2	PROPN
cana-660	2	51	article	article	NOUN
cana-660	2	52	history	history	NOUN
cana-660	2	53	:	:	PUNCT
cana-660	2	54	received	receive	VERB
cana-660	2	55	:	:	PUNCT
cana-660	2	56	20	20	NUM
cana-660	2	57	-	-	SYM
cana-660	2	58	03	03	NUM
cana-660	2	59	-	-	PUNCT
cana-660	2	60	2024	2024	NUM
cana-660	2	61	revised	revise	VERB
cana-660	2	62	:	:	PUNCT
cana-660	2	63	12	12	NUM
cana-660	2	64	-	-	SYM
cana-660	2	65	05	05	NUM
cana-660	2	66	-	-	PUNCT
cana-660	2	67	2024	2024	NUM
cana-660	2	68	accepted	accept	VERB
cana-660	2	69	:	:	PUNCT
cana-660	2	70	25	25	NUM
cana-660	2	71	-	-	PUNCT
cana-660	2	72	05	05	NUM
cana-660	2	73	-	-	PUNCT
cana-660	2	74	2024	2024	NUM
cana-660	2	75	abstract	abstract	NOUN
cana-660	2	76	:	:	PUNCT
cana-660	2	77	our	our	PRON
cana-660	2	78	study	study	NOUN
cana-660	2	79	proposes	propose	VERB
cana-660	2	80	a	a	DET
cana-660	2	81	novel	novel	ADJ
cana-660	2	82	model	model	NOUN
cana-660	2	83	for	for	ADP
cana-660	2	84	retrieving	retrieve	VERB
cana-660	2	85	objects	object	NOUN
cana-660	2	86	that	that	PRON
cana-660	2	87	utilizes	utilize	VERB
cana-660	2	88	learning	learning	NOUN
cana-660	2	89	-	-	PUNCT
cana-660	2	90	to	to	AUX
cana-660	2	91	-	-	PUNCT
cana-660	2	92	rank	rank	NOUN
cana-660	2	93	with	with	ADP
cana-660	2	94	l2	l2	NOUN
cana-660	2	95	regularization	regularization	NOUN
cana-660	2	96	.	.	PUNCT
cana-660	3	1	we	we	PRON
cana-660	3	2	employed	employ	VERB
cana-660	3	3	an	an	DET
cana-660	3	4	evolutionary	evolutionary	ADJ
cana-660	3	5	-	-	PUNCT
cana-660	3	6	based	base	VERB
cana-660	3	7	simulated	simulated	ADJ
cana-660	3	8	annealing	annealing	NOUN
cana-660	3	9	technique	technique	NOUN
cana-660	3	10	to	to	PART
cana-660	3	11	select	select	VERB
cana-660	3	12	the	the	DET
cana-660	3	13	most	most	ADV
cana-660	3	14	informative	informative	ADJ
cana-660	3	15	features	feature	NOUN
cana-660	3	16	for	for	ADP
cana-660	3	17	our	our	PRON
cana-660	3	18	system	system	NOUN
cana-660	3	19	and	and	CCONJ
cana-660	3	20	utilized	utilize	VERB
cana-660	3	21	a	a	DET
cana-660	3	22	standardized	standardized	ADJ
cana-660	3	23	regulation	regulation	NOUN
cana-660	3	24	technique	technique	NOUN
cana-660	3	25	to	to	PART
cana-660	3	26	handle	handle	VERB
cana-660	3	27	the	the	DET
cana-660	3	28	dropout	dropout	NOUN
cana-660	3	29	of	of	ADP
cana-660	3	30	active	active	ADJ
cana-660	3	31	features	feature	NOUN
cana-660	3	32	.	.	PUNCT
cana-660	4	1	learning	learn	VERB
cana-660	4	2	to	to	PART
cana-660	4	3	rank	rank	VERB
cana-660	4	4	is	be	AUX
cana-660	4	5	a	a	DET
cana-660	4	6	well	well	ADV
cana-660	4	7	-	-	PUNCT
cana-660	4	8	researched	research	VERB
cana-660	4	9	area	area	NOUN
cana-660	4	10	in	in	ADP
cana-660	4	11	machine	machine	NOUN
cana-660	4	12	learning	learning	NOUN
cana-660	4	13	and	and	CCONJ
cana-660	4	14	finds	find	VERB
cana-660	4	15	application	application	NOUN
cana-660	4	16	in	in	ADP
cana-660	4	17	recommendation	recommendation	NOUN
cana-660	4	18	systems	system	NOUN
cana-660	4	19	and	and	CCONJ
cana-660	4	20	search	search	NOUN
cana-660	4	21	engines	engine	NOUN
cana-660	4	22	.	.	PUNCT
cana-660	5	1	our	our	PRON
cana-660	5	2	study	study	NOUN
cana-660	5	3	aims	aim	VERB
cana-660	5	4	to	to	PART
cana-660	5	5	introduce	introduce	VERB
cana-660	5	6	a	a	DET
cana-660	5	7	new	new	ADJ
cana-660	5	8	approach	approach	NOUN
cana-660	5	9	to	to	ADP
cana-660	5	10	feature	feature	NOUN
cana-660	5	11	selection	selection	NOUN
cana-660	5	12	for	for	ADP
cana-660	5	13	the	the	DET
cana-660	5	14	learning	learning	NOUN
cana-660	5	15	-	-	PUNCT
cana-660	5	16	to	to	ADP
cana-660	5	17	-	-	PUNCT
cana-660	5	18	rank	rank	NOUN
cana-660	5	19	information	information	NOUN
cana-660	5	20	retrieval	retrieval	NOUN
cana-660	5	21	model	model	NOUN
cana-660	5	22	.	.	PUNCT
cana-660	6	1	by	by	ADP
cana-660	6	2	dropping	drop	VERB
cana-660	6	3	inactive	inactive	ADJ
cana-660	6	4	features	feature	NOUN
cana-660	6	5	and	and	CCONJ
cana-660	6	6	maintaining	maintain	VERB
cana-660	6	7	active	active	ADJ
cana-660	6	8	features	feature	NOUN
cana-660	6	9	,	,	PUNCT
cana-660	6	10	we	we	PRON
cana-660	6	11	can	can	AUX
cana-660	6	12	improve	improve	VERB
cana-660	6	13	the	the	DET
cana-660	6	14	ranking	rank	VERB
cana-660	6	15	function	function	NOUN
cana-660	6	16	’s	’s	PART
cana-660	6	17	performance	performance	NOUN
cana-660	6	18	.	.	PUNCT
cana-660	7	1	we	we	PRON
cana-660	7	2	tested	test	VERB
cana-660	7	3	our	our	PRON
cana-660	7	4	proposed	propose	VERB
cana-660	7	5	method	method	NOUN
cana-660	7	6	on	on	ADP
cana-660	7	7	standard	standard	ADJ
cana-660	7	8	datasets	dataset	NOUN
cana-660	7	9	and	and	CCONJ
cana-660	7	10	repeatedly	repeatedly	ADV
cana-660	7	11	improved	improve	VERB
cana-660	7	12	the	the	DET
cana-660	7	13	feature	feature	NOUN
cana-660	7	14	selection	selection	NOUN
cana-660	7	15	model	model	NOUN
cana-660	7	16	of	of	ADP
cana-660	7	17	the	the	DET
cana-660	7	18	lambdamart	lambdamart	PROPN
cana-660	7	19	algorithm	algorithm	PROPN
cana-660	7	20	.	.	PUNCT
cana-660	8	1	empirical	empirical	ADJ
cana-660	8	2	performance	performance	NOUN
cana-660	8	3	results	result	NOUN
cana-660	8	4	show	show	VERB
cana-660	8	5	that	that	SCONJ
cana-660	8	6	our	our	PRON
cana-660	8	7	heuristic	heuristic	ADJ
cana-660	8	8	model	model	NOUN
cana-660	8	9	provides	provide	VERB
cana-660	8	10	better	well	ADJ
cana-660	8	11	feature	feature	NOUN
cana-660	8	12	subset	subset	NOUN
cana-660	8	13	combinations	combination	NOUN
cana-660	8	14	,	,	PUNCT
cana-660	8	15	as	as	SCONJ
cana-660	8	16	measured	measure	VERB
cana-660	8	17	by	by	ADP
cana-660	8	18	the	the	DET
cana-660	8	19	ndcg	ndcg	PROPN
cana-660	8	20	,	,	PUNCT
cana-660	8	21	p@10	p@10	NOUN
cana-660	8	22	,	,	PUNCT
cana-660	8	23	and	and	CCONJ
cana-660	8	24	map	map	VERB
cana-660	8	25	evolutionary	evolutionary	ADJ
cana-660	8	26	metrics	metric	NOUN
cana-660	8	27	,	,	PUNCT
cana-660	8	28	than	than	SCONJ
cana-660	8	29	do	do	VERB
cana-660	8	30	baseline	baseline	VERB
cana-660	8	31	databases	database	NOUN
cana-660	8	32	.	.	PUNCT
cana-660	9	1	our	our	PRON
cana-660	9	2	proposed	propose	VERB
cana-660	9	3	method	method	NOUN
cana-660	9	4	surpasses	surpass	VERB
cana-660	9	5	existing	exist	VERB
cana-660	9	6	learning	learning	NOUN
cana-660	9	7	-	-	PUNCT
cana-660	9	8	to	to	ADP
cana-660	9	9	-	-	PUNCT
cana-660	9	10	rank	rank	NOUN
cana-660	9	11	methods	method	NOUN
cana-660	9	12	,	,	PUNCT
cana-660	9	13	paving	pave	VERB
cana-660	9	14	the	the	DET
cana-660	9	15	way	way	NOUN
cana-660	9	16	for	for	ADP
cana-660	9	17	promising	promise	VERB
cana-660	9	18	future	future	ADJ
cana-660	9	19	research	research	NOUN
cana-660	9	20	.	.	PUNCT
cana-660	10	1	keywords	keyword	NOUN
cana-660	10	2	:	:	PUNCT
cana-660	10	3	machine	machine	NOUN
cana-660	10	4	learning	learning	NOUN
cana-660	10	5	,	,	PUNCT
cana-660	10	6	l2	l2	NOUN
cana-660	10	7	regularization	regularization	NOUN
cana-660	10	8	,	,	PUNCT
cana-660	10	9	learning	learning	NOUN
cana-660	10	10	-	-	PUNCT
cana-660	10	11	to	to	ADP
cana-660	10	12	-	-	PUNCT
cana-660	10	13	rank	rank	NOUN
cana-660	10	14	,	,	PUNCT
cana-660	10	15	simulated	simulated	ADJ
cana-660	10	16	annealing	annealing	NOUN
cana-660	10	17	.	.	PUNCT
cana-660	11	1	1.introduction	1.introduction	NUM
cana-660	11	2	ranking	ranking	NOUN
cana-660	11	3	refers	refer	VERB
cana-660	11	4	to	to	ADP
cana-660	11	5	the	the	DET
cana-660	11	6	process	process	NOUN
cana-660	11	7	of	of	ADP
cana-660	11	8	ordering	order	VERB
cana-660	11	9	a	a	DET
cana-660	11	10	set	set	NOUN
cana-660	11	11	of	of	ADP
cana-660	11	12	items	item	NOUN
cana-660	11	13	based	base	VERB
cana-660	11	14	on	on	ADP
cana-660	11	15	a	a	DET
cana-660	11	16	particular	particular	ADJ
cana-660	11	17	criterion	criterion	NOUN
cana-660	11	18	or	or	CCONJ
cana-660	11	19	relevance	relevance	NOUN
cana-660	11	20	to	to	ADP
cana-660	11	21	a	a	DET
cana-660	11	22	given	give	VERB
cana-660	11	23	context	context	NOUN
cana-660	11	24	or	or	CCONJ
cana-660	11	25	query	query	NOUN
cana-660	11	26	.	.	PUNCT
cana-660	12	1	in	in	ADP
cana-660	12	2	the	the	DET
cana-660	12	3	context	context	NOUN
cana-660	12	4	of	of	ADP
cana-660	12	5	information	information	NOUN
cana-660	12	6	retrieval	retrieval	NOUN
cana-660	12	7	,	,	PUNCT
cana-660	12	8	ranking	ranking	NOUN
cana-660	12	9	involves	involve	VERB
cana-660	12	10	arranging	arrange	VERB
cana-660	12	11	a	a	DET
cana-660	12	12	set	set	NOUN
cana-660	12	13	of	of	ADP
cana-660	12	14	web	web	NOUN
cana-660	12	15	pages	page	NOUN
cana-660	12	16	or	or	CCONJ
cana-660	12	17	documents	document	NOUN
cana-660	12	18	based	base	VERB
cana-660	12	19	on	on	ADP
cana-660	12	20	their	their	PRON
cana-660	12	21	relevance	relevance	NOUN
cana-660	12	22	to	to	ADP
cana-660	12	23	a	a	DET
cana-660	12	24	user	user	NOUN
cana-660	12	25	’s	’s	PART
cana-660	12	26	query	query	NOUN
cana-660	12	27	.	.	PUNCT
cana-660	13	1	in	in	ADP
cana-660	13	2	other	other	ADJ
cana-660	13	3	domains	domain	NOUN
cana-660	13	4	,	,	PUNCT
cana-660	13	5	ranking	ranking	NOUN
cana-660	13	6	can	can	AUX
cana-660	13	7	involve	involve	VERB
cana-660	13	8	ordering	order	VERB
cana-660	13	9	products	product	NOUN
cana-660	13	10	,	,	PUNCT
cana-660	13	11	services	service	NOUN
cana-660	13	12	,	,	PUNCT
cana-660	13	13	or	or	CCONJ
cana-660	13	14	individuals	individual	NOUN
cana-660	13	15	based	base	VERB
cana-660	13	16	on	on	ADP
cana-660	13	17	factors	factor	NOUN
cana-660	13	18	such	such	ADJ
cana-660	13	19	as	as	ADP
cana-660	13	20	popularity	popularity	NOUN
cana-660	13	21	,	,	PUNCT
cana-660	13	22	quality	quality	NOUN
cana-660	13	23	,	,	PUNCT
cana-660	13	24	or	or	CCONJ
cana-660	13	25	value	value	NOUN
cana-660	13	26	.	.	PUNCT
cana-660	14	1	the	the	DET
cana-660	14	2	goal	goal	NOUN
cana-660	14	3	of	of	ADP
cana-660	14	4	ranking	ranking	NOUN
cana-660	14	5	is	be	AUX
cana-660	14	6	to	to	PART
cana-660	14	7	present	present	VERB
cana-660	14	8	the	the	DET
cana-660	14	9	most	most	ADV
cana-660	14	10	valuable	valuable	ADJ
cana-660	14	11	or	or	CCONJ
cana-660	14	12	relevant	relevant	ADJ
cana-660	14	13	items	item	NOUN
cana-660	14	14	at	at	ADP
cana-660	14	15	the	the	DET
cana-660	14	16	top	top	NOUN
cana-660	14	17	of	of	ADP
cana-660	14	18	the	the	DET
cana-660	14	19	list	list	NOUN
cana-660	14	20	,	,	PUNCT
cana-660	14	21	making	make	VERB
cana-660	14	22	it	it	PRON
cana-660	14	23	easier	easy	ADJ
cana-660	14	24	for	for	SCONJ
cana-660	14	25	users	user	NOUN
cana-660	14	26	to	to	PART
cana-660	14	27	find	find	VERB
cana-660	14	28	what	what	PRON
cana-660	14	29	they	they	PRON
cana-660	14	30	are	be	AUX
cana-660	14	31	looking	look	VERB
cana-660	14	32	for	for	ADP
cana-660	14	33	.	.	PUNCT
cana-660	15	1	various	various	ADJ
cana-660	15	2	feature	feature	NOUN
cana-660	15	3	selection	selection	NOUN
cana-660	15	4	models	model	NOUN
cana-660	15	5	and	and	CCONJ
cana-660	15	6	ranking	ranking	NOUN
cana-660	15	7	frameworks	framework	NOUN
cana-660	15	8	have	have	AUX
cana-660	15	9	been	be	AUX
cana-660	15	10	developed	develop	VERB
cana-660	15	11	and	and	CCONJ
cana-660	15	12	proposed	propose	VERB
cana-660	15	13	recently	recently	ADV
cana-660	15	14	.	.	PUNCT
cana-660	16	1	in	in	ADP
cana-660	16	2	[	[	X
cana-660	16	3	4	4	NUM
cana-660	16	4	]	]	PUNCT
cana-660	16	5	,	,	PUNCT
cana-660	16	6	the	the	DET
cana-660	16	7	authors	author	NOUN
cana-660	16	8	discussed	discuss	VERB
cana-660	16	9	the	the	DET
cana-660	16	10	significance	significance	NOUN
cana-660	16	11	of	of	ADP
cana-660	16	12	features	feature	NOUN
cana-660	16	13	and	and	CCONJ
cana-660	16	14	the	the	DET
cana-660	16	15	role	role	NOUN
cana-660	16	16	of	of	ADP
cana-660	16	17	similarity	similarity	NOUN
cana-660	16	18	information	information	NOUN
cana-660	16	19	in	in	ADP
cana-660	16	20	ranking	rank	VERB
cana-660	16	21	and	and	CCONJ
cana-660	16	22	proposed	propose	VERB
cana-660	16	23	a	a	DET
cana-660	16	24	two	two	NUM
cana-660	16	25	-	-	PUNCT
cana-660	16	26	stage	stage	NOUN
cana-660	16	27	solution	solution	NOUN
cana-660	16	28	using	use	VERB
cana-660	16	29	a	a	DET
cana-660	16	30	greedy	greedy	ADJ
cana-660	16	31	algorithm	algorithm	NOUN
cana-660	16	32	.	.	PUNCT
cana-660	17	1	other	other	ADJ
cana-660	17	2	models	model	NOUN
cana-660	17	3	developed	develop	VERB
cana-660	17	4	for	for	ADP
cana-660	17	5	the	the	DET
cana-660	17	6	same	same	ADJ
cana-660	17	7	purpose	purpose	NOUN
cana-660	17	8	but	but	CCONJ
cana-660	17	9	with	with	ADP
cana-660	17	10	different	different	ADJ
cana-660	17	11	hypothesis	hypothesis	NOUN
cana-660	17	12	functions	function	NOUN
cana-660	17	13	include	include	AUX
cana-660	17	14	ranksvm	ranksvm	VERB
cana-660	18	1	[	[	X
cana-660	18	2	5	5	NUM
cana-660	18	3	]	]	PUNCT
cana-660	18	4	and	and	CCONJ
cana-660	18	5	ranknet	ranknet	VERB
cana-660	19	1	[	[	X
cana-660	19	2	6	6	NUM
cana-660	19	3	]	]	PUNCT
cana-660	19	4	.	.	PUNCT
cana-660	20	1	in	in	ADP
cana-660	20	2	[	[	X
cana-660	20	3	7	7	NUM
cana-660	20	4	]	]	PUNCT
cana-660	20	5	,	,	PUNCT
cana-660	20	6	the	the	DET
cana-660	20	7	authors	author	NOUN
cana-660	20	8	investigated	investigate	VERB
cana-660	20	9	the	the	DET
cana-660	20	10	boosted	boosted	ADJ
cana-660	20	11	tree	tree	NOUN
cana-660	20	12	ranking	ranking	NOUN
cana-660	20	13	model	model	NOUN
cana-660	20	14	with	with	ADP
cana-660	20	15	a	a	DET
cana-660	20	16	randomized	randomized	ADJ
cana-660	20	17	,	,	PUNCT
cana-660	20	18	greedy	greedy	ADJ
cana-660	20	19	technique	technique	NOUN
cana-660	20	20	.	.	PUNCT
cana-660	21	1	fsmrank	fsmrank	PROPN
cana-660	22	1	[	[	X
cana-660	22	2	10	10	NUM
cana-660	22	3	]	]	PUNCT
cana-660	22	4	is	be	AUX
cana-660	22	5	another	another	DET
cana-660	22	6	framework	framework	NOUN
cana-660	22	7	for	for	ADP
cana-660	22	8	optimized	optimize	VERB
cana-660	22	9	feature	feature	NOUN
cana-660	22	10	selection	selection	NOUN
cana-660	22	11	for	for	ADP
cana-660	22	12	ranking	ranking	NOUN
cana-660	22	13	.	.	PUNCT
cana-660	23	1	the	the	DET
cana-660	23	2	mrmr	mrmr	PROPN
cana-660	24	1	[	[	X
cana-660	24	2	11	11	NUM
cana-660	24	3	]	]	PUNCT
cana-660	24	4	model	model	NOUN
cana-660	24	5	was	be	AUX
cana-660	24	6	suggested	suggest	VERB
cana-660	24	7	and	and	CCONJ
cana-660	24	8	used	use	VERB
cana-660	24	9	to	to	PART
cana-660	24	10	select	select	VERB
cana-660	24	11	subgroups	subgroup	NOUN
cana-660	24	12	based	base	VERB
cana-660	24	13	on	on	ADP
cana-660	24	14	relevance	relevance	NOUN
cana-660	24	15	and	and	CCONJ
cana-660	24	16	similarity	similarity	NOUN
cana-660	24	17	.	.	PUNCT
cana-660	25	1	a	a	DET
cana-660	25	2	lightweight	lightweight	ADJ
cana-660	25	3	framework	framework	NOUN
cana-660	25	4	for	for	ADP
cana-660	25	5	feature	feature	NOUN
cana-660	25	6	selection	selection	NOUN
cana-660	25	7	and	and	CCONJ
cana-660	25	8	uti	uti	PROPN
cana-660	25	9	,	,	PUNCT
cana-660	25	10	which	which	PRON
cana-660	25	11	recommends	recommend	VERB
cana-660	25	12	a	a	DET
cana-660	25	13	more	more	ADV
cana-660	25	14	reliable	reliable	ADJ
cana-660	25	15	model	model	NOUN
cana-660	25	16	and	and	CCONJ
cana-660	25	17	model	model	NOUN
cana-660	25	18	optimization	optimization	NOUN
cana-660	25	19	in	in	ADP
cana-660	25	20	combination	combination	NOUN
cana-660	25	21	with	with	ADP
cana-660	25	22	lamdamart	lamdamart	NOUN
cana-660	25	23	,	,	PUNCT
cana-660	25	24	was	be	AUX
cana-660	25	25	also	also	ADV
cana-660	25	26	proposed	propose	VERB
cana-660	25	27	[	[	X
cana-660	25	28	2	2	NUM
cana-660	25	29	]	]	PUNCT
cana-660	25	30	.	.	PUNCT
cana-660	26	1	the	the	DET
cana-660	26	2	three	three	NUM
cana-660	26	3	categories	category	NOUN
cana-660	26	4	for	for	ADP
cana-660	26	5	feature	feature	NOUN
cana-660	26	6	selection	selection	NOUN
cana-660	26	7	approaches	approach	NOUN
cana-660	26	8	are	be	AUX
cana-660	26	9	filter	filter	NOUN
cana-660	26	10	,	,	PUNCT
cana-660	26	11	wrapper	wrapper	NOUN
cana-660	26	12	,	,	PUNCT
cana-660	26	13	and	and	CCONJ
cana-660	26	14	embedding	embed	VERB
cana-660	26	15	.	.	PUNCT
cana-660	27	1	filter	filter	NOUN
cana-660	27	2	techniques	technique	NOUN
cana-660	27	3	were	be	AUX
cana-660	27	4	used	use	VERB
cana-660	27	5	in	in	ADP
cana-660	27	6	[	[	X
cana-660	27	7	4][9–13	4][9–13	X
cana-660	27	8	]	]	X
cana-660	27	9	,	,	PUNCT
cana-660	27	10	where	where	SCONJ
cana-660	27	11	a	a	DET
cana-660	27	12	subset	subset	NOUN
cana-660	27	13	of	of	ADP
cana-660	27	14	features	feature	NOUN
cana-660	27	15	was	be	AUX
cana-660	27	16	chosen	choose	VERB
cana-660	27	17	based	base	VERB
cana-660	27	18	on	on	ADP
cana-660	27	19	their	their	PRON
cana-660	27	20	communications	communication	NOUN
cana-660	27	21	on	on	ADP
cana-660	27	22	applied	apply	VERB
cana-660	27	23	nonlinear	nonlinear	ADJ
cana-660	27	24	analysis	analysis	NOUN
cana-660	27	25	issn	issn	NOUN
cana-660	27	26	:	:	PUNCT
cana-660	27	27	1074	1074	NUM
cana-660	27	28	-	-	PUNCT
cana-660	27	29	133x	133x	NUM
cana-660	27	30	vol	vol	NOUN
cana-660	27	31	31	31	NUM
cana-660	27	32	no	no	NOUN
cana-660	27	33	.	.	PUNCT
cana-660	28	1	2s	2s	NUM
cana-660	28	2	(	(	PUNCT
cana-660	28	3	2024	2024	NUM
cana-660	28	4	)	)	PUNCT
cana-660	28	5	455	455	NUM
cana-660	29	1	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	30	1	quality	quality	NOUN
cana-660	30	2	and	and	CCONJ
cana-660	30	3	correlation	correlation	NOUN
cana-660	30	4	.	.	PUNCT
cana-660	31	1	a	a	DET
cana-660	31	2	similarity	similarity	NOUN
cana-660	31	3	measure	measure	NOUN
cana-660	31	4	between	between	ADP
cana-660	31	5	the	the	DET
cana-660	31	6	query	query	NOUN
cana-660	31	7	and	and	CCONJ
cana-660	31	8	document	document	NOUN
cana-660	31	9	pair	pair	NOUN
cana-660	31	10	values	value	NOUN
cana-660	31	11	was	be	AUX
cana-660	31	12	used	use	VERB
cana-660	31	13	to	to	PART
cana-660	31	14	determine	determine	VERB
cana-660	31	15	whether	whether	SCONJ
cana-660	31	16	a	a	DET
cana-660	31	17	feature	feature	NOUN
cana-660	31	18	was	be	AUX
cana-660	31	19	stable	stable	ADJ
cana-660	31	20	or	or	CCONJ
cana-660	31	21	active	active	ADJ
cana-660	31	22	after	after	ADP
cana-660	31	23	being	be	AUX
cana-660	31	24	dropped	drop	VERB
cana-660	31	25	.	.	PUNCT
cana-660	32	1	wrapper	wrapper	NOUN
cana-660	32	2	methods	method	NOUN
cana-660	32	3	were	be	AUX
cana-660	32	4	used	use	VERB
cana-660	32	5	in	in	ADP
cana-660	32	6	the	the	DET
cana-660	32	7	development	development	NOUN
cana-660	32	8	of	of	ADP
cana-660	32	9	ranknet	ranknet	NOUN
cana-660	32	10	[	[	X
cana-660	32	11	6	6	NUM
cana-660	32	12	]	]	PUNCT
cana-660	32	13	and	and	CCONJ
cana-660	32	14	listnet	listnet	NOUN
cana-660	32	15	,	,	PUNCT
cana-660	32	16	but	but	CCONJ
cana-660	32	17	they	they	PRON
cana-660	32	18	require	require	VERB
cana-660	32	19	more	more	ADV
cana-660	32	20	computational	computational	ADJ
cana-660	32	21	time	time	NOUN
cana-660	32	22	to	to	PART
cana-660	32	23	locate	locate	VERB
cana-660	32	24	the	the	DET
cana-660	32	25	subset	subset	NOUN
cana-660	32	26	.	.	PUNCT
cana-660	33	1	embedded	embed	VERB
cana-660	33	2	algorithms	algorithm	NOUN
cana-660	33	3	operate	operate	VERB
cana-660	33	4	with	with	ADP
cana-660	33	5	sparse	sparse	ADJ
cana-660	33	6	rankers	ranker	NOUN
cana-660	33	7	,	,	PUNCT
cana-660	33	8	and	and	CCONJ
cana-660	33	9	attempts	attempt	NOUN
cana-660	33	10	have	have	AUX
cana-660	33	11	been	be	AUX
cana-660	33	12	made	make	VERB
cana-660	33	13	in	in	ADP
cana-660	33	14	some	some	DET
cana-660	33	15	studies	study	NOUN
cana-660	33	16	,	,	PUNCT
cana-660	33	17	such	such	ADJ
cana-660	33	18	as	as	ADP
cana-660	33	19	rsrank	rsrank	NOUN
cana-660	33	20	[	[	X
cana-660	33	21	15	15	NUM
cana-660	33	22	]	]	PUNCT
cana-660	33	23	and	and	CCONJ
cana-660	33	24	fsmrank	fsmrank	NOUN
cana-660	34	1	[	[	X
cana-660	34	2	8],[15	8],[15	PROPN
cana-660	34	3	-	-	SYM
cana-660	34	4	17	17	NUM
cana-660	34	5	]	]	PUNCT
cana-660	34	6	,	,	PUNCT
cana-660	34	7	to	to	PART
cana-660	34	8	regularize	regularize	VERB
cana-660	34	9	the	the	DET
cana-660	34	10	number	number	NOUN
cana-660	34	11	of	of	ADP
cana-660	34	12	features	feature	NOUN
cana-660	34	13	.	.	PUNCT
cana-660	35	1	another	another	DET
cana-660	35	2	study	study	NOUN
cana-660	35	3	employed	employ	VERB
cana-660	35	4	a	a	DET
cana-660	35	5	sparse	sparse	ADJ
cana-660	35	6	bayesian	bayesian	NOUN
cana-660	35	7	solution	solution	NOUN
cana-660	35	8	in	in	ADP
cana-660	35	9	[	[	X
cana-660	35	10	18	18	NUM
cana-660	35	11	]	]	PUNCT
cana-660	35	12	.	.	PUNCT
cana-660	36	1	optimization	optimization	NOUN
cana-660	36	2	is	be	AUX
cana-660	36	3	one	one	NUM
cana-660	36	4	of	of	ADP
cana-660	36	5	the	the	DET
cana-660	36	6	more	more	ADV
cana-660	36	7	challenging	challenging	ADJ
cana-660	36	8	tasks	task	NOUN
cana-660	36	9	in	in	ADP
cana-660	36	10	selecting	select	VERB
cana-660	36	11	features	feature	NOUN
cana-660	36	12	based	base	VERB
cana-660	36	13	on	on	ADP
cana-660	36	14	relevance	relevance	NOUN
cana-660	36	15	and	and	CCONJ
cana-660	36	16	similarity	similarity	NOUN
cana-660	36	17	while	while	SCONJ
cana-660	36	18	minimizing	minimize	VERB
cana-660	36	19	error	error	NOUN
cana-660	36	20	.	.	PUNCT
cana-660	37	1	the	the	DET
cana-660	37	2	current	current	ADJ
cana-660	37	3	study	study	NOUN
cana-660	37	4	proposes	propose	VERB
cana-660	37	5	a	a	DET
cana-660	37	6	novel	novel	ADJ
cana-660	37	7	heuristic	heuristic	ADJ
cana-660	37	8	method	method	NOUN
cana-660	37	9	that	that	PRON
cana-660	37	10	utilizes	utilize	VERB
cana-660	37	11	hill	hill	NOUN
cana-660	37	12	climbing	climbing	NOUN
cana-660	37	13	and	and	CCONJ
cana-660	37	14	random	random	ADJ
cana-660	37	15	walk	walk	NOUN
cana-660	37	16	with	with	ADP
cana-660	37	17	knn	knn	PROPN
cana-660	37	18	classification	classification	NOUN
cana-660	37	19	to	to	PART
cana-660	37	20	select	select	VERB
cana-660	37	21	and	and	CCONJ
cana-660	37	22	optimize	optimize	VERB
cana-660	37	23	features	feature	NOUN
cana-660	37	24	,	,	PUNCT
cana-660	37	25	outperforming	outperform	VERB
cana-660	37	26	existing	exist	VERB
cana-660	37	27	frameworks	framework	NOUN
cana-660	37	28	.	.	PUNCT
cana-660	38	1	we	we	PRON
cana-660	38	2	suggest	suggest	VERB
cana-660	38	3	a	a	DET
cana-660	38	4	hybrid	hybrid	ADJ
cana-660	38	5	model	model	NOUN
cana-660	38	6	that	that	PRON
cana-660	38	7	selects	select	VERB
cana-660	38	8	a	a	DET
cana-660	38	9	feature	feature	NOUN
cana-660	38	10	and	and	CCONJ
cana-660	38	11	optimizes	optimize	VERB
cana-660	38	12	it	it	PRON
cana-660	38	13	iteratively	iteratively	ADV
cana-660	38	14	.	.	PUNCT
cana-660	39	1	to	to	PART
cana-660	39	2	achieve	achieve	VERB
cana-660	39	3	feature	feature	NOUN
cana-660	39	4	selection	selection	NOUN
cana-660	39	5	,	,	PUNCT
cana-660	39	6	we	we	PRON
cana-660	39	7	utilize	utilize	VERB
cana-660	39	8	simulated	simulate	VERB
cana-660	39	9	annealing	annealing	NOUN
cana-660	39	10	with	with	ADP
cana-660	39	11	the	the	DET
cana-660	39	12	above	above	ADJ
cana-660	39	13	mentioned	mention	VERB
cana-660	39	14	techniques	technique	NOUN
cana-660	39	15	and	and	CCONJ
cana-660	39	16	apply	apply	VERB
cana-660	39	17	l2	l2	NOUN
cana-660	39	18	regularization	regularization	NOUN
cana-660	39	19	for	for	ADP
cana-660	39	20	optimization	optimization	NOUN
cana-660	39	21	.	.	PUNCT
cana-660	40	1	the	the	DET
cana-660	40	2	selection	selection	NOUN
cana-660	40	3	of	of	ADP
cana-660	40	4	active	active	ADJ
cana-660	40	5	features	feature	NOUN
cana-660	40	6	is	be	AUX
cana-660	40	7	based	base	VERB
cana-660	40	8	on	on	ADP
cana-660	40	9	the	the	DET
cana-660	40	10	activation	activation	NOUN
cana-660	40	11	function	function	NOUN
cana-660	40	12	of	of	ADP
cana-660	40	13	lamdamart	lamdamart	NOUN
cana-660	40	14	during	during	ADP
cana-660	40	15	each	each	DET
cana-660	40	16	iteration	iteration	NOUN
cana-660	40	17	until	until	SCONJ
cana-660	40	18	it	it	PRON
cana-660	40	19	converges	converge	VERB
cana-660	40	20	.	.	PUNCT
cana-660	41	1	evaluation	evaluation	NOUN
cana-660	41	2	matrices	matrix	NOUN
cana-660	41	3	demonstrated	demonstrate	VERB
cana-660	41	4	significantly	significantly	ADV
cana-660	41	5	improved	improve	VERB
cana-660	41	6	results	result	NOUN
cana-660	41	7	.	.	PUNCT
cana-660	42	1	the	the	DET
cana-660	42	2	following	follow	VERB
cana-660	42	3	questions	question	NOUN
cana-660	42	4	are	be	AUX
cana-660	42	5	the	the	DET
cana-660	42	6	main	main	ADJ
cana-660	42	7	focus	focus	NOUN
cana-660	42	8	of	of	ADP
cana-660	42	9	our	our	PRON
cana-660	42	10	research	research	NOUN
cana-660	42	11	:	:	PUNCT
cana-660	42	12	•	•	ADP
cana-660	42	13	how	how	SCONJ
cana-660	42	14	does	do	AUX
cana-660	42	15	the	the	PRON
cana-660	42	16	embedding	embed	VERB
cana-660	42	17	hybrid	hybrid	ADJ
cana-660	42	18	evolutionary	evolutionary	ADJ
cana-660	42	19	approach	approach	NOUN
cana-660	42	20	for	for	ADP
cana-660	42	21	learning	learning	NOUN
cana-660	42	22	-	-	PUNCT
cana-660	42	23	to	to	ADP
cana-660	42	24	-	-	PUNCT
cana-660	42	25	rank	rank	NOUN
cana-660	42	26	generalize	generalize	VERB
cana-660	42	27	across	across	ADP
cana-660	42	28	different	different	ADJ
cana-660	42	29	types	type	NOUN
cana-660	42	30	of	of	ADP
cana-660	42	31	ranking	rank	VERB
cana-660	42	32	task	task	NOUN
cana-660	42	33	?	?	PUNCT
cana-660	43	1	•	•	NOUN
cana-660	43	2	what	what	PRON
cana-660	43	3	are	be	AUX
cana-660	43	4	the	the	DET
cana-660	43	5	computational	computational	ADJ
cana-660	43	6	costs	cost	NOUN
cana-660	43	7	associated	associate	VERB
cana-660	43	8	with	with	ADP
cana-660	43	9	the	the	DET
cana-660	43	10	embedding	embed	VERB
cana-660	43	11	hybrid	hybrid	ADJ
cana-660	43	12	evolutionary	evolutionary	ADJ
cana-660	43	13	approach	approach	NOUN
cana-660	43	14	for	for	ADP
cana-660	43	15	learning	learning	NOUN
cana-660	43	16	-	-	PUNCT
cana-660	43	17	to	to	ADP
cana-660	43	18	-	-	PUNCT
cana-660	43	19	rank	rank	NOUN
cana-660	43	20	,	,	PUNCT
cana-660	43	21	and	and	CCONJ
cana-660	43	22	how	how	SCONJ
cana-660	43	23	do	do	AUX
cana-660	43	24	they	they	PRON
cana-660	43	25	compare	compare	VERB
cana-660	43	26	to	to	ADP
cana-660	43	27	alternative	alternative	ADJ
cana-660	43	28	feature	feature	NOUN
cana-660	43	29	selection	selection	NOUN
cana-660	43	30	methods	method	NOUN
cana-660	43	31	,	,	PUNCT
cana-660	43	32	particularly	particularly	ADV
cana-660	43	33	in	in	ADP
cana-660	43	34	terms	term	NOUN
cana-660	43	35	of	of	ADP
cana-660	43	36	time	time	NOUN
cana-660	43	37	complexity	complexity	NOUN
cana-660	43	38	and	and	CCONJ
cana-660	43	39	resource	resource	NOUN
cana-660	43	40	utilization	utilization	NOUN
cana-660	43	41	?	?	PUNCT
cana-660	44	1	•	•	NUM
cana-660	44	2	what	what	PRON
cana-660	44	3	are	be	AUX
cana-660	44	4	the	the	DET
cana-660	44	5	implications	implication	NOUN
cana-660	44	6	of	of	ADP
cana-660	44	7	using	use	VERB
cana-660	44	8	the	the	DET
cana-660	44	9	embedding	embed	VERB
cana-660	44	10	hybrid	hybrid	ADJ
cana-660	44	11	evolutionary	evolutionary	ADJ
cana-660	44	12	approach	approach	NOUN
cana-660	44	13	for	for	ADP
cana-660	44	14	learningto	learningto	NOUN
cana-660	44	15	-	-	PUNCT
cana-660	44	16	rank	rank	NOUN
cana-660	44	17	in	in	ADP
cana-660	44	18	real	real	ADJ
cana-660	44	19	-	-	PUNCT
cana-660	44	20	world	world	NOUN
cana-660	44	21	scenarios	scenario	NOUN
cana-660	44	22	,	,	PUNCT
cana-660	44	23	such	such	ADJ
cana-660	44	24	as	as	ADP
cana-660	44	25	e	e	NOUN
cana-660	44	26	-	-	NOUN
cana-660	44	27	commerce	commerce	NOUN
cana-660	44	28	platforms	platform	NOUN
cana-660	44	29	or	or	CCONJ
cana-660	44	30	search	search	NOUN
cana-660	44	31	engines	engine	NOUN
cana-660	44	32	,	,	PUNCT
cana-660	44	33	and	and	CCONJ
cana-660	44	34	how	how	SCONJ
cana-660	44	35	do	do	AUX
cana-660	44	36	these	these	DET
cana-660	44	37	insights	insight	NOUN
cana-660	44	38	inform	inform	VERB
cana-660	44	39	practical	practical	ADJ
cana-660	44	40	deployment	deployment	NOUN
cana-660	44	41	and	and	CCONJ
cana-660	44	42	integration	integration	NOUN
cana-660	44	43	strategies	strategy	NOUN
cana-660	44	44	?	?	PUNCT
cana-660	45	1	•	•	NUM
cana-660	45	2	how	how	SCONJ
cana-660	45	3	does	do	AUX
