id	sid	tid	token	lemma	pos
ijassa-751	1	1	adv	adv	PROPN
ijassa-751	1	2	syst	syst	PROPN
ijassa-751	1	3	sci	sci	PROPN
ijassa-751	1	4	appl	appl	PROPN
ijassa-751	1	5	.	.	PROPN
ijassa-751	1	6	2019	2019	NUM
ijassa-751	1	7	;	;	PUNCT
ijassa-751	1	8	03;11–22	03;11–22	NUM
ijassa-751	1	9	published	publish	VERB
ijassa-751	1	10	online	online	ADV
ijassa-751	1	11	at	at	ADP
ijassa-751	1	12	https://ijassa.ipu.ru/index.php/ijassa/article/view/751	https://ijassa.ipu.ru/index.php/ijassa/article/view/751	PROPN
ijassa-751	1	13	hybrid	hybrid	NOUN
ijassa-751	1	14	particle	particle	NOUN
ijassa-751	1	15	swarm	swarm	NOUN
ijassa-751	1	16	optimization	optimization	NOUN
ijassa-751	1	17	and	and	CCONJ
ijassa-751	1	18	pegasos	pegasos	NOUN
ijassa-751	1	19	algorithm	algorithm	NOUN
ijassa-751	1	20	for	for	ADP
ijassa-751	1	21	spam	spam	NOUN
ijassa-751	1	22	email	email	NOUN
ijassa-751	1	23	detection	detection	NOUN
ijassa-751	1	24	lamiaa	lamiaa	NOUN
ijassa-751	1	25	m.	m.	NOUN
ijassa-751	1	26	el	el	PROPN
ijassa-751	1	27	bakrawy∗	bakrawy∗	PROPN
ijassa-751	1	28	faculty	faculty	NOUN
ijassa-751	1	29	of	of	ADP
ijassa-751	1	30	science	science	NOUN
ijassa-751	1	31	,	,	PUNCT
ijassa-751	1	32	al	al	PROPN
ijassa-751	1	33	-	-	PUNCT
ijassa-751	1	34	azhar	azhar	PROPN
ijassa-751	1	35	university	university	PROPN
ijassa-751	1	36	,	,	PUNCT
ijassa-751	1	37	cairo	cairo	PROPN
ijassa-751	1	38	,	,	PUNCT
ijassa-751	1	39	egypt	egypt	PROPN
ijassa-751	1	40	e	e	PROPN
ijassa-751	1	41	-	-	NOUN
ijassa-751	1	42	mail	mail	NOUN
ijassa-751	1	43	:	:	PUNCT
ijassa-751	1	44	dr	dr	PROPN
ijassa-751	1	45	lamiaa	lamiaa	PROPN
ijassa-751	1	46	el	el	PROPN
ijassa-751	1	47	bakrawy@azhar.edu.eg	bakrawy@azhar.edu.eg	PROPN
ijassa-751	1	48	received	receive	VERB
ijassa-751	1	49	may	may	AUX
ijassa-751	1	50	25	25	NUM
ijassa-751	1	51	,	,	PUNCT
ijassa-751	1	52	2019	2019	NUM
ijassa-751	1	53	;	;	PUNCT
ijassa-751	1	54	revised	revise	VERB
ijassa-751	1	55	september	september	PROPN
ijassa-751	1	56	9	9	NUM
ijassa-751	1	57	,	,	PUNCT
ijassa-751	1	58	2019	2019	NUM
ijassa-751	1	59	;	;	PUNCT
ijassa-751	1	60	published	publish	VERB
ijassa-751	1	61	october	october	PROPN
ijassa-751	1	62	1	1	NUM
ijassa-751	1	63	,	,	PUNCT
ijassa-751	1	64	2019	2019	NUM
ijassa-751	1	65	abstract	abstract	NOUN
ijassa-751	1	66	:	:	PUNCT
ijassa-751	1	67	email	email	NOUN
ijassa-751	1	68	is	be	AUX
ijassa-751	1	69	one	one	NUM
ijassa-751	1	70	of	of	ADP
ijassa-751	1	71	the	the	DET
ijassa-751	1	72	most	most	ADV
ijassa-751	1	73	popular	popular	ADJ