cana-660	45	4	the	the	PRON
cana-660	45	5	embedding	embed	VERB
cana-660	45	6	hybrid	hybrid	ADJ
cana-660	45	7	evolutionary	evolutionary	ADJ
cana-660	45	8	approach	approach	NOUN
cana-660	45	9	for	for	ADP
cana-660	45	10	learning	learning	NOUN
cana-660	45	11	-	-	PUNCT
cana-660	45	12	to	to	ADP
cana-660	45	13	-	-	PUNCT
cana-660	45	14	rank	rank	NOUN
cana-660	45	15	address	address	NOUN
cana-660	45	16	challenges	challenge	NOUN
cana-660	45	17	related	relate	VERB
cana-660	45	18	to	to	ADP
cana-660	45	19	imbalanced	imbalanced	ADJ
cana-660	45	20	datasets	dataset	NOUN
cana-660	45	21	,	,	PUNCT
cana-660	45	22	noisy	noisy	ADJ
cana-660	45	23	features	feature	NOUN
cana-660	45	24	,	,	PUNCT
cana-660	45	25	and	and	CCONJ
cana-660	45	26	sparse	sparse	ADJ
cana-660	45	27	data	datum	NOUN
cana-660	45	28	,	,	PUNCT
cana-660	45	29	and	and	CCONJ
cana-660	45	30	what	what	PRON
cana-660	45	31	techniques	technique	NOUN
cana-660	45	32	can	can	AUX
cana-660	45	33	be	be	AUX
cana-660	45	34	employed	employ	VERB
cana-660	45	35	to	to	PART
cana-660	45	36	enhance	enhance	VERB
cana-660	45	37	its	its	PRON
cana-660	45	38	robustness	robustness	NOUN
cana-660	45	39	and	and	CCONJ
cana-660	45	40	reliability	reliability	NOUN
cana-660	45	41	in	in	ADP
cana-660	45	42	such	such	ADJ
cana-660	45	43	scenarios	scenario	NOUN
cana-660	45	44	?	?	PUNCT
cana-660	46	1	in	in	ADP
cana-660	46	2	research	research	NOUN
cana-660	46	3	on	on	ADP
cana-660	46	4	evolutionary	evolutionary	ADJ
cana-660	46	5	learning	learning	NOUN
cana-660	46	6	to	to	PART
cana-660	46	7	rank	rank	VERB
cana-660	46	8	approaches	approach	NOUN
cana-660	46	9	presented	present	VERB
cana-660	46	10	to	to	PART
cana-660	46	11	aims	aim	VERB
cana-660	46	12	to	to	PART
cana-660	46	13	address	address	VERB
cana-660	46	14	the	the	DET
cana-660	46	15	above	above	ADJ
cana-660	46	16	concerns	concern	NOUN
cana-660	46	17	.	.	PUNCT
cana-660	47	1	four	four	NUM
cana-660	47	2	different	different	ADJ
cana-660	47	3	sizes	size	NOUN
cana-660	47	4	of	of	ADP
cana-660	47	5	the	the	DET
cana-660	47	6	lotor	lotor	NOUN
cana-660	47	7	and	and	CCONJ
cana-660	47	8	microsoft	microsoft	PROPN
cana-660	47	9	database	database	NOUN
cana-660	47	10	which	which	PRON
cana-660	47	11	are	be	AUX
cana-660	47	12	available	available	ADJ
cana-660	47	13	in	in	ADP
cana-660	47	14	public	public	ADJ
cana-660	47	15	.	.	PUNCT
cana-660	48	1	extermination	extermination	NOUN
cana-660	48	2	performs	perform	VERB
cana-660	48	3	on	on	ADP
cana-660	48	4	with	with	ADP
cana-660	48	5	three	three	NUM
cana-660	48	6	traditional	traditional	ADJ
cana-660	48	7	algorithms	algorithm	NOUN
cana-660	48	8	and	and	CCONJ
cana-660	48	9	one	one	NUM
cana-660	48	10	evolutionary	evolutionary	ADJ
cana-660	48	11	algorithm	algorithm	NOUN
cana-660	48	12	.	.	PUNCT
cana-660	49	1	three	three	NUM
cana-660	49	2	evaluation	evaluation	NOUN
cana-660	49	3	methods	method	NOUN
cana-660	49	4	are	be	AUX
cana-660	49	5	commonly	commonly	ADV
cana-660	49	6	used	use	VERB
cana-660	49	7	to	to	PART
cana-660	49	8	evaluate	evaluate	VERB
cana-660	49	9	the	the	DET
cana-660	49	10	model	model	NOUN
cana-660	49	11	,	,	PUNCT
cana-660	49	12	namely	namely	ADV
cana-660	49	13	accuracy	accuracy	NOUN
cana-660	49	14	,	,	PUNCT
cana-660	49	15	map	map	NOUN
cana-660	49	16	(	(	PUNCT
cana-660	49	17	average	average	ADJ
cana-660	49	18	accuracy	accuracy	NOUN
cana-660	49	19	)	)	PUNCT
cana-660	49	20	and	and	CCONJ
cana-660	49	21	ndcg	ndcg	NOUN
cana-660	49	22	(	(	PUNCT
cana-660	49	23	value	value	NOUN
cana-660	49	24	reduction	reduction	NOUN
cana-660	49	25	increment	increment	NOUN
cana-660	49	26	)	)	PUNCT
cana-660	49	27	.	.	PUNCT
cana-660	50	1	research	research	NOUN
cana-660	50	2	results	result	NOUN
cana-660	50	3	show	show	VERB
cana-660	50	4	that	that	SCONJ
cana-660	50	5	using	use	VERB
cana-660	50	6	geographic	geographic	ADJ
cana-660	50	7	features	feature	NOUN
cana-660	50	8	to	to	PART
cana-660	50	9	drive	drive	VERB
cana-660	50	10	the	the	DET
cana-660	50	11	model	model	NOUN
cana-660	50	12	can	can	AUX
cana-660	50	13	improve	improve	VERB
cana-660	50	14	results	result	NOUN
cana-660	50	15	.	.	PUNCT
cana-660	51	1	the	the	DET
cana-660	51	2	significant	significant	ADJ
cana-660	51	3	contributions	contribution	NOUN
cana-660	51	4	of	of	ADP
cana-660	51	5	this	this	DET
cana-660	51	6	paper	paper	NOUN
cana-660	51	7	are	be	AUX
cana-660	51	8	,	,	PUNCT
cana-660	51	9	in	in	ADP
cana-660	51	10	brief	brief	ADJ
cana-660	51	11	,	,	PUNCT
cana-660	51	12	as	as	SCONJ
cana-660	51	13	follows	follow	VERB
cana-660	51	14	:	:	PUNCT
cana-660	51	15	•	•	ADP
cana-660	51	16	the	the	PRON
cana-660	51	17	embedding	embed	VERB
cana-660	51	18	hybrid	hybrid	ADJ
cana-660	51	19	evolutionary	evolutionary	ADJ
cana-660	51	20	approach	approach	NOUN
cana-660	51	21	for	for	ADP
cana-660	51	22	learning	learning	NOUN
cana-660	51	23	-	-	PUNCT
cana-660	51	24	to	to	ADP
cana-660	51	25	-	-	PUNCT
cana-660	51	26	rank	rank	NOUN
cana-660	51	27	typically	typically	ADV
cana-660	51	28	outperforms	outperform	VERB
cana-660	51	29	traditional	traditional	ADJ
cana-660	51	30	feature	feature	NOUN
cana-660	51	31	selection	selection	NOUN
cana-660	51	32	methods	method	NOUN
cana-660	51	33	due	due	ADP
cana-660	51	34	to	to	ADP
cana-660	51	35	its	its	PRON
cana-660	51	36	ability	ability	NOUN
cana-660	51	37	to	to	PART
cana-660	51	38	adaptively	adaptively	ADV
cana-660	51	39	select	select	VERB
cana-660	51	40	relevant	relevant	ADJ
cana-660	51	41	features	feature	NOUN
cana-660	51	42	and	and	CCONJ
cana-660	51	43	optimize	optimize	VERB
cana-660	51	44	ranking	ranking	NOUN
cana-660	51	45	models	model	NOUN
cana-660	51	46	based	base	VERB
cana-660	51	47	on	on	ADP
cana-660	51	48	evolutionary	evolutionary	ADJ
cana-660	51	49	processes	process	NOUN
cana-660	51	50	and	and	CCONJ
cana-660	51	51	embedding	embed	VERB
cana-660	51	52	techniques	technique	NOUN
cana-660	51	53	.	.	PUNCT
cana-660	52	1	this	this	DET
cana-660	52	2	superiority	superiority	NOUN
cana-660	52	3	is	be	AUX
cana-660	52	4	demonstrated	demonstrate	VERB
cana-660	52	5	through	through	ADP
cana-660	52	6	comprehensive	comprehensive	ADJ
cana-660	52	7	performance	performance	NOUN
cana-660	52	8	evaluation	evaluation	NOUN
cana-660	52	9	metrics	metric	NOUN
cana-660	52	10	such	such	ADJ
cana-660	52	11	as	as	ADP
cana-660	52	12	the	the	DET
cana-660	52	13	mean	mean	ADJ
cana-660	52	14	average	average	ADJ
cana-660	52	15	precision	precision	NOUN
cana-660	52	16	(	(	PUNCT
cana-660	52	17	map	map	NOUN
cana-660	52	18	)	)	PUNCT
cana-660	52	19	,	,	PUNCT
cana-660	52	20	normalized	normalize	VERB
cana-660	52	21	discounted	discount	VERB
cana-660	52	22	cumulative	cumulative	ADJ
cana-660	52	23	gain	gain	NOUN
cana-660	52	24	(	(	PUNCT
cana-660	52	25	ndcg	ndcg	PROPN
cana-660	52	26	)	)	PUNCT
cana-660	52	27	,	,	PUNCT
cana-660	52	28	and	and	CCONJ
cana-660	52	29	precision	precision	VERB
cana-660	52	30	•	•	CCONJ
cana-660	52	31	effective	effective	ADJ
cana-660	52	32	incorporation	incorporation	NOUN
cana-660	52	33	of	of	ADP
cana-660	52	34	domain	domain	NOUN
cana-660	52	35	-	-	PUNCT
cana-660	52	36	specific	specific	ADJ
cana-660	52	37	knowledge	knowledge	NOUN
cana-660	52	38	into	into	ADP
cana-660	52	39	the	the	DET
cana-660	52	40	hybrid	hybrid	ADJ
cana-660	52	41	evolutionary	evolutionary	ADJ
cana-660	52	42	approach	approach	NOUN
cana-660	52	43	involves	involve	VERB
cana-660	52	44	leveraging	leverage	VERB
cana-660	52	45	domain	domain	NOUN
cana-660	52	46	experts	expert	NOUN
cana-660	52	47	'	'	PART
cana-660	52	48	insights	insight	NOUN
cana-660	52	49	to	to	PART
cana-660	52	50	guide	guide	VERB
cana-660	52	51	the	the	DET
cana-660	52	52	evolutionary	evolutionary	ADJ
cana-660	52	53	process	process	NOUN
cana-660	52	54	and	and	CCONJ
cana-660	52	55	communications	communication	NOUN
cana-660	52	56	on	on	ADP
cana-660	52	57	applied	apply	VERB
cana-660	52	58	nonlinear	nonlinear	ADJ
cana-660	52	59	analysis	analysis	NOUN
cana-660	52	60	issn	issn	NOUN
cana-660	52	61	:	:	PUNCT
cana-660	52	62	1074	1074	NUM
cana-660	52	63	-	-	PUNCT
cana-660	52	64	133x	133x	NUM
cana-660	52	65	vol	vol	NOUN
cana-660	52	66	31	31	NUM
cana-660	52	67	no	no	NOUN
cana-660	52	68	.	.	PUNCT
cana-660	53	1	2s	2s	NUM
cana-660	53	2	(	(	PUNCT
cana-660	53	3	2024	2024	NUM
cana-660	53	4	)	)	PUNCT
cana-660	53	5	456	456	NUM
cana-660	53	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	53	7	embedding	embed	VERB
cana-660	53	8	strategies	strategy	NOUN
cana-660	53	9	.	.	PUNCT
cana-660	54	1	this	this	DET
cana-660	54	2	collaboration	collaboration	NOUN
cana-660	54	3	enhances	enhance	VERB
cana-660	54	4	feature	feature	NOUN
cana-660	54	5	relevance	relevance	NOUN
cana-660	54	6	assessment	assessment	NOUN
cana-660	54	7	and	and	CCONJ
cana-660	54	8	ranking	ranking	ADJ
cana-660	54	9	model	model	NOUN
cana-660	54	10	performance	performance	NOUN
cana-660	54	11	,	,	PUNCT
cana-660	54	12	ultimately	ultimately	ADV
cana-660	54	13	leading	lead	VERB
cana-660	54	14	to	to	ADP
cana-660	54	15	more	more	ADV
cana-660	54	16	interpretable	interpretable	ADJ
cana-660	54	17	and	and	CCONJ
cana-660	54	18	domain	domain	NOUN
cana-660	54	19	-	-	PUNCT
cana-660	54	20	adaptive	adaptive	ADJ
cana-660	54	21	solutions	solution	NOUN
cana-660	54	22	.	.	PUNCT
cana-660	55	1	•	•	NUM
cana-660	55	2	while	while	SCONJ
cana-660	55	3	the	the	DET
cana-660	55	4	embedding	embed	VERB
cana-660	55	5	hybrid	hybrid	ADJ
cana-660	55	6	evolutionary	evolutionary	ADJ
cana-660	55	7	approach	approach	NOUN
cana-660	55	8	may	may	AUX
cana-660	55	9	entail	entail	VERB
cana-660	55	10	higher	high	ADJ
cana-660	55	11	computational	computational	ADJ
cana-660	55	12	costs	cost	NOUN
cana-660	55	13	than	than	ADP
cana-660	55	14	simpler	simple	ADJ
cana-660	55	15	methods	method	NOUN
cana-660	55	16	,	,	PUNCT
cana-660	55	17	its	its	PRON
cana-660	55	18	scalability	scalability	NOUN
cana-660	55	19	and	and	CCONJ
cana-660	55	20	efficiency	efficiency	NOUN
cana-660	55	21	are	be	AUX
cana-660	55	22	demonstrated	demonstrate	VERB
cana-660	55	23	through	through	ADP
cana-660	55	24	parallelization	parallelization	NOUN
cana-660	55	25	techniques	technique	NOUN
cana-660	55	26	,	,	PUNCT
cana-660	55	27	adaptive	adaptive	ADJ
cana-660	55	28	optimization	optimization	NOUN
cana-660	55	29	algorithms	algorithm	NOUN
cana-660	55	30	,	,	PUNCT
cana-660	55	31	and	and	CCONJ
cana-660	55	32	distributed	distribute	VERB
cana-660	55	33	computing	computing	NOUN
cana-660	55	34	frameworks	framework	NOUN
cana-660	55	35	.	.	PUNCT
cana-660	56	1	these	these	DET
cana-660	56	2	optimizations	optimization	NOUN
cana-660	56	3	ensure	ensure	VERB
cana-660	56	4	that	that	SCONJ
cana-660	56	5	the	the	DET
cana-660	56	6	approach	approach	NOUN
cana-660	56	7	remains	remain	VERB
cana-660	56	8	viable	viable	ADJ
cana-660	56	9	for	for	ADP
cana-660	56	10	large	large	ADJ
cana-660	56	11	-	-	PUNCT
cana-660	56	12	scale	scale	NOUN
cana-660	56	13	datasets	dataset	NOUN
cana-660	56	14	and	and	CCONJ
cana-660	56	15	complex	complex	ADJ
cana-660	56	16	feature	feature	NOUN
cana-660	56	17	spaces	space	NOUN
cana-660	56	18	.	.	PUNCT
cana-660	57	1	the	the	DET
cana-660	57	2	paper	paper	NOUN
cana-660	57	3	is	be	AUX
cana-660	57	4	organized	organize	VERB
cana-660	57	5	as	as	SCONJ
cana-660	57	6	follows	follow	VERB
cana-660	57	7	:	:	PUNCT
cana-660	57	8	section	section	PROPN
cana-660	57	9	ii	ii	PROPN
cana-660	57	10	reviews	review	NOUN
cana-660	57	11	prior	prior	ADV
cana-660	57	12	related	relate	VERB
cana-660	57	13	research	research	NOUN
cana-660	57	14	and	and	CCONJ
cana-660	57	15	provides	provide	VERB
cana-660	57	16	the	the	DET
cana-660	57	17	motivation	motivation	NOUN
cana-660	57	18	for	for	ADP
cana-660	57	19	the	the	DET
cana-660	57	20	current	current	ADJ
cana-660	57	21	study	study	NOUN
cana-660	57	22	.	.	PUNCT
cana-660	58	1	in	in	ADP
cana-660	58	2	section	section	PROPN
cana-660	58	3	iii	iii	PROPN
cana-660	58	4	,	,	PUNCT
cana-660	58	5	we	we	PRON
cana-660	58	6	provide	provide	VERB
cana-660	58	7	an	an	DET
cana-660	58	8	overview	overview	NOUN
cana-660	58	9	of	of	ADP
cana-660	58	10	feature	feature	NOUN
cana-660	58	11	selection	selection	NOUN
cana-660	58	12	for	for	ADP
cana-660	58	13	a	a	DET
cana-660	58	14	few	few	ADJ
cana-660	58	15	fundamental	fundamental	ADJ
cana-660	58	16	algorithms	algorithm	NOUN
cana-660	58	17	.	.	PUNCT
cana-660	59	1	section	section	NOUN
cana-660	59	2	iv	iv	NUM
cana-660	59	3	outlines	outline	VERB
cana-660	59	4	the	the	DET
cana-660	59	5	detailed	detailed	ADJ
cana-660	59	6	design	design	NOUN
cana-660	59	7	and	and	CCONJ
cana-660	59	8	experimentation	experimentation	NOUN
cana-660	59	9	of	of	ADP
cana-660	59	10	the	the	DET
cana-660	59	11	proposed	propose	VERB
cana-660	59	12	model	model	NOUN
cana-660	59	13	.	.	PUNCT
cana-660	60	1	the	the	DET
cana-660	60	2	results	result	NOUN
cana-660	60	3	of	of	ADP
cana-660	60	4	the	the	DET
cana-660	60	5	number	number	NOUN
cana-660	60	6	of	of	ADP
cana-660	60	7	features	feature	NOUN
cana-660	60	8	required	require	VERB
cana-660	60	9	in	in	ADP
cana-660	60	10	less	less	ADJ
cana-660	60	11	time	time	NOUN
cana-660	60	12	and	and	CCONJ
cana-660	60	13	how	how	SCONJ
cana-660	60	14	we	we	PRON
cana-660	60	15	find	find	VERB
cana-660	60	16	suitable	suitable	ADJ
cana-660	60	17	features	feature	NOUN
cana-660	60	18	using	use	VERB
cana-660	60	19	the	the	DET
cana-660	60	20	proposed	propose	VERB
cana-660	60	21	framework	framework	NOUN
cana-660	60	22	,	,	PUNCT
cana-660	60	23	which	which	PRON
cana-660	60	24	yields	yield	VERB
cana-660	60	25	better	well	ADJ
cana-660	60	26	performance	performance	NOUN
cana-660	60	27	than	than	ADP
cana-660	60	28	other	other	ADJ
cana-660	60	29	methods	method	NOUN
cana-660	60	30	,	,	PUNCT
cana-660	60	31	are	be	AUX
cana-660	60	32	presented	present	VERB
cana-660	60	33	in	in	ADP
cana-660	60	34	section	section	NOUN
cana-660	60	35	v	v	NOUN
cana-660	60	36	along	along	ADP
cana-660	60	37	with	with	ADP
cana-660	60	38	any	any	DET
cana-660	60	39	limitations	limitation	NOUN
cana-660	60	40	or	or	CCONJ
cana-660	60	41	shortcomings	shortcoming	NOUN
cana-660	60	42	.	.	PUNCT
cana-660	61	1	2.literature	2.literature	NUM
cana-660	61	2	review	review	VERB
cana-660	61	3	the	the	DET
cana-660	61	4	majority	majority	NOUN
cana-660	61	5	of	of	ADP
cana-660	61	6	feature	feature	NOUN
cana-660	61	7	selection	selection	NOUN
cana-660	61	8	models	model	NOUN
cana-660	61	9	that	that	PRON
cana-660	61	10	include	include	VERB
cana-660	61	11	learning	learn	VERB
cana-660	61	12	to	to	PART
cana-660	61	13	rank	rank	VERB
cana-660	61	14	are	be	AUX
cana-660	61	15	employed	employ	VERB
cana-660	61	16	as	as	ADP
cana-660	61	17	an	an	DET
cana-660	61	18	effective	effective	ADJ
cana-660	61	19	means	mean	NOUN
cana-660	61	20	of	of	ADP
cana-660	61	21	managing	manage	VERB
cana-660	61	22	large	large	ADJ
cana-660	61	23	dimensions	dimension	NOUN
cana-660	61	24	with	with	ADP
cana-660	61	25	the	the	DET
cana-660	61	26	goal	goal	NOUN
cana-660	61	27	of	of	ADP
cana-660	61	28	gathering	gather	VERB
cana-660	61	29	the	the	DET
cana-660	61	30	ideal	ideal	NOUN
cana-660	61	31	subset	subset	NOUN
cana-660	61	32	that	that	PRON
cana-660	61	33	offers	offer	VERB
cana-660	61	34	the	the	DET
cana-660	61	35	right	right	ADJ
cana-660	61	36	characteristics	characteristic	NOUN
cana-660	61	37	.	.	PUNCT
cana-660	62	1	the	the	DET
cana-660	62	2	following	follow	VERB
cana-660	62	3	groups	group	NOUN
cana-660	62	4	of	of	ADP
cana-660	62	5	feature	feature	NOUN
cana-660	62	6	selection	selection	NOUN
cana-660	62	7	techniques	technique	NOUN
cana-660	62	8	,	,	PUNCT
cana-660	62	9	including	include	VERB
cana-660	62	10	filters	filter	NOUN
cana-660	62	11	,	,	PUNCT
cana-660	62	12	wrappers	wrapper	NOUN
cana-660	62	13	,	,	PUNCT
cana-660	62	14	embedding	embed	VERB
cana-660	62	15	,	,	PUNCT
cana-660	62	16	and	and	CCONJ
cana-660	62	17	hybrid	hybrid	ADJ
cana-660	62	18	techniques	technique	NOUN
cana-660	62	19	,	,	PUNCT
cana-660	62	20	can	can	AUX
cana-660	62	21	be	be	AUX
cana-660	62	22	generally	generally	ADV
cana-660	62	23	categorized	categorize	VERB
cana-660	62	24	.	.	PUNCT
cana-660	63	1	prior	prior	ADV
cana-660	63	2	to	to	ADP
cana-660	63	3	the	the	DET
cana-660	63	4	commencement	commencement	NOUN
cana-660	63	5	of	of	ADP
cana-660	63	6	learning	learn	VERB
cana-660	63	7	,	,	PUNCT
cana-660	63	8	we	we	PRON
cana-660	63	9	may	may	AUX
cana-660	63	10	identify	identify	VERB
cana-660	63	11	candidate	candidate	NOUN
cana-660	63	12	feature	feature	NOUN
cana-660	63	13	sets	set	NOUN
cana-660	63	14	with	with	ADP
cana-660	63	15	improved	improved	ADJ
cana-660	63	16	performance	performance	NOUN
cana-660	63	17	and	and	CCONJ
cana-660	63	18	accuracy	accuracy	NOUN
cana-660	63	19	.	.	PUNCT
cana-660	64	1	it	it	PRON
cana-660	64	2	is	be	AUX
cana-660	64	3	not	not	PART
cana-660	64	4	feasible	feasible	ADJ
cana-660	64	5	to	to	PART
cana-660	64	6	apply	apply	VERB
cana-660	64	7	the	the	DET
cana-660	64	8	approach	approach	NOUN
cana-660	64	9	to	to	ADP
cana-660	64	10	every	every	DET
cana-660	64	11	real	real	ADJ
cana-660	64	12	-	-	PUNCT
cana-660	64	13	time	time	NOUN
cana-660	64	14	application.we	application.we	X
cana-660	64	15	have	have	AUX
cana-660	64	16	outlined	outline	VERB
cana-660	64	17	much	much	ADJ
cana-660	64	18	research	research	NOUN
cana-660	64	19	pertaining	pertain	VERB
cana-660	64	20	to	to	ADP
cana-660	64	21	distinct	distinct	ADJ
cana-660	64	22	feature	feature	NOUN
cana-660	64	23	selection	selection	NOUN
cana-660	64	24	models	model	NOUN
cana-660	64	25	in	in	ADP
cana-660	64	26	this	this	DET
cana-660	64	27	area	area	NOUN
cana-660	64	28	.	.	PUNCT
cana-660	65	1	changsheng	changsheng	PROPN
cana-660	65	2	li	li	PROPN
cana-660	65	3	et	et	PROPN
cana-660	65	4	.	.	PUNCT
cana-660	66	1	al	al	PROPN
cana-660	66	2	.	.	PUNCT
cana-660	67	1	[	[	X
cana-660	67	2	20	20	NUM
cana-660	67	3	]	]	PUNCT
cana-660	67	4	proposed	propose	VERB
cana-660	67	5	a	a	DET
cana-660	67	6	new	new	ADJ
cana-660	67	7	ranking	ranking	NOUN
cana-660	67	8	method	method	NOUN
cana-660	67	9	with	with	ADP
cana-660	67	10	l	l	PROPN
cana-660	67	11	-	-	PUNCT
cana-660	67	12	t	t	NOUN
cana-660	67	13	-	-	PUNCT
cana-660	67	14	r	r	NOUN
cana-660	67	15	in	in	ADP
cana-660	67	16	which	which	PRON
cana-660	67	17	the	the	DET
cana-660	67	18	feature	feature	NOUN
cana-660	67	19	subset	subset	NOUN
cana-660	67	20	is	be	AUX
cana-660	67	21	sorted	sort	VERB
cana-660	67	22	with	with	ADP
cana-660	67	23	respect	respect	NOUN
cana-660	67	24	to	to	ADP
cana-660	67	25	ranking	ranking	NOUN
cana-660	67	26	and	and	CCONJ
cana-660	67	27	its	its	PRON
cana-660	67	28	accuracy	accuracy	NOUN
cana-660	67	29	.	.	PUNCT
cana-660	68	1	multiple	multiple	ADJ
cana-660	68	2	times	time	NOUN
cana-660	68	3	,	,	PUNCT
cana-660	68	4	the	the	DET
cana-660	68	5	process	process	NOUN
cana-660	68	6	was	be	AUX
cana-660	68	7	repeated	repeat	VERB
cana-660	68	8	,	,	PUNCT
cana-660	68	9	and	and	CCONJ
cana-660	68	10	the	the	DET
cana-660	68	11	results	result	NOUN
cana-660	68	12	were	be	AUX
cana-660	68	13	merged	merge	VERB
cana-660	68	14	to	to	PART
cana-660	68	15	obtain	obtain	VERB
cana-660	68	16	highly	highly	ADV
cana-660	68	17	accurate	accurate	ADJ
cana-660	68	18	results.the	results.the	DET
cana-660	68	19	results	result	NOUN
cana-660	68	20	are	be	AUX
cana-660	68	21	shown	show	VERB
cana-660	68	22	where	where	SCONJ
cana-660	68	23	the	the	DET
cana-660	68	24	maximum	maximum	ADJ
cana-660	68	25	ndcg	ndcg	NOUN
cana-660	68	26	is	be	AUX
cana-660	68	27	0.92	0.92	NUM
cana-660	68	28	with	with	ADP
cana-660	68	29	old	old	ADJ
cana-660	68	30	datasets	dataset	NOUN
cana-660	68	31	such	such	ADJ
cana-660	68	32	as	as	ADP
cana-660	68	33	.gov	.gov	ADJ
cana-660	68	34	,	,	PUNCT
cana-660	68	35	and	and	CCONJ
cana-660	69	1	caltech101	caltech101	PROPN
cana-660	69	2	.	.	PUNCT
cana-660	70	1	evaluation	evaluation	NOUN
cana-660	70	2	on	on	ADP
cana-660	70	3	a	a	DET
cana-660	70	4	standard	standard	ADJ
cana-660	70	5	dataset	dataset	NOUN
cana-660	70	6	was	be	AUX
cana-660	70	7	suggested	suggest	VERB
cana-660	70	8	by	by	ADP
cana-660	70	9	the	the	DET
cana-660	70	10	authors	author	NOUN
cana-660	70	11	.	.	PUNCT
cana-660	71	1	parth	parth	PROPN
cana-660	71	2	gupta	gupta	PROPN
cana-660	71	3	et	et	PROPN
cana-660	71	4	.	.	PUNCT
cana-660	72	1	al.[21	al.[21	PROPN
cana-660	72	2	]	]	PUNCT
cana-660	72	3	proposed	propose	VERB
cana-660	72	4	divergence	divergence	NOUN
cana-660	72	5	based	base	VERB
cana-660	72	6	feature	feature	NOUN
cana-660	72	7	selection	selection	NOUN
cana-660	72	8	on	on	ADP
cana-660	72	9	standard	standard	ADJ
cana-660	72	10	datasets	dataset	NOUN
cana-660	72	11	.	.	PUNCT
cana-660	73	1	an	an	DET
cana-660	73	2	important	important	ADJ
cana-660	73	3	feature	feature	NOUN
cana-660	73	4	of	of	ADP
cana-660	73	5	this	this	DET
cana-660	73	6	approach	approach	NOUN
cana-660	73	7	is	be	AUX
cana-660	73	8	that	that	SCONJ
cana-660	73	9	it	it	PRON
cana-660	73	10	is	be	AUX
cana-660	73	11	parallelized	parallelize	VERB
cana-660	73	12	.	.	PUNCT
cana-660	74	1	its	its	PRON
cana-660	74	2	performance	performance	NOUN
cana-660	74	3	is	be	AUX
cana-660	74	4	better	well	ADJ
cana-660	74	5	in	in	ADP
cana-660	74	6	some	some	DET
cana-660	74	7	cases	case	NOUN
cana-660	74	8	than	than	ADP
cana-660	74	9	that	that	PRON
cana-660	74	10	of	of	ADP
cana-660	74	11	the	the	DET
cana-660	74	12	baseline	baseline	NOUN
cana-660	74	13	for	for	ADP
cana-660	74	14	all	all	DET
cana-660	74	15	the	the	DET
cana-660	74	16	databases	database	NOUN
cana-660	74	17	.	.	PUNCT
cana-660	75	1	finally	finally	ADV
cana-660	75	2	,	,	PUNCT
cana-660	75	3	the	the	DET
cana-660	75	4	authors	author	NOUN
cana-660	75	5	applied	apply	VERB
cana-660	75	6	the	the	DET
cana-660	75	7	greedy	greedy	ADJ
cana-660	75	8	large	large	ADJ
cana-660	75	9	marginal	marginal	ADJ
cana-660	75	10	classifier	classifier	NOUN
cana-660	75	11	-based	-base	VERB
cana-660	75	12	ranking	ranking	NOUN
cana-660	75	13	method	method	NOUN
cana-660	75	14	.	.	PUNCT
cana-660	76	1	han	han	PROPN
cana-660	76	2	-	-	PUNCT
cana-660	76	3	jiang	jiang	PROPN
cana-660	76	4	lai	lai	PROPN
cana-660	76	5	et	et	PROPN
cana-660	76	6	.	.	PUNCT
cana-660	77	1	al	al	PROPN
cana-660	77	2	.	.	PUNCT
cana-660	78	1	[	[	X
cana-660	78	2	22	22	NUM
cana-660	78	3	]	]	PUNCT
cana-660	78	4	proposed	propose	VERB
cana-660	78	5	the	the	DET
cana-660	78	6	fsmrank	fsmrank	ADJ
cana-660	78	7	algorithm	algorithm	NOUN
cana-660	78	8	for	for	ADP
cana-660	78	9	feature	feature	NOUN
cana-660	78	10	selection	selection	NOUN
cana-660	78	11	,	,	PUNCT
cana-660	78	12	which	which	PRON
cana-660	78	13	is	be	AUX
cana-660	78	14	used	use	VERB
cana-660	78	15	for	for	ADP
cana-660	78	16	ranking	rank	VERB
cana-660	78	17	.	.	PUNCT
cana-660	79	1	the	the	DET
cana-660	79	2	authors	author	NOUN
cana-660	79	3	developed	develop	VERB
cana-660	79	4	a	a	DET
cana-660	79	5	formula	formula	NOUN
cana-660	79	6	with	with	ADP
cana-660	79	7	join	join	VERB
cana-660	79	8	convex	convex	NOUN
cana-660	79	9	optimization	optimization	NOUN
cana-660	79	10	.	.	PUNCT
cana-660	80	1	this	this	DET
cana-660	80	2	approach	approach	NOUN
cana-660	80	3	is	be	AUX
cana-660	80	4	useful	useful	ADJ
cana-660	80	5	for	for	ADP
cana-660	80	6	reducing	reduce	VERB
cana-660	80	7	the	the	DET
cana-660	80	8	ranking	ranking	NOUN
cana-660	80	9	error	error	NOUN
cana-660	80	10	with	with	ADP
cana-660	80	11	feature	feature	NOUN
cana-660	80	12	selection.finally	selection.finally	ADV
cana-660	80	13	,	,	PUNCT
cana-660	80	14	they	they	PRON
cana-660	80	15	concluded	conclude	VERB
cana-660	80	16	that	that	SCONJ
cana-660	80	17	this	this	PRON
cana-660	80	18	is	be	AUX
cana-660	80	19	a	a	DET
cana-660	80	20	flexible	flexible	ADJ
cana-660	80	21	framework	framework	NOUN
cana-660	80	22	with	with	ADP
cana-660	80	23	optimization	optimization	NOUN
cana-660	80	24	.	.	PUNCT
cana-660	81	1	andrea	andrea	PROPN
cana-660	81	2	gigli	gigli	PROPN
cana-660	81	3	et	et	PROPN
cana-660	81	4	.	.	PUNCT
cana-660	82	1	al.[13	al.[13	PROPN
cana-660	82	2	]	]	PUNCT
cana-660	82	3	proposed	propose	VERB
cana-660	82	4	three	three	NUM
cana-660	82	5	greedy	greedy	ADJ
cana-660	82	6	algorithms	algorithm	NOUN
cana-660	82	7	,	,	PUNCT
cana-660	82	8	namely	namely	ADV
cana-660	82	9	,	,	PUNCT
cana-660	82	10	ngas	ngas	ADJ
cana-660	82	11	,	,	PUNCT
cana-660	82	12	xgas	xga	NOUN
cana-660	82	13	,	,	PUNCT
cana-660	82	14	and	and	CCONJ
cana-660	82	15	hcas	hca	NOUN
cana-660	82	16	.	.	PUNCT
cana-660	83	1	in	in	ADP
cana-660	83	2	one	one	NUM
cana-660	83	3	of	of	ADP
cana-660	83	4	the	the	DET
cana-660	83	5	algorithms	algorithm	NOUN
cana-660	83	6	,	,	PUNCT
cana-660	83	7	feature	feature	NOUN
cana-660	83	8	selection	selection	NOUN
cana-660	83	9	is	be	AUX
cana-660	83	10	based	base	VERB
cana-660	83	11	on	on	ADP
cana-660	83	12	pairwise	pairwise	NOUN
cana-660	83	13	similarity	similarity	NOUN
cana-660	83	14	with	with	ADP
cana-660	83	15	relevance	relevance	NOUN
cana-660	83	16	.	.	PUNCT
cana-660	84	1	furthermore	furthermore	ADV
cana-660	84	2	,	,	PUNCT
cana-660	84	3	each	each	DET
cana-660	84	4	algorithm	algorithm	NOUN
cana-660	84	5	considers	consider	VERB
cana-660	84	6	a	a	DET
cana-660	84	7	larger	large	ADJ
cana-660	84	8	number	number	NOUN
cana-660	84	9	of	of	ADP
cana-660	84	10	subset	subset	NOUN
cana-660	84	11	iterations	iteration	NOUN
cana-660	84	12	.	.	PUNCT
cana-660	85	1	hcas	hcas	NOUN
cana-660	85	2	works	work	VERB
cana-660	85	3	on	on	ADP
cana-660	85	4	clustering	cluster	VERB
cana-660	85	5	to	to	PART
cana-660	85	6	perform	perform	VERB
cana-660	85	7	feature	feature	NOUN
cana-660	85	8	selection	selection	NOUN
cana-660	85	9	.	.	PUNCT
cana-660	86	1	the	the	DET
cana-660	86	2	authors	author	NOUN
cana-660	86	3	conclude	conclude	VERB
cana-660	86	4	the	the	DET
cana-660	86	5	paper	paper	NOUN
cana-660	86	6	with	with	ADP
cana-660	86	7	the	the	DET
cana-660	86	8	future	future	ADJ
cana-660	86	9	scope	scope	NOUN
cana-660	86	10	of	of	ADP
cana-660	86	11	work	work	NOUN
cana-660	86	12	on	on	ADP
cana-660	86	13	various	various	ADJ
cana-660	86	14	dimensions	dimension	NOUN
cana-660	86	15	with	with	ADP
cana-660	86	16	other	other	ADJ
cana-660	86	17	classes	class	NOUN
cana-660	86	18	of	of	ADP
cana-660	86	19	classification	classification	NOUN
cana-660	86	20	.	.	PUNCT
cana-660	87	1	communications	communication	NOUN
cana-660	87	2	on	on	ADP
cana-660	87	3	applied	apply	VERB
cana-660	87	4	nonlinear	nonlinear	ADJ
cana-660	87	5	analysis	analysis	NOUN
cana-660	87	6	issn	issn	NOUN
cana-660	87	7	:	:	PUNCT
cana-660	87	8	1074	1074	NUM
cana-660	87	9	-	-	PUNCT
cana-660	87	10	133x	133x	NUM
cana-660	87	11	vol	vol	NOUN
cana-660	87	12	31	31	NUM
cana-660	87	13	no	no	NOUN
cana-660	87	14	.	.	PUNCT
cana-660	88	1	2s	2s	NUM
cana-660	88	2	(	(	PUNCT
cana-660	88	3	2024	2024	NUM
cana-660	88	4	)	)	PUNCT
cana-660	88	5	457	457	NUM
cana-660	88	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	88	7	to	to	PART
cana-660	88	8	address	address	VERB
cana-660	88	9	the	the	DET
cana-660	88	10	issue	issue	NOUN
cana-660	88	11	of	of	ADP
cana-660	88	12	risk	risk	NOUN
cana-660	88	13	sensitivity	sensitivity	NOUN
cana-660	88	14	,	,	PUNCT
cana-660	88	15	the	the	DET
cana-660	88	16	number	number	NOUN
cana-660	88	17	of	of	ADP
cana-660	88	18	best	good	ADJ
cana-660	88	19	subsets	subset	NOUN
cana-660	88	20	of	of	ADP
cana-660	88	21	features	feature	NOUN
cana-660	88	22	and	and	CCONJ
cana-660	88	23	performance	performance	NOUN
cana-660	88	24	were	be	AUX
cana-660	88	25	calculated	calculate	VERB
cana-660	88	26	according	accord	VERB
cana-660	88	27	to	to	ADP
cana-660	88	28	daniel	daniel	PROPN
cana-660	88	29	xavier	xavier	PROPN
cana-660	88	30	et	et	PROPN
cana-660	88	31	al	al	PROPN
cana-660	88	32	.	.	PUNCT
cana-660	89	1	[	[	X
cana-660	89	2	24	24	NUM
cana-660	89	3	]	]	PUNCT
cana-660	89	4	.	.	PUNCT
cana-660	90	1	proposed	propose	VERB
cana-660	90	2	multii	multii	PROPN
cana-660	90	3	-	-	PUNCT
cana-660	90	4	objective	objective	ADJ
cana-660	90	5	feature	feature	NOUN
cana-660	90	6	selection	selection	NOUN
cana-660	90	7	.	.	PUNCT
cana-660	91	1	additionally	additionally	ADV
cana-660	91	2	,	,	PUNCT
cana-660	91	3	they	they	PRON
cana-660	91	4	reduce	reduce	VERB
cana-660	91	5	the	the	DET
cana-660	91	6	multidimensionality	multidimensionality	NOUN
cana-660	91	7	while	while	SCONJ
cana-660	91	8	solving	solve	VERB
cana-660	91	9	risk	risk	NOUN
cana-660	91	10	in	in	ADP
cana-660	91	11	many	many	ADJ
cana-660	91	12	queries	query	NOUN
cana-660	91	13	.	.	PUNCT
cana-660	92	1	the	the	DET
cana-660	92	2	results	result	NOUN
cana-660	92	3	are	be	AUX
cana-660	92	4	improved	improve	VERB
cana-660	92	5	compared	compare	VERB
cana-660	92	6	with	with	ADP
cana-660	92	7	those	those	PRON
cana-660	92	8	of	of	ADP
cana-660	92	9	previous	previous	ADJ
cana-660	92	10	studies	study	NOUN
cana-660	92	11	on	on	ADP
cana-660	92	12	handling	handle	VERB
cana-660	92	13	risk	risk	NOUN
cana-660	92	14	.	.	PUNCT
cana-660	93	1	the	the	DET
cana-660	93	2	conclusions	conclusion	NOUN
cana-660	93	3	of	of	ADP
cana-660	93	4	this	this	DET
cana-660	93	5	study	study	NOUN
cana-660	93	6	suggest	suggest	VERB
cana-660	93	7	that	that	SCONJ
cana-660	93	8	multiple	multiple	ADJ
cana-660	93	9	objective	objective	ADJ
cana-660	93	10	methods	method	NOUN
cana-660	93	11	are	be	AUX
cana-660	93	12	useful	useful	ADJ
cana-660	93	13	in	in	ADP
cana-660	93	14	many	many	ADJ
cana-660	93	15	domains	domain	NOUN
cana-660	93	16	.	.	PUNCT
cana-660	94	1	mehrnoush	mehrnoush	PROPN
cana-660	94	2	shirzad	shirzad	PROPN
cana-660	94	3	et	et	PROPN
cana-660	94	4	al	al	PROPN
cana-660	94	5	.	.	PUNCT
cana-660	95	1	[	[	X
cana-660	95	2	25	25	NUM
cana-660	95	3	]	]	PUNCT
cana-660	95	4	provided	provide	VERB
cana-660	95	5	an	an	DET
cana-660	95	6	overview	overview	NOUN
cana-660	95	7	of	of	ADP
cana-660	95	8	all	all	DET
cana-660	95	9	feature	feature	NOUN
cana-660	95	10	selection	selection	NOUN
cana-660	95	11	methods	method	NOUN
cana-660	95	12	and	and	CCONJ
cana-660	95	13	applied	apply	VERB
cana-660	95	14	them	they	PRON
cana-660	95	15	to	to	ADP
cana-660	95	16	the	the	DET
cana-660	95	17	fslr	fslr	NOUN
cana-660	95	18	framework	framework	NOUN
cana-660	95	19	.	.	PUNCT
cana-660	96	1	the	the	DET
cana-660	96	2	exploration	exploration	NOUN
cana-660	96	3	of	of	ADP
cana-660	96	4	filter	filter	NOUN
cana-660	96	5	,	,	PUNCT
cana-660	96	6	wrapper	wrapper	NOUN
cana-660	96	7	and	and	CCONJ
cana-660	96	8	embedded	embed	VERB
cana-660	96	9	techniques	technique	NOUN
cana-660	96	10	was	be	AUX
cana-660	96	11	useful	useful	ADJ
cana-660	96	12	for	for	ADP
cana-660	96	13	identifying	identify	VERB
cana-660	96	14	better	well	ADJ
cana-660	96	15	subsets	subset	NOUN
cana-660	96	16	of	of	ADP
cana-660	96	17	features	feature	NOUN
cana-660	96	18	with	with	ADP
cana-660	96	19	respect	respect	NOUN
cana-660	96	20	to	to	ADP
cana-660	96	21	the	the	DET
cana-660	96	22	hypothesis	hypothesis	NOUN
cana-660	96	23	of	of	ADP
cana-660	96	24	classification	classification	NOUN
cana-660	96	25	.	.	PUNCT
cana-660	97	1	collaborative	collaborative	ADJ
cana-660	97	2	features	feature	NOUN
cana-660	97	3	will	will	AUX
cana-660	97	4	help	help	VERB
cana-660	97	5	improve	improve	VERB
cana-660	97	6	fs	fs	ADP
cana-660	97	7	and	and	CCONJ
cana-660	97	8	work	work	VERB
cana-660	97	9	on	on	ADP
cana-660	97	10	many	many	ADJ
cana-660	97	11	applications.fan	applications.fan	X
cana-660	97	12	cheng	cheng	PROPN
cana-660	97	13	et	et	PROPN
cana-660	97	14	.	.	PUNCT
cana-660	98	1	al.[26	al.[26	PROPN
cana-660	98	2	]	]	PUNCT
cana-660	98	3	proposed	propose	VERB
cana-660	98	4	an	an	DET
cana-660	98	5	evolutionary	evolutionary	ADJ
cana-660	98	6	system	system	NOUN
cana-660	98	7	based	base	VERB
cana-660	98	8	on	on	ADP
cana-660	98	9	a	a	DET
cana-660	98	10	multiobjective	multiobjective	ADJ
cana-660	98	11	function	function	NOUN
cana-660	98	12	called	call	VERB
cana-660	98	13	mofsrank	mofsrank	PROPN
cana-660	98	14	.	.	PUNCT
cana-660	99	1	with	with	ADP
cana-660	99	2	the	the	DET
cana-660	99	3	integration	integration	NOUN
cana-660	99	4	of	of	ADP
cana-660	99	5	moea	moea	NOUN
cana-660	99	6	,	,	PUNCT
cana-660	99	7	mofs	mof	NOUN
cana-660	99	8	,	,	PUNCT
cana-660	99	9	moen	moen	NOUN
cana-660	99	10	and	and	CCONJ
cana-660	99	11	mofs	mof	NOUN
cana-660	99	12	,	,	PUNCT
cana-660	99	13	mofsrank	mofsrank	PROPN
cana-660	99	14	was	be	AUX
cana-660	99	15	developed	develop	VERB
cana-660	99	16	,	,	PUNCT
cana-660	99	17	and	and	CCONJ
cana-660	99	18	its	its	PRON
cana-660	99	19	performance	performance	NOUN
cana-660	99	20	improved	improve	VERB
cana-660	99	21	.	.	PUNCT
cana-660	100	1	in	in	ADP
cana-660	100	2	the	the	DET
cana-660	100	3	future	future	NOUN
cana-660	100	4	,	,	PUNCT
cana-660	100	5	we	we	PRON
cana-660	100	6	will	will	AUX
cana-660	100	7	focus	focus	VERB
cana-660	100	8	on	on	ADP
cana-660	100	9	listwise	listwise	ADJ
cana-660	100	10	approaches	approach	NOUN
cana-660	100	11	with	with	ADP
cana-660	100	12	more	more	ADJ
cana-660	100	13	evolutionary	evolutionary	ADJ
cana-660	100	14	methods	method	NOUN
cana-660	100	15	with	with	ADP
cana-660	100	16	different	different	ADJ
cana-660	100	17	datasets	dataset	NOUN
cana-660	100	18	.	.	PUNCT
cana-660	101	1	fahandar	fahandar	PROPN
cana-660	101	2	,	,	PUNCT
cana-660	101	3	mohsen	mohsen	PROPN
cana-660	101	4	et	et	PROPN
cana-660	101	5	.	.	PUNCT
cana-660	102	1	al.[28	al.[28	PROPN
cana-660	102	2	]	]	PUNCT
cana-660	102	3	proposed	propose	VERB
cana-660	102	4	a	a	DET
cana-660	102	5	new	new	ADJ
cana-660	102	6	framework	framework	NOUN
cana-660	102	7	for	for	ADP
cana-660	102	8	feature	feature	NOUN
cana-660	102	9	selection	selection	NOUN
cana-660	102	10	called	call	VERB
cana-660	102	11	analogy	analogy	NOUN
cana-660	102	12	-	-	PUNCT
cana-660	102	13	based	base	VERB
cana-660	102	14	ltr	ltr	NOUN
cana-660	102	15	,	,	PUNCT
cana-660	102	16	author	author	NOUN
cana-660	102	17	described	describe	VERB
cana-660	102	18	the	the	DET
cana-660	102	19	problem	problem	NOUN
cana-660	102	20	of	of	ADP
cana-660	102	21	fs	fs	ADP
cana-660	102	22	techniques	technique	NOUN
cana-660	102	23	,	,	PUNCT
cana-660	102	24	which	which	PRON
cana-660	102	25	was	be	AUX
cana-660	102	26	explored	explore	VERB
cana-660	102	27	by	by	ADP
cana-660	102	28	fan	fan	PROPN
cana-660	102	29	cheng	cheng	PROPN
cana-660	102	30	et	et	PROPN
cana-660	102	31	.	.	PUNCT
cana-660	103	1	al.[26	al.[26	PROPN
cana-660	103	2	]	]	PUNCT
cana-660	103	3	.	.	PUNCT
cana-660	104	1	by	by	ADP
cana-660	104	2	correlation	correlation	NOUN
cana-660	104	3	and	and	CCONJ
cana-660	104	4	relief	relief	NOUN
cana-660	104	5	base	base	NOUN
cana-660	104	6	technique	technique	NOUN
cana-660	104	7	technique	technique	NOUN
cana-660	104	8	,	,	PUNCT
cana-660	104	9	the	the	DET
cana-660	104	10	authors	author	NOUN
cana-660	104	11	evaluated	evaluate	VERB
cana-660	104	12	the	the	DET
cana-660	104	13	real	real	ADJ
cana-660	104	14	-time	-time	PROPN
cana-660	104	15	data	datum	NOUN
cana-660	104	16	and	and	CCONJ
cana-660	104	17	proved	prove	VERB
cana-660	104	18	the	the	DET
cana-660	104	19	necessity	necessity	NOUN
cana-660	104	20	of	of	ADP
cana-660	104	21	fs	fs	PROPN
cana-660	104	22	.	.	PUNCT
cana-660	105	1	the	the	DET
cana-660	105	2	weighted	weight	VERB
cana-660	105	3	matrix	matrix	NOUN
cana-660	105	4	and	and	CCONJ
cana-660	105	5	co	co	VERB
cana-660	105	6	-	-	VERB
cana-660	105	7	embedding	embed	VERB
cana-660	105	8	can	can	AUX
cana-660	105	9	be	be	AUX
cana-660	105	10	used	use	VERB
cana-660	105	11	as	as	ADP
cana-660	105	12	future	future	ADJ
cana-660	105	13	functions	function	NOUN
cana-660	105	14	of	of	ADP
cana-660	105	15	the	the	DET
cana-660	105	16	same	same	ADJ
cana-660	105	17	categorical	categorical	ADJ
cana-660	105	18	data.a	data.a	PROPN
cana-660	105	19	.	.	PROPN
cana-660	105	20	rahangdale	rahangdale	PROPN
cana-660	105	21	et	et	PROPN
cana-660	105	22	al	al	PROPN
cana-660	105	23	.	.	PUNCT
cana-660	106	1	[	[	X
cana-660	106	2	1	1	X
cana-660	106	3	]	]	PUNCT
cana-660	106	4	suggested	suggest	VERB
cana-660	106	5	a	a	DET
cana-660	106	6	deep	deep	ADJ
cana-660	106	7	learning	learning	NOUN
cana-660	106	8	model	model	NOUN
cana-660	106	9	for	for	ADP
cana-660	106	10	l1	l1	PROPN
cana-660	106	11	and	and	CCONJ
cana-660	106	12	l2	l2	VERB
cana-660	106	13	regularization	regularization	NOUN
cana-660	106	14	-	-	PUNCT
cana-660	106	15	based	base	VERB
cana-660	106	16	feature	feature	NOUN
cana-660	106	17	selection	selection	NOUN
cana-660	106	18	.	.	PUNCT
cana-660	107	1	the	the	DET
cana-660	107	2	author	author	NOUN
cana-660	107	3	assessed	assess	VERB
cana-660	107	4	the	the	DET
cana-660	107	5	outcomes	outcome	NOUN
cana-660	107	6	of	of	ADP
cana-660	107	7	conventional	conventional	ADJ
cana-660	107	8	learning	learning	NOUN
cana-660	107	9	in	in	ADP
cana-660	107	10	terms	term	NOUN
cana-660	107	11	of	of	ADP
cana-660	107	12	feature	feature	NOUN
cana-660	107	13	selection	selection	NOUN
cana-660	107	14	methods	method	NOUN
cana-660	107	15	and	and	CCONJ
cana-660	107	16	rankings	ranking	NOUN
cana-660	107	17	.	.	PUNCT
cana-660	108	1	furthermore	furthermore	ADV
cana-660	108	2	,	,	PUNCT
cana-660	108	3	they	they	PRON
cana-660	108	4	concluded	conclude	VERB
cana-660	108	5	that	that	SCONJ
cana-660	108	6	a	a	DET
cana-660	108	7	deep	deep	ADJ
cana-660	108	8	neural	neural	ADJ
cana-660	108	9	network	network	NOUN
cana-660	108	10	design	design	NOUN
cana-660	108	11	with	with	ADP
cana-660	108	12	appropriate	appropriate	ADJ
cana-660	108	13	regularization	regularization	NOUN
cana-660	108	14	techniques	technique	NOUN
cana-660	108	15	can	can	AUX
cana-660	108	16	aid	aid	VERB
cana-660	108	17	in	in	ADP
cana-660	108	18	the	the	DET
cana-660	108	19	discovery	discovery	NOUN
cana-660	108	20	of	of	ADP
cana-660	108	21	greater	great	ADJ
cana-660	108	22	functionality	functionality	NOUN
cana-660	108	23	.	.	PUNCT
cana-660	109	1	a.	a.	NOUN
cana-660	109	2	purpura	purpura	PROPN
cana-660	109	3	et	et	PROPN
cana-660	109	4	al	al	PROPN
cana-660	109	5	.	.	PUNCT
cana-660	110	1	[	[	X
cana-660	110	2	27	27	NUM
cana-660	110	3	]	]	PUNCT
cana-660	110	4	suggested	suggest	VERB
cana-660	110	5	a	a	DET
cana-660	110	6	neural	neural	ADJ
cana-660	110	7	network	network	NOUN
cana-660	110	8	for	for	ADP
cana-660	110	9	fss	fss	ADJ
cana-660	110	10	over	over	ADP
cana-660	110	11	large	large	ADJ
cana-660	110	12	-	-	PUNCT
cana-660	110	13	scale	scale	NOUN
cana-660	110	14	search	search	NOUN
cana-660	110	15	models	model	NOUN
cana-660	110	16	named	name	VERB
cana-660	110	17	neural	neural	ADJ
cana-660	110	18	reranker	reranker	NOUN
cana-660	110	19	.	.	PUNCT
cana-660	111	1	it	it	PRON
cana-660	111	2	is	be	AUX
cana-660	111	3	proposed	propose	VERB
cana-660	111	4	for	for	ADP
cana-660	111	5	the	the	DET
cana-660	111	6	optimization	optimization	NOUN
cana-660	111	7	of	of	ADP
cana-660	111	8	letor	letor	ADJ
cana-660	111	9	methods	method	NOUN
cana-660	111	10	without	without	ADP
cana-660	111	11	changing	change	VERB
cana-660	111	12	the	the	DET
cana-660	111	13	architecture.the	architecture.the	PRON
cana-660	111	14	training	training	NOUN
cana-660	111	15	time	time	NOUN
cana-660	111	16	was	be	AUX
cana-660	111	17	reduced	reduce	VERB
cana-660	111	18	in	in	ADP
cana-660	111	19	the	the	DET
cana-660	111	20	proposed	propose	VERB
cana-660	111	21	system	system	NOUN
cana-660	111	22	,	,	PUNCT
cana-660	111	23	and	and	CCONJ
cana-660	111	24	the	the	DET
cana-660	111	25	efficiency	efficiency	NOUN
cana-660	111	26	was	be	AUX
cana-660	111	27	significantly	significantly	ADV
cana-660	111	28	improved	improve	VERB
cana-660	111	29	.	.	PUNCT
cana-660	112	1	they	they	PRON
cana-660	112	2	applied	apply	VERB
cana-660	112	3	the	the	DET
cana-660	112	4	approach	approach	NOUN
cana-660	112	5	to	to	ADP
cana-660	112	6	the	the	DET
cana-660	112	7	standard	standard	ADJ
cana-660	112	8	datasets	dataset	NOUN
cana-660	112	9	mslr	mslr	NOUN
cana-660	112	10	-	-	PUNCT
cana-660	112	11	web30k	web30k	PUNCT
cana-660	112	12	and	and	CCONJ
cana-660	112	13	ohsumed	ohsume	VERB
cana-660	112	14	.	.	PUNCT
cana-660	113	1	the	the	DET
cana-660	113	2	study	study	NOUN
cana-660	113	3	concluded	conclude	VERB
cana-660	113	4	that	that	SCONJ
cana-660	113	5	this	this	DET
cana-660	113	6	method	method	NOUN
cana-660	113	7	should	should	AUX
cana-660	113	8	be	be	AUX
cana-660	113	9	used	use	VERB
cana-660	113	10	for	for	ADP
cana-660	113	11	other	other	ADJ
cana-660	113	12	datasets.the	datasets.the	NOUN
cana-660	113	13	above	above	ADP
cana-660	113	14	literature	literature	NOUN
cana-660	113	15	review	review	NOUN
cana-660	113	16	suggested	suggest	VERB
cana-660	113	17	that	that	SCONJ
cana-660	113	18	feature	feature	NOUN
cana-660	113	19	selection	selection	NOUN
cana-660	113	20	is	be	AUX
cana-660	113	21	an	an	DET
cana-660	113	22	important	important	ADJ
cana-660	113	23	aspect	aspect	NOUN
cana-660	113	24	of	of	ADP
cana-660	113	25	learning	learn	VERB
cana-660	113	26	to	to	PART
cana-660	113	27	rank	rank	VERB
cana-660	113	28	,	,	PUNCT
cana-660	113	29	as	as	ADP
cana-660	113	30	per	per	ADP
cana-660	113	31	past	past	ADJ
cana-660	113	32	studies	study	NOUN
cana-660	113	33	,	,	PUNCT
cana-660	113	34	but	but	CCONJ
cana-660	113	35	can	can	AUX
cana-660	113	36	be	be	AUX
cana-660	113	37	improved	improve	VERB
cana-660	113	38	by	by	ADP
cana-660	113	39	using	use	VERB
cana-660	113	40	any	any	DET
cana-660	113	41	hybrid	hybrid	ADJ
cana-660	113	42	method	method	NOUN
cana-660	113	43	.	.	PUNCT
cana-660	114	1	sr	sr	PROPN
cana-660	114	2	.	.	PUNCT
cana-660	115	1	no	no	INTJ
cana-660	115	2	.	.	PUNCT
cana-660	116	1	citation	citation	NOUN
cana-660	116	2	number	number	NOUN
cana-660	116	3	approach	approach	NOUN
cana-660	116	4	type	type	NOUN
cana-660	116	5	method	method	NOUN
cana-660	116	6	name	name	NOUN
cana-660	116	7	database	database	NOUN
cana-660	116	8	used	use	VERB
cana-660	116	9	evaluation	evaluation	NOUN
cana-660	116	10	1	1	NUM
cana-660	117	1	[	[	SYM
cana-660	117	2	20	20	NUM
cana-660	117	3	]	]	PUNCT
cana-660	117	4	listwise	listwise	ADJ
cana-660	117	5	new	new	ADJ
cana-660	117	6	ranking	ranking	NOUN
cana-660	117	7	method	method	NOUN
cana-660	117	8	with	with	ADP
cana-660	117	9	l	l	PROPN
cana-660	117	10	-	-	PUNCT
cana-660	117	11	t	t	NOUN
cana-660	117	12	-	-	PUNCT
cana-660	117	13	r	r	NOUN
cana-660	117	14	.gov	.gov	NOUN
cana-660	117	15	,	,	PUNCT
cana-660	117	16	caltech101	caltech101	PROPN
cana-660	117	17	evaluation	evaluation	NOUN
cana-660	117	18	on	on	ADP
cana-660	117	19	standard	standard	ADJ
cana-660	117	20	dataset	dataset	NOUN
cana-660	117	21	suggested	suggest	VERB
cana-660	117	22	by	by	ADP
cana-660	117	23	the	the	DET
cana-660	117	24	authors	author	NOUN
cana-660	117	25	2	2	NUM
cana-660	117	26	[	[	X
cana-660	117	27	21	21	NUM
cana-660	117	28	]	]	AUX
cana-660	117	29	pointwise	pointwise	VERB
cana-660	117	30	divergence	divergence	NOUN
cana-660	117	31	-	-	PUNCT
cana-660	117	32	based	base	VERB
cana-660	117	33	feature	feature	NOUN
cana-660	117	34	selection	selection	NOUN
cana-660	117	35	,	,	PUNCT
cana-660	117	36	greedy	greedy	ADJ
cana-660	117	37	large	large	ADJ
cana-660	117	38	marginal	marginal	ADJ
cana-660	117	39	classifier	classifier	NOUN
cana-660	117	40	-	-	PUNCT
cana-660	117	41	based	base	VERB
cana-660	117	42	ranking	ranking	NOUN
cana-660	117	43	ohsumed	ohsume	VERB
cana-660	117	44	,	,	PUNCT
cana-660	117	45	hp2004	hp2004	PROPN
cana-660	117	46	,	,	PUNCT
cana-660	117	47	np2004	np2004	PROPN
cana-660	117	48	,	,	PUNCT
cana-660	117	49	mq2008	mq2008	NOUN
cana-660	117	50	future	future	ADJ
cana-660	117	51	focus	focus	VERB
cana-660	117	52	on	on	ADP
cana-660	117	53	listwise	listwise	ADJ
cana-660	117	54	approaches	approach	NOUN
cana-660	117	55	with	with	ADP
cana-660	117	56	evolutionary	evolutionary	ADJ
cana-660	117	57	methods	method	NOUN
cana-660	117	58	3	3	NUM
cana-660	117	59	[	[	X
cana-660	117	60	22	22	NUM
cana-660	117	61	]	]	PUNCT
cana-660	117	62	listwise	listwise	ADJ
cana-660	117	63	fsmrank	fsmrank	ADJ
cana-660	117	64	algorithm	algorithm	NOUN
cana-660	117	65	for	for	ADP
cana-660	117	66	feature	feature	NOUN
cana-660	117	67	selection	selection	NOUN
cana-660	117	68	and	and	CCONJ
cana-660	117	69	ranking	ranking	NOUN
cana-660	117	70	ohsumed	ohsume	VERB
cana-660	117	71	,	,	PUNCT
cana-660	117	72	hp2004	hp2004	PROPN
cana-660	117	73	,	,	PUNCT
cana-660	117	74	np2004	np2004	PROPN
cana-660	117	75	,	,	PUNCT
cana-660	117	76	mq2008	mq2008	NOUN
cana-660	117	77	future	future	ADJ
cana-660	117	78	scope	scope	NOUN
cana-660	117	79	on	on	ADP
cana-660	117	80	various	various	ADJ
cana-660	117	81	dimensions	dimension	NOUN
cana-660	117	82	4	4	NUM
cana-660	117	83	[	[	SYM
cana-660	117	84	13	13	NUM
cana-660	117	85	]	]	PUNCT
cana-660	117	86	listwise	listwise	ADJ
cana-660	117	87	ngas	ngas	NOUN
cana-660	117	88	,	,	PUNCT
cana-660	117	89	xgas	xga	NOUN
cana-660	117	90	,	,	PUNCT
cana-660	117	91	hcas	hca	NOUN
cana-660	117	92	algorithms	algorithm	NOUN
cana-660	117	93	for	for	ADP
cana-660	117	94	feature	feature	NOUN
cana-660	117	95	selection	selection	NOUN
cana-660	117	96	,	,	PUNCT
cana-660	117	97	pairwise	pairwise	PROPN
cana-660	117	98	ohsumed	ohsume	VERB
cana-660	117	99	,	,	PUNCT
cana-660	117	100	letor	letor	NOUN
cana-660	117	101	4.0,y	4.0,y	PROPN
cana-660	117	102	ahoo	ahoo	NOUN
cana-660	117	103	!	!	PROPN
cana-660	117	104	,	,	PUNCT
cana-660	117	105	future	future	ADJ
cana-660	117	106	scope	scope	NOUN
cana-660	117	107	of	of	ADP
cana-660	117	108	work	work	NOUN
cana-660	117	109	on	on	ADP
cana-660	117	110	various	various	ADJ
cana-660	117	111	dimensions	dimension	NOUN
cana-660	117	112	with	with	ADP
cana-660	117	113	communications	communication	NOUN
cana-660	117	114	on	on	ADP
cana-660	117	115	applied	apply	VERB
cana-660	117	116	nonlinear	nonlinear	ADJ
cana-660	117	117	analysis	analysis	NOUN
cana-660	117	118	issn	issn	NOUN
cana-660	117	119	:	:	PUNCT
cana-660	117	120	1074	1074	NUM
cana-660	117	121	-	-	PUNCT
cana-660	117	122	133x	133x	NUM
cana-660	117	123	vol	vol	NOUN
cana-660	117	124	31	31	NUM
cana-660	117	125	no	no	NOUN
cana-660	117	126	.	.	PUNCT
cana-660	118	1	2s	2s	NUM
cana-660	118	2	(	(	PUNCT
cana-660	118	3	2024	2024	NUM
cana-660	118	4	)	)	PUNCT
cana-660	118	5	458	458	NUM
cana-660	118	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	118	7	similarity	similarity	NOUN
cana-660	118	8	-	-	PUNCT
cana-660	118	9	based	base	VERB
cana-660	118	10	feature	feature	NOUN
cana-660	118	11	selection	selection	NOUN
cana-660	118	12	other	other	ADJ
cana-660	118	13	classes	class	NOUN
cana-660	118	14	of	of	ADP
cana-660	118	15	classification	classification	NOUN
cana-660	118	16	5	5	NUM
cana-660	118	17	[	[	SYM
cana-660	118	18	24	24	NUM
cana-660	118	19	]	]	PUNCT
cana-660	118	20	listwise	listwise	ADJ
cana-660	118	21	multi	multi	ADJ
cana-660	118	22	-	-	ADJ
cana-660	118	23	objective	objective	ADJ
cana-660	118	24	feature	feature	NOUN
cana-660	118	25	selection	selection	NOUN
cana-660	118	26	to	to	PART
cana-660	118	27	address	address	VERB
cana-660	118	28	risk	risk	NOUN
cana-660	118	29	sensitivity	sensitivity	NOUN
cana-660	118	30	web10k	web10k	NOUN
cana-660	118	31	,	,	PUNCT
cana-660	118	32	web30k	web30k	X
cana-660	118	33	,	,	PUNCT
cana-660	118	34	yahoo	yahoo	PROPN
cana-660	118	35	!	!	PUNCT
cana-660	118	36	multiple	multiple	ADJ
cana-660	118	37	objective	objective	ADJ
cana-660	118	38	methods	method	NOUN
cana-660	118	39	useful	useful	ADJ
cana-660	118	40	in	in	ADP
cana-660	118	41	many	many	ADJ
cana-660	118	42	domains	domain	NOUN
cana-660	118	43	6	6	NUM
cana-660	118	44	[	[	SYM
cana-660	118	45	25	25	NUM
cana-660	118	46	]	]	PUNCT
cana-660	118	47	listwise	listwise	ADJ
cana-660	118	48	overview	overview	NOUN
cana-660	118	49	of	of	ADP
cana-660	118	50	all	all	DET
cana-660	118	51	feature	feature	NOUN
cana-660	118	52	selection	selection	NOUN
cana-660	118	53	methods	method	NOUN
cana-660	118	54	,	,	PUNCT
cana-660	118	55	exploration	exploration	NOUN
cana-660	118	56	of	of	ADP
cana-660	118	57	filter	filter	NOUN
cana-660	118	58	,	,	PUNCT
cana-660	118	59	wrapper	wrapper	NOUN
cana-660	118	60	,	,	PUNCT
cana-660	118	61	and	and	CCONJ
cana-660	118	62	embedded	embed	VERB
cana-660	118	63	techniques	technique	NOUN
cana-660	118	64	ohsumed	ohsume	VERB
cana-660	118	65	,	,	PUNCT
cana-660	118	66	td2003	td2003	PROPN
cana-660	118	67	,	,	PUNCT
cana-660	118	68	td2004	td2004	NOUN
cana-660	118	69	,	,	PUNCT
cana-660	118	70	hp2003	hp2003	PROPN
cana-660	118	71	,	,	PUNCT
cana-660	118	72	hp20044	hp20044	PROPN
cana-660	118	73	,	,	PUNCT
cana-660	118	74	np2003	np2003	PROPN
cana-660	118	75	,	,	PUNCT
cana-660	118	76	np2004	np2004	PROPN
cana-660	118	77	,	,	PUNCT
cana-660	118	78	mq2007	mq2007	PROPN
cana-660	118	79	,	,	PUNCT
cana-660	118	80	mq2008	mq2008	NOUN
cana-660	118	81	,	,	PUNCT
cana-660	118	82	yahoo(set2	yahoo(set2	PROPN
cana-660	118	83	)	)	PUNCT
cana-660	119	1	letor2.0	letor2.0	PROPN
cana-660	119	2	work	work	VERB
cana-660	119	3	on	on	ADP
cana-660	119	4	many	many	ADJ
cana-660	119	5	applications	application	NOUN
cana-660	119	6	7	7	NUM
cana-660	119	7	[	[	SYM
cana-660	119	8	26	26	NUM
cana-660	119	9	]	]	PUNCT
cana-660	119	10	listwise	listwise	ADJ
cana-660	119	11	evolutionary	evolutionary	ADJ
cana-660	119	12	system	system	NOUN
cana-660	119	13	mofsrank	mofsrank	NOUN
cana-660	119	14	based	base	VERB
cana-660	119	15	on	on	ADP
cana-660	119	16	multiobjective	multiobjective	ADJ
cana-660	119	17	function	function	NOUN
cana-660	119	18	np2004,hp2004,td2004,mq2008	np2004,hp2004,td2004,mq2008	PROPN
cana-660	119	19	,	,	PUNCT
cana-660	119	20	ohsumed	ohsume	VERB
cana-660	119	21	focus	focus	NOUN
cana-660	119	22	on	on	ADP
cana-660	119	23	listwise	listwise	ADJ
cana-660	119	24	approaches	approach	NOUN
cana-660	119	25	with	with	ADP
cana-660	119	26	more	more	ADJ
cana-660	119	27	evolutionary	evolutionary	ADJ
cana-660	119	28	methods	method	NOUN
cana-660	119	29	with	with	ADP
cana-660	119	30	different	different	ADJ
cana-660	119	31	datasets	dataset	NOUN
cana-660	119	32	8	8	NUM
cana-660	119	33	[	[	X
cana-660	119	34	28	28	NUM
cana-660	119	35	]	]	X
cana-660	119	36	listwise	listwise	ADJ
cana-660	119	37	analogy	analogy	NOUN
cana-660	119	38	-	-	PUNCT
cana-660	119	39	based	base	VERB
cana-660	119	40	ltr	ltr	NOUN
cana-660	119	41	for	for	ADP
cana-660	119	42	feature	feature	NOUN
cana-660	119	43	selection	selection	NOUN
cana-660	119	44	,	,	PUNCT
cana-660	119	45	evaluation	evaluation	NOUN
cana-660	119	46	using	use	VERB
cana-660	119	47	correlation	correlation	NOUN
cana-660	119	48	and	and	CCONJ
cana-660	119	49	relief	relief	NOUN
cana-660	119	50	-	-	PUNCT
cana-660	119	51	based	base	VERB
cana-660	119	52	techniques	technique	NOUN
cana-660	119	53	decathlon	decathlon	NOUN
cana-660	119	54	,	,	PUNCT
cana-660	119	55	bundesliga	bundesliga	PROPN
cana-660	119	56	,	,	PUNCT
cana-660	119	57	fifa	fifa	PROPN
cana-660	119	58	,	,	PUNCT
cana-660	119	59	hotels	hotel	NOUN
cana-660	119	60	,	,	PUNCT
cana-660	119	61	uni	uni	PROPN
cana-660	119	62	.	.	PROPN
cana-660	119	63	rankings	rankings	PROPN
cana-660	119	64	,	,	PUNCT
cana-660	119	65	volleyball	volleyball	NOUN
cana-660	119	66	wl	wl	PROPN
cana-660	119	67	,	,	PUNCT
cana-660	119	68	netflix	netflix	PROPN
cana-660	119	69	use	use	VERB
cana-660	119	70	weighted	weight	VERB
cana-660	119	71	matrix	matrix	NOUN
cana-660	119	72	and	and	CCONJ
cana-660	119	73	co	co	VERB
cana-660	119	74	-	-	VERB
cana-660	119	75	embedding	embed	VERB
cana-660	119	76	as	as	ADP
cana-660	119	77	future	future	ADJ
cana-660	119	78	functions	function	NOUN
cana-660	119	79	for	for	ADP
cana-660	119	80	categorical	categorical	ADJ
cana-660	119	81	data	datum	NOUN
cana-660	119	82	9	9	NUM
cana-660	119	83	[	[	SYM
cana-660	119	84	1	1	NUM
cana-660	119	85	]	]	PUNCT
cana-660	119	86	listwise	listwise	ADJ
cana-660	119	87	deep	deep	ADJ
cana-660	119	88	learning	learning	NOUN
cana-660	119	89	model	model	NOUN
cana-660	119	90	for	for	ADP
cana-660	119	91	l1	l1	PROPN
cana-660	119	92	and	and	CCONJ
cana-660	119	93	l2	l2	NOUN
cana-660	119	94	regularizationbased	regularizationbase	VERB
cana-660	119	95	feature	feature	NOUN
cana-660	119	96	selection	selection	NOUN
cana-660	119	97	td2003	td2003	PROPN
cana-660	119	98	,	,	PUNCT
cana-660	119	99	td2004	td2004	NOUN
cana-660	119	100	,	,	PUNCT
cana-660	119	101	td2003	td2003	PROPN
cana-660	119	102	,	,	PUNCT
cana-660	119	103	td2004	td2004	NOUN
cana-660	119	104	,	,	PUNCT
cana-660	119	105	np2003	np2003	PROPN
cana-660	119	106	,	,	PUNCT
cana-660	119	107	np2004	np2004	PROPN
cana-660	119	108	,	,	PUNCT
cana-660	119	109	hp2003	hp2003	PROPN
cana-660	119	110	,	,	PUNCT
cana-660	119	111	hp2004	hp2004	PROPN
cana-660	119	112	,	,	PUNCT
cana-660	119	113	mq2007	mq2007	ADJ
cana-660	119	114	,	,	PUNCT
cana-660	119	115	mq2008	mq2008	NOUN
cana-660	119	116	,	,	PUNCT
cana-660	119	117	mslr	mslr	NOUN
cana-660	119	118	-	-	PUNCT
cana-660	119	119	web30k	web30k	ADJ
cana-660	119	120	,	,	PUNCT
cana-660	119	121	mslr	mslr	ADJ
cana-660	119	122	-	-	NOUN
cana-660	119	123	web10k	web10k	NOUN
cana-660	119	124	apply	apply	VERB
cana-660	119	125	to	to	ADP
cana-660	119	126	other	other	ADJ
cana-660	119	127	datasets	dataset	NOUN
cana-660	119	128	10	10	NUM
cana-660	119	129	[	[	SYM
cana-660	119	130	27	27	NUM
cana-660	119	131	]	]	X
cana-660	119	132	listwise	listwise	ADJ
cana-660	119	133	neural	neural	ADJ
cana-660	119	134	reranker	reranker	NOUN
cana-660	119	135	for	for	ADP
cana-660	119	136	largescale	largescale	NOUN
cana-660	119	137	search	search	NOUN
cana-660	119	138	models	model	NOUN
cana-660	119	139	mslr	mslr	NOUN
cana-660	119	140	-	-	PUNCT
cana-660	119	141	web30k	web30k	X
cana-660	119	142	,	,	PUNCT
cana-660	119	143	ohsumed	ohsume	VERB
cana-660	119	144	use	use	NOUN
cana-660	119	145	for	for	ADP
cana-660	119	146	other	other	ADJ
cana-660	119	147	datasets	dataset	NOUN
cana-660	119	148	table1	table1	NOUN
cana-660	119	149	:	:	PUNCT
cana-660	119	150	brief	brief	ADJ
cana-660	119	151	summary	summary	NOUN
cana-660	119	152	of	of	ADP
cana-660	119	153	feature	feature	NOUN
cana-660	119	154	selection	selection	NOUN
cana-660	119	155	algorithms	algorithm	VERB
cana-660	119	156	3.feature	3.feature	NUM
cana-660	119	157	selection	selection	NOUN
cana-660	119	158	of	of	ADP
cana-660	119	159	baseline	baseline	ADJ
cana-660	119	160	algorithms	algorithm	NOUN
cana-660	119	161	:	:	PUNCT
cana-660	119	162	the	the	DET
cana-660	119	163	general	general	ADJ
cana-660	119	164	framework	framework	NOUN
cana-660	119	165	for	for	ADP
cana-660	119	166	the	the	DET
cana-660	119	167	ranking	rank	VERB
cana-660	119	168	framework	framework	NOUN
cana-660	119	169	is	be	AUX
cana-660	119	170	as	as	SCONJ
cana-660	119	171	follows	follow	VERB
cana-660	119	172	:	:	PUNCT
cana-660	119	173	fig	fig	NOUN
cana-660	119	174	.	.	PUNCT
cana-660	120	1	1	1	NUM
cana-660	120	2	.	.	X
cana-660	120	3	basic	basic	ADJ
cana-660	120	4	ranking	ranking	NOUN
cana-660	120	5	model	model	NOUN
cana-660	120	6	as	as	SCONJ
cana-660	120	7	depicted	depict	VERB
cana-660	120	8	in	in	ADP
cana-660	120	9	the	the	DET
cana-660	120	10	above	above	ADJ
cana-660	120	11	model	model	NOUN
cana-660	120	12	diagram	diagram	PROPN
cana-660	120	13	,	,	PUNCT
cana-660	120	14	we	we	PRON
cana-660	120	15	have	have	VERB
cana-660	120	16	a	a	DET
cana-660	120	17	learning	learning	NOUN
cana-660	120	18	system	system	NOUN
cana-660	120	19	that	that	PRON
cana-660	120	20	provides	provide	VERB
cana-660	120	21	the	the	DET
cana-660	120	22	score	score	NOUN
cana-660	120	23	for	for	ADP
cana-660	120	24	the	the	DET
cana-660	120	25	f	f	PROPN
cana-660	120	26	(	(	PUNCT
cana-660	120	27	q	q	PROPN
cana-660	120	28	,	,	PUNCT