ijassa-751	1	74	communication	communication	NOUN
ijassa-751	1	75	tools	tool	NOUN
ijassa-751	1	76	for	for	ADP
ijassa-751	1	77	most	most	ADJ
ijassa-751	1	78	internet	internet	NOUN
ijassa-751	1	79	users	user	NOUN
ijassa-751	1	80	nowadays	nowadays	ADV
ijassa-751	1	81	.	.	PUNCT
ijassa-751	2	1	it	it	PRON
ijassa-751	2	2	has	have	AUX
ijassa-751	2	3	become	become	VERB
ijassa-751	2	4	fast	fast	ADJ
ijassa-751	2	5	and	and	CCONJ
ijassa-751	2	6	an	an	DET
ijassa-751	2	7	effective	effective	ADJ
ijassa-751	2	8	method	method	NOUN
ijassa-751	2	9	to	to	PART
ijassa-751	2	10	share	share	VERB
ijassa-751	2	11	and	and	CCONJ
ijassa-751	2	12	exchange	exchange	VERB
ijassa-751	2	13	information	information	NOUN
ijassa-751	2	14	all	all	ADV
ijassa-751	2	15	over	over	ADP
ijassa-751	2	16	the	the	DET
ijassa-751	2	17	world	world	NOUN
ijassa-751	2	18	.	.	PUNCT
ijassa-751	3	1	despite	despite	SCONJ
ijassa-751	3	2	the	the	DET
ijassa-751	3	3	great	great	ADJ
ijassa-751	3	4	advantages	advantage	NOUN
ijassa-751	3	5	of	of	ADP
ijassa-751	3	6	emails	email	NOUN
ijassa-751	3	7	,	,	PUNCT
ijassa-751	3	8	its	its	PRON
ijassa-751	3	9	usage	usage	NOUN
ijassa-751	3	10	is	be	AUX
ijassa-751	3	11	facing	face	VERB
ijassa-751	3	12	problem	problem	NOUN
ijassa-751	3	13	which	which	PRON
ijassa-751	3	14	is	be	AUX
ijassa-751	3	15	spam	spam	NOUN
ijassa-751	3	16	emails	email	NOUN
ijassa-751	3	17	.	.	PUNCT
ijassa-751	4	1	spam	spam	NOUN
ijassa-751	4	2	emails	email	NOUN
ijassa-751	4	3	are	be	AUX
ijassa-751	4	4	the	the	DET
ijassa-751	4	5	huge	huge	ADJ
ijassa-751	4	6	presence	presence	NOUN
ijassa-751	4	7	of	of	ADP
ijassa-751	4	8	bulk	bulk	ADJ
ijassa-751	4	9	and	and	CCONJ
ijassa-751	4	10	unsolicited	unsolicited	ADJ
ijassa-751	4	11	emails	email	NOUN
ijassa-751	4	12	which	which	PRON
ijassa-751	4	13	are	be	AUX
ijassa-751	4	14	expensive	expensive	ADJ
ijassa-751	4	15	for	for	ADP
ijassa-751	4	16	the	the	DET
ijassa-751	4	17	companies	company	NOUN
ijassa-751	4	18	,	,	PUNCT
ijassa-751	4	19	consume	consume	VERB
ijassa-751	4	20	a	a	DET
ijassa-751	4	21	huge	huge	ADJ
ijassa-751	4	22	amount	amount	NOUN
ijassa-751	4	23	of	of	ADP
ijassa-751	4	24	mail	mail	NOUN
ijassa-751	4	25	servers	server	NOUN
ijassa-751	4	26	,	,	PUNCT
ijassa-751	4	27	network	network	NOUN
ijassa-751	4	28	bandwidth	bandwidth	NOUN
ijassa-751	4	29	and	and	CCONJ
ijassa-751	4	30	waste	waste	NOUN
ijassa-751	4	31	of	of	ADP
ijassa-751	4	32	time	time	NOUN
ijassa-751	4	33	.	.	PUNCT
ijassa-751	5	1	isolating	isolate	VERB