cana-660	120	29	d	d	NOUN
cana-660	120	30	)	)	PUNCT
cana-660	120	31	pair	pair	NOUN
cana-660	120	32	.	.	PUNCT
cana-660	121	1	after	after	ADP
cana-660	121	2	receiving	receive	VERB
cana-660	121	3	the	the	DET
cana-660	121	4	score	score	NOUN
cana-660	121	5	,	,	PUNCT
cana-660	121	6	sorting	sorting	NOUN
cana-660	121	7	was	be	AUX
cana-660	121	8	applied	apply	VERB
cana-660	121	9	,	,	PUNCT
cana-660	121	10	and	and	CCONJ
cana-660	121	11	then	then	ADV
cana-660	121	12	testing	testing	NOUN
cana-660	121	13	was	be	AUX
cana-660	121	14	performed	perform	VERB
cana-660	121	15	.	.	PUNCT
cana-660	122	1	(	(	PUNCT
cana-660	122	2	q	q	X
cana-660	122	3	,	,	PUNCT
cana-660	122	4	d	d	NOUN
cana-660	122	5	)	)	PUNCT
cana-660	122	6	training	training	NOUN
cana-660	122	7	system	system	NOUN
cana-660	122	8	learning	learn	VERB
cana-660	122	9	systems	system	NOUN
cana-660	122	10	ranking	ranking	NOUN
cana-660	122	11	model	model	NOUN
cana-660	122	12	(	(	PUNCT
cana-660	122	13	q	q	NOUN
cana-660	122	14	,	,	PUNCT
cana-660	122	15	d	d	NOUN
cana-660	122	16	)	)	PUNCT
cana-660	122	17	testing	testing	NOUN
cana-660	122	18	system	system	NOUN
cana-660	122	19	ranking	rank	VERB
cana-660	122	20	systems	system	NOUN
cana-660	122	21	ranking	ranking	NOUN
cana-660	122	22	results	result	NOUN
cana-660	122	23	communications	communication	NOUN
cana-660	122	24	on	on	ADP
cana-660	122	25	applied	apply	VERB
cana-660	122	26	nonlinear	nonlinear	ADJ
cana-660	122	27	analysis	analysis	NOUN
cana-660	122	28	issn	issn	NOUN
cana-660	122	29	:	:	PUNCT
cana-660	122	30	1074	1074	NUM
cana-660	122	31	-	-	PUNCT
cana-660	122	32	133x	133x	NUM
cana-660	122	33	vol	vol	NOUN
cana-660	122	34	31	31	NUM
cana-660	122	35	no	no	NOUN
cana-660	122	36	.	.	PUNCT
cana-660	123	1	2s	2s	NUM
cana-660	123	2	(	(	PUNCT
cana-660	123	3	2024	2024	NUM
cana-660	123	4	)	)	PUNCT
cana-660	123	5	459	459	NUM
cana-660	123	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	123	7	as	as	SCONJ
cana-660	123	8	mentioned	mention	VERB
cana-660	123	9	in	in	ADP
cana-660	123	10	the	the	DET
cana-660	123	11	above	above	PROPN
cana-660	123	12	literature	literature	NOUN
cana-660	123	13	survey	survey	NOUN
cana-660	123	14	,	,	PUNCT
cana-660	123	15	we	we	PRON
cana-660	123	16	used	use	VERB
cana-660	123	17	standard	standard	ADJ
cana-660	123	18	datasets	dataset	NOUN
cana-660	123	19	for	for	ADP
cana-660	123	20	learning	learning	NOUN
cana-660	123	21	-	-	PUNCT
cana-660	123	22	to	to	ADP
cana-660	123	23	-	-	PUNCT
cana-660	123	24	rank	rank	NOUN
cana-660	123	25	.	.	PUNCT
cana-660	124	1	to	to	PART
cana-660	124	2	determine	determine	VERB
cana-660	124	3	the	the	DET
cana-660	124	4	importance	importance	NOUN
cana-660	124	5	of	of	ADP
cana-660	124	6	the	the	DET
cana-660	124	7	fss	fss	NOUN
cana-660	124	8	,	,	PUNCT
cana-660	124	9	we	we	PRON
cana-660	124	10	used	use	VERB
cana-660	124	11	the	the	DET
cana-660	124	12	mslr	mslr	NOUN
cana-660	124	13	-	-	NOUN
cana-660	124	14	web10k	web10k	NOUN
cana-660	124	15	microsoft	microsoft	PROPN
cana-660	124	16	supervised	supervise	VERB
cana-660	124	17	database	database	NOUN
cana-660	124	18	of	of	ADP
cana-660	124	19	136	136	NUM
cana-660	124	20	features	feature	NOUN
cana-660	124	21	with	with	ADP
cana-660	124	22	10,000	10,000	NUM
cana-660	124	23	queries	query	NOUN
cana-660	124	24	and	and	CCONJ
cana-660	124	25	the	the	DET
cana-660	124	26	q	q	NOUN
cana-660	124	27	,	,	PUNCT
cana-660	124	28	d	d	PRON
cana-660	124	29	pair	pair	NOUN
cana-660	124	30	1200192	1200192	NUM
cana-660	124	31	with	with	ADP
cana-660	124	32	five	five	NUM
cana-660	124	33	relevance	relevance	NOUN
cana-660	124	34	labels	label	NOUN
cana-660	124	35	.	.	PUNCT
cana-660	125	1	it	it	PRON
cana-660	125	2	is	be	AUX
cana-660	125	3	an	an	DET
cana-660	125	4	open	open	ADJ
cana-660	125	5	source	source	NOUN
cana-660	125	6	dataset	dataset	NOUN
cana-660	125	7	that	that	PRON
cana-660	125	8	provides	provide	VERB
cana-660	125	9	five	five	NUM
cana-660	125	10	fold	fold	ADJ
cana-660	125	11	data	datum	NOUN
cana-660	125	12	.	.	PUNCT
cana-660	126	1	to	to	PART
cana-660	126	2	identify	identify	VERB
cana-660	126	3	the	the	DET
cana-660	126	4	best	good	ADJ
cana-660	126	5	performing	perform	VERB
cana-660	126	6	algorithm	algorithm	NOUN
cana-660	126	7	with	with	ADP
cana-660	126	8	minimum	minimum	ADJ
cana-660	126	9	features	feature	NOUN
cana-660	126	10	,	,	PUNCT
cana-660	126	11	we	we	PRON
cana-660	126	12	applied	apply	VERB
cana-660	126	13	the	the	DET
cana-660	126	14	learning	learning	NOUN
cana-660	126	15	-	-	PUNCT
cana-660	126	16	torank	torank	NOUN
cana-660	126	17	algorithm	algorithm	NOUN
cana-660	126	18	to	to	ADP
cana-660	126	19	the	the	DET
cana-660	126	20	above	above	ADJ
cana-660	126	21	dataset	dataset	NOUN
cana-660	126	22	on	on	ADP
cana-660	126	23	several	several	ADJ
cana-660	126	24	algorithms	algorithm	NOUN
cana-660	126	25	,	,	PUNCT
cana-660	126	26	such	such	ADJ
cana-660	126	27	as	as	ADP
cana-660	126	28	directranker	directranker	PROPN
cana-660	126	29	,	,	PUNCT
cana-660	126	30	ranknet	ranknet	NOUN
cana-660	126	31	,	,	PUNCT
cana-660	126	32	lamdamart	lamdamart	NOUN
cana-660	126	33	and	and	CCONJ
cana-660	126	34	lamdarank	lamdarank	PROPN
cana-660	126	35	.	.	PUNCT
cana-660	127	1	we	we	PRON
cana-660	127	2	first	first	ADV
cana-660	127	3	apply	apply	VERB
cana-660	127	4	the	the	DET
cana-660	127	5	range	range	NOUN
cana-660	127	6	for	for	ADP
cana-660	127	7	the	the	DET
cana-660	127	8	best	good	ADJ
cana-660	127	9	8	8	NUM
cana-660	127	10	features	feature	NOUN
cana-660	127	11	,	,	PUNCT
cana-660	127	12	16	16	NUM
cana-660	127	13	features	feature	NOUN
cana-660	127	14	and	and	CCONJ
cana-660	127	15	so	so	ADV
cana-660	127	16	on	on	ADV
cana-660	127	17	,	,	PUNCT
cana-660	127	18	and	and	CCONJ
cana-660	127	19	find	find	VERB
cana-660	127	20	the	the	DET
cana-660	127	21	minimum	minimum	NOUN
cana-660	127	22	subset	subset	NOUN
cana-660	127	23	requirement.the	requirement.the	DET
cana-660	127	24	experimental	experimental	ADJ
cana-660	127	25	results	result	NOUN
cana-660	127	26	of	of	ADP
cana-660	127	27	ndcg@10	ndcg@10	NOUN
cana-660	127	28	with	with	ADP
cana-660	127	29	respect	respect	NOUN
cana-660	127	30	to	to	ADP
cana-660	127	31	the	the	DET
cana-660	127	32	run	run	NOUN
cana-660	127	33	-	-	PUNCT
cana-660	127	34	time	time	NOUN
cana-660	127	35	(	(	PUNCT
cana-660	127	36	in	in	ADP
cana-660	127	37	(	(	PUNCT
cana-660	127	38	ms	ms	NOUN
cana-660	127	39	)	)	PUNCT
cana-660	127	40	for	for	ADP
cana-660	127	41	the	the	DET
cana-660	127	42	abovementioned	abovementione	VERB
cana-660	127	43	algorithms	algorithm	NOUN
cana-660	127	44	are	be	AUX
cana-660	127	45	shown	show	VERB
cana-660	127	46	below	below	ADP
cana-660	127	47	,	,	PUNCT
cana-660	127	48	where	where	SCONJ
cana-660	127	49	each	each	DET
cana-660	127	50	time	time	NOUN
cana-660	127	51	we	we	PRON
cana-660	127	52	increase	increase	VERB
cana-660	127	53	the	the	DET
cana-660	127	54	feature	feature	NOUN
cana-660	127	55	values	value	NOUN
cana-660	127	56	.	.	PUNCT
cana-660	128	1	3.1	3.1	NUM
cana-660	128	2	directranker	directranker	NOUN
cana-660	128	3	algorithm	algorithm	NOUN
cana-660	128	4	:	:	PUNCT
cana-660	128	5	table	table	NOUN
cana-660	128	6	2	2	NUM
cana-660	128	7	:	:	PUNCT
cana-660	128	8	ndcg@10	ndcg@10	VERB
cana-660	128	9	scores	score	NOUN
cana-660	128	10	with	with	ADP
cana-660	128	11	different	different	ADJ
cana-660	128	12	feature	feature	NOUN
cana-660	128	13	on	on	ADP
cana-660	128	14	directranker	directranker	PROPN
cana-660	128	15	sr	sr	PROPN
cana-660	128	16	no	no	INTJ
cana-660	128	17	.	.	PUNCT
cana-660	129	1	features	feature	NOUN
cana-660	129	2	value	value	NOUN
cana-660	129	3	ndcg@10	ndcg@10	PROPN
cana-660	129	4	average	average	ADJ
cana-660	129	5	runtime	runtime	NOUN
cana-660	129	6	1	1	NUM
cana-660	129	7	.	.	PROPN
cana-660	129	8	17	17	NUM
cana-660	129	9	0.4378±0.2451	0.4378±0.2451	NOUN
cana-660	129	10	39.6070±0.3022	39.6070±0.3022	NOUN
cana-660	129	11	2	2	NUM
cana-660	129	12	.	.	X
cana-660	129	13	34	34	NUM
cana-660	129	14	0.4298±0.2459	0.4298±0.2459	NOUN
cana-660	129	15	40.4866±0.2508	40.4866±0.2508	NUM
cana-660	129	16	3	3	NUM
cana-660	129	17	.	.	X
cana-660	129	18	51	51	NUM
cana-660	129	19	0.4286±0.2448	0.4286±0.2448	NOUN
cana-660	130	1	41.4559±0.2215	41.4559±0.2215	NUM
cana-660	130	2	4	4	NUM
cana-660	130	3	.	.	PUNCT
cana-660	130	4	68	68	NUM
cana-660	130	5	0.4272±0.2420	0.4272±0.2420	NOUN
cana-660	131	1	43.7252±0.2889	43.7252±0.2889	NOUN
cana-660	131	2	5	5	NUM
cana-660	131	3	.	.	NOUN
cana-660	131	4	102	102	NUM
cana-660	131	5	0.4269±0.2419	0.4269±0.2419	NOUN
cana-660	131	6	44.7012±0.2628	44.7012±0.2628	NUM
cana-660	132	1	the	the	DET
cana-660	132	2	experimental	experimental	ADJ
cana-660	132	3	results	result	NOUN
cana-660	132	4	by	by	ADP
cana-660	132	5	using	use	VERB
cana-660	132	6	standard	standard	ADJ
cana-660	132	7	procedure	procedure	NOUN
cana-660	132	8	with	with	ADP
cana-660	132	9	leaning	lean	VERB
cana-660	132	10	to	to	PART
cana-660	132	11	rank	rank	VERB
cana-660	132	12	with	with	ADP
cana-660	132	13	different	different	ADJ
cana-660	132	14	number	number	NOUN
cana-660	132	15	of	of	ADP
cana-660	132	16	feature	feature	NOUN
cana-660	132	17	is	be	AUX
cana-660	132	18	shown	show	VERB
cana-660	132	19	in	in	ADP
cana-660	132	20	the	the	DET
cana-660	132	21	table2	table2	NOUN
cana-660	132	22	represent	represent	VERB
cana-660	132	23	the	the	DET
cana-660	132	24	ndcg@10	ndcg@10	PROPN
cana-660	132	25	for	for	ADP
cana-660	132	26	directranker	directranker	NOUN
cana-660	132	27	algorithm.the	algorithm.the	DET
cana-660	132	28	experiment	experiment	NOUN
cana-660	132	29	is	be	AUX
cana-660	132	30	executed	execute	VERB
cana-660	132	31	across	across	ADP
cana-660	132	32	fold	fold	NOUN
cana-660	132	33	1	1	NUM
cana-660	132	34	of	of	ADP
cana-660	132	35	the	the	DET
cana-660	132	36	mslr	mslr	ADJ
cana-660	132	37	-	-	NOUN
cana-660	132	38	web10k	web10k	NOUN
cana-660	132	39	dataset	dataset	NOUN
cana-660	132	40	.	.	PUNCT
cana-660	133	1	3.2ranknet	3.2ranknet	NUM
cana-660	133	2	algorithm	algorithm	NOUN
cana-660	133	3	:	:	PUNCT
cana-660	133	4	table	table	NOUN
cana-660	133	5	3	3	NUM
cana-660	133	6	ndcg@10	ndcg@10	NOUN
cana-660	133	7	scores	score	NOUN
cana-660	133	8	with	with	ADP
cana-660	133	9	different	different	ADJ
cana-660	133	10	feature	feature	NOUN
cana-660	133	11	on	on	ADP
cana-660	133	12	ranknet	ranknet	PROPN
cana-660	133	13	sr	sr	PROPN
cana-660	134	1	no	no	INTJ
cana-660	134	2	.	.	PUNCT
cana-660	135	1	features	feature	NOUN
cana-660	135	2	value	value	NOUN
cana-660	135	3	ndcg@10	ndcg@10	PROPN
cana-660	135	4	average	average	ADJ
cana-660	135	5	runtime	runtime	NOUN
cana-660	135	6	1	1	NUM
cana-660	135	7	.	.	NUM
cana-660	135	8	17	17	NUM
cana-660	135	9	0.3074±0.244	0.3074±0.244	NUM
cana-660	136	1	39.1682±0.3236	39.1682±0.3236	NUM
cana-660	136	2	2	2	NUM
cana-660	136	3	.	.	X
cana-660	136	4	34	34	NUM
cana-660	136	5	0.266±0.2110	0.266±0.2110	NOUN
cana-660	136	6	40.2048±0.2896	40.2048±0.2896	NOUN
cana-660	136	7	3	3	NUM
cana-660	136	8	.	.	X
cana-660	136	9	51	51	NUM
cana-660	136	10	0.2573±0.2123	0.2573±0.2123	NOUN
cana-660	136	11	40.9475±0.2972	40.9475±0.2972	NUM
cana-660	136	12	4	4	NUM
cana-660	136	13	.	.	X
cana-660	136	14	68	68	NUM
cana-660	136	15	0.4272±0.2420	0.4272±0.2420	NOUN
cana-660	136	16	43.7252±0.2889	43.7252±0.2889	NOUN
cana-660	136	17	5	5	NUM
cana-660	136	18	.	.	NOUN
cana-660	136	19	102	102	NUM
cana-660	136	20	0.4269±0.2419	0.4269±0.2419	NOUN
cana-660	136	21	44.7012±0.2628	44.7012±0.2628	NUM
cana-660	136	22	the	the	DET
cana-660	136	23	experimental	experimental	ADJ
cana-660	136	24	results	result	NOUN
cana-660	136	25	by	by	ADP
cana-660	136	26	using	use	VERB
cana-660	136	27	standard	standard	ADJ
cana-660	136	28	procedure	procedure	NOUN
cana-660	136	29	with	with	ADP
cana-660	136	30	leaning	lean	VERB
cana-660	136	31	to	to	PART
cana-660	136	32	rank	rank	VERB
cana-660	136	33	different	different	ADJ
cana-660	136	34	number	number	NOUN
cana-660	136	35	of	of	ADP
cana-660	136	36	features	feature	NOUN
cana-660	136	37	are	be	AUX
cana-660	136	38	shown	show	VERB
cana-660	136	39	in	in	ADP
cana-660	136	40	the	the	DET
cana-660	136	41	table3	table3	PROPN
cana-660	136	42	represent	represent	VERB
cana-660	136	43	the	the	DET
cana-660	136	44	ndcg@10	ndcg@10	PROPN
cana-660	136	45	for	for	ADP
cana-660	136	46	ranknet	ranknet	NOUN
cana-660	136	47	algorithm	algorithm	NOUN
cana-660	136	48	.	.	PUNCT
cana-660	137	1	the	the	DET
cana-660	137	2	experiment	experiment	NOUN
cana-660	137	3	is	be	AUX
cana-660	137	4	executed	execute	VERB
cana-660	137	5	across	across	ADP
cana-660	137	6	fold	fold	NOUN
cana-660	137	7	1	1	NUM
cana-660	137	8	of	of	ADP
cana-660	137	9	the	the	DET
cana-660	137	10	mslr	mslr	ADJ
cana-660	137	11	-	-	ADJ
cana-660	137	12	web10k	web10k	NOUN
cana-660	137	13	dataset	dataset	NOUN
cana-660	137	14	.	.	PUNCT
cana-660	138	1	communications	communication	NOUN
cana-660	138	2	on	on	ADP
cana-660	138	3	applied	apply	VERB
cana-660	138	4	nonlinear	nonlinear	ADJ
cana-660	138	5	analysis	analysis	NOUN
cana-660	138	6	issn	issn	NOUN
cana-660	138	7	:	:	PUNCT
cana-660	138	8	1074	1074	NUM
cana-660	138	9	-	-	PUNCT
cana-660	138	10	133x	133x	NUM
cana-660	138	11	vol	vol	NOUN
cana-660	138	12	31	31	NUM
cana-660	138	13	no	no	NOUN
cana-660	138	14	.	.	PUNCT
cana-660	139	1	2s	2s	NUM
cana-660	139	2	(	(	PUNCT
cana-660	139	3	2024	2024	NUM
cana-660	139	4	)	)	PUNCT
cana-660	139	5	460	460	NUM
cana-660	139	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	139	7	fig2(a	fig2(a	NOUN
cana-660	139	8	):	):	PUNCT
cana-660	139	9	pictorial	pictorial	ADJ
cana-660	139	10	representation	representation	NOUN
cana-660	139	11	of	of	ADP
cana-660	139	12	ndcg@10	ndcg@10	PROPN
cana-660	139	13	ranker	ranker	PROPN
cana-660	139	14	&	&	CCONJ
cana-660	139	15	ranknet	ranknet	PROPN
cana-660	139	16	fig2(b	fig2(b	NUM
cana-660	139	17	):	):	PUNCT
cana-660	139	18	pictorial	pictorial	ADJ
cana-660	139	19	representation	representation	NOUN
cana-660	139	20	of	of	ADP
cana-660	139	21	average	average	ADJ
cana-660	139	22	runtime	runtime	NOUN
cana-660	139	23	ranker	ranker	PROPN
cana-660	139	24	&	&	CCONJ
cana-660	139	25	ranknet	ranknet	VERB
cana-660	139	26	the	the	DET
cana-660	139	27	above	above	ADJ
cana-660	139	28	experimental	experimental	ADJ
cana-660	139	29	fig	fig	NOUN
cana-660	139	30	.	.	PUNCT
cana-660	140	1	2(a	2(a	NUM
cana-660	140	2	)	)	PUNCT
cana-660	140	3	shows	show	VERB
cana-660	140	4	the	the	DET
cana-660	140	5	ndcg@10	ndcg@10	PROPN
cana-660	140	6	results	result	NOUN
cana-660	140	7	of	of	ADP
cana-660	140	8	directranker	directranker	NOUN
cana-660	140	9	and	and	CCONJ
cana-660	140	10	ranknet	ranknet	NOUN
cana-660	140	11	algorithms	algorithm	NOUN
cana-660	140	12	.	.	PUNCT
cana-660	141	1	fig	fig	NOUN
cana-660	141	2	.	.	PUNCT
cana-660	142	1	2(b	2(b	NUM
cana-660	142	2	)	)	PUNCT
cana-660	142	3	shows	show	VERB
cana-660	142	4	the	the	DET
cana-660	142	5	change	change	NOUN
cana-660	142	6	in	in	ADP
cana-660	142	7	the	the	DET
cana-660	142	8	average	average	ADJ
cana-660	142	9	runtime	runtime	NOUN
cana-660	142	10	of	of	ADP
cana-660	142	11	each	each	DET
cana-660	142	12	execution	execution	NOUN
cana-660	142	13	.	.	PUNCT
cana-660	143	1	it	it	PRON
cana-660	143	2	is	be	AUX
cana-660	143	3	easily	easily	ADV
cana-660	143	4	concluded	conclude	VERB
cana-660	143	5	that	that	SCONJ
cana-660	143	6	the	the	DET
cana-660	143	7	direct	direct	ADJ
cana-660	143	8	ranker	ranker	NOUN
cana-660	143	9	algorithm	algorithm	NOUN
cana-660	143	10	performed	perform	VERB
cana-660	143	11	well	well	ADV
cana-660	143	12	compared	compare	VERB
cana-660	143	13	to	to	ADP
cana-660	143	14	the	the	DET
cana-660	143	15	rank	rank	NOUN
cana-660	143	16	net	net	ADJ
cana-660	143	17	algorithm	algorithm	NOUN
cana-660	143	18	with	with	ADP
cana-660	143	19	the	the	DET
cana-660	143	20	mslr	mslr	ADJ
cana-660	143	21	-	-	PUNCT
cana-660	143	22	web10k	web10k	NOUN
cana-660	143	23	data	datum	NOUN
cana-660	143	24	.	.	PUNCT
cana-660	144	1	3.3lambdamart	3.3lambdamart	NUM
cana-660	144	2	algorithm	algorithm	NOUN
cana-660	144	3	:	:	PUNCT
cana-660	144	4	table	table	NOUN
cana-660	144	5	4	4	NUM
cana-660	144	6	ndcg@10	ndcg@10	NOUN
cana-660	144	7	scores	score	NOUN
cana-660	144	8	with	with	ADP
cana-660	144	9	different	different	ADJ
cana-660	144	10	feature	feature	NOUN
cana-660	144	11	on	on	ADP
cana-660	144	12	lambdamart	lambdamart	PROPN
cana-660	144	13	sr	sr	PROPN
cana-660	145	1	no	no	INTJ
cana-660	145	2	.	.	PUNCT
cana-660	146	1	features	feature	NOUN
cana-660	146	2	value	value	NOUN
cana-660	146	3	ndcg@10	ndcg@10	PROPN
cana-660	146	4	average	average	ADJ
cana-660	146	5	runtime	runtime	NOUN
cana-660	146	6	1	1	NUM
cana-660	146	7	.	.	NOUN
cana-660	146	8	8	8	NUM
cana-660	146	9	0.6240±0.2729	0.6240±0.2729	NOUN
cana-660	146	10	22.6980±0.1765	22.6980±0.1765	PROPN
cana-660	146	11	2	2	NUM
cana-660	146	12	.	.	NUM
cana-660	147	1	16	16	NUM
cana-660	147	2	0.6214±0.0974	0.6214±0.0974	NUM
cana-660	148	1	24.0207±0.1923	24.0207±0.1923	NUM
cana-660	148	2	3	3	NUM
cana-660	148	3	.	.	NOUN
cana-660	148	4	24	24	NUM
cana-660	148	5	0.6176±0.2665	0.6176±0.2665	NOUN
cana-660	148	6	26.2134±0.1308	26.2134±0.1308	NUM
cana-660	148	7	4	4	NUM
cana-660	148	8	.	.	X
cana-660	148	9	32	32	NUM
cana-660	148	10	0.6152±0.2632	0.6152±0.2632	NUM
cana-660	149	1	26.7485±0.1930	26.7485±0.1930	NUM
cana-660	149	2	5	5	NUM
cana-660	149	3	.	.	X
cana-660	149	4	40	40	NUM
cana-660	149	5	0.6143±0.27940	0.6143±0.27940	NOUN
cana-660	149	6	28.1716±0.0872	28.1716±0.0872	NUM
cana-660	149	7	6	6	NUM
cana-660	149	8	.	.	NOUN
cana-660	149	9	46	46	NUM
cana-660	149	10	0.6050±0.2603	0.6050±0.2603	NOUN
cana-660	149	11	29.1436±0.1652	29.1436±0.1652	NUM
cana-660	149	12	the	the	DET
cana-660	149	13	experimental	experimental	ADJ
cana-660	149	14	results	result	NOUN
cana-660	149	15	by	by	ADP
cana-660	149	16	using	use	VERB
cana-660	149	17	standard	standard	ADJ
cana-660	149	18	procedure	procedure	NOUN
cana-660	149	19	with	with	ADP
cana-660	149	20	leaning	lean	VERB
cana-660	149	21	to	to	PART
cana-660	149	22	rank	rank	VERB
cana-660	149	23	different	different	ADJ
cana-660	149	24	number	number	NOUN
cana-660	149	25	of	of	ADP
cana-660	149	26	features	feature	NOUN
cana-660	149	27	is	be	AUX
cana-660	149	28	shown	show	VERB
cana-660	149	29	in	in	ADP
cana-660	149	30	the	the	DET
cana-660	149	31	table4	table4	NOUN
cana-660	149	32	represent	represent	VERB
cana-660	149	33	the	the	DET
cana-660	149	34	ndcg@10	ndcg@10	PROPN
cana-660	149	35	for	for	ADP
cana-660	149	36	ranknet	ranknet	NOUN
cana-660	149	37	algorithm	algorithm	NOUN
cana-660	149	38	.	.	PUNCT
cana-660	150	1	the	the	DET
cana-660	150	2	experiment	experiment	NOUN
cana-660	150	3	is	be	AUX
cana-660	150	4	executed	execute	VERB
cana-660	150	5	across	across	ADP
cana-660	150	6	fold	fold	NOUN
cana-660	150	7	1	1	NUM
cana-660	150	8	of	of	ADP
cana-660	150	9	the	the	DET
cana-660	150	10	mslr	mslr	ADJ
cana-660	150	11	-	-	NOUN
cana-660	150	12	web10k	web10k	NOUN
cana-660	150	13	dataset	dataset	VERB
cana-660	150	14	with	with	ADP
cana-660	150	15	across	across	ADP
cana-660	150	16	sample	sample	NOUN
cana-660	150	17	dataset	dataset	NOUN
cana-660	150	18	of	of	ADP
cana-660	150	19	shape	shape	NOUN
cana-660	150	20	(	(	PUNCT
cana-660	150	21	9630	9630	NUM
cana-660	150	22	,	,	PUNCT
cana-660	150	23	48	48	NUM
cana-660	150	24	)	)	PUNCT
cana-660	150	25	.	.	PUNCT
cana-660	151	1	communications	communication	NOUN
cana-660	151	2	on	on	ADP
cana-660	151	3	applied	apply	VERB
cana-660	151	4	nonlinear	nonlinear	ADJ
cana-660	151	5	analysis	analysis	NOUN
cana-660	151	6	issn	issn	NOUN
cana-660	151	7	:	:	PUNCT
cana-660	151	8	1074	1074	NUM
cana-660	151	9	-	-	PUNCT
cana-660	151	10	133x	133x	NUM
cana-660	151	11	vol	vol	NOUN
cana-660	151	12	31	31	NUM
cana-660	151	13	no	no	NOUN
cana-660	151	14	.	.	PUNCT
cana-660	152	1	2s	2s	NUM
cana-660	152	2	(	(	PUNCT
cana-660	152	3	2024	2024	NUM
cana-660	152	4	)	)	PUNCT
cana-660	152	5	461	461	NUM
cana-660	152	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	152	7	3.4lambdarank	3.4lambdarank	NUM
cana-660	152	8	algorithm	algorithm	NOUN
cana-660	152	9	:	:	PUNCT
cana-660	152	10	table	table	NOUN
cana-660	152	11	5	5	NUM
cana-660	152	12	ndcg@10	ndcg@10	NOUN
cana-660	152	13	scores	score	NOUN
cana-660	152	14	with	with	ADP
cana-660	152	15	different	different	ADJ
cana-660	152	16	feature	feature	NOUN
cana-660	152	17	on	on	ADP
cana-660	152	18	lambdamart	lambdamart	PROPN
cana-660	152	19	sr	sr	PROPN
cana-660	153	1	no	no	INTJ
cana-660	153	2	.	.	PUNCT
cana-660	154	1	features	feature	NOUN
cana-660	154	2	value	value	NOUN
cana-660	154	3	ndcg@10	ndcg@10	PROPN
cana-660	154	4	average	average	ADJ
cana-660	154	5	runtime	runtime	NOUN
cana-660	154	6	1	1	NUM
cana-660	154	7	.	.	NOUN
cana-660	154	8	8	8	NUM
cana-660	154	9	0.7504±0.2160	0.7504±0.2160	NOUN
cana-660	154	10	21.7811±0.0925	21.7811±0.0925	NUM
cana-660	154	11	2	2	NUM
cana-660	154	12	.	.	NUM
cana-660	154	13	16	16	NUM
cana-660	154	14	0.7461±0.2244	0.7461±0.2244	NOUN
cana-660	154	15	21.8933±0.6690	21.8933±0.6690	NUM
cana-660	154	16	3	3	NUM
cana-660	154	17	.	.	SYM
cana-660	154	18	24	24	NUM
cana-660	154	19	0.7434±0.22195	0.7434±0.22195	NOUN
cana-660	154	20	22.0993±0.0969	22.0993±0.0969	NUM
cana-660	154	21	4	4	NUM
cana-660	154	22	.	.	X
cana-660	154	23	32	32	NUM
cana-660	154	24	0.7427±0.2118	0.7427±0.2118	NOUN
cana-660	154	25	22.3138±0.0674	22.3138±0.0674	NUM
cana-660	154	26	5	5	NUM
cana-660	154	27	.	.	PUNCT
cana-660	154	28	40	40	NUM
cana-660	154	29	0.7356±0.2184	0.7356±0.2184	X
cana-660	155	1	22.4164±0.0802	22.4164±0.0802	NUM
cana-660	155	2	6	6	NUM
cana-660	155	3	.	.	PUNCT
cana-660	156	1	46	46	NUM
cana-660	156	2	0.7342±0.2153	0.7342±0.2153	NOUN
cana-660	156	3	22.5089±0.0428	22.5089±0.0428	NUM
cana-660	156	4	the	the	DET
cana-660	156	5	experimental	experimental	ADJ
cana-660	156	6	results	result	NOUN
cana-660	156	7	by	by	ADP
cana-660	156	8	using	use	VERB
cana-660	156	9	standard	standard	ADJ
cana-660	156	10	procedure	procedure	NOUN
cana-660	156	11	with	with	ADP
cana-660	156	12	leaning	lean	VERB
cana-660	156	13	to	to	PART
cana-660	156	14	rank	rank	VERB
cana-660	156	15	different	different	ADJ
cana-660	156	16	number	number	NOUN
cana-660	156	17	of	of	ADP
cana-660	156	18	features	feature	NOUN
cana-660	156	19	are	be	AUX
cana-660	156	20	shown	show	VERB
cana-660	156	21	in	in	ADP
cana-660	156	22	the	the	DET
cana-660	156	23	table4	table4	NOUN
cana-660	156	24	represent	represent	VERB
cana-660	156	25	the	the	DET
cana-660	156	26	ndcg@10	ndcg@10	PROPN
cana-660	156	27	for	for	ADP
cana-660	156	28	ranknet	ranknet	NOUN
cana-660	156	29	algorithm	algorithm	NOUN
cana-660	156	30	.	.	PUNCT
cana-660	157	1	the	the	DET
cana-660	157	2	experiment	experiment	NOUN
cana-660	157	3	is	be	AUX
cana-660	157	4	executed	execute	VERB
cana-660	157	5	across	across	ADP
cana-660	157	6	fold	fold	NOUN
cana-660	157	7	1	1	NUM
cana-660	157	8	of	of	ADP
cana-660	157	9	the	the	DET
cana-660	157	10	mslr	mslr	ADJ
cana-660	157	11	-	-	NOUN
cana-660	157	12	web10k	web10k	NOUN
cana-660	157	13	dataset	dataset	VERB
cana-660	157	14	with	with	ADP
cana-660	157	15	across	across	ADP
cana-660	157	16	sample	sample	NOUN
cana-660	157	17	dataset	dataset	NOUN
cana-660	157	18	of	of	ADP
cana-660	157	19	shape	shape	NOUN
cana-660	157	20	(	(	PUNCT
cana-660	157	21	9630	9630	NUM
cana-660	157	22	,	,	PUNCT
cana-660	157	23	48	48	NUM
cana-660	157	24	)	)	PUNCT
cana-660	157	25	.	.	PUNCT
cana-660	158	1	fig3(a	fig3(a	X
cana-660	158	2	):	):	PUNCT
cana-660	158	3	pictorial	pictorial	ADJ
cana-660	158	4	representation	representation	NOUN
cana-660	158	5	of	of	ADP
cana-660	158	6	ndcg@10	ndcg@10	PROPN
cana-660	158	7	of	of	ADP
cana-660	158	8	lamdamart	lamdamart	PROPN
cana-660	158	9	&	&	CCONJ
cana-660	158	10	lamdarank	lamdarank	PROPN
cana-660	158	11	fig3(b	fig3(b	NUM
cana-660	158	12	):	):	PUNCT
cana-660	158	13	pictorial	pictorial	ADJ
cana-660	158	14	representation	representation	NOUN
cana-660	158	15	of	of	ADP
cana-660	158	16	average	average	ADJ
cana-660	158	17	runtime	runtime	NOUN
cana-660	158	18	of	of	ADP
cana-660	158	19	lamdamart	lamdamart	PROPN
cana-660	158	20	&	&	CCONJ
cana-660	158	21	lamdarank	lamdarank	PROPN
cana-660	158	22	the	the	DET
cana-660	158	23	above	above	ADJ
cana-660	158	24	experiments	experiment	NOUN
cana-660	158	25	clearly	clearly	ADV
cana-660	158	26	reveal	reveal	VERB
cana-660	158	27	that	that	SCONJ
cana-660	158	28	the	the	DET
cana-660	158	29	number	number	NOUN
cana-660	158	30	of	of	ADP
cana-660	158	31	features	feature	NOUN
cana-660	158	32	influences	influence	VERB
cana-660	158	33	the	the	DET
cana-660	158	34	efficiency	efficiency	NOUN
cana-660	158	35	of	of	ADP
cana-660	158	36	the	the	DET
cana-660	158	37	machine	machine	NOUN
cana-660	158	38	learning	learning	NOUN
cana-660	158	39	model	model	NOUN
cana-660	158	40	.	.	PUNCT
cana-660	159	1	based	base	VERB
cana-660	159	2	on	on	ADP
cana-660	159	3	the	the	DET
cana-660	159	4	results	result	NOUN
cana-660	159	5	shown	show	VERB
cana-660	159	6	in	in	ADP
cana-660	159	7	both	both	DET
cana-660	159	8	fig	fig	NOUN
cana-660	159	9	.	.	PUNCT
cana-660	160	1	3(a	3(a	NUM
cana-660	160	2	)	)	PUNCT
cana-660	160	3	and	and	CCONJ
cana-660	160	4	fig	fig	NOUN
cana-660	160	5	.	.	PUNCT
cana-660	161	1	3(b	3(b	NUM
cana-660	161	2	)	)	PUNCT
cana-660	162	1	,	,	PUNCT
cana-660	162	2	both	both	DET
cana-660	162	3	halves	half	NOUN
cana-660	162	4	of	of	ADP
cana-660	162	5	the	the	DET
cana-660	162	6	total	total	ADJ
cana-660	162	7	feature	feature	NOUN
cana-660	162	8	set	set	NOUN
cana-660	162	9	will	will	AUX
cana-660	162	10	yield	yield	VERB
cana-660	162	11	better	well	ADJ
cana-660	162	12	performance	performance	NOUN
cana-660	162	13	in	in	ADP
cana-660	162	14	less	less	ADJ
cana-660	162	15	time	time	NOUN
cana-660	162	16	.	.	PUNCT
cana-660	163	1	this	this	PRON
cana-660	163	2	can	can	AUX
cana-660	163	3	also	also	ADV
cana-660	163	4	be	be	AUX
cana-660	163	5	verified	verify	VERB
cana-660	163	6	on	on	ADP
cana-660	163	7	different	different	ADJ
cana-660	163	8	datasets	dataset	NOUN
cana-660	163	9	.	.	PUNCT
cana-660	164	1	communications	communication	NOUN
cana-660	164	2	on	on	ADP
cana-660	164	3	applied	apply	VERB
cana-660	164	4	nonlinear	nonlinear	ADJ
cana-660	164	5	analysis	analysis	NOUN
cana-660	164	6	issn	issn	NOUN
cana-660	164	7	:	:	PUNCT
cana-660	164	8	1074	1074	NUM
cana-660	164	9	-	-	PUNCT
cana-660	164	10	133x	133x	NUM
cana-660	164	11	vol	vol	NOUN
cana-660	164	12	31	31	NUM
cana-660	164	13	no	no	NOUN
cana-660	164	14	.	.	PUNCT
cana-660	165	1	2s	2s	NUM
cana-660	165	2	(	(	PUNCT
cana-660	165	3	2024	2024	NUM
cana-660	165	4	)	)	PUNCT
cana-660	165	5	462	462	NUM
cana-660	165	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	165	7	doc	doc	PROPN
cana-660	165	8	1	1	NUM
cana-660	165	9	doc	doc	PROPN
cana-660	165	10	1	1	NUM
cana-660	165	11	doc	doc	PROPN
cana-660	165	12	1	1	NUM
cana-660	165	13	doc	doc	PROPN
cana-660	165	14	1	1	NUM
cana-660	165	15	q1	q1	PROPN
cana-660	165	16	q2	q2	NOUN
cana-660	165	17	.	.	PUNCT
cana-660	165	18	.	.	PUNCT
cana-660	166	1	qn	qn	PROPN
cana-660	166	2	proposed	propose	VERB
cana-660	166	3	evolutionary	evolutionary	ADJ
cana-660	166	4	algorithm	algorithm	NOUN
cana-660	166	5	learning	learn	VERB
cana-660	166	6	score	score	NOUN
cana-660	166	7	s	s	PROPN
cana-660	166	8	q1	q1	PROPN
cana-660	166	9	q2	q2	PROPN
cana-660	166	10	q3	q3	PROPN
cana-660	166	11	.	.	PUNCT
cana-660	166	12	.	.	PUNCT
cana-660	167	1	qn	qn	PROPN
cana-660	167	2	q1	q1	PROPN
cana-660	167	3	q2	q2	PROPN
cana-660	167	4	q3	q3	PROPN
cana-660	167	5	.	.	PUNCT
cana-660	167	6	.	.	PUNCT
cana-660	168	1	qn	qn	PROPN
cana-660	168	2	q1	q1	PROPN
cana-660	168	3	q2	q2	PROPN
cana-660	168	4	q3	q3	PROPN
cana-660	168	5	.	.	PUNCT
cana-660	168	6	.	.	PUNCT
cana-660	169	1	qn	qn	NOUN
cana-660	169	2	model	model	NOUN
cana-660	169	3	by	by	ADP
cana-660	169	4	lamdamart	lamdamart	NOUN
cana-660	169	5	database	database	NOUN
cana-660	169	6	feature	feature	NOUN
cana-660	169	7	subset	subset	NOUN
cana-660	169	8	l2	l2	NOUN
cana-660	169	9	regulation	regulation	NOUN
cana-660	169	10	q1	q1	PROPN
cana-660	169	11	q2	q2	PROPN
cana-660	169	12	q3	q3	PROPN
cana-660	169	13	.	.	PUNCT
cana-660	170	1	qn	qn	PROPN
cana-660	170	2	final	final	ADJ
cana-660	170	3	ranking	ranking	ADJ
cana-660	170	4	4.evolutionary	4.evolutionary	ADJ
cana-660	170	5	learning	learning	NOUN
cana-660	170	6	with	with	ADP
cana-660	170	7	lamdamart	lamdamart	NOUN
cana-660	170	8	4.1	4.1	NUM
cana-660	170	9	architecture	architecture	NOUN
cana-660	170	10	fig	fig	NOUN
cana-660	170	11	.	.	PUNCT
cana-660	171	1	4	4	X
cana-660	171	2	.	.	NUM
cana-660	171	3	proposed	propose	VERB
cana-660	171	4	architecture	architecture	NOUN
cana-660	171	5	with	with	ADP
cana-660	171	6	the	the	DET
cana-660	171	7	evolutionary	evolutionary	ADJ
cana-660	171	8	algorithm	algorithm	NOUN
cana-660	171	9	.	.	PUNCT
cana-660	172	1	traditional	traditional	ADJ
cana-660	172	2	learning	learning	NOUN
cana-660	172	3	with	with	ADP
cana-660	172	4	an	an	DET
cana-660	172	5	evolutionary	evolutionary	ADJ
cana-660	172	6	algorithm	algorithm	NOUN
cana-660	172	7	multiobjective	multiobjective	ADJ
cana-660	172	8	function	function	NOUN
cana-660	172	9	or	or	CCONJ
cana-660	172	10	convex	convex	NOUN
cana-660	172	11	optimization	optimization	NOUN
cana-660	172	12	is	be	AUX
cana-660	172	13	the	the	DET
cana-660	172	14	major	major	ADJ
cana-660	172	15	focus	focus	NOUN
cana-660	172	16	,	,	PUNCT
cana-660	172	17	as	as	SCONJ
cana-660	172	18	depicted	depict	VERB
cana-660	172	19	in	in	ADP
cana-660	172	20	the	the	DET
cana-660	172	21	literature	literature	NOUN
cana-660	172	22	survey	survey	NOUN
cana-660	172	23	.	.	PUNCT
cana-660	173	1	the	the	DET
cana-660	173	2	main	main	ADJ
cana-660	173	3	objective	objective	NOUN
cana-660	173	4	of	of	ADP
cana-660	173	5	this	this	DET
cana-660	173	6	paper	paper	NOUN
cana-660	173	7	is	be	AUX
cana-660	173	8	to	to	PART
cana-660	173	9	use	use	VERB
cana-660	173	10	the	the	DET
cana-660	173	11	hybrid	hybrid	ADJ
cana-660	173	12	evolutionary	evolutionary	ADJ
cana-660	173	13	model	model	NOUN
cana-660	173	14	for	for	ADP
cana-660	173	15	feature	feature	NOUN
cana-660	173	16	selection	selection	NOUN
cana-660	173	17	only	only	ADV
cana-660	173	18	.	.	PUNCT
cana-660	174	1	the	the	DET
cana-660	174	2	features	feature	NOUN
cana-660	174	3	of	of	ADP
cana-660	174	4	the	the	DET
cana-660	174	5	selected	select	VERB
cana-660	174	6	datasets	dataset	NOUN
cana-660	174	7	are	be	AUX
cana-660	174	8	used	use	VERB
cana-660	174	9	as	as	ADP
cana-660	174	10	inputs	input	NOUN
cana-660	174	11	to	to	ADP
cana-660	174	12	this	this	DET
cana-660	174	13	model	model	NOUN
cana-660	174	14	,	,	PUNCT
cana-660	174	15	and	and	CCONJ
cana-660	174	16	the	the	DET
cana-660	174	17	output	output	NOUN
cana-660	174	18	is	be	AUX
cana-660	174	19	the	the	DET
cana-660	174	20	feature	feature	NOUN
cana-660	174	21	subset	subset	NOUN
cana-660	174	22	,	,	PUNCT
cana-660	174	23	which	which	PRON
cana-660	174	24	can	can	AUX
cana-660	174	25	be	be	AUX
cana-660	174	26	trained	train	VERB
cana-660	174	27	on	on	ADP
cana-660	174	28	the	the	DET
cana-660	174	29	lamdamart	lamdamart	NOUN
cana-660	174	30	algorithm	algorithm	NOUN
cana-660	174	31	for	for	ADP
cana-660	174	32	ranking	rank	VERB
cana-660	174	33	.	.	PUNCT
cana-660	175	1	a	a	DET
cana-660	175	2	detailed	detailed	ADJ
cana-660	175	3	architecture	architecture	NOUN
cana-660	175	4	diagram	diagram	NOUN
cana-660	175	5	is	be	AUX
cana-660	175	6	shown	show	VERB
cana-660	175	7	above	above	ADV
cana-660	175	8	in	in	ADP
cana-660	175	9	fig6.we	fig6.we	NOUN
cana-660	175	10	evaluate	evaluate	VERB
cana-660	175	11	the	the	DET
cana-660	175	12	proposed	propose	VERB
cana-660	175	13	model	model	NOUN
cana-660	175	14	with	with	ADP
cana-660	175	15	all	all	DET
cana-660	175	16	the	the	DET
cana-660	175	17	conventional	conventional	ADJ
cana-660	175	18	metrics	metric	NOUN
cana-660	175	19	,	,	PUNCT
cana-660	175	20	such	such	ADJ
cana-660	175	21	as	as	ADP
cana-660	175	22	precision@k	precision@k	NOUN
cana-660	175	23	,	,	PUNCT
cana-660	175	24	mean	mean	ADJ
cana-660	175	25	average	average	ADJ
cana-660	175	26	precision	precision	NOUN
cana-660	175	27	(	(	PUNCT
cana-660	175	28	map	map	NOUN
cana-660	175	29	)	)	PUNCT
cana-660	175	30	,	,	PUNCT
cana-660	175	31	and	and	CCONJ
cana-660	175	32	normalized	normalize	VERB
cana-660	175	33	discounted	discount	VERB
cana-660	175	34	cumulative	cumulative	ADJ
cana-660	175	35	gain	gain	NOUN
cana-660	175	36	(	(	PUNCT
cana-660	175	37	ndcg	ndcg	PROPN
cana-660	175	38	)	)	PUNCT
cana-660	175	39	.	.	PUNCT
cana-660	176	1	the	the	DET
cana-660	176	2	evolutionary	evolutionary	ADJ
cana-660	176	3	algorithm	algorithm	NOUN
cana-660	176	4	used	use	VERB
cana-660	176	5	was	be	AUX
cana-660	176	6	simulated	simulate	VERB
cana-660	176	7	annealing	anneal	VERB
cana-660	176	8	with	with	ADP
cana-660	176	9	a	a	DET
cana-660	176	10	knn	knn	NOUN
cana-660	176	11	classifier	classifier	NOUN
cana-660	176	12	.	.	PUNCT
cana-660	177	1	the	the	DET
cana-660	177	2	modified	modify	VERB
cana-660	177	3	simulated	simulated	ADJ
cana-660	177	4	annealing	anneal	VERB
cana-660	177	5	algorithm	algorithm	NOUN
cana-660	177	6	can	can	AUX
cana-660	177	7	be	be	AUX
cana-660	177	8	used	use	VERB
cana-660	177	9	to	to	PART
cana-660	177	10	optimize	optimize	VERB
cana-660	177	11	the	the	DET
cana-660	177	12	weights	weight	NOUN
cana-660	177	13	of	of	ADP
cana-660	177	14	the	the	DET
cana-660	177	15	ranking	rank	VERB
cana-660	177	16	function	function	NOUN
cana-660	177	17	.	.	PUNCT
cana-660	178	1	initially	initially	ADV
cana-660	178	2	,	,	PUNCT
cana-660	178	3	by	by	ADP
cana-660	178	4	using	use	VERB
cana-660	178	5	the	the	DET
cana-660	178	6	elbow	elbow	NOUN
cana-660	178	7	method	method	NOUN
cana-660	178	8	,	,	PUNCT
cana-660	178	9	the	the	DET
cana-660	178	10	optimal	optimal	ADJ
cana-660	178	11	k	k	PROPN
cana-660	178	12	value	value	NOUN
cana-660	178	13	was	be	AUX
cana-660	178	14	found	find	VERB
cana-660	178	15	for	for	ADP
cana-660	178	16	the	the	DET
cana-660	178	17	classification	classification	NOUN
cana-660	178	18	.	.	PUNCT
cana-660	179	1	we	we	PRON
cana-660	179	2	applied	apply	VERB
cana-660	179	3	standard	standard	ADJ
cana-660	179	4	simulated	simulated	ADJ
cana-660	179	5	annealing	annealing	NOUN
cana-660	179	6	with	with	ADP
cana-660	179	7	some	some	DET
cana-660	179	8	modifications	modification	NOUN
cana-660	179	9	.	.	PUNCT
cana-660	180	1	given	give	VERB
cana-660	180	2	a	a	DET
cana-660	180	3	set	set	NOUN
cana-660	180	4	of	of	ADP
cana-660	180	5	weights	weight	NOUN
cana-660	180	6	w	w	PROPN
cana-660	180	7	,	,	PUNCT
cana-660	180	8	a	a	DET
cana-660	180	9	query	query	NOUN
cana-660	180	10	q	q	NOUN
cana-660	180	11	,	,	PUNCT
cana-660	180	12	and	and	CCONJ
cana-660	180	13	a	a	DET
cana-660	180	14	set	set	NOUN
cana-660	180	15	of	of	ADP
cana-660	180	16	documents	document	NOUN
cana-660	180	17	d	d	ADP
cana-660	180	18	,	,	PUNCT
cana-660	180	19	the	the	DET
cana-660	180	20	relevance	relevance	NOUN
cana-660	180	21	scores	score	NOUN
cana-660	180	22	can	can	AUX
cana-660	180	23	be	be	AUX
cana-660	180	24	computed	compute	VERB
cana-660	180	25	using	use	VERB
cana-660	180	26	the	the	DET
cana-660	180	27	following	follow	VERB
cana-660	180	28	method	method	NOUN
cana-660	180	29	.	.	PUNCT
cana-660	181	1	figure	figure	NOUN
cana-660	181	2	4	4	NUM
cana-660	181	3	depreciated	depreciate	VERB
cana-660	181	4	the	the	DET
cana-660	181	5	flow	flow	NOUN
cana-660	181	6	of	of	ADP
cana-660	181	7	process	process	NOUN
cana-660	181	8	carried	carry	VERB
cana-660	181	9	out	out	ADP
cana-660	181	10	during	during	ADP
cana-660	181	11	experimentation	experimentation	NOUN
cana-660	181	12	.	.	PUNCT
cana-660	182	1	databases	database	NOUN
cana-660	182	2	are	be	AUX
cana-660	182	3	from	from	ADP
cana-660	182	4	above	above	ADV
cana-660	182	5	mention	mention	VERB
cana-660	182	6	datasets	dataset	NOUN
cana-660	182	7	.	.	PUNCT
cana-660	183	1	dataset	dataset	NOUN
cana-660	183	2	is	be	AUX
cana-660	183	3	given	give	VERB
cana-660	183	4	to	to	ADP
cana-660	183	5	proposed	propose	VERB
cana-660	183	6	evolutionary	evolutionary	ADJ
cana-660	183	7	algorithm	algorithm	NOUN
cana-660	183	8	which	which	PRON
cana-660	183	9	mostly	mostly	ADV
cana-660	183	10	used	use	VERB
cana-660	183	11	simulated	simulated	ADJ
cana-660	183	12	annealing	annealing	NOUN
cana-660	183	13	which	which	PRON
cana-660	183	14	results	result	VERB
cana-660	183	15	into	into	ADP
cana-660	183	16	subsets	subset	NOUN
cana-660	183	17	of	of	ADP
cana-660	183	18	features	feature	NOUN
cana-660	183	19	.	.	PUNCT
cana-660	184	1	which	which	PRON
cana-660	184	2	then	then	ADV
cana-660	184	3	trained	train	VERB
cana-660	184	4	on	on	ADP
cana-660	184	5	communications	communication	NOUN
cana-660	184	6	on	on	ADP
cana-660	184	7	applied	apply	VERB
cana-660	184	8	nonlinear	nonlinear	ADJ
cana-660	184	9	analysis	analysis	NOUN
cana-660	184	10	issn	issn	NOUN
cana-660	184	11	:	:	PUNCT
cana-660	184	12	1074	1074	NUM
cana-660	184	13	-	-	PUNCT
cana-660	184	14	133x	133x	NUM
cana-660	184	15	vol	vol	NOUN
cana-660	184	16	31	31	NUM
cana-660	184	17	no	no	NOUN
cana-660	184	18	.	.	PUNCT
cana-660	185	1	2s	2s	NUM
cana-660	185	2	(	(	PUNCT
cana-660	185	3	2024	2024	NUM
cana-660	185	4	)	)	PUNCT
cana-660	185	5	463	463	NUM
cana-660	185	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	185	7	activation	activation	NOUN
cana-660	185	8	function	function	NOUN
cana-660	185	9	of	of	ADP
cana-660	185	10	lamdamart	lamdamart	NOUN
cana-660	185	11	with	with	ADP
cana-660	185	12	l2	l2	NOUN
cana-660	185	13	regularization	regularization	NOUN
cana-660	185	14	to	to	PART
cana-660	185	15	avoid	avoid	VERB
cana-660	185	16	the	the	DET
cana-660	185	17	over	over	ADP
cana-660	185	18	fitting	fitting	ADJ
cana-660	185	19	and	and	CCONJ
cana-660	185	20	generate	generate	VERB
cana-660	185	21	the	the	DET
cana-660	185	22	sorted	sorted	ADJ
cana-660	185	23	list	list	NOUN
cana-660	185	24	of	of	ADP
cana-660	185	25	documents	document	NOUN
cana-660	185	26	.	.	PUNCT
cana-660	186	1	4.2	4.2	NUM
cana-660	186	2	.	.	PUNCT
cana-660	186	3	databse	databse	NOUN
cana-660	186	4	as	as	ADP
cana-660	186	5	per	per	ADP
cana-660	186	6	proposed	propose	VERB
cana-660	186	7	model	model	NOUN
cana-660	186	8	standard	standard	ADJ
cana-660	186	9	datasets	dataset	NOUN
cana-660	186	10	are	be	AUX
cana-660	186	11	used	use	VERB
cana-660	186	12	details	detail	NOUN
cana-660	186	13	of	of	ADP
cana-660	186	14	datasets	dataset	NOUN
cana-660	186	15	are	be	AUX
cana-660	186	16	as	as	SCONJ
cana-660	186	17	follows	follow	VERB
cana-660	186	18	:	:	PUNCT
cana-660	186	19	table	table	NOUN
cana-660	186	20	6	6	NUM
cana-660	186	21	:	:	PUNCT
cana-660	186	22	data	datum	NOUN
cana-660	186	23	set	set	VERB
cana-660	186	24	description	description	NOUN
cana-660	186	25	we	we	PRON
cana-660	186	26	are	be	AUX
cana-660	186	27	going	go	VERB
cana-660	186	28	to	to	PART
cana-660	186	29	evaluate	evaluate	VERB
cana-660	186	30	the	the	DET
cana-660	186	31	proposed	propose	VERB
cana-660	186	32	model	model	NOUN
cana-660	186	33	with	with	ADP
cana-660	186	34	all	all	DET
cana-660	186	35	the	the	DET
cana-660	186	36	conventional	conventional	ADJ
cana-660	186	37	measures	measure	NOUN
cana-660	186	38	such	such	ADJ
cana-660	186	39	as	as	ADP
cana-660	186	40	precision	precision	NOUN
cana-660	186	41	@k	@k	NOUN
cana-660	186	42	,	,	PUNCT
cana-660	186	43	mean	mean	ADJ
cana-660	186	44	average	average	ADJ
cana-660	186	45	precision	precision	NOUN
cana-660	186	46	(	(	PUNCT
cana-660	186	47	map	map	NOUN
cana-660	186	48	)	)	PUNCT
cana-660	186	49	,	,	PUNCT
cana-660	186	50	normalized	normalize	VERB
cana-660	186	51	discounted	discount	VERB
cana-660	186	52	cumulative	cumulative	ADJ
cana-660	186	53	gain	gain	NOUN
cana-660	186	54	(	(	PUNCT
cana-660	186	55	ndcg	ndcg	PROPN
cana-660	186	56	)	)	PUNCT
cana-660	186	57	.	.	PUNCT
cana-660	187	1	evolutionary	evolutionary	ADJ
cana-660	187	2	algorithm	algorithm	NOUN
cana-660	187	3	used	use	VERB
cana-660	187	4	is	be	AUX
cana-660	187	5	simulated	simulate	VERB
cana-660	187	6	annealing	anneal	VERB
cana-660	187	7	with	with	ADP
cana-660	187	8	some	some	DET
cana-660	187	9	knn	knn	PROPN
cana-660	187	10	classifier	classifier	PROPN
cana-660	187	11	.	.	PUNCT
cana-660	188	1	the	the	DET
cana-660	188	2	modified	modify	VERB
cana-660	188	3	simulated	simulated	ADJ
cana-660	188	4	annealing	anneal	VERB
cana-660	188	5	algorithm	algorithm	NOUN
cana-660	188	6	can	can	AUX
cana-660	188	7	be	be	AUX
cana-660	188	8	used	use	VERB
cana-660	188	9	to	to	PART
cana-660	188	10	optimize	optimize	VERB
cana-660	188	11	the	the	DET
cana-660	188	12	weights	weight	NOUN
cana-660	188	13	of	of	ADP
cana-660	188	14	the	the	DET
cana-660	188	15	ranking	rank	VERB
cana-660	188	16	function	function	NOUN
cana-660	188	17	.	.	PUNCT
cana-660	189	1	initially	initially	ADV
cana-660	189	2	by	by	ADP
cana-660	189	3	using	use	VERB
cana-660	189	4	elbow	elbow	NOUN
cana-660	189	5	method	method	NOUN
cana-660	189	6	find	find	VERB
cana-660	189	7	the	the	DET
cana-660	189	8	optimal	optimal	ADJ
cana-660	189	9	k	k	PROPN
cana-660	189	10	value	value	NOUN
cana-660	189	11	for	for	ADP
cana-660	189	12	the	the	DET
cana-660	189	13	classification	classification	NOUN
cana-660	189	14	.	.	PUNCT
cana-660	190	1	we	we	PRON
cana-660	190	2	apply	apply	VERB
cana-660	190	3	standard	standard	ADJ
cana-660	190	4	simulated	simulated	ADJ
cana-660	190	5	annealing	annealing	NOUN
cana-660	190	6	with	with	ADP
cana-660	190	7	some	some	DET
cana-660	190	8	modification	modification	NOUN
cana-660	190	9	.	.	PUNCT
cana-660	191	1	given	give	VERB
cana-660	191	2	a	a	DET
cana-660	191	3	set	set	NOUN
cana-660	191	4	of	of	ADP
cana-660	191	5	weights	weight	NOUN
cana-660	191	6	w	w	PROPN
cana-660	191	7	,	,	PUNCT
cana-660	191	8	a	a	DET
cana-660	191	9	query	query	NOUN
cana-660	191	10	q	q	NOUN
cana-660	191	11	,	,	PUNCT
cana-660	191	12	and	and	CCONJ
cana-660	191	13	a	a	DET
cana-660	191	14	set	set	NOUN
cana-660	191	15	of	of	ADP
cana-660	191	16	documents	document	NOUN
cana-660	191	17	d	d	ADP
cana-660	191	18	,	,	PUNCT
cana-660	191	19	the	the	DET
cana-660	191	20	relevance	relevance	NOUN
cana-660	191	21	scores	score	NOUN
cana-660	191	22	can	can	AUX
cana-660	191	23	be	be	AUX
cana-660	191	24	computed	compute	VERB
cana-660	191	25	using	use	VERB
cana-660	191	26	following	follow	VERB
cana-660	191	27	method	method	NOUN
cana-660	191	28	.	.	PUNCT
cana-660	192	1	algorithm	algorithm	NOUN
cana-660	192	2	1	1	NUM
cana-660	192	3	:	:	PUNCT
cana-660	192	4	process	process	NOUN
cana-660	192	5	of	of	ADP
cana-660	192	6	proposed	propose	VERB
cana-660	192	7	evolutionary	evolutionary	ADJ
cana-660	192	8	model	model	NOUN
cana-660	192	9	•	•	ADP
cana-660	192	10	define	define	VERB
cana-660	192	11	the	the	DET
cana-660	192	12	search	search	NOUN
cana-660	192	13	space	space	NOUN
cana-660	192	14	:	:	PUNCT
cana-660	192	15	identify	identify	VERB
cana-660	192	16	the	the	DET
cana-660	192	17	weights	weight	NOUN
cana-660	192	18	that	that	PRON
cana-660	192	19	need	need	VERB
cana-660	192	20	to	to	PART
cana-660	192	21	be	be	AUX
cana-660	192	22	tuned	tune	VERB
cana-660	192	23	to	to	PART
cana-660	192	24	optimize	optimize	VERB
cana-660	192	25	the	the	DET
cana-660	192	26	ranking	rank	VERB
cana-660	192	27	function	function	NOUN
cana-660	192	28	,	,	PUNCT
cana-660	192	29	create	create	VERB
cana-660	192	30	an	an	DET
cana-660	192	31	initial	initial	ADJ
cana-660	192	32	random	random	ADJ
cana-660	192	33	subset	subset	NOUN
cana-660	192	34	(	(	PUNCT
cana-660	192	35	let	let	VERB
cana-660	192	36	s	s	PRON
cana-660	192	37	=	=	NOUN
cana-660	192	38	s0	s0	PROPN
cana-660	192	39	)	)	PUNCT
cana-660	192	40	with	with	ADP
cana-660	192	41	iteration	iteration	NOUN
cana-660	192	42	(	(	PUNCT
cana-660	192	43	k	k	NOUN
cana-660	192	44	)	)	PUNCT
cana-660	192	45	.	.	PUNCT
cana-660	193	1	•	•	NOUN
cana-660	193	2	define	define	VERB
cana-660	193	3	probability	probability	NOUN
cana-660	193	4	function	function	NOUN
cana-660	193	5	of	of	ADP
cana-660	193	6	random	random	ADJ
cana-660	193	7	subset	subset	NOUN
cana-660	193	8	and	and	CCONJ
cana-660	193	9	snewsubset	snewsubset	VERB
cana-660	193	10	•	•	ADP
cana-660	193	11	while	while	SCONJ
cana-660	193	12	kmax	kmax	NOUN
cana-660	193	13	!	!	PUNCT
cana-660	194	1	=	=	SYM
cana-660	195	1	0	0	PUNCT
cana-660	195	2	do	do	AUX
cana-660	195	3	o	o	NOUN
cana-660	195	4	p(accept	p(accept	PROPN
cana-660	195	5	)	)	PUNCT
cana-660	195	6	←	←	PROPN
cana-660	195	7	min⁡(1	min⁡(1	PROPN
cana-660	195	8	,	,	PUNCT
cana-660	195	9	⌈	⌈	X
cana-660	195	10	𝑒(−(𝑜𝑏𝑗𝑛𝑒𝑤−𝑜𝑏𝑗𝑜𝑙𝑑	𝑒(−(𝑜𝑏𝑗𝑛𝑒𝑤−𝑜𝑏𝑗𝑜𝑙𝑑	ADJ
cana-660	195	11	)	)	PUNCT
cana-660	195	12	𝑇	𝑇	PROPN
cana-660	195	13	⌉	⌉	NOUN
cana-660	195	14	)	)	PUNCT
cana-660	195	15	o	o	NOUN
cana-660	195	16	perturbed	perturb	VERB
cana-660	195	17	the	the	DET
cana-660	195	18	current	current	ADJ
cana-660	195	19	subset	subset	NOUN
cana-660	195	20	and	and	CCONJ
cana-660	195	21	fit	fit	VERB
cana-660	195	22	the	the	DET
cana-660	195	23	model	model	NOUN
cana-660	195	24	;	;	PUNCT
cana-660	195	25	o	o	PROPN
cana-660	195	26	𝑟(𝑞	𝑟(𝑞	PROPN
cana-660	195	27	,	,	PUNCT
cana-660	195	28	𝑑	𝑑	NOUN
cana-660	195	29	)	)	PUNCT
cana-660	195	30	=	=	PUNCT
cana-660	196	1	∑(𝑤𝑖	∑(𝑤𝑖	PROPN
cana-660	196	2	×	×	NOUN
cana-660	196	3	𝑓𝑖(𝑞	𝑓𝑖(𝑞	PUNCT
cana-660	196	4	,	,	PUNCT
cana-660	196	5	𝑑	𝑑	NOUN
cana-660	196	6	)	)	PUNCT
cana-660	196	7	o	o	NOUN
cana-660	196	8	find	find	VERB
cana-660	196	9	all	all	DET
cana-660	196	10	the	the	DET
cana-660	196	11	neighbour	neighbour	NOUN
cana-660	196	12	:	:	PUNCT
cana-660	196	13	define	define	VERB
cana-660	196	14	neighbour	neighbour	NOUN
cana-660	196	15	function	function	NOUN
cana-660	196	16	to	to	PART
cana-660	196	17	find	find	VERB
cana-660	196	18	random	random	ADJ
cana-660	196	19	neighbour	neighbour	NOUN
cana-660	196	20	.	.	PUNCT
cana-660	197	1	o	o	PROPN
cana-660	197	2	𝑠𝑛𝑒𝑤	𝑠𝑛𝑒𝑤	NOUN
cana-660	198	1	=	=	PUNCT
cana-660	199	1	𝑐𝑎𝑙𝑙⁡𝑛𝑒𝑖𝑔ℎ𝑏𝑜𝑢𝑟⁡𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛	𝑐𝑎𝑙𝑙⁡𝑛𝑒𝑖𝑔ℎ𝑏𝑜𝑢𝑟⁡𝑓𝑢𝑛𝑐𝑡𝑖𝑜𝑛	X
cana-660	199	2	;	;	PUNCT
cana-660	199	3	o	o	NOUN
cana-660	199	4	call	call	NOUN
cana-660	199	5	probability	probability	NOUN
cana-660	199	6	function	function	NOUN
cana-660	199	7	with	with	ADP
cana-660	199	8	random	random	ADJ
cana-660	199	9	subset	subset	NOUN
cana-660	199	10	and	and	CCONJ
cana-660	199	11	𝑠𝑛𝑒𝑤𝑠𝑢𝑏𝑠𝑒𝑡	𝑠𝑛𝑒𝑤𝑠𝑢𝑏𝑠𝑒𝑡	ADJ
cana-660	199	12	;	;	PUNCT
cana-660	199	13	▪	▪	NOUN
cana-660	199	14	if	if	SCONJ
cana-660	199	15	performance	performance	NOUN
cana-660	199	16	is	be	AUX
cana-660	199	17	better	well	ADJ
cana-660	199	18	than	than	SCONJ
cana-660	199	19	perturbed	perturb	VERB
cana-660	199	20	set	set	VERB
cana-660	199	21	then	then	ADV
cana-660	199	22	•	•	NUM
cana-660	199	23	accept	accept	VERB
cana-660	199	24	new	new	ADJ
cana-660	199	25	subset	subset	NOUN
cana-660	199	26	▪	▪	NOUN
cana-660	199	27	else	else	ADV
cana-660	199	28	•	•	NOUN
cana-660	199	29	calculate	calculate	VERB
cana-660	199	30	the	the	DET
cana-660	199	31	acceptance	acceptance	NOUN
cana-660	199	32	probability	probability	NOUN
cana-660	199	33	;	;	PUNCT
cana-660	199	34	o	o	NOUN
cana-660	199	35	if(𝑃(𝐸(𝑠	if(𝑃(𝐸(𝑠	PROPN
cana-660	199	36	)	)	PUNCT
cana-660	199	37	,	,	PUNCT
cana-660	199	38	𝐸(𝑠𝑛𝑒𝑤	𝐸(𝑠𝑛𝑒𝑤	NOUN
cana-660	199	39	)	)	PUNCT
cana-660	199	40	,	,	PUNCT
cana-660	199	41	𝑇	𝑇	PROPN
cana-660	199	42	)	)	PUNCT
cana-660	199	43	random	random	ADJ
cana-660	199	44	(	(	PUNCT
cana-660	199	45	0,1	0,1	NUM
cana-660	199	46	)	)	PUNCT
cana-660	199	47	then	then	ADV
cana-660	199	48	▪	▪	ADV
cana-660	199	49	s=𝑠𝑛𝑒𝑤	s=𝑠𝑛𝑒𝑤	NOUN
cana-660	199	50	o	o	NOUN
cana-660	199	51	else	else	ADV
cana-660	199	52	communications	communication	NOUN
cana-660	199	53	on	on	ADP
cana-660	199	54	applied	apply	VERB
cana-660	199	55	nonlinear	nonlinear	ADJ
cana-660	199	56	analysis	analysis	NOUN
cana-660	199	57	issn	issn	NOUN
cana-660	199	58	:	:	PUNCT
cana-660	199	59	1074	1074	NUM
cana-660	199	60	-	-	PUNCT
cana-660	199	61	133x	133x	NUM
cana-660	199	62	vol	vol	NOUN
cana-660	199	63	31	31	NUM
cana-660	199	64	no	no	NOUN
cana-660	199	65	.	.	PUNCT
cana-660	200	1	2s	2s	NUM
cana-660	200	2	(	(	PUNCT
cana-660	200	3	2024	2024	NUM
cana-660	200	4	)	)	PUNCT
cana-660	200	5	464	464	NUM
cana-660	200	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	200	7	▪	▪	X
cana-660	200	8	accept	accept	VERB
cana-660	200	9	new	new	ADJ
cana-660	200	10	subset	subset	NOUN
cana-660	200	11	o	o	NOUN
cana-660	200	12	end	end	NOUN
cana-660	200	13	▪	▪	ADJ
cana-660	200	14	end	end	NOUN
cana-660	200	15	o	o	NOUN
cana-660	200	16	update	update	NOUN
cana-660	200	17	the	the	DET
cana-660	200	18	k	k	PROPN
cana-660	200	19	value	value	NOUN
cana-660	200	20	by	by	ADP
cana-660	200	21	1	1	NUM
cana-660	200	22	;	;	PUNCT
cana-660	200	23	•	•	NUM
cana-660	200	24	end	end	NOUN
cana-660	200	25	neighbour	neighbour	NOUN
cana-660	200	26	function	function	NOUN
cana-660	200	27	caution	caution	NOUN
cana-660	200	28	is	be	AUX
cana-660	200	29	done	do	VERB
cana-660	200	30	as	as	SCONJ
cana-660	200	31	follows	follow	VERB
cana-660	200	32	:	:	PUNCT
cana-660	200	33	let	let	VERB
cana-660	200	34	s	s	PRON
cana-660	200	35	represent	represent	VERB
cana-660	200	36	the	the	DET
cana-660	200	37	current	current	ADJ
cana-660	200	38	feature	feature	NOUN
cana-660	200	39	subset	subset	NOUN
cana-660	200	40	,	,	PUNCT
cana-660	200	41	and	and	CCONJ
cana-660	200	42	let	let	VERB
cana-660	200	43	s′	s′	PROPN
cana-660	200	44	represent	represent	VERB
cana-660	200	45	a	a	DET
cana-660	200	46	neighbouring	neighbouring	ADJ
cana-660	200	47	solution	solution	NOUN
cana-660	200	48	generated	generate	VERB
cana-660	200	49	by	by	ADP
cana-660	200	50	applying	apply	VERB
cana-660	200	51	a	a	DET
cana-660	200	52	local	local	ADJ
cana-660	200	53	change	change	NOUN
cana-660	200	54	to	to	ADP
cana-660	200	55	s.	s.	PROPN
cana-660	200	56	•	•	ADV
cana-660	200	57	let	let	VERB
cana-660	200	58	s′=s∪	s′=s∪	PROPN
cana-660	200	59	{	{	PUNCT
cana-660	200	60	fi	fi	NOUN
cana-660	200	61	}	}	PUNCT
cana-660	200	62	represent	represent	VERB
cana-660	200	63	the	the	DET
cana-660	200	64	neighbour	neighbour	NOUN
cana-660	200	65	obtained	obtain	VERB
cana-660	200	66	by	by	ADP
cana-660	200	67	adding	add	VERB
cana-660	200	68	feature	feature	NOUN
cana-660	200	69	fi	fi	NOUN
cana-660	200	70	to	to	ADP
cana-660	200	71	the	the	DET
cana-660	200	72	current	current	ADJ
cana-660	200	73	subset	subset	NOUN
cana-660	200	74	ss	ss	PROPN
cana-660	200	75	.	.	PUNCT
cana-660	201	1	this	this	DET
cana-660	201	2	operation	operation	NOUN
cana-660	201	3	can	can	AUX
cana-660	201	4	be	be	AUX
cana-660	201	5	represented	represent	VERB
cana-660	201	6	as	as	ADP
cana-660	201	7	:	:	PUNCT
cana-660	201	8	s′=s+fi	s′=s+fi	X
cana-660	201	9	(	(	PUNCT
cana-660	201	10	1	1	NUM
cana-660	201	11	)	)	PUNCT
cana-660	201	12	•	•	NOUN
cana-660	201	13	let	let	VERB
cana-660	201	14	s′=s∖{fi	s′=s∖{fi	NOUN
cana-660	201	15	}	}	PUNCT
cana-660	201	16	represent	represent	VERB
cana-660	201	17	the	the	DET
cana-660	201	18	neighbor	neighbor	NOUN
cana-660	201	19	obtained	obtain	VERB
cana-660	201	20	by	by	ADP
cana-660	201	21	removing	remove	VERB
cana-660	201	22	feature	feature	NOUN
cana-660	201	23	fi	fi	NOUN
cana-660	201	24	from	from	ADP
cana-660	201	25	the	the	DET
cana-660	201	26	current	current	ADJ
cana-660	201	27	subset	subset	NOUN
cana-660	201	28	s.	s.	PROPN
cana-660	201	29	this	this	DET
cana-660	201	30	operation	operation	NOUN
cana-660	201	31	can	can	AUX
cana-660	201	32	be	be	AUX
cana-660	201	33	represented	represent	VERB
cana-660	201	34	as	as	ADP
cana-660	201	35	:	:	PUNCT
cana-660	201	36	s′=s−fi	s′=s−fi	NOUN
cana-660	201	37	(	(	PUNCT
cana-660	201	38	2	2	NUM
cana-660	201	39	)	)	PUNCT
cana-660	201	40	•	•	NOUN
cana-660	201	41	let	let	VERB
cana-660	201	42	s′	s′	PROPN
cana-660	201	43	represent	represent	VERB
cana-660	201	44	the	the	DET
cana-660	201	45	neighbor	neighbor	NOUN
cana-660	201	46	obtained	obtain	VERB
cana-660	201	47	by	by	ADP
cana-660	201	48	swapping	swap	VERB
cana-660	201	49	two	two	NUM
cana-660	201	50	features	feature	NOUN
cana-660	201	51	fi	fi	NOUN
cana-660	201	52	and	and	CCONJ
cana-660	201	53	fj	fj	PROPN
cana-660	201	54	in	in	ADP
cana-660	201	55	the	the	DET
cana-660	201	56	current	current	ADJ
cana-660	201	57	subset	subset	NOUN
cana-660	201	58	s.	s.	PROPN
cana-660	201	59	this	this	DET
cana-660	201	60	operation	operation	NOUN
cana-660	201	61	can	can	AUX
cana-660	201	62	be	be	AUX
cana-660	201	63	represented	represent	VERB
cana-660	201	64	as	as	ADP
cana-660	201	65	:	:	PUNCT
cana-660	201	66	s′=s−fi+fj	s′=s−fi+fj	X
cana-660	201	67	(	(	PUNCT
cana-660	201	68	3	3	X
cana-660	201	69	)	)	PUNCT
cana-660	201	70	dimention	dimention	NOUN
cana-660	201	71	reduction	reduction	NOUN
cana-660	201	72	is	be	AUX
cana-660	201	73	done	do	VERB
cana-660	201	74	via	via	ADP
cana-660	201	75	t	t	NOUN
cana-660	201	76	-	-	PUNCT
cana-660	201	77	distributed	distribute	VERB
cana-660	201	78	stochastic	stochastic	ADJ
cana-660	201	79	neighbor	neighbor	NOUN
cana-660	201	80	embedding	embed	VERB
cana-660	201	81	by	by	ADP
cana-660	201	82	using	use	VERB
cana-660	201	83	x′=t	x′=t	PROPN
cana-660	201	84	-	-	PUNCT
cana-660	201	85	sne(x	sne(x	PROPN
cana-660	201	86	)	)	PUNCT
cana-660	201	87	(	(	PUNCT
cana-660	201	88	4	4	X
cana-660	201	89	)	)	PUNCT
cana-660	201	90	where	where	SCONJ
cana-660	201	91	t	t	PROPN
cana-660	201	92	-	-	PUNCT
cana-660	201	93	sne	sne	PROPN
cana-660	201	94	is	be	AUX
cana-660	201	95	a	a	DET
cana-660	201	96	non	non	ADJ
cana-660	201	97	-	-	ADJ
cana-660	201	98	linear	linear	ADJ
cana-660	201	99	dimensionality	dimensionality	NOUN
cana-660	201	100	reduction	reduction	NOUN
cana-660	201	101	technique	technique	NOUN
cana-660	201	102	that	that	PRON
cana-660	201	103	maps	map	VERB
cana-660	201	104	the	the	DET
cana-660	201	105	high	high	ADV
cana-660	201	106	-	-	PUNCT
cana-660	201	107	dimensional	dimensional	ADJ
cana-660	201	108	feature	feature	NOUN
cana-660	201	109	space	space	NOUN
cana-660	201	110	x	x	X
cana-660	201	111	to	to	ADP
cana-660	201	112	a	a	DET
cana-660	201	113	lower	lower	ADV
cana-660	201	114	-	-	PUNCT
cana-660	201	115	dimensional	dimensional	ADJ
cana-660	201	116	space	space	NOUN
cana-660	201	117	x′x′	x′x′	PROPN
cana-660	201	118	while	while	SCONJ
cana-660	201	119	preserving	preserve	VERB
cana-660	201	120	the	the	DET
cana-660	201	121	local	local	ADJ
cana-660	201	122	structure	structure	NOUN
cana-660	201	123	of	of	ADP
cana-660	201	124	the	the	DET
cana-660	201	125	data	datum	NOUN
cana-660	201	126	.	.	PUNCT
cana-660	202	1	5.result	5.result	NUM
cana-660	202	2	the	the	DET
cana-660	202	3	evolutionary	evolutionary	ADJ
cana-660	202	4	result	result	NOUN
cana-660	202	5	of	of	ADP
cana-660	202	6	the	the	DET
cana-660	202	7	modified	modify	VERB
cana-660	202	8	simulated	simulated	ADJ
cana-660	202	9	annealing	anneal	VERB
cana-660	202	10	algorithm	algorithm	NOUN
cana-660	202	11	with	with	ADP
cana-660	202	12	classification	classification	NOUN
cana-660	202	13	for	for	ADP
cana-660	202	14	ranking	rank	VERB
cana-660	202	15	using	use	VERB
cana-660	202	16	learning	learn	VERB
cana-660	202	17	to	to	PART
cana-660	202	18	rank	rank	VERB
cana-660	202	19	depends	depend	VERB
cana-660	202	20	on	on	ADP
cana-660	202	21	various	various	ADJ
cana-660	202	22	factors	factor	NOUN
cana-660	202	23	,	,	PUNCT
cana-660	202	24	such	such	ADJ
cana-660	202	25	as	as	ADP
cana-660	202	26	the	the	DET
cana-660	202	27	quality	quality	NOUN
cana-660	202	28	of	of	ADP