ijassa-751	5	2	and	and	CCONJ
ijassa-751	5	3	detecting	detect	VERB
ijassa-751	5	4	these	these	DET
ijassa-751	5	5	emails	email	NOUN
ijassa-751	5	6	is	be	AUX
ijassa-751	5	7	known	know	VERB
ijassa-751	5	8	as	as	ADP
ijassa-751	5	9	spam	spam	NOUN
ijassa-751	5	10	detection	detection	NOUN
ijassa-751	5	11	.	.	PUNCT
ijassa-751	6	1	many	many	ADJ
ijassa-751	6	2	spam	spam	NOUN
ijassa-751	6	3	detection	detection	NOUN
ijassa-751	6	4	methods	method	NOUN
ijassa-751	6	5	have	have	AUX
ijassa-751	6	6	been	be	AUX
ijassa-751	6	7	proposed	propose	VERB
ijassa-751	6	8	but	but	CCONJ
ijassa-751	6	9	there	there	PRON
ijassa-751	6	10	is	be	VERB
ijassa-751	6	11	still	still	ADV
ijassa-751	6	12	need	need	ADJ
ijassa-751	6	13	to	to	PART
ijassa-751	6	14	detect	detect	VERB
ijassa-751	6	15	the	the	DET
ijassa-751	6	16	email	email	NOUN
ijassa-751	6	17	spam	spam	NOUN
ijassa-751	6	18	effectively	effectively	ADV
ijassa-751	6	19	with	with	ADP
ijassa-751	6	20	high	high	ADJ
ijassa-751	6	21	accuracy	accuracy	NOUN
ijassa-751	6	22	.	.	PUNCT
ijassa-751	7	1	in	in	ADP
ijassa-751	7	2	this	this	DET
ijassa-751	7	3	paper	paper	NOUN
ijassa-751	7	4	,	,	PUNCT
ijassa-751	7	5	hybrid	hybrid	ADJ
ijassa-751	7	6	particle	particle	NOUN
ijassa-751	7	7	swarm	swarm	NOUN
ijassa-751	7	8	optimization	optimization	NOUN
ijassa-751	7	9	and	and	CCONJ
ijassa-751	7	10	pegasos	pegasos	PROPN
ijassa-751	7	11	algorithm	algorithm	PROPN
ijassa-751	7	12	,	,	PUNCT
ijassa-751	7	13	which	which	PRON
ijassa-751	7	14	is	be	AUX
ijassa-751	7	15	called	call	VERB
ijassa-751	7	16	(	(	PUNCT
ijassa-751	7	17	psopegasos	psopegasos	NOUN
ijassa-751	7	18	)	)	PUNCT
ijassa-751	7	19	is	be	AUX
ijassa-751	7	20	proposed	propose	VERB
ijassa-751	7	21	for	for	ADP
ijassa-751	7	22	spam	spam	NOUN
ijassa-751	7	23	email	email	NOUN
ijassa-751	7	24	detection	detection	NOUN
ijassa-751	7	25	.	.	PUNCT
ijassa-751	8	1	particle	particle	NOUN
ijassa-751	8	2	swarm	swarm	NOUN
ijassa-751	8	3	optimization	optimization	NOUN
ijassa-751	8	4	is	be	AUX
ijassa-751	8	5	employed	employ	VERB
ijassa-751	8	6	as	as	ADP
ijassa-751	8	7	a	a	DET
ijassa-751	8	8	search	search	NOUN
ijassa-751	8	9	strategy	strategy	NOUN
ijassa-751	8	10	to	to	PART
ijassa-751	8	11	determine	determine	VERB
ijassa-751	8	12	the	the	DET
ijassa-751	8	13	optimal	optimal	ADJ
ijassa-751	8	14	parameters	parameter	NOUN
ijassa-751	8	15	for	for	ADP
ijassa-751	8	16	pegasos	pegasos	NOUN
ijassa-751	8	17	algorithm	algorithm	NOUN
ijassa-751	8	18	in	in	ADP
ijassa-751	8	19	order	order	NOUN