cana-660	202	29	the	the	DET
cana-660	202	30	training	training	NOUN
cana-660	202	31	data	datum	NOUN
cana-660	202	32	,	,	PUNCT
cana-660	202	33	the	the	DET
cana-660	202	34	choice	choice	NOUN
cana-660	202	35	of	of	ADP
cana-660	202	36	cost	cost	NOUN
cana-660	202	37	function	function	NOUN
cana-660	202	38	,	,	PUNCT
cana-660	202	39	the	the	DET
cana-660	202	40	selection	selection	NOUN
cana-660	202	41	of	of	ADP
cana-660	202	42	the	the	DET
cana-660	202	43	mutation	mutation	NOUN
cana-660	202	44	and	and	CCONJ
cana-660	202	45	acceptance	acceptance	NOUN
cana-660	202	46	functions	function	NOUN
cana-660	202	47	,	,	PUNCT
cana-660	202	48	and	and	CCONJ
cana-660	202	49	the	the	DET
cana-660	202	50	length	length	NOUN
cana-660	202	51	of	of	ADP
cana-660	202	52	the	the	DET
cana-660	202	53	optimization	optimization	NOUN
cana-660	202	54	process	process	NOUN
cana-660	202	55	.	.	PUNCT
cana-660	203	1	all	all	DET
cana-660	203	2	the	the	DET
cana-660	203	3	data	datum	NOUN
cana-660	203	4	are	be	AUX
cana-660	203	5	well	well	ADV
cana-660	203	6	organized	organize	VERB
cana-660	203	7	and	and	CCONJ
cana-660	203	8	provided	provide	VERB
cana-660	203	9	in	in	ADP
cana-660	203	10	different	different	ADJ
cana-660	203	11	folds	fold	NOUN
cana-660	203	12	;	;	PUNCT
cana-660	203	13	thus	thus	ADV
cana-660	203	14	,	,	PUNCT
cana-660	203	15	training	training	NOUN
cana-660	203	16	,	,	PUNCT
cana-660	203	17	validation	validation	NOUN
cana-660	203	18	and	and	CCONJ
cana-660	203	19	testing	testing	NOUN
cana-660	203	20	are	be	AUX
cana-660	203	21	easy	easy	ADJ
cana-660	203	22	.	.	PUNCT
cana-660	204	1	in	in	ADP
cana-660	204	2	above	above	ADP
cana-660	204	3	mentioned	mention	VERB
cana-660	204	4	algorithm	algorithm	NOUN
cana-660	204	5	𝑟(𝑞	𝑟(𝑞	NUM
cana-660	204	6	,	,	PUNCT
cana-660	204	7	𝑑	𝑑	NOUN
cana-660	204	8	)	)	PUNCT
cana-660	204	9	=	=	SYM
cana-660	204	10	∑𝑤_𝑏	∑𝑤_𝑏	PROPN
cana-660	204	11	∗	∗	PROPN
cana-660	204	12	𝑓_𝑏(𝑞	𝑓_𝑏(𝑞	PROPN
cana-660	204	13	,	,	PUNCT
cana-660	204	14	𝑑	𝑑	NOUN
cana-660	204	15	)	)	PUNCT
cana-660	204	16	(	(	PUNCT
cana-660	204	17	5	5	NUM
cana-660	204	18	)	)	PUNCT
cana-660	204	19	where	where	SCONJ
cana-660	204	20	r(q	r(q	PROPN
cana-660	204	21	,	,	PUNCT
cana-660	204	22	d	d	X
cana-660	204	23	)	)	PUNCT
cana-660	204	24	is	be	AUX
cana-660	204	25	the	the	DET
cana-660	204	26	relevance	relevance	NOUN
cana-660	204	27	score	score	NOUN
cana-660	204	28	of	of	ADP
cana-660	204	29	document	document	NOUN
cana-660	204	30	d	d	NOUN
cana-660	204	31	for	for	ADP
cana-660	204	32	query	query	NOUN
cana-660	204	33	q	q	NOUN
cana-660	204	34	,	,	PUNCT
cana-660	204	35	w_b	w_b	PROPN
cana-660	204	36	is	be	AUX
cana-660	204	37	the	the	DET
cana-660	204	38	weight	weight	NOUN
cana-660	204	39	of	of	ADP
cana-660	204	40	feature	feature	NOUN
cana-660	204	41	i	i	PRON
cana-660	204	42	,	,	PUNCT
cana-660	204	43	and	and	CCONJ
cana-660	204	44	f_b(q	f_b(q	NOUN
cana-660	204	45	,	,	PUNCT
cana-660	204	46	d	d	NOUN
cana-660	204	47	)	)	PUNCT
cana-660	204	48	is	be	AUX
cana-660	204	49	the	the	DET
cana-660	204	50	value	value	NOUN
cana-660	204	51	of	of	ADP
cana-660	204	52	feature	feature	NOUN
cana-660	204	53	i	i	PRON
cana-660	204	54	for	for	ADP
cana-660	204	55	query	query	NOUN
cana-660	204	56	q	q	NOUN
cana-660	204	57	and	and	CCONJ
cana-660	204	58	document	document	NOUN
cana-660	204	59	d.	d.	NOUN
cana-660	204	60	where	where	SCONJ
cana-660	204	61	obj_new	obj_new	ADV
cana-660	204	62	is	be	AUX
cana-660	204	63	the	the	DET
cana-660	204	64	objective	objective	ADJ
cana-660	204	65	function	function	NOUN
cana-660	204	66	value	value	NOUN
cana-660	204	67	of	of	ADP
cana-660	204	68	the	the	DET
cana-660	204	69	proposed	propose	VERB
cana-660	204	70	solution	solution	NOUN
cana-660	204	71	,	,	PUNCT
cana-660	204	72	obj_old	obj_old	PROPN
cana-660	204	73	is	be	AUX
cana-660	204	74	the	the	DET
cana-660	204	75	objective	objective	ADJ
cana-660	204	76	function	function	NOUN
cana-660	204	77	value	value	NOUN
cana-660	204	78	of	of	ADP
cana-660	204	79	the	the	DET
cana-660	204	80	current	current	ADJ
cana-660	204	81	solution	solution	NOUN
cana-660	204	82	,	,	PUNCT
cana-660	204	83	and	and	CCONJ
cana-660	204	84	t	t	PROPN
cana-660	204	85	is	be	AUX
cana-660	204	86	the	the	DET
cana-660	204	87	current	current	ADJ
cana-660	204	88	final	final	ADJ
cana-660	204	89	subset	subset	NOUN
cana-660	204	90	.	.	PUNCT
cana-660	205	1	this	this	DET
cana-660	205	2	equation	equation	NOUN
cana-660	205	3	ensures	ensure	VERB
cana-660	205	4	that	that	SCONJ
cana-660	205	5	the	the	DET
cana-660	205	6	probability	probability	NOUN
cana-660	205	7	of	of	ADP
cana-660	205	8	accepting	accept	VERB
cana-660	205	9	a	a	DET
cana-660	205	10	worse	bad	ADJ
cana-660	205	11	solution	solution	NOUN
cana-660	205	12	decreases	decrease	VERB
cana-660	205	13	as	as	SCONJ
cana-660	205	14	the	the	DET
cana-660	205	15	temperature	temperature	NOUN
cana-660	205	16	decreases	decrease	VERB
cana-660	205	17	,	,	PUNCT
cana-660	205	18	allowing	allow	VERB
cana-660	205	19	the	the	DET
cana-660	205	20	algorithm	algorithm	NOUN
cana-660	205	21	to	to	PART
cana-660	205	22	converge	converge	VERB
cana-660	205	23	to	to	ADP
cana-660	205	24	a	a	DET
cana-660	205	25	good	good	ADJ
cana-660	205	26	solution	solution	NOUN
cana-660	205	27	.	.	PUNCT
cana-660	206	1	communications	communication	NOUN
cana-660	206	2	on	on	ADP
cana-660	206	3	applied	apply	VERB
cana-660	206	4	nonlinear	nonlinear	ADJ
cana-660	206	5	analysis	analysis	NOUN
cana-660	206	6	issn	issn	NOUN
cana-660	206	7	:	:	PUNCT
cana-660	206	8	1074	1074	NUM
cana-660	206	9	-	-	PUNCT
cana-660	206	10	133x	133x	NUM
cana-660	206	11	vol	vol	NOUN
cana-660	206	12	31	31	NUM
cana-660	206	13	no	no	NOUN
cana-660	206	14	.	.	PUNCT
cana-660	207	1	2s	2s	NUM
cana-660	207	2	(	(	PUNCT
cana-660	207	3	2024	2024	NUM
cana-660	207	4	)	)	PUNCT
cana-660	207	5	465	465	NUM
cana-660	207	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	207	7	the	the	DET
cana-660	207	8	model	model	NOUN
cana-660	207	9	’s	’s	PART
cana-660	207	10	performance	performance	NOUN
cana-660	207	11	was	be	AUX
cana-660	207	12	evaluated	evaluate	VERB
cana-660	207	13	by	by	ADP
cana-660	207	14	comparing	compare	VERB
cana-660	207	15	it	it	PRON
cana-660	207	16	to	to	ADP
cana-660	207	17	that	that	PRON
cana-660	207	18	of	of	ADP
cana-660	207	19	standard	standard	ADJ
cana-660	207	20	benchmark	benchmark	ADJ
cana-660	207	21	algorithms	algorithm	NOUN
cana-660	207	22	for	for	ADP
cana-660	207	23	learning	learn	VERB
cana-660	207	24	to	to	PART
cana-660	207	25	rank	rank	VERB
cana-660	207	26	.	.	PUNCT
cana-660	208	1	specifically	specifically	ADV
cana-660	208	2	,	,	PUNCT
cana-660	208	3	the	the	DET
cana-660	208	4	ranknet	ranknet	NOUN
cana-660	208	5	,	,	PUNCT
cana-660	208	6	lambdanet	lambdanet	NOUN
cana-660	208	7	,	,	PUNCT
cana-660	208	8	and	and	CCONJ
cana-660	208	9	lambdamart	lambdamart	ADJ
cana-660	208	10	algorithms	algorithm	NOUN
cana-660	208	11	were	be	AUX
cana-660	208	12	chosen	choose	VERB
cana-660	208	13	because	because	SCONJ
cana-660	208	14	they	they	PRON
cana-660	208	15	have	have	AUX
cana-660	208	16	demonstrated	demonstrate	VERB
cana-660	208	17	strong	strong	ADJ
cana-660	208	18	performance	performance	NOUN
cana-660	208	19	in	in	ADP
cana-660	208	20	various	various	ADJ
cana-660	208	21	applications	application	NOUN
cana-660	208	22	.	.	PUNCT
cana-660	209	1	additionally	additionally	ADV
cana-660	209	2	,	,	PUNCT
cana-660	209	3	feature	feature	NOUN
cana-660	209	4	selection	selection	NOUN
cana-660	209	5	was	be	AUX
cana-660	209	6	evaluated	evaluate	VERB
cana-660	209	7	using	use	VERB
cana-660	209	8	fsm	fsm	PROPN
cana-660	209	9	rank	rank	PROPN
cana-660	209	10	and	and	CCONJ
cana-660	209	11	heuristic	heuristic	ADJ
cana-660	209	12	rank	rank	NOUN
cana-660	209	13	(	(	PUNCT
cana-660	209	14	ha	ha	INTJ
cana-660	209	15	)	)	PUNCT
cana-660	209	16	.	.	PUNCT
cana-660	210	1	above	above	ADP
cana-660	210	2	result	result	NOUN
cana-660	210	3	shows	show	VERB
cana-660	210	4	only	only	ADV
cana-660	210	5	ndcg@10	ndcg@10	VERB
cana-660	210	6	evaluation	evaluation	NOUN
cana-660	210	7	of	of	ADP
cana-660	210	8	mslr	mslr	ADJ
cana-660	210	9	web	web	NOUN
cana-660	210	10	10k	10k	NOUN
cana-660	210	11	data	datum	NOUN
cana-660	210	12	-	-	PUNCT
cana-660	210	13	sets	set	NOUN
cana-660	210	14	only	only	ADV
cana-660	210	15	.	.	PUNCT
cana-660	211	1	before	before	ADP
cana-660	211	2	applying	apply	VERB
cana-660	211	3	to	to	ADP
cana-660	211	4	all	all	DET
cana-660	211	5	data	data	NOUN
cana-660	211	6	-	-	PUNCT
cana-660	211	7	set	set	NOUN
cana-660	211	8	,	,	PUNCT
cana-660	211	9	the	the	DET
cana-660	211	10	model	model	NOUN
cana-660	211	11	performance	performance	NOUN
cana-660	211	12	was	be	AUX
cana-660	211	13	checked	check	VERB
cana-660	211	14	.	.	PUNCT
cana-660	212	1	above	above	ADP
cana-660	212	2	results	result	NOUN
cana-660	212	3	shows	show	VERB
cana-660	212	4	that	that	SCONJ
cana-660	212	5	subset	subset	NOUN
cana-660	212	6	selection	selection	NOUN
cana-660	212	7	method	method	NOUN
cana-660	212	8	perform	perform	VERB
cana-660	212	9	well	well	ADV
cana-660	212	10	as	as	ADP
cana-660	212	11	compare	compare	VERB
cana-660	212	12	to	to	ADP
cana-660	212	13	existing	exist	VERB
cana-660	212	14	algorithms	algorithm	NOUN
cana-660	212	15	mentioned	mention	VERB
cana-660	212	16	in	in	ADP
cana-660	212	17	above	above	ADP
cana-660	212	18	also	also	ADV
cana-660	212	19	details	detail	NOUN
cana-660	212	20	available	available	ADJ
cana-660	212	21	in	in	ADP
cana-660	212	22	the	the	DET
cana-660	212	23	graph	graph	NOUN
cana-660	212	24	as	as	ADP
cana-660	212	25	well.our	well.our	NOUN
cana-660	212	26	proposed	propose	VERB
cana-660	212	27	algorithm	algorithm	NOUN
cana-660	212	28	named	name	VERB
cana-660	212	29	as	as	ADP
cana-660	212	30	ha	ha	PROPN
cana-660	212	31	algorithm	algorithm	PROPN
cana-660	212	32	.	.	PUNCT
cana-660	213	1	(	(	PUNCT
cana-660	213	2	a	a	X
cana-660	213	3	)	)	PUNCT
cana-660	213	4	(	(	PUNCT
cana-660	213	5	b	b	X
cana-660	213	6	)	)	PUNCT
cana-660	213	7	(	(	PUNCT
cana-660	213	8	c	c	X
cana-660	213	9	)	)	PUNCT
cana-660	213	10	(	(	PUNCT
cana-660	213	11	d	d	X
cana-660	213	12	)	)	PUNCT
cana-660	213	13	fig5	fig5	NOUN
cana-660	213	14	:	:	PUNCT
cana-660	213	15	ndcg@10	ndcg@10	VERB
cana-660	213	16	score	score	NOUN
cana-660	213	17	comparison	comparison	NOUN
cana-660	213	18	on	on	ADP
cana-660	213	19	different	different	ADJ
cana-660	213	20	dataset	dataset	NOUN
cana-660	213	21	.	.	PUNCT
cana-660	214	1	we	we	PRON
cana-660	214	2	compare	compare	VERB
cana-660	214	3	the	the	DET
cana-660	214	4	prediction	prediction	NOUN
cana-660	214	5	of	of	ADP
cana-660	214	6	our	our	PRON
cana-660	214	7	proposed	propose	VERB
cana-660	214	8	frameworks	framework	NOUN
cana-660	214	9	against	against	ADP
cana-660	214	10	those	those	PRON
cana-660	214	11	of	of	ADP
cana-660	214	12	the	the	DET
cana-660	214	13	other	other	ADJ
cana-660	214	14	state	state	NOUN
cana-660	214	15	-	-	PUNCT
cana-660	214	16	of	of	ADP
cana-660	214	17	-	-	PUNCT
cana-660	214	18	the	the	DET
cana-660	214	19	-	-	PUNCT
cana-660	214	20	art	art	NOUN
cana-660	214	21	algorithm	algorithm	NOUN
cana-660	214	22	ranknet[6	ranknet[6	NOUN
cana-660	214	23	]	]	SYM
cana-660	214	24	,	,	PUNCT
cana-660	214	25	lambdanet	lambdanet	NOUN
cana-660	214	26	,	,	PUNCT
cana-660	214	27	lambdamart[3	lambdamart[3	PROPN
cana-660	214	28	]	]	X
cana-660	214	29	,	,	PUNCT
cana-660	214	30	fsmrank[10	fsmrank[10	X
cana-660	214	31	]	]	PUNCT
cana-660	214	32	.	.	PUNCT
cana-660	215	1	figure	figure	NOUN
cana-660	215	2	5	5	NUM
cana-660	215	3	represent	represent	VERB
cana-660	215	4	ndcg@10	ndcg@10	NOUN
cana-660	215	5	score	score	NOUN
cana-660	215	6	of	of	ADP
cana-660	215	7	each	each	DET
cana-660	215	8	algorithm	algorithm	NOUN
cana-660	215	9	with	with	ADP
cana-660	215	10	proposed	propose	VERB
cana-660	215	11	method	method	NOUN
cana-660	215	12	.	.	PUNCT
cana-660	216	1	we	we	PRON
cana-660	216	2	can	can	AUX
cana-660	216	3	notice	notice	VERB
cana-660	216	4	that	that	SCONJ
cana-660	216	5	proposed	propose	VERB
cana-660	216	6	algorithm	algorithm	NOUN
cana-660	216	7	perform	perform	VERB
cana-660	216	8	well	well	ADV
cana-660	216	9	in	in	ADP
cana-660	216	10	all	all	DET
cana-660	216	11	selected	select	VERB
cana-660	216	12	database	database	NOUN
cana-660	216	13	.	.	PUNCT
cana-660	217	1	fig	fig	NOUN
cana-660	217	2	5(a	5(a	NUM
cana-660	217	3	)	)	PUNCT
cana-660	217	4	represents	represent	VERB
cana-660	217	5	the	the	DET
cana-660	217	6	comparison	comparison	NOUN
cana-660	217	7	for	for	ADP
cana-660	217	8	mq2007	mq2007	NOUN
cana-660	217	9	.	.	PUNCT
cana-660	218	1	mq2008	mq2008	NOUN
cana-660	218	2	,	,	PUNCT
cana-660	218	3	mslr10k	mslr10k	NOUN
cana-660	218	4	and	and	CCONJ
cana-660	218	5	mslr30k	mslr30k	ADJ
cana-660	218	6	comparison	comparison	NOUN
cana-660	218	7	provided	provide	VERB
cana-660	218	8	in	in	ADP
cana-660	218	9	figure	figure	NOUN
cana-660	218	10	number	number	NOUN
cana-660	218	11	5(b),5(c),5(d	5(b),5(c),5(d	PROPN
cana-660	218	12	)	)	PUNCT
cana-660	218	13	respectively	respectively	ADV
cana-660	218	14	.	.	PUNCT
cana-660	219	1	communications	communication	NOUN
cana-660	219	2	on	on	ADP
cana-660	219	3	applied	apply	VERB
cana-660	219	4	nonlinear	nonlinear	ADJ
cana-660	219	5	analysis	analysis	NOUN
cana-660	219	6	issn	issn	NOUN
cana-660	219	7	:	:	PUNCT
cana-660	219	8	1074	1074	NUM
cana-660	219	9	-	-	PUNCT
cana-660	219	10	133x	133x	NUM
cana-660	219	11	vol	vol	NOUN
cana-660	219	12	31	31	NUM
cana-660	219	13	no	no	NOUN
cana-660	219	14	.	.	PUNCT
cana-660	220	1	2s	2s	NUM
cana-660	220	2	(	(	PUNCT
cana-660	220	3	2024	2024	NUM
cana-660	220	4	)	)	PUNCT
cana-660	220	5	466	466	NUM
cana-660	220	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	220	7	(	(	PUNCT
cana-660	220	8	a	a	NOUN
cana-660	220	9	)	)	PUNCT
cana-660	220	10	(	(	PUNCT
cana-660	220	11	b	b	X
cana-660	220	12	)	)	PUNCT
cana-660	220	13	(	(	PUNCT
cana-660	220	14	c	c	X
cana-660	220	15	)	)	PUNCT
cana-660	220	16	(	(	PUNCT
cana-660	220	17	d	d	X
cana-660	220	18	)	)	PUNCT
cana-660	220	19	fig6	fig6	ADJ
cana-660	220	20	:	:	PUNCT
cana-660	220	21	performance	performance	NOUN
cana-660	220	22	evaluation	evaluation	NOUN
cana-660	220	23	with	with	ADP
cana-660	220	24	all	all	DET
cana-660	220	25	matrix	matrix	NOUN
cana-660	220	26	after	after	ADP
cana-660	220	27	comparison	comparison	NOUN
cana-660	220	28	of	of	ADP
cana-660	220	29	with	with	ADP
cana-660	220	30	ndcg@10	ndcg@10	NOUN
cana-660	220	31	,	,	PUNCT
cana-660	220	32	all	all	DET
cana-660	220	33	algorithms	algorithm	NOUN
cana-660	220	34	are	be	AUX
cana-660	220	35	also	also	ADV
cana-660	220	36	comparing	compare	VERB
cana-660	220	37	with	with	ADP
cana-660	220	38	other	other	ADJ
cana-660	220	39	evaluation	evaluation	NOUN
cana-660	220	40	parameters	parameter	NOUN
cana-660	220	41	such	such	ADJ
cana-660	220	42	as	as	ADP
cana-660	220	43	p@10	p@10	NOUN
cana-660	220	44	,	,	PUNCT
cana-660	220	45	map	map	NOUN
cana-660	220	46	.	.	PUNCT
cana-660	221	1	based	base	VERB
cana-660	221	2	on	on	ADP
cana-660	221	3	improved	improved	ADJ
cana-660	221	4	performance	performance	NOUN
cana-660	221	5	above	above	ADP
cana-660	221	6	model	model	NOUN
cana-660	221	7	is	be	AUX
cana-660	221	8	applied	apply	VERB
cana-660	221	9	on	on	ADP
cana-660	221	10	all	all	DET
cana-660	221	11	detests	detest	NOUN
cana-660	221	12	mention	mention	NOUN
cana-660	221	13	with	with	ADP
cana-660	221	14	all	all	DET
cana-660	221	15	fold	fold	ADJ
cana-660	221	16	and	and	CCONJ
cana-660	221	17	also	also	ADV
cana-660	221	18	evacuated	evacuate	VERB
cana-660	221	19	on	on	ADP
cana-660	221	20	all	all	DET
cana-660	221	21	the	the	DET
cana-660	221	22	parameters	parameter	NOUN
cana-660	221	23	.	.	PUNCT
cana-660	222	1	5.1	5.1	NUM
cana-660	222	2	map	map	NOUN
cana-660	222	3	analysis	analysis	NOUN
cana-660	222	4	:	:	PUNCT
cana-660	222	5	in	in	ADP
cana-660	222	6	figure6	figure6	NOUN
cana-660	222	7	map	map	NOUN
cana-660	222	8	values	value	NOUN
cana-660	222	9	of	of	ADP
cana-660	222	10	evaluation	evaluation	NOUN
cana-660	222	11	are	be	AUX
cana-660	222	12	better	well	ADJ
cana-660	222	13	perform	perform	VERB
cana-660	222	14	where	where	SCONJ
cana-660	222	15	two	two	NUM
cana-660	222	16	relevance	relevance	NOUN
cana-660	222	17	score	score	NOUN
cana-660	222	18	are	be	AUX
cana-660	222	19	mentioned	mention	VERB
cana-660	222	20	.	.	PUNCT
cana-660	223	1	by	by	ADP
cana-660	223	2	using	use	VERB
cana-660	223	3	our	our	PRON
cana-660	223	4	architecture	architecture	NOUN
cana-660	223	5	we	we	PRON
cana-660	223	6	match	match	VERB
cana-660	223	7	the	the	DET
cana-660	223	8	relevance	relevance	NOUN
cana-660	223	9	appropriately	appropriately	ADV
cana-660	223	10	and	and	CCONJ
cana-660	223	11	find	find	VERB
cana-660	223	12	the	the	DET
cana-660	223	13	evaluation	evaluation	NOUN
cana-660	223	14	of	of	ADP
cana-660	223	15	proposed	propose	VERB
cana-660	223	16	model	model	NOUN
cana-660	223	17	.	.	PUNCT
cana-660	224	1	in	in	ADP
cana-660	224	2	mq2007	mq2007	PROPN
cana-660	224	3	and	and	CCONJ
cana-660	224	4	mq2008	mq2008	NOUN
cana-660	224	5	the	the	DET
cana-660	224	6	map	map	NOUN
cana-660	224	7	values	value	NOUN
cana-660	224	8	are	be	AUX
cana-660	224	9	less	less	ADJ
cana-660	224	10	and	and	CCONJ
cana-660	224	11	mslr	mslr	ADJ
cana-660	224	12	web	web	NOUN
cana-660	224	13	10k	10k	NOUN
cana-660	224	14	and	and	CCONJ
cana-660	224	15	mslr	mslr	ADJ
cana-660	224	16	web	web	NOUN
cana-660	224	17	10k	10k	NOUN
cana-660	224	18	the	the	DET
cana-660	224	19	values	value	NOUN
cana-660	224	20	are	be	AUX
cana-660	224	21	more	more	ADJ
cana-660	224	22	.	.	PUNCT
cana-660	225	1	amongst	amongst	ADP
cana-660	225	2	all	all	DET
cana-660	225	3	the	the	DET
cana-660	225	4	baseline	baseline	ADJ
cana-660	225	5	algorithms	algorithm	NOUN
cana-660	225	6	shown	show	VERB
cana-660	225	7	in	in	ADP
cana-660	225	8	diagram	diagram	NOUN
cana-660	225	9	indicates	indicate	VERB
cana-660	225	10	that	that	SCONJ
cana-660	225	11	the	the	DET
cana-660	225	12	performance	performance	NOUN
cana-660	225	13	of	of	ADP
cana-660	225	14	ranking	ranking	NOUN
cana-660	225	15	is	be	AUX
cana-660	225	16	improved	improve	VERB
cana-660	225	17	.	.	PUNCT
cana-660	226	1	dimension	dimension	NOUN
cana-660	226	2	reduction	reduction	NOUN
cana-660	226	3	and	and	CCONJ
cana-660	226	4	regulation	regulation	NOUN
cana-660	226	5	improve	improve	VERB
cana-660	226	6	the	the	DET
cana-660	226	7	results	result	NOUN
cana-660	226	8	.	.	PUNCT
cana-660	227	1	approximately	approximately	ADV
cana-660	227	2	(	(	PUNCT
cana-660	227	3	8	8	NUM
cana-660	227	4	%	%	NOUN
cana-660	227	5	)	)	PUNCT
cana-660	227	6	map	map	NOUN
cana-660	227	7	improvement	improvement	NOUN
cana-660	227	8	are	be	AUX
cana-660	227	9	visible	visible	ADJ
cana-660	227	10	in	in	ADP
cana-660	227	11	the	the	DET
cana-660	227	12	results	result	NOUN
cana-660	227	13	also	also	ADV
cana-660	227	14	show	show	VERB
cana-660	227	15	.	.	PUNCT
cana-660	228	1	5.2	5.2	NUM
cana-660	228	2	ndcg@n	ndcg@n	NOUN
cana-660	228	3	analysis	analysis	NOUN
cana-660	228	4	:	:	PUNCT
cana-660	228	5	in	in	ADP
cana-660	228	6	figure	figure	NOUN
cana-660	228	7	6	6	NUM
cana-660	228	8	evaluation	evaluation	NOUN
cana-660	228	9	shown	show	VERB
cana-660	228	10	on	on	ADP
cana-660	228	11	ndcg@10	ndcg@10	NOUN
cana-660	228	12	for	for	ADP
cana-660	228	13	only	only	ADV
cana-660	228	14	mslr	mslr	ADJ
cana-660	228	15	web	web	NOUN
cana-660	228	16	10k	10k	NOUN
cana-660	228	17	data	datum	NOUN
cana-660	228	18	.	.	PUNCT
cana-660	229	1	in	in	ADP
cana-660	229	2	figure	figure	NOUN
cana-660	229	3	6	6	NUM
cana-660	229	4	the	the	DET
cana-660	229	5	analysis	analysis	NOUN
cana-660	229	6	shown	show	VERB
cana-660	229	7	in	in	ADP
cana-660	229	8	all	all	DET
cana-660	229	9	the	the	DET
cana-660	229	10	mentioned	mention	VERB
cana-660	229	11	data	datum	NOUN
cana-660	229	12	where	where	SCONJ
cana-660	229	13	many	many	ADJ
cana-660	229	14	up	up	ADP
cana-660	229	15	-	-	PUNCT
cana-660	229	16	gradation	gradation	NOUN
cana-660	229	17	and	and	CCONJ
cana-660	229	18	degradation	degradation	NOUN
cana-660	229	19	were	be	AUX
cana-660	229	20	visible	visible	ADJ
cana-660	229	21	.	.	PUNCT
cana-660	230	1	in	in	ADP
cana-660	230	2	non	non	PRON
cana-660	230	3	evolutionary	evolutionary	ADJ
cana-660	230	4	category	category	NOUN
cana-660	230	5	the	the	DET
cana-660	230	6	ndcg@10	ndcg@10	PROPN
cana-660	230	7	values	value	NOUN
cana-660	230	8	are	be	AUX
cana-660	230	9	less	less	ADJ
cana-660	230	10	in	in	ADP
cana-660	230	11	other	other	ADJ
cana-660	230	12	case	case	NOUN
cana-660	230	13	it	it	PRON
cana-660	230	14	is	be	AUX
cana-660	230	15	increased	increase	VERB
cana-660	230	16	.	.	PUNCT
cana-660	231	1	communications	communication	NOUN
cana-660	231	2	on	on	ADP
cana-660	231	3	applied	apply	VERB
cana-660	231	4	nonlinear	nonlinear	ADJ
cana-660	231	5	analysis	analysis	NOUN
cana-660	231	6	issn	issn	NOUN
cana-660	231	7	:	:	PUNCT
cana-660	231	8	1074	1074	NUM
cana-660	231	9	-	-	PUNCT
cana-660	231	10	133x	133x	NUM
cana-660	231	11	vol	vol	NOUN
cana-660	231	12	31	31	NUM
cana-660	231	13	no	no	NOUN
cana-660	231	14	.	.	PUNCT
cana-660	232	1	2s	2s	NUM
cana-660	232	2	(	(	PUNCT
cana-660	232	3	2024	2024	NUM
cana-660	232	4	)	)	PUNCT
cana-660	232	5	467	467	NUM
cana-660	232	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	232	7	in	in	ADP
cana-660	232	8	evolutionary	evolutionary	ADJ
cana-660	232	9	category	category	NOUN
cana-660	232	10	the	the	DET
cana-660	232	11	performance	performance	NOUN
cana-660	232	12	were	be	AUX
cana-660	232	13	increased	increase	VERB
cana-660	232	14	in	in	ADP
cana-660	232	15	all	all	DET
cana-660	232	16	the	the	DET
cana-660	232	17	database	database	NOUN
cana-660	232	18	.	.	PUNCT
cana-660	233	1	various	various	ADJ
cana-660	233	2	of	of	ADP
cana-660	233	3	performance	performance	NOUN
cana-660	233	4	is	be	AUX
cana-660	233	5	clearly	clearly	ADV
cana-660	233	6	visible	visible	ADJ
cana-660	233	7	in	in	ADP
cana-660	233	8	mq2007	mq2007	NOUN
cana-660	233	9	and	and	CCONJ
cana-660	233	10	mq2008	mq2008	NOUN
cana-660	233	11	but	but	CCONJ
cana-660	233	12	for	for	ADP
cana-660	233	13	mslr	mslr	ADJ
cana-660	233	14	databases	database	NOUN
cana-660	233	15	in	in	ADP
cana-660	233	16	it	it	PRON
cana-660	233	17	slightly	slightly	ADV
cana-660	233	18	improved	improve	VERB
cana-660	233	19	.	.	PUNCT
cana-660	234	1	approximately	approximately	ADV
cana-660	234	2	(	(	PUNCT
cana-660	234	3	3	3	NUM
cana-660	234	4	to	to	PART
cana-660	234	5	4	4	NUM
cana-660	234	6	%	%	NOUN
cana-660	234	7	)	)	PUNCT
cana-660	234	8	improvement	improvement	NOUN
cana-660	234	9	are	be	AUX
cana-660	234	10	visible	visible	ADJ
cana-660	234	11	in	in	ADP
cana-660	234	12	the	the	DET
cana-660	234	13	results	result	NOUN
cana-660	234	14	.	.	PUNCT
cana-660	235	1	but	but	CCONJ
cana-660	235	2	in	in	ADP
cana-660	235	3	case	case	NOUN
cana-660	235	4	letor	letor	NOUN
cana-660	235	5	3	3	NUM
cana-660	235	6	and	and	CCONJ
cana-660	235	7	4	4	NUM
cana-660	235	8	the	the	DET
cana-660	235	9	improvement	improvement	NOUN
cana-660	235	10	is	be	AUX
cana-660	235	11	around	around	ADV
cana-660	235	12	(	(	PUNCT
cana-660	235	13	10	10	NUM
cana-660	235	14	%	%	NOUN
cana-660	235	15	)	)	PUNCT
cana-660	235	16	.	.	PUNCT
cana-660	236	1	5.3.p@10	5.3.p@10	NUM
cana-660	236	2	analysis	analysis	NOUN
cana-660	236	3	in	in	ADP
cana-660	236	4	figure	figure	NOUN
cana-660	236	5	6	6	NUM
cana-660	236	6	the	the	DET
cana-660	236	7	analysis	analysis	NOUN
cana-660	236	8	shown	show	VERB
cana-660	236	9	in	in	ADP
cana-660	236	10	all	all	DET
cana-660	236	11	the	the	DET
cana-660	236	12	mentioned	mention	VERB
cana-660	236	13	data	datum	NOUN
cana-660	236	14	where	where	SCONJ
cana-660	236	15	many	many	ADJ
cana-660	236	16	changes	change	NOUN
cana-660	236	17	in	in	ADP
cana-660	236	18	evaluation	evaluation	NOUN
cana-660	236	19	measures	measure	NOUN
cana-660	236	20	was	be	AUX
cana-660	236	21	found	find	VERB
cana-660	236	22	were	be	AUX
cana-660	236	23	visible	visible	ADJ
cana-660	236	24	.	.	PUNCT
cana-660	237	1	in	in	ADP
cana-660	237	2	non	non	PRON
cana-660	237	3	evolutionary	evolutionary	ADJ
cana-660	237	4	category	category	NOUN
cana-660	237	5	the	the	DET
cana-660	237	6	p@10	p@10	NUM
cana-660	237	7	values	value	NOUN
cana-660	237	8	are	be	AUX
cana-660	237	9	less	less	ADJ
cana-660	237	10	in	in	ADP
cana-660	237	11	other	other	ADJ
cana-660	237	12	case	case	NOUN
cana-660	237	13	it	it	PRON
cana-660	237	14	is	be	AUX
cana-660	237	15	increased	increase	VERB
cana-660	237	16	.	.	PUNCT
cana-660	238	1	in	in	ADP
cana-660	238	2	evolutionary	evolutionary	ADJ
cana-660	238	3	category	category	NOUN
cana-660	238	4	the	the	DET
cana-660	238	5	performance	performance	NOUN
cana-660	238	6	were	be	AUX
cana-660	238	7	increased	increase	VERB
cana-660	238	8	in	in	ADP
cana-660	238	9	all	all	DET
cana-660	238	10	the	the	DET
cana-660	238	11	database	database	NOUN
cana-660	238	12	.	.	PUNCT
cana-660	239	1	various	various	ADJ
cana-660	239	2	of	of	ADP
cana-660	239	3	performance	performance	NOUN
cana-660	239	4	is	be	AUX
cana-660	239	5	clearly	clearly	ADV
cana-660	239	6	visible	visible	ADJ
cana-660	239	7	in	in	ADP
cana-660	239	8	mq2007	mq2007	NOUN
cana-660	239	9	and	and	CCONJ
cana-660	239	10	mq2008	mq2008	NOUN
cana-660	239	11	but	but	CCONJ
cana-660	239	12	for	for	ADP
cana-660	239	13	mslr	mslr	ADJ
cana-660	239	14	databases	database	NOUN
cana-660	239	15	in	in	ADP
cana-660	239	16	it	it	PRON
cana-660	239	17	slightly	slightly	ADV
cana-660	239	18	improved	improve	VERB
cana-660	239	19	.	.	PUNCT
cana-660	240	1	approximately	approximately	ADV
cana-660	240	2	(	(	PUNCT
cana-660	240	3	2	2	NUM
cana-660	240	4	to	to	PART
cana-660	240	5	3	3	NUM
cana-660	240	6	%	%	NOUN
cana-660	240	7	)	)	PUNCT
cana-660	240	8	improvement	improvement	NOUN
cana-660	240	9	are	be	AUX
cana-660	240	10	visible	visible	ADJ
cana-660	240	11	in	in	ADP
cana-660	240	12	the	the	DET
cana-660	240	13	results	result	NOUN
cana-660	240	14	.	.	PUNCT
cana-660	241	1	but	but	CCONJ
cana-660	241	2	in	in	ADP
cana-660	241	3	case	case	NOUN
cana-660	241	4	letor	letor	NOUN
cana-660	241	5	3	3	NUM
cana-660	241	6	and	and	CCONJ
cana-660	241	7	4	4	NUM
cana-660	241	8	the	the	DET
cana-660	241	9	improvement	improvement	NOUN
cana-660	241	10	is	be	AUX
cana-660	241	11	around	around	ADV
cana-660	241	12	(	(	PUNCT
cana-660	241	13	15	15	NUM
cana-660	241	14	%	%	NOUN
cana-660	241	15	)	)	PUNCT
cana-660	241	16	.	.	PUNCT
cana-660	242	1	6.discussion	6.discussion	NUM
cana-660	242	2	in	in	ADP
cana-660	242	3	the	the	DET
cana-660	242	4	above	above	ADJ
cana-660	242	5	sections	section	NOUN
cana-660	242	6	,	,	PUNCT
cana-660	242	7	we	we	PRON
cana-660	242	8	have	have	AUX
cana-660	242	9	discussed	discuss	VERB
cana-660	242	10	the	the	DET
cana-660	242	11	proposed	propose	VERB
cana-660	242	12	model	model	NOUN
cana-660	242	13	and	and	CCONJ
cana-660	242	14	its	its	PRON
cana-660	242	15	results	result	NOUN
cana-660	242	16	on	on	ADP
cana-660	242	17	benchmark	benchmark	ADJ
cana-660	242	18	datasets	dataset	NOUN
cana-660	242	19	.	.	PUNCT
cana-660	243	1	the	the	DET
cana-660	243	2	performance	performance	NOUN
cana-660	243	3	feature	feature	NOUN
cana-660	243	4	selection	selection	NOUN
cana-660	243	5	using	use	VERB
cana-660	243	6	the	the	DET
cana-660	243	7	heuristic	heuristic	ADJ
cana-660	243	8	approach	approach	NOUN
cana-660	243	9	method	method	NOUN
cana-660	243	10	outperforms	outperform	VERB
cana-660	243	11	the	the	DET
cana-660	243	12	other	other	ADJ
cana-660	243	13	methods	method	NOUN
cana-660	243	14	,	,	PUNCT
cana-660	243	15	which	which	PRON
cana-660	243	16	were	be	AUX
cana-660	243	17	compared	compare	VERB
cana-660	243	18	in	in	ADP
cana-660	243	19	the	the	DET
cana-660	243	20	results	result	NOUN
cana-660	243	21	.	.	PUNCT
cana-660	244	1	the	the	DET
cana-660	244	2	proposed	propose	VERB
cana-660	244	3	model	model	NOUN
cana-660	244	4	utilized	utilize	VERB
cana-660	244	5	optimization	optimization	NOUN
cana-660	244	6	as	as	ADP
cana-660	244	7	a	a	DET
cana-660	244	8	tool	tool	NOUN
cana-660	244	9	for	for	ADP
cana-660	244	10	feature	feature	NOUN
cana-660	244	11	selection	selection	NOUN
cana-660	244	12	.	.	PUNCT
cana-660	245	1	in	in	ADP
cana-660	245	2	the	the	DET
cana-660	245	3	complete	complete	ADJ
cana-660	245	4	system	system	NOUN
cana-660	245	5	,	,	PUNCT
cana-660	245	6	there	there	PRON
cana-660	245	7	is	be	VERB
cana-660	245	8	more	more	ADJ
cana-660	245	9	concern	concern	NOUN
cana-660	245	10	about	about	ADP
cana-660	245	11	the	the	DET
cana-660	245	12	relevance	relevance	NOUN
cana-660	245	13	of	of	ADP
cana-660	245	14	the	the	DET
cana-660	245	15	document	document	NOUN
cana-660	245	16	within	within	ADP
cana-660	245	17	the	the	DET
cana-660	245	18	subset	subset	NOUN
cana-660	245	19	so	so	SCONJ
cana-660	245	20	that	that	SCONJ
cana-660	245	21	we	we	PRON
cana-660	245	22	can	can	AUX
cana-660	245	23	obtain	obtain	VERB
cana-660	245	24	an	an	DET
cana-660	245	25	acceptable	acceptable	ADJ
cana-660	245	26	subset	subset	NOUN
cana-660	245	27	for	for	ADP
cana-660	245	28	learning	learn	VERB
cana-660	245	29	to	to	PART
cana-660	245	30	rank	rank	VERB
cana-660	245	31	.	.	PUNCT
cana-660	246	1	by	by	ADP
cana-660	246	2	finding	find	VERB
cana-660	246	3	the	the	DET
cana-660	246	4	optimized	optimized	ADJ
cana-660	246	5	k	k	PROPN
cana-660	246	6	value	value	NOUN
cana-660	246	7	,	,	PUNCT
cana-660	246	8	the	the	DET
cana-660	246	9	evolutionary	evolutionary	ADJ
cana-660	246	10	process	process	NOUN
cana-660	246	11	is	be	AUX
cana-660	246	12	completed	complete	VERB
cana-660	246	13	fewer	few	ADJ
cana-660	246	14	times	time	NOUN
cana-660	246	15	with	with	ADP
cana-660	246	16	an	an	DET
cana-660	246	17	improvement	improvement	NOUN
cana-660	246	18	in	in	ADP
cana-660	246	19	the	the	DET
cana-660	246	20	ranking	ranking	NOUN
cana-660	246	21	.	.	PUNCT
cana-660	247	1	figure	figure	NOUN
cana-660	247	2	7	7	NUM
cana-660	247	3	shows	show	VERB
cana-660	247	4	the	the	DET
cana-660	247	5	results	result	NOUN
cana-660	247	6	of	of	ADP
cana-660	247	7	the	the	DET
cana-660	247	8	ndcg	ndcg	PROPN
cana-660	247	9	measurements	measurement	NOUN
cana-660	247	10	only	only	ADV
cana-660	247	11	.	.	PUNCT
cana-660	248	1	after	after	ADP
cana-660	248	2	improvement	improvement	NOUN
cana-660	248	3	,	,	PUNCT
cana-660	248	4	the	the	DET
cana-660	248	5	remaining	remain	VERB
cana-660	248	6	rankings	ranking	NOUN
cana-660	248	7	were	be	AUX
cana-660	248	8	calculated	calculate	VERB
cana-660	248	9	with	with	ADP
cana-660	248	10	ranknet	ranknet	NOUN
cana-660	248	11	,	,	PUNCT
cana-660	248	12	lamdanet	lamdanet	NOUN
cana-660	248	13	,	,	PUNCT
cana-660	248	14	and	and	CCONJ
cana-660	248	15	lamdamart	lamdamart	NOUN
cana-660	248	16	via	via	ADP
cana-660	248	17	one	one	NUM
cana-660	248	18	evolutionary	evolutionary	ADJ
cana-660	248	19	algorithm	algorithm	NOUN
cana-660	248	20	,	,	PUNCT
cana-660	248	21	fsm	fsm	PROPN
cana-660	248	22	rannk	rannk	NOUN
cana-660	248	23	.	.	PUNCT
cana-660	249	1	the	the	DET
cana-660	249	2	first	first	ADJ
cana-660	249	3	three	three	NUM
cana-660	249	4	algorithms	algorithm	NOUN
cana-660	249	5	are	be	AUX
cana-660	249	6	non	non	X
cana-660	249	7	evolutionary	evolutionary	ADJ
cana-660	249	8	algorithms	algorithm	NOUN
cana-660	249	9	,	,	PUNCT
cana-660	249	10	and	and	CCONJ
cana-660	249	11	the	the	DET
cana-660	249	12	last	last	ADJ
cana-660	249	13	one	one	NOUN
cana-660	249	14	is	be	AUX
cana-660	249	15	an	an	DET
cana-660	249	16	evolutionary	evolutionary	ADJ
cana-660	249	17	algorithm	algorithm	NOUN
cana-660	249	18	.	.	PUNCT
cana-660	250	1	figure	figure	NOUN
cana-660	250	2	8	8	NUM
cana-660	250	3	shows	show	VERB
cana-660	250	4	the	the	DET
cana-660	250	5	comparisons	comparison	NOUN
cana-660	250	6	of	of	ADP
cana-660	250	7	all	all	DET
cana-660	250	8	the	the	DET
cana-660	250	9	measures	measure	NOUN
cana-660	250	10	.	.	PUNCT
cana-660	251	1	as	as	SCONJ
cana-660	251	2	the	the	DET
cana-660	251	3	first	first	ADJ
cana-660	251	4	subset	subset	NOUN
cana-660	251	5	is	be	AUX
cana-660	251	6	found	find	VERB
cana-660	251	7	,	,	PUNCT
cana-660	251	8	ltr	ltr	PROPN
cana-660	251	9	is	be	AUX
cana-660	251	10	used	use	VERB
cana-660	251	11	in	in	ADP
cana-660	251	12	most	most	ADJ
cana-660	251	13	of	of	ADP
cana-660	251	14	the	the	DET
cana-660	251	15	cases	case	NOUN
cana-660	251	16	in	in	ADP
cana-660	251	17	which	which	PRON
cana-660	251	18	improved	improve	VERB
cana-660	251	19	results	result	NOUN
cana-660	251	20	are	be	AUX
cana-660	251	21	shown	show	VERB
cana-660	251	22	.	.	PUNCT
cana-660	252	1	no	no	DET
cana-660	252	2	changes	change	NOUN
cana-660	252	3	in	in	ADP
cana-660	252	4	the	the	DET
cana-660	252	5	mslr	mslr	ADJ
cana-660	252	6	web10k	web10k	NOUN
cana-660	252	7	algorithm	algorithm	NOUN
cana-660	252	8	were	be	AUX
cana-660	252	9	detected	detect	VERB
cana-660	252	10	for	for	ADP
cana-660	252	11	p@k	p@k	NOUN
cana-660	252	12	or	or	CCONJ
cana-660	252	13	map	map	VERB
cana-660	252	14	.	.	PUNCT
cana-660	253	1	the	the	DET
cana-660	253	2	remaining	remain	VERB
cana-660	253	3	cases	case	NOUN
cana-660	253	4	were	be	AUX
cana-660	253	5	improved	improve	VERB
cana-660	253	6	on	on	ADP
cana-660	253	7	each	each	DET
cana-660	253	8	dataset	dataset	NOUN
cana-660	253	9	.	.	PUNCT
cana-660	254	1	according	accord	VERB
cana-660	254	2	to	to	ADP
cana-660	254	3	the	the	DET
cana-660	254	4	below	below	ADJ
cana-660	254	5	diagram	diagram	NOUN
cana-660	254	6	,	,	PUNCT
cana-660	254	7	the	the	DET
cana-660	254	8	performance	performance	NOUN
cana-660	254	9	of	of	ADP
cana-660	254	10	the	the	DET
cana-660	254	11	proposed	propose	VERB
cana-660	254	12	model	model	NOUN
cana-660	254	13	increases	increase	NOUN
cana-660	254	14	in	in	ADP
cana-660	254	15	the	the	DET
cana-660	254	16	matrix	matrix	NOUN
cana-660	254	17	of	of	ADP
cana-660	254	18	ndcg	ndcg	NOUN
cana-660	254	19	and	and	CCONJ
cana-660	254	20	map	map	NOUN
cana-660	254	21	.	.	PUNCT
cana-660	255	1	however	however	ADV
cana-660	255	2	,	,	PUNCT
cana-660	255	3	the	the	DET
cana-660	255	4	p@10	p@10	NUM
cana-660	255	5	values	value	NOUN
cana-660	255	6	vary	vary	VERB
cana-660	255	7	with	with	ADP
cana-660	255	8	the	the	DET
cana-660	255	9	subset	subset	NOUN
cana-660	255	10	value	value	NOUN
cana-660	255	11	.	.	PUNCT
cana-660	256	1	by	by	ADP
cana-660	256	2	changing	change	VERB
cana-660	256	3	the	the	DET
cana-660	256	4	probability	probability	NOUN
cana-660	256	5	function	function	NOUN
cana-660	256	6	,	,	PUNCT
cana-660	256	7	it	it	PRON
cana-660	256	8	will	will	AUX
cana-660	256	9	increase	increase	VERB
cana-660	256	10	.	.	PUNCT
cana-660	257	1	the	the	DET
cana-660	257	2	increasing	increase	VERB
cana-660	257	3	results	result	NOUN
cana-660	257	4	are	be	AUX
cana-660	257	5	shown	show	VERB
cana-660	257	6	in	in	ADP
cana-660	257	7	the	the	DET
cana-660	257	8	bellow	bellow	ADJ
cana-660	257	9	diagram	diagram	NOUN
cana-660	257	10	.	.	PUNCT
cana-660	258	1	communications	communication	NOUN
cana-660	258	2	on	on	ADP
cana-660	258	3	applied	apply	VERB
cana-660	258	4	nonlinear	nonlinear	ADJ
cana-660	258	5	analysis	analysis	NOUN
cana-660	258	6	issn	issn	NOUN
cana-660	258	7	:	:	PUNCT
cana-660	258	8	1074	1074	NUM
cana-660	258	9	-	-	PUNCT
cana-660	258	10	133x	133x	NUM
cana-660	258	11	vol	vol	NOUN
cana-660	258	12	31	31	NUM
cana-660	258	13	no	no	NOUN
cana-660	258	14	.	.	PUNCT
cana-660	259	1	2s	2s	NUM
cana-660	259	2	(	(	PUNCT
cana-660	259	3	2024	2024	NUM
cana-660	259	4	)	)	PUNCT
cana-660	259	5	468	468	NUM
cana-660	259	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	259	7	fig	fig	NOUN
cana-660	259	8	.	.	PUNCT
cana-660	260	1	9	9	X
cana-660	260	2	.	.	X
cana-660	260	3	performance	performance	NOUN
cana-660	260	4	of	of	ADP
cana-660	260	5	the	the	DET
cana-660	260	6	proposed	propose	VERB
cana-660	260	7	system	system	NOUN
cana-660	260	8	7.conclusion	7.conclusion	NUM
cana-660	260	9	in	in	ADP
cana-660	260	10	this	this	DET
cana-660	260	11	paper	paper	NOUN
cana-660	260	12	,	,	PUNCT
cana-660	260	13	we	we	PRON
cana-660	260	14	applied	apply	VERB
cana-660	260	15	an	an	DET
cana-660	260	16	evolutionary	evolutionary	ADJ
cana-660	260	17	method	method	NOUN
cana-660	260	18	that	that	PRON
cana-660	260	19	involved	involve	VERB
cana-660	260	20	hill	hill	NOUN
cana-660	260	21	climbing	climbing	NOUN
cana-660	260	22	and	and	CCONJ
cana-660	260	23	random	random	ADJ
cana-660	260	24	walk	walk	NOUN
cana-660	260	25	learning	learn	VERB
cana-660	260	26	with	with	ADP
cana-660	260	27	knn	knn	PROPN
cana-660	260	28	classification	classification	NOUN
cana-660	260	29	.	.	PUNCT
cana-660	261	1	we	we	PRON
cana-660	261	2	propose	propose	VERB
cana-660	261	3	a	a	DET
cana-660	261	4	hybrid	hybrid	ADJ
cana-660	261	5	model	model	NOUN
cana-660	261	6	that	that	PRON
cana-660	261	7	selects	select	VERB
cana-660	261	8	a	a	DET
cana-660	261	9	feature	feature	NOUN
cana-660	261	10	,	,	PUNCT
cana-660	261	11	optimizes	optimize	VERB
cana-660	261	12	it	it	PRON
cana-660	261	13	throughout	throughout	ADP
cana-660	261	14	the	the	DET
cana-660	261	15	process	process	NOUN
cana-660	261	16	,	,	PUNCT
cana-660	261	17	and	and	CCONJ
cana-660	261	18	outperforms	outperform	VERB
cana-660	261	19	existing	exist	VERB
cana-660	261	20	frameworks	framework	NOUN
cana-660	261	21	.	.	PUNCT
cana-660	262	1	simulated	simulate	VERB
cana-660	262	2	annealing	anneal	VERB
cana-660	262	3	using	use	VERB
cana-660	262	4	the	the	DET
cana-660	262	5	above	above	ADJ
cana-660	262	6	mentioned	mention	VERB
cana-660	262	7	techniques	technique	NOUN
cana-660	262	8	was	be	AUX
cana-660	262	9	employed	employ	VERB
cana-660	262	10	for	for	ADP
cana-660	262	11	feature	feature	NOUN
cana-660	262	12	selection	selection	NOUN
cana-660	262	13	,	,	PUNCT
cana-660	262	14	and	and	CCONJ
cana-660	262	15	l2	l2	NOUN
cana-660	262	16	regularization	regularization	NOUN
cana-660	262	17	was	be	AUX
cana-660	262	18	applied	apply	VERB
cana-660	262	19	for	for	ADP
cana-660	262	20	optimization	optimization	NOUN
cana-660	262	21	.	.	PUNCT
cana-660	263	1	we	we	PRON
cana-660	263	2	applied	apply	VERB
cana-660	263	3	this	this	DET
cana-660	263	4	process	process	NOUN
cana-660	263	5	to	to	ADP
cana-660	263	6	four	four	NUM
cana-660	263	7	standard	standard	ADJ
cana-660	263	8	datasets	dataset	NOUN
cana-660	263	9	.	.	PUNCT
cana-660	264	1	the	the	DET
cana-660	264	2	selection	selection	NOUN
cana-660	264	3	of	of	ADP
cana-660	264	4	active	active	ADJ
cana-660	264	5	features	feature	NOUN
cana-660	264	6	is	be	AUX
cana-660	264	7	based	base	VERB
cana-660	264	8	on	on	ADP
cana-660	264	9	the	the	DET
cana-660	264	10	activation	activation	NOUN
cana-660	264	11	function	function	NOUN
cana-660	264	12	of	of	ADP
cana-660	264	13	lamdamart	lamdamart	NOUN
cana-660	264	14	in	in	ADP
cana-660	264	15	each	each	DET
cana-660	264	16	iteration	iteration	NOUN
cana-660	264	17	until	until	SCONJ
cana-660	264	18	it	it	PRON
cana-660	264	19	reaches	reach	VERB
cana-660	264	20	the	the	DET
cana-660	264	21	convergence	convergence	NOUN
cana-660	264	22	state	state	NOUN
cana-660	264	23	.	.	PUNCT
cana-660	265	1	we	we	PRON
cana-660	265	2	compare	compare	VERB
cana-660	265	3	proposed	propose	VERB
cana-660	265	4	system	system	NOUN
cana-660	265	5	with	with	ADP
cana-660	265	6	ranknet	ranknet	NOUN
cana-660	265	7	,	,	PUNCT
cana-660	265	8	lamdanet	lamdanet	NOUN
cana-660	265	9	,	,	PUNCT
cana-660	265	10	lamdamart	lamdamart	NOUN
cana-660	265	11	algorithms	algorithm	NOUN
cana-660	265	12	which	which	PRON
cana-660	265	13	used	use	VERB
cana-660	265	14	optimization	optimization	NOUN
cana-660	265	15	techniques	technique	NOUN
cana-660	265	16	for	for	ADP
cana-660	265	17	proper	proper	ADJ
cana-660	265	18	subset	subset	NOUN
cana-660	265	19	creation	creation	NOUN
cana-660	265	20	and	and	CCONJ
cana-660	265	21	also	also	ADV
cana-660	265	22	with	with	ADP
cana-660	265	23	fsmrank	fsmrank	NOUN
cana-660	265	24	which	which	PRON
cana-660	265	25	is	be	AUX
cana-660	265	26	heuristics	heuristic	NOUN
cana-660	265	27	method	method	NOUN
cana-660	265	28	for	for	ADP
cana-660	265	29	learning	learn	VERB
cana-660	265	30	to	to	PART
cana-660	265	31	rank	rank	VERB
cana-660	265	32	.	.	PUNCT
cana-660	266	1	all	all	DET
cana-660	266	2	the	the	DET
cana-660	266	3	case	case	NOUN
cana-660	266	4	the	the	DET
cana-660	266	5	evaluation	evaluation	NOUN
cana-660	266	6	matrices	matrix	NOUN
cana-660	266	7	show	show	VERB
cana-660	266	8	the	the	DET
cana-660	266	9	improved	improved	ADJ
cana-660	266	10	results	result	NOUN
cana-660	266	11	.	.	PUNCT
cana-660	267	1	our	our	PRON
cana-660	267	2	findings	finding	NOUN
cana-660	267	3	concluded	conclude	VERB
cana-660	267	4	that	that	SCONJ
cana-660	267	5	optimization	optimization	NOUN
cana-660	267	6	techniques	technique	NOUN
cana-660	267	7	can	can	AUX
cana-660	267	8	also	also	ADV
cana-660	267	9	be	be	AUX
cana-660	267	10	used	use	VERB
cana-660	267	11	for	for	ADP
cana-660	267	12	feature	feature	NOUN
cana-660	267	13	selection	selection	NOUN
cana-660	267	14	.	.	PUNCT
cana-660	268	1	in	in	ADP
cana-660	268	2	the	the	DET
cana-660	268	3	future	future	NOUN
cana-660	268	4	,	,	PUNCT
cana-660	268	5	we	we	PRON
cana-660	268	6	can	can	AUX
cana-660	268	7	reduce	reduce	VERB
cana-660	268	8	the	the	DET
cana-660	268	9	dimensionality	dimensionality	NOUN
cana-660	268	10	of	of	ADP
cana-660	268	11	features	feature	NOUN
cana-660	268	12	to	to	PART
cana-660	268	13	increase	increase	VERB
cana-660	268	14	the	the	DET
cana-660	268	15	time	time	NOUN
cana-660	268	16	complexity	complexity	NOUN
cana-660	268	17	of	of	ADP
cana-660	268	18	ranking	ranking	NOUN
cana-660	268	19	.	.	PUNCT
cana-660	269	1	references	reference	NOUN
cana-660	269	2	[	[	X
cana-660	269	3	1	1	NUM
cana-660	269	4	]	]	X
cana-660	269	5	rahangdale	rahangdale	ADJ
cana-660	269	6	,	,	PUNCT
cana-660	269	7	ashwini	ashwini	NOUN
cana-660	269	8	,	,	PUNCT
cana-660	269	9	and	and	CCONJ
cana-660	269	10	shital	shital	PROPN
cana-660	269	11	raut	raut	PROPN
cana-660	269	12	.	.	PUNCT
cana-660	270	1	”	"	PUNCT
cana-660	270	2	deep	deep	ADJ
cana-660	270	3	neural	neural	ADJ
cana-660	270	4	network	network	NOUN
cana-660	270	5	regularization	regularization	NOUN
cana-660	270	6	for	for	ADP
cana-660	270	7	feature	feature	NOUN
cana-660	270	8	selection	selection	NOUN
cana-660	270	9	in	in	ADP
cana-660	270	10	learning	learning	NOUN
cana-660	270	11	-	-	PUNCT
cana-660	270	12	torank	torank	NOUN
cana-660	270	13	.	.	PUNCT
cana-660	270	14	”	"	PUNCT
cana-660	271	1	ieee	ieee	NOUN
cana-660	271	2	access	access	NOUN
cana-660	271	3	7	7	NUM
cana-660	271	4	(	(	PUNCT
cana-660	271	5	2019	2019	NUM
cana-660	271	6	):	):	PUNCT
cana-660	271	7	53988	53988	NUM
cana-660	271	8	-	-	SYM
cana-660	271	9	54006	54006	NUM
cana-660	271	10	.	.	PUNCT
cana-660	272	1	[	[	X
cana-660	272	2	2	2	X
cana-660	272	3	]	]	X
cana-660	272	4	mohd	mohd	PROPN
cana-660	272	5	wazih	wazih	PROPN
cana-660	272	6	ahmad	ahmad	PROPN
cana-660	272	7	,	,	PUNCT
cana-660	272	8	m.n	m.n	PROPN
cana-660	272	9	.	.	PROPN
cana-660	272	10	doja	doja	NOUN
cana-660	272	11	,	,	PUNCT
cana-660	272	12	tanvir	tanvir	PROPN
cana-660	272	13	ahmad	ahmad	PROPN
cana-660	272	14	,	,	PUNCT
cana-660	272	15	enumerative	enumerative	ADJ
cana-660	272	16	feature	feature	NOUN
cana-660	272	17	subset	subset	NOUN
cana-660	272	18	based	base	VERB
cana-660	272	19	ranking	ranking	NOUN
cana-660	272	20	system	system	NOUN
cana-660	272	21	for	for	ADP
cana-660	272	22	learning	learn	VERB
cana-660	272	23	to	to	PART
cana-660	272	24	rank	rank	VERB
cana-660	272	25	in	in	ADP
cana-660	272	26	presence	presence	NOUN
cana-660	272	27	of	of	ADP
cana-660	272	28	implicit	implicit	ADJ
cana-660	272	29	user	user	NOUN
cana-660	272	30	feedback	feedback	NOUN
cana-660	272	31	,	,	PUNCT
cana-660	272	32	journal	journal	NOUN
cana-660	272	33	of	of	ADP
cana-660	272	34	king	king	PROPN
cana-660	272	35	saud	saud	PROPN
cana-660	272	36	university	university	PROPN
cana-660	272	37	computer	computer	NOUN
cana-660	272	38	and	and	CCONJ
cana-660	272	39	information	information	NOUN
cana-660	272	40	sciences	science	NOUN
cana-660	272	41	,	,	PUNCT
cana-660	272	42	volume	volume	NOUN
cana-660	272	43	32	32	NUM
cana-660	272	44	,	,	PUNCT
cana-660	272	45	issue	issue	NOUN
cana-660	272	46	8,2020	8,2020	NUM
cana-660	272	47	,	,	PUNCT
cana-660	272	48	pages	page	VERB
cana-660	272	49	965	965	NUM
cana-660	272	50	-	-	SYM
cana-660	272	51	976	976	NUM
cana-660	272	52	.	.	PUNCT
cana-660	273	1	[	[	X
cana-660	273	2	3	3	NUM
cana-660	273	3	]	]	PUNCT
cana-660	273	4	chavhan	chavhan	PROPN
cana-660	273	5	,	,	PUNCT
cana-660	273	6	sushil	sushil	NOUN
cana-660	273	7	,	,	PUNCT
cana-660	273	8	raghuwanshi	raghuwanshi	PROPN
cana-660	273	9	,	,	PUNCT
cana-660	273	10	m	m	PRON
cana-660	273	11	,	,	PUNCT
cana-660	273	12	dharmik	dharmik	VERB
cana-660	273	13	,	,	PUNCT
cana-660	273	14	r.	r.	PROPN
cana-660	273	15	(	(	PUNCT
cana-660	273	16	2021	2021	NUM
cana-660	273	17	)	)	PUNCT
cana-660	273	18	.	.	PUNCT
cana-660	274	1	information	information	NOUN
cana-660	274	2	retrieval	retrieval	NOUN
cana-660	274	3	using	use	VERB
cana-660	274	4	machine	machine	NOUN
cana-660	274	5	learning	learning	NOUN
cana-660	274	6	for	for	ADP
cana-660	274	7	ranking	rank	VERB
cana-660	274	8	:	:	PUNCT
cana-660	274	9	a	a	DET
cana-660	274	10	review	review	NOUN
cana-660	274	11	.	.	PUNCT
cana-660	275	1	journal	journal	PROPN
cana-660	275	2	of	of	ADP
cana-660	275	3	physics	physics	PROPN
cana-660	275	4	:	:	PUNCT
cana-660	275	5	conference	conference	NOUN
cana-660	275	6	series	series	NOUN
cana-660	275	7	.	.	PUNCT
cana-660	276	1	1913	1913	NUM
cana-660	276	2	.	.	PUNCT
cana-660	277	1	01215	01215	NUM
cana-660	277	2	,	,	PUNCT
cana-660	277	3	2021	2021	NUM
cana-660	277	4	.	.	PUNCT
cana-660	278	1	[	[	X
cana-660	278	2	4	4	X
cana-660	278	3	]	]	X
cana-660	278	4	xiubo	xiubo	PROPN
cana-660	278	5	geng	geng	PROPN
cana-660	278	6	,	,	PUNCT
cana-660	278	7	tie	tie	NOUN
cana-660	278	8	-	-	PUNCT
cana-660	278	9	yan	yan	NOUN
cana-660	278	10	liu	liu	PROPN
cana-660	278	11	,	,	PUNCT
cana-660	278	12	tao	tao	PROPN
cana-660	278	13	qin	qin	PROPN
cana-660	278	14	,	,	PUNCT
cana-660	278	15	and	and	CCONJ
cana-660	278	16	hang	hang	VERB
cana-660	278	17	li	li	PROPN
cana-660	278	18	.	.	PROPN
cana-660	278	19	2007	2007	NUM
cana-660	278	20	.	.	PUNCT
cana-660	279	1	”	"	PUNCT
cana-660	279	2	feature	feature	NOUN
cana-660	279	3	selection	selection	NOUN
cana-660	279	4	for	for	ADP
cana-660	279	5	ranking	rank	VERB
cana-660	279	6	”	"	PUNCT
cana-660	279	7	.	.	PUNCT
cana-660	280	1	in	in	ADP
cana-660	280	2	proceedings	proceeding	NOUN
cana-660	280	3	of	of	ADP
cana-660	280	4	the	the	DET
cana-660	280	5	30th	30th	ADJ
cana-660	280	6	annual	annual	ADJ
cana-660	280	7	international	international	PROPN
cana-660	280	8	acm	acm	PROPN
cana-660	280	9	sigir	sigir	PROPN
cana-660	280	10	conference	conference	PROPN
cana-660	280	11	on	on	ADP
cana-660	280	12	research	research	NOUN
cana-660	280	13	and	and	CCONJ
cana-660	280	14	development	development	NOUN
cana-660	280	15	in	in	ADP
cana-660	280	16	information	information	NOUN
cana-660	280	17	retrieval	retrieval	NOUN
cana-660	280	18	(	(	PUNCT
cana-660	280	19	sigir	sigir	PROPN
cana-660	280	20	’	'	PUNCT
cana-660	280	21	07	07	NUM
cana-660	280	22	)	)	PUNCT
cana-660	280	23	.	.	PUNCT
cana-660	281	1	[	[	X
cana-660	281	2	5	5	X
cana-660	281	3	]	]	PUNCT
cana-660	281	4	t.	t.	NOUN
cana-660	281	5	joachims	joachim	NOUN
cana-660	281	6	,	,	PUNCT
cana-660	281	7	“	"	PUNCT
cana-660	281	8	training	train	VERB
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cana-660	281	10	svms	svms	NOUN
cana-660	281	11	in	in	ADP
cana-660	281	12	linear	linear	ADJ
cana-660	281	13	time	time	NOUN
cana-660	281	14	,	,	PUNCT
cana-660	281	15	”	"	PUNCT
cana-660	281	16	in	in	ADP
cana-660	281	17	proc	proc	NOUN
cana-660	281	18	.	.	PUNCT
cana-660	282	1	12th	12th	ADJ
cana-660	282	2	acm	acm	PROPN
cana-660	282	3	sigkdd	sigkdd	NOUN
cana-660	282	4	int	int	NOUN
cana-660	282	5	.	.	PUNCT
cana-660	282	6	conf	conf	PROPN
cana-660	282	7	.	.	PUNCT
cana-660	282	8	knowl	knowl	PROPN
cana-660	282	9	.	.	PUNCT
cana-660	283	1	discovery	discovery	NOUN
cana-660	283	2	data	datum	NOUN
cana-660	283	3	mining	mining	NOUN
cana-660	283	4	,	,	PUNCT
cana-660	283	5	2006	2006	NUM
cana-660	283	6	,	,	PUNCT
cana-660	283	7	pp	pp	ADV
cana-660	283	8	.	.	PUNCT
cana-660	284	1	217–226	217–226	NUM
cana-660	284	2	.	.	PUNCT
cana-660	285	1	[	[	X
cana-660	285	2	6	6	NUM
cana-660	285	3	]	]	PUNCT
cana-660	285	4	c.	c.	PROPN
cana-660	285	5	j.	j.	PROPN
cana-660	285	6	c.	c.	PROPN
cana-660	285	7	burges	burges	PROPN
cana-660	285	8	,	,	PUNCT
cana-660	285	9	t.	t.	PROPN
cana-660	285	10	shaked	shaked	PROPN
cana-660	285	11	,	,	PUNCT
cana-660	285	12	e.	e.	PROPN
cana-660	285	13	renshaw	renshaw	PROPN
cana-660	285	14	,	,	PUNCT
cana-660	285	15	a.	a.	NOUN
cana-660	285	16	lazier	lazier	PROPN
cana-660	285	17	,	,	PUNCT
cana-660	285	18	m.	m.	NOUN
cana-660	285	19	deeds	deed	NOUN
cana-660	285	20	,	,	PUNCT
cana-660	285	21	n.	n.	NOUN
cana-660	285	22	halmilton	halmilton	PROPN
cana-660	285	23	,	,	PUNCT
cana-660	285	24	and	and	CCONJ
cana-660	285	25	g.	g.	PROPN
cana-660	285	26	hullender	hullender	PROPN
cana-660	285	27	,	,	PUNCT
cana-660	285	28	“	"	PUNCT
cana-660	285	29	learning	learn	VERB
cana-660	285	30	to	to	PART
cana-660	285	31	rank	rank	VERB
cana-660	285	32	using	use	VERB
cana-660	285	33	gradient	gradient	ADJ
cana-660	285	34	descent	descent	NOUN
cana-660	285	35	,	,	PUNCT
cana-660	285	36	”	"	PUNCT
cana-660	285	37	in	in	ADP
cana-660	285	38	proc	proc	NOUN
cana-660	285	39	.	.	PUNCT
cana-660	286	1	int	int	NOUN
cana-660	286	2	.	.	PUNCT
cana-660	286	3	conf	conf	PROPN
cana-660	286	4	.	.	PUNCT
cana-660	287	1	mach	mach	PROPN
cana-660	287	2	.	.	PUNCT
cana-660	288	1	learn	learn	VERB
cana-660	288	2	.	.	PROPN
cana-660	288	3	,	,	PUNCT
cana-660	288	4	2005	2005	NUM
cana-660	288	5	,	,	PUNCT
cana-660	288	6	pp	pp	ADJ
cana-660	288	7	.	.	PUNCT
cana-660	289	1	89–96	89–96	NUM
cana-660	289	2	.	.	PUNCT
cana-660	290	1	[	[	X
cana-660	290	2	7	7	X
cana-660	290	3	]	]	X
cana-660	290	4	f.	f.	PROPN
cana-660	290	5	pan	pan	PROPN
cana-660	290	6	,	,	PUNCT
cana-660	290	7	t.	t.	PROPN
cana-660	290	8	converse	converse	PROPN
cana-660	290	9	,	,	PUNCT
cana-660	290	10	d.	d.	PROPN
cana-660	290	11	ahn	ahn	PROPN
cana-660	290	12	,	,	PUNCT
cana-660	290	13	f.	f.	PROPN
cana-660	290	14	salvetti	salvetti	PROPN
cana-660	290	15	,	,	PUNCT
cana-660	290	16	and	and	CCONJ
cana-660	290	17	g.	g.	PROPN
cana-660	290	18	donato	donato	PROPN
cana-660	290	19	,	,	PUNCT
cana-660	290	20	“	"	PUNCT
cana-660	290	21	greedy	greedy	ADJ
cana-660	290	22	and	and	CCONJ
cana-660	290	23	randomized	randomized	ADJ
cana-660	290	24	feature	feature	NOUN
cana-660	290	25	selection	selection	NOUN
cana-660	290	26	for	for	ADP
cana-660	290	27	web	web	NOUN
cana-660	290	28	search	search	NOUN
cana-660	290	29	ranking	ranking	NOUN
cana-660	290	30	,	,	PUNCT
cana-660	290	31	”	"	PUNCT
cana-660	290	32	in	in	ADP
cana-660	290	33	proc	proc	NOUN
cana-660	290	34	.	.	PUNCT
cana-660	291	1	11th	11th	ADJ
cana-660	291	2	int	int	NOUN
cana-660	291	3	.	.	PUNCT
cana-660	291	4	conf	conf	NOUN
cana-660	291	5	.	.	PUNCT
cana-660	292	1	comput	comput	PROPN
cana-660	292	2	.	.	PUNCT
cana-660	293	1	inf	inf	PROPN
cana-660	293	2	.	.	PUNCT
cana-660	293	3	technol	technol	PROPN
cana-660	293	4	.	.	PROPN
cana-660	293	5	,	,	PUNCT
cana-660	293	6	2011	2011	NUM
cana-660	293	7	,	,	PUNCT
cana-660	293	8	pp	pp	ADV
cana-660	293	9	.	.	PUNCT
cana-660	294	1	436–442	436–442	NUM
cana-660	294	2	.	.	PUNCT
cana-660	295	1	[	[	X
cana-660	295	2	8	8	NUM
cana-660	295	3	]	]	X
cana-660	295	4	lai	lai	PROPN
cana-660	295	5	,	,	PUNCT
cana-660	295	6	h.	h.	PROPN
cana-660	295	7	j.	j.	PROPN
cana-660	295	8	,	,	PUNCT
cana-660	295	9	pan	pan	PROPN
cana-660	295	10	,	,	PUNCT
cana-660	295	11	y.	y.	PROPN
cana-660	295	12	,	,	PUNCT
cana-660	295	13	tang	tang	PROPN
cana-660	295	14	,	,	PUNCT
cana-660	295	15	y.	y.	PROPN
cana-660	295	16	,	,	PUNCT
cana-660	295	17	yu	yu	PROPN
cana-660	295	18	,	,	PUNCT
cana-660	295	19	r.	r.	PROPN
cana-660	295	20	(	(	PUNCT
cana-660	295	21	2013	2013	NUM
cana-660	295	22	)	)	PUNCT
cana-660	295	23	.	.	PUNCT
cana-660	296	1	fsmrank	fsmrank	NOUN
cana-660	296	2	:	:	PUNCT
cana-660	296	3	feature	feature	NOUN
cana-660	296	4	selection	selection	NOUN
cana-660	296	5	algorithm	algorithm	NOUN
cana-660	296	6	for	for	ADP
cana-660	296	7	learning	learn	VERB
cana-660	296	8	to	to	PART
cana-660	296	9	rank	rank	VERB
cana-660	296	10	.	.	PUNCT
cana-660	297	1	ieee	ieee	NOUN
cana-660	297	2	transactions	transaction	NOUN
cana-660	297	3	on	on	ADP
cana-660	297	4	neural	neural	ADJ
cana-660	297	5	networks	network	NOUN
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cana-660	297	7	learning	learning	NOUN
cana-660	297	8	systems	system	NOUN
cana-660	297	9	,	,	PUNCT
cana-660	297	10	24(6	24(6	NUM
cana-660	297	11	)	)	PUNCT
cana-660	297	12	,	,	PUNCT
cana-660	297	13	940–952	940–952	NUM
cana-660	297	14	.	.	PUNCT
cana-660	298	1	doi:10.1109	doi:10.1109	VERB
cana-660	298	2	/	/	SYM
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cana-660	298	4	pmid:24808475	pmid:24808475	VERB
cana-660	298	5	communications	communication	NOUN
cana-660	298	6	on	on	ADP
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cana-660	298	8	nonlinear	nonlinear	ADJ
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cana-660	298	10	issn	issn	NOUN
cana-660	298	11	:	:	PUNCT
cana-660	298	12	1074	1074	NUM
cana-660	298	13	-	-	PUNCT
cana-660	298	14	133x	133x	NUM
cana-660	298	15	vol	vol	NOUN
cana-660	298	16	31	31	NUM
cana-660	298	17	no	no	NOUN
cana-660	298	18	.	.	PUNCT
cana-660	299	1	2s	2s	NUM
cana-660	299	2	(	(	PUNCT
cana-660	299	3	2024	2024	NUM
cana-660	299	4	)	)	PUNCT
cana-660	299	5	469	469	NUM
cana-660	299	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-660	300	1	[	[	X
cana-660	300	2	9	9	NUM
cana-660	300	3	]	]	X
cana-660	300	4	naini	naini	PROPN
cana-660	300	5	,	,	PUNCT
cana-660	300	6	k.	k.	PROPN
cana-660	300	7	d.	d.	PROPN
cana-660	300	8	,	,	PUNCT
cana-660	300	9	altingovde	altingovde	PROPN
cana-660	300	10	,	,	PUNCT
cana-660	300	11	i.	i.	PROPN
cana-660	300	12	s.	s.	PROPN
cana-660	300	13	(	(	PUNCT
cana-660	300	14	2014	2014	NUM
cana-660	300	15	)	)	PUNCT
cana-660	300	16	.	.	PUNCT
cana-660	301	1	exploiting	exploit	VERB
cana-660	301	2	result	result	NOUN
cana-660	301	3	diversification	diversification	NOUN
cana-660	301	4	methods	method	NOUN
cana-660	301	5	for	for	ADP
cana-660	301	6	feature	feature	NOUN
cana-660	301	7	selection	selection	NOUN
cana-660	301	8	in	in	ADP
cana-660	301	9	learning	learn	VERB
cana-660	301	10	to	to	PART
cana-660	301	11	rank	rank	VERB
cana-660	301	12	.	.	PUNCT
cana-660	302	1	in	in	ADP
cana-660	302	2	mecir	mecir	PROPN
cana-660	302	3	2014	2014	NUM
cana-660	302	4	,	,	PUNCT
cana-660	302	5	lncs	lncs	NOUN
cana-660	302	6	(	(	PUNCT
cana-660	302	7	vol	vol	NOUN
cana-660	302	8	.	.	PUNCT
cana-660	302	9	8416	8416	NUM
cana-660	302	10	,	,	PUNCT
cana-660	302	11	pp	pp	ADV
cana-660	302	12	.	.	PUNCT
cana-660	303	1	455–461	455–461	NUM
cana-660	303	2	)	)	PUNCT
cana-660	304	1	[	[	X
cana-660	304	2	10	10	NUM
cana-660	304	3	]	]	X
cana-660	304	4	gupta	gupta	PROPN
cana-660	304	5	,	,	PUNCT
cana-660	304	6	p.	p.	NOUN
cana-660	304	7	,	,	PUNCT
cana-660	304	8	rosso	rosso	PROPN
cana-660	304	9	.	.	PUNCT
cana-660	304	10	(	(	PUNCT
cana-660	304	11	2012	2012	NUM
cana-660	304	12	)	)	PUNCT
cana-660	304	13	.	.	PUNCT
cana-660	305	1	expected	expect	VERB
cana-660	305	2	divergence	divergence	NOUN
cana-660	305	3	based	base	VERB
cana-660	305	4	feature	feature	NOUN