ijassa-751	8	20	to	to	PART
ijassa-751	8	21	achieve	achieve	VERB
ijassa-751	8	22	higher	high	ADJ
ijassa-751	8	23	performance	performance	NOUN
ijassa-751	8	24	.	.	PUNCT
ijassa-751	9	1	the	the	DET
ijassa-751	9	2	proposed	propose	VERB
ijassa-751	9	3	algorithm	algorithm	NOUN
ijassa-751	9	4	has	have	AUX
ijassa-751	9	5	been	be	AUX
ijassa-751	9	6	applied	apply	VERB
ijassa-751	9	7	on	on	ADP
ijassa-751	9	8	spambase	spambase	PROPN
ijassa-751	9	9	dataset	dataset	PROPN
ijassa-751	9	10	downloaded	download	VERB
ijassa-751	9	11	from	from	ADP
ijassa-751	9	12	uci	uci	PROPN
ijassa-751	9	13	machine	machine	NOUN
ijassa-751	9	14	learning	learn	VERB
ijassa-751	9	15	repository	repository	NOUN
ijassa-751	9	16	.	.	PUNCT
ijassa-751	10	1	experimental	experimental	ADJ
ijassa-751	10	2	results	result	NOUN
ijassa-751	10	3	demonstrate	demonstrate	VERB
ijassa-751	10	4	that	that	SCONJ
ijassa-751	10	5	the	the	DET
ijassa-751	10	6	proposed	propose	VERB
ijassa-751	10	7	algorithm	algorithm	NOUN
ijassa-751	10	8	outperforms	outperform	VERB
ijassa-751	10	9	the	the	DET
ijassa-751	10	10	performance	performance	NOUN
ijassa-751	10	11	of	of	ADP
ijassa-751	10	12	all	all	DET
ijassa-751	10	13	the	the	DET
ijassa-751	10	14	earlier	early	ADV
ijassa-751	10	15	proposed	propose	VERB
ijassa-751	10	16	algorithms	algorithm	NOUN
ijassa-751	10	17	,	,	PUNCT
ijassa-751	10	18	considering	consider	VERB
ijassa-751	10	19	the	the	DET
ijassa-751	10	20	accuracy	accuracy	NOUN
ijassa-751	10	21	,	,	PUNCT
ijassa-751	10	22	recall	recall	NOUN
ijassa-751	10	23	,	,	PUNCT
ijassa-751	10	24	precision	precision	NOUN
ijassa-751	10	25	and	and	CCONJ
ijassa-751	10	26	f	f	NOUN
ijassa-751	10	27	-	-	PUNCT
ijassa-751	10	28	measure	measure	NOUN
ijassa-751	10	29	on	on	ADP
ijassa-751	10	30	the	the	DET
ijassa-751	10	31	same	same	ADJ
ijassa-751	10	32	dataset	dataset	NOUN
ijassa-751	10	33	.	.	PUNCT
ijassa-751	11	1	keywords	keyword	NOUN
ijassa-751	11	2	:	:	PUNCT
ijassa-751	11	3	particle	particle	NOUN
ijassa-751	11	4	swarm	swarm	NOUN
ijassa-751	11	5	optimization	optimization	NOUN
ijassa-751	11	6	,	,	PUNCT
ijassa-751	11	7	pegasos	pegasos	PROPN
ijassa-751	11	8	algorithm	algorithm	PROPN
ijassa-751	11	9	,	,	PUNCT
ijassa-751	11	10	email	email	NOUN
ijassa-751	11	11	spam	spam	NOUN
ijassa-751	11	12	,	,	PUNCT
ijassa-751	11	13	spam	spam	NOUN
ijassa-751	11	14	detection	detection	NOUN
ijassa-751	11	15	,	,	PUNCT
ijassa-751	11	16	accuracy	accuracy	NOUN
ijassa-751	11	17	.	.	PUNCT
ijassa-751	12	1	1	1	X