cana-660	305	5	selection	selection	NOUN
cana-660	305	6	for	for	ADP
cana-660	305	7	learning	learn	VERB
cana-660	305	8	to	to	PART
cana-660	305	9	rank	rank	VERB
cana-660	305	10	.	.	PUNCT
cana-660	306	1	in	in	ADP
cana-660	306	2	proceedings	proceeding	NOUN
cana-660	306	3	of	of	ADP
cana-660	306	4	the	the	DET
cana-660	306	5	24th	24th	ADJ
cana-660	306	6	international	international	ADJ
cana-660	306	7	conference	conference	NOUN
cana-660	306	8	on	on	ADP
cana-660	306	9	computational	computational	ADJ
cana-660	306	10	linguistics	linguistic	NOUN
cana-660	306	11	,	,	PUNCT
cana-660	306	12	coling-2012	coling-2012	NOUN
cana-660	306	13	(	(	PUNCT
cana-660	306	14	pp	pp	ADJ
cana-660	306	15	.	.	PUNCT
cana-660	306	16	10	10	NUM
cana-660	306	17	-	-	SYM
cana-660	306	18	14	14	NUM
cana-660	306	19	)	)	PUNCT
cana-660	306	20	.	.	PUNCT
cana-660	307	1	[	[	X
cana-660	307	2	11	11	NUM
cana-660	307	3	]	]	PUNCT
cana-660	307	4	shirzad	shirzad	PROPN
cana-660	307	5	,	,	PUNCT
cana-660	307	6	m.	m.	PROPN
cana-660	307	7	b.	b.	PROPN
cana-660	307	8	,	,	PUNCT
cana-660	307	9	keyvanpour	keyvanpour	PROPN
cana-660	307	10	,	,	PUNCT
cana-660	307	11	m.	m.	NOUN
cana-660	307	12	(	(	PUNCT
cana-660	307	13	2015	2015	NUM
cana-660	307	14	)	)	PUNCT
cana-660	307	15	.	.	PUNCT
cana-660	308	1	a	a	DET
cana-660	308	2	feature	feature	NOUN
cana-660	308	3	selection	selection	NOUN
cana-660	308	4	method	method	NOUN
cana-660	308	5	based	base	VERB
cana-660	308	6	on	on	ADP
cana-660	308	7	minimum	minimum	ADJ
cana-660	308	8	redundancy	redundancy	NOUN
cana-660	308	9	maximum	maximum	ADJ
cana-660	308	10	relevance	relevance	NOUN
cana-660	308	11	for	for	ADP
cana-660	308	12	learning	learning	NOUN
cana-660	308	13	-	-	PUNCT
cana-660	308	14	to	to	ADP
cana-660	308	15	-	-	PUNCT
cana-660	308	16	rank	rank	NOUN
cana-660	308	17	.	.	PUNCT
cana-660	309	1	qazvin	qazvin	ADJ
cana-660	309	2	:	:	PUNCT
cana-660	309	3	5th	5th	ADJ
cana-660	309	4	conference	conference	NOUN
cana-660	309	5	on	on	ADP
cana-660	309	6	artificial	artificial	ADJ
cana-660	309	7	intelligence	intelligence	NOUN
cana-660	309	8	and	and	CCONJ
cana-660	309	9	robotics	robotic	NOUN
cana-660	309	10	,	,	PUNCT
cana-660	309	11	iranopen	iranopen	VERB
cana-660	309	12	[	[	X
cana-660	309	13	12	12	NUM
cana-660	309	14	]	]	X
cana-660	309	15	gigli	gigli	PROPN
cana-660	309	16	,	,	PUNCT
cana-660	309	17	a.	a.	NOUN
cana-660	309	18	,	,	PUNCT
cana-660	309	19	lucchese	lucchese	NOUN
cana-660	309	20	,	,	PUNCT
cana-660	309	21	c.	c.	PROPN
cana-660	309	22	,	,	PUNCT
cana-660	309	23	nardini	nardini	PROPN
cana-660	309	24	,	,	PUNCT
cana-660	309	25	f.	f.	PROPN
cana-660	309	26	m.	m.	PROPN
cana-660	309	27	,	,	PUNCT
cana-660	309	28	perego	perego	PROPN
cana-660	309	29	,	,	PUNCT
cana-660	309	30	r.	r.	PROPN
cana-660	309	31	(	(	PUNCT
cana-660	309	32	2016	2016	NUM
cana-660	309	33	)	)	PUNCT
cana-660	309	34	fast	fast	ADJ
cana-660	309	35	feature	feature	NOUN
cana-660	309	36	selection	selection	NOUN
cana-660	309	37	for	for	ADP
cana-660	309	38	learning	learning	NOUN
cana-660	309	39	-	-	PUNCT
cana-660	309	40	to	to	ADP
cana-660	309	41	-	-	PUNCT
cana-660	309	42	rank	rank	NOUN
cana-660	309	43	.	.	PUNCT
cana-660	310	1	in	in	ADP
cana-660	310	2	proceedings	proceeding	NOUN
cana-660	310	3	of	of	ADP
cana-660	310	4	the	the	DET
cana-660	310	5	2016	2016	NUM
cana-660	310	6	acm	acm	PROPN
cana-660	310	7	international	international	ADJ
cana-660	310	8	conference	conference	NOUN
cana-660	310	9	on	on	ADP
cana-660	310	10	the	the	DET
cana-660	310	11	theory	theory	NOUN
cana-660	310	12	of	of	ADP
cana-660	310	13	information	information	NOUN
cana-660	310	14	retrieval	retrieval	NOUN
cana-660	310	15	(	(	PUNCT
cana-660	310	16	ictir	ictir	ADJ
cana-660	310	17	‘	'	PUNCT
cana-660	310	18	16	16	NUM
cana-660	310	19	)	)	PUNCT
cana-660	311	1	[	[	X
cana-660	311	2	13	13	NUM
cana-660	311	3	]	]	SYM
cana-660	311	4	hua	hua	PROPN
cana-660	311	5	,	,	PUNCT
cana-660	311	6	g.	g.	PROPN
cana-660	311	7	,	,	PUNCT
cana-660	311	8	zhang	zhang	PROPN
cana-660	311	9	,	,	PUNCT
cana-660	311	10	m.	m.	NOUN
cana-660	311	11	,	,	PUNCT
cana-660	311	12	liu	liu	PROPN
cana-660	311	13	,	,	PUNCT
cana-660	311	14	y.	y.	PROPN
cana-660	311	15	,	,	PUNCT
cana-660	311	16	ma	ma	PROPN
cana-660	311	17	,	,	PUNCT
cana-660	311	18	s.	s.	PROPN
cana-660	311	19	,	,	PUNCT
cana-660	311	20	ru	ru	PROPN
cana-660	311	21	,	,	PUNCT
cana-660	311	22	l.	l.	PROPN
cana-660	311	23	(	(	PUNCT
cana-660	311	24	2010	2010	NUM
cana-660	311	25	)	)	PUNCT
cana-660	311	26	.	.	PUNCT
cana-660	312	1	hierarchical	hierarchical	ADJ
cana-660	312	2	feature	feature	NOUN
cana-660	312	3	selection	selection	NOUN
cana-660	312	4	for	for	ADP
cana-660	312	5	ranking	rank	VERB
cana-660	312	6	.	.	PUNCT
cana-660	313	1	in	in	ADP
cana-660	313	2	proceedings	proceeding	NOUN
cana-660	313	3	of	of	ADP
cana-660	313	4	19th	19th	ADJ
cana-660	313	5	international	international	ADJ
cana-660	313	6	conference	conference	NOUN
cana-660	313	7	world	world	NOUN
cana-660	313	8	wide	wide	ADJ
cana-660	313	9	web	web	NOUN
cana-660	313	10	(	(	PUNCT
cana-660	313	11	pp	pp	ADJ
cana-660	313	12	.	.	PUNCT
cana-660	313	13	1113–1114	1113–1114	NUM
cana-660	313	14	)	)	PUNCT
cana-660	313	15	.	.	PUNCT
cana-660	314	1	[	[	X
cana-660	314	2	14	14	NUM
cana-660	314	3	]	]	X
cana-660	314	4	sun	sun	PROPN
cana-660	314	5	,	,	PUNCT
cana-660	314	6	z.	z.	PROPN
cana-660	314	7	,	,	PUNCT
cana-660	314	8	qin	qin	PROPN
cana-660	314	9	,	,	PUNCT
cana-660	314	10	t.	t.	PROPN
cana-660	314	11	,	,	PUNCT
cana-660	314	12	tao	tao	PROPN
cana-660	314	13	,	,	PUNCT
cana-660	314	14	q.	q.	PROPN
cana-660	314	15	,	,	PUNCT
cana-660	314	16	wang	wang	PROPN
cana-660	314	17	,	,	PUNCT
cana-660	314	18	j.	j.	PROPN
cana-660	314	19	(	(	PUNCT
cana-660	314	20	2009	2009	NUM
cana-660	314	21	)	)	PUNCT
cana-660	314	22	.	.	PUNCT
cana-660	315	1	robust	robust	ADJ
cana-660	315	2	sparse	sparse	ADJ
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cana-660	315	4	learning	learning	NOUN
cana-660	315	5	for	for	ADP
cana-660	315	6	non	non	ADJ
cana-660	315	7	-	-	ADJ
cana-660	315	8	smooth	smooth	ADJ
cana-660	315	9	ranking	ranking	ADJ
cana-660	315	10	measures	measure	NOUN
cana-660	315	11	.	.	PUNCT
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cana-660	316	2	proceedings	proceeding	NOUN
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cana-660	316	12	and	and	CCONJ
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cana-660	316	14	in	in	ADP
cana-660	316	15	information	information	NOUN
cana-660	316	16	retrieval	retrieval	NOUN
cana-660	316	17	(	(	PUNCT
cana-660	316	18	pp	pp	ADJ
cana-660	316	19	.	.	PUNCT
cana-660	317	1	259–266	259–266	NUM
cana-660	317	2	)	)	PUNCT
cana-660	317	3	.	.	PUNCT
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cana-660	318	2	[	[	X
cana-660	318	3	15	15	NUM
cana-660	318	4	]	]	X
cana-660	318	5	lai	lai	PROPN
cana-660	318	6	,	,	PUNCT
cana-660	318	7	h.	h.	PROPN
cana-660	318	8	,	,	PUNCT
cana-660	318	9	pan	pan	PROPN
cana-660	318	10	,	,	PUNCT
cana-660	318	11	y.	y.	PROPN
cana-660	318	12	,	,	PUNCT
cana-660	318	13	liu	liu	PROPN
cana-660	318	14	,	,	PUNCT
cana-660	318	15	c.	c.	PROPN
cana-660	318	16	,	,	PUNCT
cana-660	318	17	lin	lin	PROPN
cana-660	318	18	,	,	PUNCT
cana-660	318	19	l.	l.	PROPN
cana-660	318	20	,	,	PUNCT
cana-660	318	21	wu	wu	PROPN
cana-660	318	22	,	,	PUNCT
cana-660	318	23	j.	j.	PROPN
cana-660	318	24	(	(	PUNCT
cana-660	318	25	2012	2012	NUM
cana-660	318	26	)	)	PUNCT
cana-660	318	27	.	.	PUNCT
cana-660	319	1	sparse	sparse	ADJ
cana-660	319	2	learning	learn	VERB
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cana-660	319	4	rank	rank	VERB
cana-660	319	5	via	via	ADP
cana-660	319	6	an	an	DET
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cana-660	319	8	primal	primal	ADJ
cana-660	319	9	-	-	PUNCT
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cana-660	319	12	.	.	PUNCT
cana-660	320	1	ieee	ieee	NOUN
cana-660	320	2	transactions	transaction	NOUN
cana-660	320	3	on	on	ADP
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cana-660	320	5	,	,	PUNCT
cana-660	320	6	99(6	99(6	NUM
cana-660	320	7	)	)	PUNCT
cana-660	320	8	,	,	PUNCT
cana-660	320	9	1221–1233	1221–1233	NUM
cana-660	320	10	.	.	PUNCT
cana-660	321	1	[	[	X
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cana-660	321	3	]	]	X
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cana-660	321	7	,	,	PUNCT
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cana-660	321	9	,	,	PUNCT
cana-660	321	10	y.	y.	PROPN
cana-660	321	11	,	,	PUNCT
cana-660	321	12	tang	tang	PROPN
cana-660	321	13	,	,	PUNCT
cana-660	321	14	y.	y.	PROPN
cana-660	321	15	,	,	PUNCT
cana-660	321	16	liu	liu	PROPN
cana-660	321	17	,	,	PUNCT
cana-660	321	18	n.	n.	PROPN
cana-660	321	19	(	(	PUNCT
cana-660	321	20	2013	2013	NUM
cana-660	321	21	)	)	PUNCT
cana-660	321	22	.	.	PUNCT
cana-660	322	1	efficient	efficient	ADJ
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cana-660	322	4	algorithm	algorithm	NOUN
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cana-660	322	8	with	with	ADP
cana-660	322	9	application	application	NOUN
cana-660	322	10	in	in	ADP
cana-660	322	11	learning	learning	NOUN
cana-660	322	12	-	-	PUNCT
cana-660	322	13	to	to	ADP
cana-660	322	14	-	-	PUNCT
cana-660	322	15	rank	rank	NOUN
cana-660	322	16	.	.	PUNCT
cana-660	323	1	knowledge	knowledge	NOUN
cana-660	323	2	-	-	PUNCT
cana-660	323	3	based	base	VERB
cana-660	323	4	systems	system	NOUN
cana-660	323	5	,	,	PUNCT
cana-660	323	6	49	49	NUM
cana-660	323	7	,	,	PUNCT
cana-660	323	8	190–198	190–198	NUM
cana-660	323	9	.	.	PUNCT
cana-660	324	1	[	[	X
cana-660	324	2	17	17	NUM
cana-660	324	3	]	]	PUNCT
cana-660	324	4	laporte	laporte	NOUN
cana-660	324	5	,	,	PUNCT
cana-660	324	6	l.	l.	PROPN
cana-660	324	7	,	,	PUNCT
cana-660	324	8	flamary	flamary	NOUN
cana-660	324	9	,	,	PUNCT
cana-660	324	10	r.	r.	PROPN
cana-660	324	11	,	,	PUNCT
cana-660	324	12	canu	canu	PROPN
cana-660	324	13	,	,	PUNCT
cana-660	324	14	s.	s.	PROPN
cana-660	324	15	,	,	PUNCT
cana-660	324	16	d´ejean	d´ejean	PROPN
cana-660	324	17	,	,	PUNCT
cana-660	324	18	s.	s.	PROPN
cana-660	324	19	,	,	PUNCT
cana-660	324	20	mothe	mothe	PROPN
cana-660	324	21	,	,	PUNCT
cana-660	324	22	j.	j.	PROPN
cana-660	324	23	(	(	PUNCT
cana-660	324	24	2014	2014	NUM
cana-660	324	25	)	)	PUNCT
cana-660	324	26	.	.	PUNCT
cana-660	325	1	nonconvex	nonconvex	NOUN
cana-660	325	2	regularizations	regularization	NOUN
cana-660	325	3	for	for	ADP
cana-660	325	4	feature	feature	NOUN
cana-660	325	5	selection	selection	NOUN
cana-660	325	6	in	in	ADP
cana-660	325	7	ranking	rank	VERB
cana-660	325	8	with	with	ADP
cana-660	325	9	sparse	sparse	ADJ
cana-660	325	10	svm	svm	PROPN
cana-660	325	11	.	.	PROPN
cana-660	325	12	ieee	ieee	NOUN
cana-660	325	13	transactions	transaction	NOUN
cana-660	325	14	on	on	ADP
cana-660	325	15	neural	neural	ADJ
cana-660	325	16	networks	network	NOUN
cana-660	325	17	and	and	CCONJ
cana-660	325	18	learning	learning	NOUN
cana-660	325	19	systems	system	NOUN
cana-660	325	20	,	,	PUNCT
cana-660	325	21	25(6	25(6	NOUN
cana-660	325	22	)	)	PUNCT
cana-660	325	23	,	,	PUNCT
cana-660	325	24	1118–1130	1118–1130	NUM
cana-660	325	25	.	.	PUNCT
cana-660	326	1	doi:10.1109	doi:10.1109	VERB
cana-660	326	2	/	/	SYM
cana-660	327	1	tnnls.2013.2286696	tnnls.2013.2286696	NUM
cana-660	327	2	[	[	SYM
cana-660	327	3	18	18	NUM
cana-660	327	4	]	]	PUNCT
cana-660	327	5	krasotkina	krasotkina	NOUN
cana-660	327	6	,	,	PUNCT
cana-660	327	7	o.	o.	PROPN
cana-660	327	8	,	,	PUNCT
cana-660	327	9	mottl	mottl	PROPN
cana-660	327	10	,	,	PUNCT
cana-660	327	11	v.	v.	PROPN
cana-660	327	12	(	(	PUNCT
cana-660	327	13	2015	2015	NUM
cana-660	327	14	)	)	PUNCT
cana-660	327	15	.	.	PUNCT
cana-660	328	1	a	a	DET
cana-660	328	2	bayesian	bayesian	NOUN
cana-660	328	3	approach	approach	NOUN
cana-660	328	4	to	to	AUX
cana-660	328	5	sparse	sparse	VERB
cana-660	328	6	learning	learn	VERB
cana-660	328	7	to	to	PART
cana-660	328	8	rank	rank	VERB
cana-660	328	9	for	for	ADP
cana-660	328	10	search	search	NOUN
cana-660	328	11	engine	engine	NOUN
cana-660	328	12	optimization	optimization	NOUN
cana-660	328	13	.	.	PUNCT
cana-660	329	1	in	in	ADP
cana-660	329	2	proceedings	proceeding	NOUN
cana-660	329	3	of	of	ADP
cana-660	329	4	the	the	DET
cana-660	329	5	11th	11th	ADJ
cana-660	329	6	international	international	ADJ
cana-660	329	7	machine	machine	NOUN
cana-660	329	8	learning	learning	NOUN
cana-660	329	9	and	and	CCONJ
cana-660	329	10	data	datum	NOUN
cana-660	329	11	mining	mining	NOUN
cana-660	329	12	in	in	ADP
cana-660	329	13	pattern	pattern	NOUN
cana-660	329	14	recognition	recognition	NOUN
cana-660	329	15	conference	conference	NOUN
cana-660	329	16	mldm	mldm	NOUN
cana-660	329	17	’	'	PUNCT
cana-660	329	18	15	15	NUM
cana-660	329	19	,	,	PUNCT
cana-660	329	20	lncs	lncs	NOUN
cana-660	329	21	(	(	PUNCT
cana-660	329	22	vol	vol	NOUN
cana-660	329	23	.	.	PUNCT
cana-660	329	24	9166	9166	NUM
cana-660	329	25	,	,	PUNCT
cana-660	329	26	pp	pp	ADJ
cana-660	329	27	.	.	PUNCT
cana-660	330	1	382	382	NUM
cana-660	330	2	-	-	SYM
cana-660	330	3	394	394	NUM
cana-660	330	4	)	)	PUNCT
cana-660	330	5	.	.	PUNCT
cana-660	331	1	[	[	X
cana-660	331	2	19	19	NUM
cana-660	331	3	]	]	X
cana-660	331	4	changsheng	changsheng	PROPN
cana-660	331	5	li	li	PROPN
cana-660	331	6	,	,	PUNCT
cana-660	331	7	ling	ling	PROPN
cana-660	331	8	shao	shao	PROPN
cana-660	331	9	,	,	PUNCT
cana-660	331	10	changsheng	changsheng	PROPN
cana-660	331	11	xu	xu	PROPN
cana-660	331	12	,	,	PUNCT
cana-660	331	13	and	and	CCONJ
cana-660	331	14	hanqing	hanqe	VERB
cana-660	331	15	lu	lu	PROPN
cana-660	331	16	.	.	PROPN
cana-660	331	17	2011	2011	NUM
cana-660	331	18	.	.	PUNCT
cana-660	332	1	feature	feature	NOUN
cana-660	332	2	selection	selection	NOUN
cana-660	332	3	under	under	ADP
cana-660	332	4	learning	learn	VERB
cana-660	332	5	to	to	PART
cana-660	332	6	rank	rank	VERB
cana-660	332	7	model	model	NOUN
cana-660	332	8	for	for	ADP
cana-660	332	9	multimedia	multimedia	NOUN
cana-660	332	10	retrieve	retrieve	NOUN
cana-660	332	11	.	.	PUNCT
cana-660	333	1	in	in	ADP
cana-660	333	2	proceedings	proceeding	NOUN
cana-660	333	3	of	of	ADP
cana-660	333	4	the	the	DET
cana-660	333	5	second	second	ADJ
cana-660	333	6	international	international	ADJ
cana-660	333	7	conference	conference	NOUN
cana-660	333	8	on	on	ADP
cana-660	333	9	internet	internet	NOUN
cana-660	333	10	multimedia	multimedia	NOUN
cana-660	333	11	computing	computing	NOUN
cana-660	333	12	and	and	CCONJ
cana-660	333	13	service	service	NOUN
cana-660	333	14	(	(	PUNCT
cana-660	333	15	icimcs	icimcs	NOUN
cana-660	333	16	'	'	NUM
cana-660	333	17	10	10	NUM
cana-660	333	18	)	)	PUNCT
cana-660	333	19	.	.	PUNCT
cana-660	334	1	association	association	NOUN
cana-660	334	2	for	for	ADP
cana-660	334	3	computing	compute	VERB
cana-660	334	4	machinery	machinery	NOUN
cana-660	334	5	,	,	PUNCT
cana-660	334	6	new	new	PROPN
cana-660	334	7	york	york	PROPN
cana-660	334	8	,	,	PUNCT
cana-660	334	9	ny	ny	PROPN
cana-660	334	10	,	,	PUNCT
cana-660	334	11	usa	usa	PROPN
cana-660	334	12	,	,	PUNCT
cana-660	334	13	69–72	69–72	NUM
cana-660	334	14	.	.	PUNCT
cana-660	334	15	https://doi.org/10.1145/1937728.1937745	https://doi.org/10.1145/1937728.1937745	PROPN
cana-660	334	16	.	.	PUNCT
cana-660	335	1	[	[	X
cana-660	335	2	20	20	NUM
cana-660	335	3	]	]	X
cana-660	335	4	gupta	gupta	PROPN
cana-660	335	5	,	,	PUNCT
cana-660	335	6	parth	parth	NOUN
cana-660	335	7	,	,	PUNCT
cana-660	335	8	and	and	CCONJ
cana-660	335	9	paolo	paolo	NOUN
cana-660	335	10	rosso	rosso	NOUN
cana-660	335	11	.	.	PUNCT
cana-660	336	1	"	"	PUNCT
cana-660	336	2	expected	expect	VERB
cana-660	336	3	divergence	divergence	NOUN
cana-660	336	4	based	base	VERB
cana-660	336	5	feature	feature	NOUN
cana-660	336	6	selection	selection	NOUN
cana-660	336	7	for	for	ADP
cana-660	336	8	learning	learn	VERB
cana-660	336	9	to	to	PART
cana-660	336	10	rank	rank	VERB
cana-660	336	11	.	.	PUNCT
cana-660	336	12	"	"	PUNCT
cana-660	337	1	in	in	ADP
cana-660	337	2	proceedings	proceeding	NOUN
cana-660	337	3	of	of	ADP
cana-660	337	4	coling	cole	VERB
cana-660	337	5	2012	2012	NUM
cana-660	337	6	:	:	PUNCT
cana-660	337	7	posters	poster	NOUN
cana-660	337	8	,	,	PUNCT
cana-660	337	9	pp	pp	ADV
cana-660	337	10	.	.	PUNCT
cana-660	338	1	431	431	NUM
cana-660	338	2	-	-	SYM
cana-660	338	3	440	440	NUM
cana-660	338	4	.	.	PUNCT
cana-660	339	1	2012	2012	NUM
cana-660	339	2	.	.	PUNCT
cana-660	340	1	[	[	X
cana-660	340	2	21	21	NUM
cana-660	340	3	]	]	X
cana-660	340	4	lai	lai	PROPN
cana-660	340	5	,	,	PUNCT
cana-660	340	6	han	han	PROPN
cana-660	340	7	-	-	PUNCT
cana-660	340	8	jiang	jiang	PROPN
cana-660	340	9	,	,	PUNCT
cana-660	340	10	yan	yan	PROPN
cana-660	340	11	pan	pan	PROPN
cana-660	340	12	,	,	PUNCT
cana-660	340	13	yong	yong	PROPN
cana-660	340	14	tang	tang	PROPN
cana-660	340	15	,	,	PUNCT
cana-660	340	16	and	and	CCONJ
cana-660	340	17	rong	rong	PROPN
cana-660	340	18	yu	yu	PROPN
cana-660	340	19	.	.	PUNCT
cana-660	341	1	"	"	PUNCT
cana-660	341	2	fsmrank	fsmrank	NOUN
cana-660	341	3	:	:	PUNCT
cana-660	341	4	feature	feature	NOUN
cana-660	341	5	selection	selection	NOUN
cana-660	341	6	algorithm	algorithm	NOUN
cana-660	341	7	for	for	ADP
cana-660	341	8	learning	learn	VERB
cana-660	341	9	to	to	PART
cana-660	341	10	rank	rank	VERB
cana-660	341	11	.	.	PUNCT
cana-660	341	12	"	"	PUNCT
cana-660	342	1	ieee	ieee	NOUN
cana-660	342	2	transactions	transaction	NOUN
cana-660	342	3	on	on	ADP
cana-660	342	4	neural	neural	ADJ
cana-660	342	5	networks	network	NOUN
cana-660	342	6	and	and	CCONJ
cana-660	342	7	learning	learn	VERB
cana-660	342	8	systems	system	NOUN
cana-660	342	9	24	24	NUM
cana-660	342	10	,	,	PUNCT
cana-660	342	11	no	no	INTJ
cana-660	342	12	.	.	NOUN
cana-660	342	13	6	6	NUM
cana-660	342	14	(	(	PUNCT
cana-660	342	15	2013	2013	NUM
cana-660	342	16	):	):	PUNCT
cana-660	342	17	940	940	NUM
cana-660	342	18	-	-	SYM
cana-660	342	19	952	952	NUM
cana-660	342	20	.	.	PUNCT
cana-660	343	1	[	[	X
cana-660	343	2	22	22	NUM
cana-660	343	3	]	]	X
cana-660	343	4	gigli	gigli	PROPN
cana-660	343	5	,	,	PUNCT
cana-660	343	6	andrea	andrea	PROPN
cana-660	343	7	,	,	PUNCT
cana-660	343	8	claudio	claudio	NOUN
cana-660	343	9	lucchese	lucchese	NOUN
cana-660	343	10	,	,	PUNCT
cana-660	343	11	franco	franco	PROPN
cana-660	343	12	maria	maria	PROPN
cana-660	343	13	nardini	nardini	PROPN
cana-660	343	14	,	,	PUNCT
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cana-660	343	16	raffaele	raffaele	PROPN
cana-660	343	17	perego	perego	PROPN
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cana-660	344	1	"	"	PUNCT
cana-660	344	2	fast	fast	ADJ
cana-660	344	3	feature	feature	NOUN
cana-660	344	4	selection	selection	NOUN
cana-660	344	5	for	for	ADP
cana-660	344	6	learning	learn	VERB
cana-660	344	7	to	to	PART
cana-660	344	8	rank	rank	VERB
cana-660	344	9	.	.	PUNCT
cana-660	344	10	"	"	PUNCT
cana-660	345	1	in	in	ADP
cana-660	345	2	proceedings	proceeding	NOUN
cana-660	345	3	of	of	ADP
cana-660	345	4	the	the	DET
cana-660	345	5	2016	2016	NUM
cana-660	345	6	acm	acm	PROPN
cana-660	345	7	international	international	ADJ
cana-660	345	8	conference	conference	NOUN
cana-660	345	9	on	on	ADP
cana-660	345	10	the	the	DET
cana-660	345	11	theory	theory	NOUN
cana-660	345	12	of	of	ADP
cana-660	345	13	information	information	NOUN
cana-660	345	14	retrieval	retrieval	NOUN
cana-660	345	15	,	,	PUNCT
cana-660	345	16	pp	pp	ADP
cana-660	345	17	.	.	PUNCT
cana-660	345	18	167170	167170	NUM
cana-660	345	19	.	.	PUNCT
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cana-660	345	21	.	.	PUNCT
cana-660	346	1	[	[	X
cana-660	346	2	23	23	NUM
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cana-660	346	4	sousa	sousa	NOUN
cana-660	346	5	,	,	PUNCT
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cana-660	346	7	xavier	xavier	PROPN
cana-660	346	8	de	de	PROPN
cana-660	346	9	,	,	PUNCT
cana-660	346	10	sérgio	sérgio	PROPN
cana-660	346	11	daniel	daniel	PROPN
cana-660	346	12	canuto	canuto	PROPN
cana-660	346	13	,	,	PUNCT
cana-660	346	14	thierson	thierson	NOUN
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cana-660	346	17	,	,	PUNCT
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cana-660	346	21	,	,	PUNCT
cana-660	346	22	and	and	CCONJ
cana-660	346	23	marcos	marcos	PROPN
cana-660	346	24	andré	andré	PROPN
cana-660	346	25	gonçalves	gonçalves	PROPN
cana-660	346	26	.	.	PUNCT
cana-660	347	1	"	"	PUNCT
cana-660	347	2	incorporating	incorporate	VERB
cana-660	347	3	risk	risk	NOUN
cana-660	347	4	-	-	PUNCT
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cana-660	347	6	into	into	ADP
cana-660	347	7	feature	feature	NOUN
cana-660	347	8	selection	selection	NOUN
cana-660	347	9	for	for	ADP
cana-660	347	10	learning	learn	VERB
cana-660	347	11	to	to	PART
cana-660	347	12	rank	rank	VERB
cana-660	347	13	.	.	PUNCT
cana-660	347	14	"	"	PUNCT
cana-660	348	1	in	in	ADP
cana-660	348	2	proceedings	proceeding	NOUN
cana-660	348	3	of	of	ADP
cana-660	348	4	the	the	DET
cana-660	348	5	25th	25th	ADJ
cana-660	348	6	acm	acm	PROPN
cana-660	348	7	international	international	PROPN
cana-660	348	8	on	on	ADP
cana-660	348	9	conference	conference	NOUN
cana-660	348	10	on	on	ADP
cana-660	348	11	information	information	NOUN
cana-660	348	12	and	and	CCONJ
cana-660	348	13	knowledge	knowledge	NOUN
cana-660	348	14	management	management	NOUN
cana-660	348	15	,	,	PUNCT
cana-660	348	16	pp	pp	ADP
cana-660	348	17	.	.	PUNCT
cana-660	349	1	257	257	NUM
cana-660	349	2	-	-	SYM
cana-660	349	3	266	266	NUM
cana-660	349	4	.	.	PUNCT
cana-660	350	1	2016	2016	NUM
cana-660	350	2	.	.	PUNCT
cana-660	351	1	[	[	X
cana-660	351	2	24	24	NUM
cana-660	351	3	]	]	X
cana-660	351	4	shirzad	shirzad	PROPN
cana-660	351	5	,	,	PUNCT
cana-660	351	6	mehrnoush	mehrnoush	ADJ
cana-660	351	7	barani	barani	NOUN
cana-660	351	8	,	,	PUNCT
cana-660	351	9	and	and	CCONJ
cana-660	351	10	mohammad	mohammad	PROPN
cana-660	351	11	reza	reza	PROPN
cana-660	351	12	keyvanpour	keyvanpour	PROPN
cana-660	351	13	.	.	PUNCT
cana-660	352	1	"	"	PUNCT
cana-660	352	2	a	a	DET
cana-660	352	3	systematic	systematic	ADJ
cana-660	352	4	study	study	NOUN
cana-660	352	5	of	of	ADP
cana-660	352	6	feature	feature	NOUN
cana-660	352	7	selection	selection	NOUN
cana-660	352	8	methods	method	NOUN
cana-660	352	9	for	for	ADP
cana-660	352	10	learning	learn	VERB
cana-660	352	11	to	to	PART
cana-660	352	12	rank	rank	VERB
cana-660	352	13	algorithms	algorithm	NOUN
cana-660	352	14	.	.	PUNCT
cana-660	352	15	"	"	PUNCT
cana-660	353	1	international	international	ADJ
cana-660	353	2	journal	journal	NOUN
cana-660	353	3	of	of	ADP
cana-660	353	4	information	information	NOUN
cana-660	353	5	retrieval	retrieval	NOUN
cana-660	353	6	research	research	NOUN
cana-660	353	7	(	(	PUNCT
cana-660	353	8	ijirr	ijirr	ADJ
cana-660	353	9	)	)	PUNCT
cana-660	353	10	8	8	NUM
cana-660	353	11	,	,	PUNCT
cana-660	353	12	no	no	INTJ
cana-660	353	13	.	.	NOUN
cana-660	353	14	3	3	NUM
cana-660	353	15	(	(	PUNCT
cana-660	353	16	2018	2018	NUM
cana-660	353	17	):	):	PUNCT
cana-660	353	18	46	46	NUM
cana-660	353	19	-	-	SYM
cana-660	353	20	67	67	NUM
cana-660	353	21	.	.	PUNCT
cana-660	354	1	[	[	X
cana-660	354	2	25	25	NUM
cana-660	354	3	]	]	X
cana-660	354	4	cheng	cheng	PROPN
cana-660	354	5	,	,	PUNCT
cana-660	354	6	fan	fan	PROPN
cana-660	354	7	,	,	PUNCT
cana-660	354	8	wei	wei	PROPN
cana-660	354	9	guo	guo	PROPN
cana-660	354	10	,	,	PUNCT
cana-660	354	11	and	and	CCONJ
cana-660	354	12	xingyi	xingyi	PROPN
cana-660	354	13	zhang	zhang	PROPN
cana-660	354	14	.	.	PUNCT
cana-660	355	1	"	"	PUNCT
cana-660	355	2	mofsrank	mofsrank	NOUN
cana-660	355	3	:	:	PUNCT
cana-660	355	4	a	a	DET
cana-660	355	5	multiobjective	multiobjective	ADJ
cana-660	355	6	evolutionary	evolutionary	ADJ
cana-660	355	7	algorithm	algorithm	NOUN
cana-660	355	8	for	for	ADP
cana-660	355	9	feature	feature	NOUN
cana-660	355	10	selection	selection	NOUN
cana-660	355	11	in	in	ADP
cana-660	355	12	learning	learn	VERB
cana-660	355	13	to	to	PART
cana-660	355	14	rank	rank	VERB
cana-660	355	15	.	.	PUNCT
cana-660	355	16	"	"	PUNCT
cana-660	356	1	complexity	complexity	NOUN
cana-660	356	2	2018	2018	NUM
cana-660	356	3	(	(	PUNCT
cana-660	356	4	2018	2018	NUM
cana-660	356	5	):	):	PUNCT
cana-660	356	6	1	1	NUM
cana-660	356	7	-	-	SYM
cana-660	356	8	14	14	NUM
cana-660	356	9	.	.	PUNCT
cana-660	357	1	[	[	X
cana-660	357	2	26	26	NUM
cana-660	357	3	]	]	X
cana-660	357	4	purpura	purpura	NOUN
cana-660	357	5	,	,	PUNCT
cana-660	357	6	alberto	alberto	PROPN
cana-660	357	7	,	,	PUNCT
cana-660	357	8	karolina	karolina	PROPN
cana-660	357	9	buchner	buchner	PROPN
cana-660	357	10	,	,	PUNCT
cana-660	357	11	gianmaria	gianmaria	PROPN
cana-660	357	12	silvello	silvello	NOUN
cana-660	357	13	,	,	PUNCT
cana-660	357	14	and	and	CCONJ
cana-660	357	15	gian	gian	PROPN
cana-660	357	16	antonio	antonio	PROPN
cana-660	357	17	susto	susto	PROPN
cana-660	357	18	.	.	PUNCT
cana-660	358	1	"	"	PUNCT
cana-660	358	2	neural	neural	ADJ
cana-660	358	3	feature	feature	NOUN
cana-660	358	4	selection	selection	NOUN
cana-660	358	5	for	for	ADP
cana-660	358	6	learning	learn	VERB
cana-660	358	7	to	to	PART
cana-660	358	8	rank	rank	VERB
cana-660	358	9	.	.	PUNCT
cana-660	358	10	"	"	PUNCT
cana-660	359	1	in	in	ADP
cana-660	359	2	advances	advance	NOUN
cana-660	359	3	in	in	ADP
cana-660	359	4	information	information	NOUN
cana-660	359	5	retrieval	retrieval	NOUN
cana-660	359	6	:	:	PUNCT
cana-660	359	7	43rd	43rd	ADJ
cana-660	359	8	european	european	ADJ
cana-660	359	9	conference	conference	NOUN
cana-660	359	10	on	on	ADP
cana-660	359	11	ir	ir	PROPN
cana-660	359	12	research	research	NOUN
cana-660	359	13	,	,	PUNCT
cana-660	359	14	ecir	ecir	NOUN
cana-660	359	15	2021	2021	NUM
cana-660	359	16	,	,	PUNCT
cana-660	359	17	virtual	virtual	ADJ
cana-660	359	18	event	event	NOUN
cana-660	359	19	,	,	PUNCT
cana-660	359	20	march	march	PROPN
cana-660	359	21	28	28	NUM
cana-660	359	22	–	–	PUNCT
cana-660	359	23	april	april	PROPN
cana-660	359	24	1	1	NUM
cana-660	359	25	,	,	PUNCT
cana-660	359	26	2021	2021	NUM
cana-660	359	27	,	,	PUNCT
cana-660	359	28	proceedings	proceeding	NOUN
cana-660	359	29	,	,	PUNCT
cana-660	359	30	part	part	NOUN
cana-660	359	31	ii	ii	PROPN
cana-660	359	32	43	43	NUM
cana-660	359	33	,	,	PUNCT
cana-660	359	34	pp	pp	ADJ
cana-660	359	35	.	.	PUNCT
cana-660	360	1	342	342	NUM
cana-660	360	2	-	-	SYM
cana-660	360	3	349	349	NUM
cana-660	360	4	.	.	PUNCT
cana-660	361	1	springer	springer	NOUN
cana-660	361	2	international	international	ADJ
cana-660	361	3	publishing	publishing	NOUN
cana-660	361	4	,	,	PUNCT
cana-660	361	5	2021	2021	NUM
cana-660	361	6	.	.	PUNCT
cana-660	362	1	[	[	X
cana-660	362	2	27	27	NUM
cana-660	362	3	]	]	X
cana-660	362	4	fahandar	fahandar	NOUN
cana-660	362	5	,	,	PUNCT
cana-660	362	6	mohsen	mohsen	PROPN
cana-660	362	7	&	&	CCONJ
cana-660	362	8	hüllermeier	hüllermeier	PROPN
cana-660	362	9	,	,	PUNCT
cana-660	362	10	eyke	eyke	ADJ
cana-660	362	11	.	.	PUNCT
cana-660	362	12	”analogical	”analogical	ADJ
cana-660	362	13	embedding	embed	VERB
cana-660	362	14	for	for	ADP
cana-660	362	15	analogy	analogy	NOUN
cana-660	362	16	-	-	PUNCT
cana-660	362	17	based	base	VERB
cana-660	362	18	learning	learning	NOUN
cana-660	362	19	to	to	PART
cana-660	362	20	rank	rank	VERB
cana-660	362	21	”	"	PUNCT
cana-660	362	22	.	.	PUNCT
cana-660	363	1	10.1007/978	10.1007/978	NUM
cana-660	363	2	-	-	SYM
cana-660	363	3	3	3	NUM
cana-660	363	4	-	-	PUNCT
cana-660	363	5	030	030	NUM
cana-660	363	6	-	-	PUNCT
cana-660	363	7	74251	74251	NUM
cana-660	363	8	-	-	PUNCT
cana-660	363	9	5_7	5_7	NUM
cana-660	363	10	.	.	NUM
cana-660	363	11	,	,	PUNCT
cana-660	363	12	2021	2021	NUM
cana-660	363	13	.	.	PUNCT
cana-660	364	1	https://doi.org/10.1145/1937728.1937745	https://doi.org/10.1145/1937728.1937745	ADJ