ijassa-751	12	2	.	.	X
ijassa-751	12	3	introduction	introduction	NOUN
ijassa-751	12	4	nowadays	nowadays	ADV
ijassa-751	12	5	,	,	PUNCT
ijassa-751	12	6	email	email	NOUN
ijassa-751	12	7	is	be	AUX
ijassa-751	12	8	one	one	NUM
ijassa-751	12	9	of	of	ADP
ijassa-751	12	10	the	the	DET
ijassa-751	12	11	most	most	ADV
ijassa-751	12	12	popular	popular	ADJ
ijassa-751	12	13	communication	communication	NOUN
ijassa-751	12	14	tools	tool	NOUN
ijassa-751	12	15	for	for	ADP
ijassa-751	12	16	most	most	ADJ
ijassa-751	12	17	internet	internet	NOUN
ijassa-751	12	18	users	user	NOUN
ijassa-751	12	19	because	because	SCONJ
ijassa-751	12	20	of	of	ADP
ijassa-751	12	21	its	its	PRON
ijassa-751	12	22	free	free	ADJ
ijassa-751	12	23	availability	availability	NOUN
ijassa-751	12	24	and	and	CCONJ
ijassa-751	12	25	efficiency	efficiency	NOUN
ijassa-751	12	26	[	[	X
ijassa-751	12	27	1	1	NUM
ijassa-751	12	28	,	,	PUNCT
ijassa-751	12	29	2	2	NUM
ijassa-751	12	30	]	]	PUNCT
ijassa-751	12	31	.	.	PUNCT
ijassa-751	13	1	email	email	NOUN
ijassa-751	13	2	is	be	AUX
ijassa-751	13	3	a	a	DET
ijassa-751	13	4	method	method	NOUN
ijassa-751	13	5	of	of	ADP
ijassa-751	13	6	receiving	receive	VERB
ijassa-751	13	7	and	and	CCONJ
ijassa-751	13	8	sending	send	VERB
ijassa-751	13	9	information	information	NOUN
ijassa-751	13	10	over	over	ADP
ijassa-751	13	11	electronic	electronic	ADJ
ijassa-751	13	12	networks	network	NOUN
ijassa-751	13	13	such	such	ADJ
ijassa-751	13	14	as	as	ADP
ijassa-751	13	15	the	the	DET
ijassa-751	13	16	internet	internet	NOUN
ijassa-751	13	17	.	.	PUNCT
ijassa-751	14	1	however	however	ADV
ijassa-751	14	2	,	,	PUNCT
ijassa-751	14	3	the	the	DET
ijassa-751	14	4	major	major	ADJ
ijassa-751	14	5	problem	problem	NOUN
ijassa-751	14	6	is	be	AUX
ijassa-751	14	7	the	the	DET
ijassa-751	14	8	presence	presence	NOUN
ijassa-751	14	9	of	of	ADP
ijassa-751	14	10	bulk	bulk	NOUN
ijassa-751	14	11	and	and	CCONJ
ijassa-751	14	12	unsolicited	unsolicited	ADJ
ijassa-751	14	13	email	email	NOUN
ijassa-751	14	14	which	which	PRON
ijassa-751	14	15	is	be	AUX
ijassa-751	14	16	known	know	VERB
ijassa-751	14	17	as	as	ADP
ijassa-751	14	18	spam	spam	NOUN
ijassa-751	14	19	.	.	PUNCT
ijassa-751	15	1	spammer	spammer	NOUN
ijassa-751	15	2	is	be	AUX
ijassa-751	15	3	the	the	DET
ijassa-751	15	4	person	person	NOUN
ijassa-751	15	5	who	who	PRON
ijassa-751	15	6	sends	send	VERB
ijassa-751	15	7	mass	mass	ADJ
ijassa-751	15	8	quantity	quantity	NOUN
ijassa-751	15	9	of	of	ADP
ijassa-751	15	10	spam	spam	NOUN
ijassa-751	15	11	emails	email	NOUN
ijassa-751	15	12	and	and	CCONJ
ijassa-751	15	13	collects	collect	VERB
ijassa-751	15	14	email	email	NOUN
ijassa-751	15	15	addresses	address	NOUN
ijassa-751	15	16	from	from	ADP
ijassa-751	15	17	chatrooms	chatroom	NOUN
ijassa-751	15	18	,	,	PUNCT
ijassa-751	15	19	viruses	virus	NOUN
ijassa-751	15	20	,	,	PUNCT
ijassa-751	15	21	customer	customer	NOUN
ijassa-751	15	22	lists	list	NOUN
ijassa-751	15	23	and	and	CCONJ
ijassa-751	15	24	websites	website	NOUN
ijassa-751	15	25	.	.	PUNCT
ijassa-751	16	1	spam	spam	NOUN
ijassa-751	16	2	email	email	NOUN
ijassa-751	16	3	consumes	consume	VERB
ijassa-751	16	4	a	a	DET
ijassa-751	16	5	huge	huge	ADJ
ijassa-751	16	6	amount	amount	NOUN
ijassa-751	16	7	of	of	ADP
ijassa-751	16	8	mail	mail	NOUN
ijassa-751	16	9	servers	server	NOUN
ijassa-751	16	10	,	,	PUNCT
ijassa-751	16	11	network	network	NOUN
ijassa-751	16	12	bandwidth	bandwidth	NOUN
ijassa-751	16	13	and	and	CCONJ
ijassa-751	16	14	wastes	waste	VERB
ijassa-751	16	15	users	user	NOUN
ijassa-751	16	16	’	’	PART
ijassa-751	16	17	time	time	NOUN
ijassa-751	16	18	to	to	PART
ijassa-751	16	19	remove	remove	VERB
ijassa-751	16	20	all	all	DET
ijassa-751	16	21	spam	spam	NOUN
ijassa-751	16	22	emails	email	NOUN
ijassa-751	16	23	which	which	PRON
ijassa-751	16	24	causes	cause	VERB
ijassa-751	16	25	lower	low	ADJ
ijassa-751	16	26	productivity	productivity	NOUN
ijassa-751	16	27	.	.	PUNCT
ijassa-751	17	1	thus	thus	ADV
ijassa-751	17	2	,	,	PUNCT
ijassa-751	17	3	how	how	SCONJ
ijassa-751	17	4	to	to	PART
ijassa-751	17	5	isolate	isolate	VERB
ijassa-751	17	6	and	and	CCONJ
ijassa-751	17	7	detect	detect	VERB
ijassa-751	17	8	spam	spam	NOUN
ijassa-751	17	9	email	email	NOUN
ijassa-751	17	10	in	in	ADP
ijassa-751	17	11	efficient	efficient	ADJ
ijassa-751	17	12	way	way	NOUN
ijassa-751	17	13	with	with	ADP
ijassa-751	17	14	high	high	ADJ
ijassa-751	17	15	accuracy	accuracy	NOUN
ijassa-751	17	16	becomes	become	VERB
ijassa-751	17	17	an	an	DET
ijassa-751	17	18	important	important	ADJ
ijassa-751	17	19	study	study	NOUN
ijassa-751	17	20	.	.	PUNCT
ijassa-751	18	1	spam	spam	NOUN
ijassa-751	18	2	email	email	NOUN
ijassa-751	18	3	detection	detection	NOUN
ijassa-751	18	4	can	can	AUX
ijassa-751	18	5	be	be	AUX
ijassa-751	18	6	considered	consider	VERB
ijassa-751	18	7	as	as	ADP
ijassa-751	18	8	classification	classification	NOUN
ijassa-751	18	9	problem	problem	NOUN
ijassa-751	18	10	which	which	PRON
ijassa-751	18	11	is	be	AUX
ijassa-751	18	12	used	use	VERB
ijassa-751	18	13	to	to	PART
ijassa-751	18	14	detect	detect	VERB
ijassa-751	18	15	the	the	DET
ijassa-751	18	16	spam	spam	NOUN
ijassa-751	18	17	emails	email	NOUN
ijassa-751	18	18	one	one	NUM
ijassa-751	18	19	by	by	ADP
ijassa-751	18	20	one	one	NUM
ijassa-751	18	21	to	to	PART
ijassa-751	18	22	classify	classify	VERB
ijassa-751	18	23	email	email	NOUN
ijassa-751	18	24	as	as	ADP
ijassa-751	18	25	spam	spam	NOUN
ijassa-751	18	26	or	or	CCONJ
ijassa-751	18	27	non	non	ADJ
ijassa-751	18	28	-	-	NOUN
ijassa-751	18	29	spam	spam	NOUN
ijassa-751	18	30	[	[	X
ijassa-751	18	31	3	3	NUM
ijassa-751	18	32	]	]	PUNCT
ijassa-751	18	33	.	.	PUNCT
ijassa-751	19	1	in	in	ADP
ijassa-751	19	2	recent	recent	ADJ
ijassa-751	19	3	years	year	NOUN
ijassa-751	19	4	,	,	PUNCT
ijassa-751	19	5	most	most	ADJ
ijassa-751	19	6	of	of	ADP
ijassa-751	19	7	the	the	DET
ijassa-751	19	8	spam	spam	NOUN
ijassa-751	19	9	detection	detection	NOUN
ijassa-751	19	10	algorithms	algorithm	NOUN
ijassa-751	19	11	based	base	VERB
ijassa-751	19	12	on	on	ADP
ijassa-751	19	13	machine	machine	NOUN
ijassa-751	19	14	learning	learning	NOUN
ijassa-751	19	15	techniques	technique	NOUN
ijassa-751	19	16	is	be	AUX
ijassa-751	19	17	used	use	VERB
ijassa-751	19	18	,	,	PUNCT
ijassa-751	19	19	but	but	CCONJ
ijassa-751	19	20	still	still	ADV
ijassa-751	19	21	the	the	DET
ijassa-751	19	22	reported	report	VERB
ijassa-751	19	23	accuracy	accuracy	NOUN
ijassa-751	19	24	requires	require	VERB
ijassa-751	19	25	more	more	ADJ
ijassa-751	19	26	work	work	NOUN
ijassa-751	19	27	to	to	PART
ijassa-751	19	28	accomplish	accomplish	VERB
ijassa-751	19	29	better	well	ADJ
ijassa-751	19	30	accuracy	accuracy	NOUN
ijassa-751	19	31	.	.	PUNCT
ijassa-751	20	1	sabri	sabri	NOUN
ijassa-751	20	2	et	et	PROPN
ijassa-751	20	3	al	al	PROPN
ijassa-751	20	4	.	.	PUNCT
ijassa-751	21	1	in	in	ADP
ijassa-751	21	2	[	[	X
ijassa-751	21	3	4	4	X
ijassa-751	21	4	]	]	PUNCT
ijassa-751	21	5	presented	present	VERB
ijassa-751	21	6	continuous	continuous	ADJ
ijassa-751	21	7	learning	learning	NOUN
ijassa-751	21	8	approach	approach	NOUN
ijassa-751	21	9	based	base	VERB
ijassa-751	21	10	on	on	ADP
ijassa-751	21	11	artificial	artificial	ADJ
ijassa-751	21	12	neural	neural	ADJ
ijassa-751	21	13	network	network	NOUN
ijassa-751	21	14	(	(	PUNCT
ijassa-751	21	15	cla	cla	PROPN
ijassa-751	21	16	ann	ann	PROPN
ijassa-751	21	17	)	)	PUNCT
ijassa-751	21	18	for	for	ADP
ijassa-751	21	19	spam	spam	NOUN
ijassa-751	21	20	email	email	NOUN
ijassa-751	21	21	detection	detection	NOUN
ijassa-751	21	22	.	.	PUNCT
ijassa-751	22	1	they	they	PRON
ijassa-751	22	2	made	make	VERB
ijassa-751	22	3	core	core	ADJ
ijassa-751	22	4	modifications	modification	NOUN
ijassa-751	22	5	in	in	ADP
ijassa-751	22	6	the	the	DET
ijassa-751	22	7	input	input	NOUN
ijassa-751	22	8	layer	layer	NOUN
ijassa-751	22	9	of	of	ADP
ijassa-751	22	10	artificial	artificial	ADJ
ijassa-751	22	11	neural	neural	ADJ
ijassa-751	22	12	network	network	NOUN
ijassa-751	22	13	to	to	PART
ijassa-751	22	14	substitute	substitute	VERB
ijassa-751	22	15	the	the	DET
ijassa-751	22	16	useless	useless	ADJ
ijassa-751	22	17	layers	layer	NOUN
ijassa-751	22	18	with	with	ADP
ijassa-751	22	19	new	new	ADJ
ijassa-751	22	20	favorable	favorable	ADJ
ijassa-751	22	21	layers	layer	NOUN
ijassa-751	22	22	and	and	CCONJ
ijassa-751	22	23	to	to	PART
ijassa-751	22	24	be	be	AUX
ijassa-751	22	25	varied	varied	ADJ
ijassa-751	22	26	with	with	ADP
ijassa-751	22	27	time	time	NOUN
ijassa-751	22	28	.	.	PUNCT
ijassa-751	23	1	∗corresponding	∗corresponde	VERB
ijassa-751	23	2	author	author	NOUN
ijassa-751	23	3	:	:	PUNCT
ijassa-751	23	4	dr	dr	PROPN
ijassa-751	23	5	lamiaa	lamiaa	PROPN
ijassa-751	23	6	el	el	PROPN
ijassa-751	23	7	bakrawy@azhar.edu.eg	bakrawy@azhar.edu.eg	PROPN
ijassa-751	23	8	12	12	NUM
ijassa-751	23	9	l.m	l.m	PROPN
ijassa-751	23	10	.	.	PROPN
ijassa-751	23	11	el	el	PROPN
ijassa-751	23	12	bakrawy	bakrawy	VERB
ijassa-751	23	13	the	the	DET
ijassa-751	23	14	results	result	NOUN
ijassa-751	23	15	showed	show	VERB
ijassa-751	23	16	that	that	SCONJ
ijassa-751	23	17	applying	apply	VERB
ijassa-751	23	18	cla	cla	NOUN
ijassa-751	23	19	ann	ann	PROPN
ijassa-751	23	20	using	use	VERB
ijassa-751	23	21	300	300	NUM
ijassa-751	23	22	input	input	NOUN
ijassa-751	23	23	layers	layer	NOUN
ijassa-751	23	24	succeeded	succeed	VERB
ijassa-751	23	25	in	in	ADP
ijassa-751	23	26	achieving	achieve	VERB
ijassa-751	23	27	3.668	3.668	NUM
ijassa-751	23	28	%	%	NOUN
ijassa-751	23	29	false	false	ADJ
ijassa-751	23	30	negative	negative	ADJ
ijassa-751	23	31	and	and	CCONJ
ijassa-751	23	32	0.534	0.534	NUM
ijassa-751	23	33	%	%	NOUN
ijassa-751	23	34	false	false	ADJ
ijassa-751	23	35	positive	positive	NOUN
ijassa-751	23	36	.	.	PUNCT
ijassa-751	24	1	zhang	zhang	PROPN
ijassa-751	24	2	et	et	PROPN
ijassa-751	24	3	al	al	PROPN
ijassa-751	24	4	.	.	PUNCT
ijassa-751	25	1	in	in	ADP
ijassa-751	25	2	[	[	X
ijassa-751	25	3	5	5	NUM
ijassa-751	25	4	]	]	PUNCT
ijassa-751	25	5	presented	present	VERB
ijassa-751	25	6	naive	naive	ADJ
ijassa-751	25	7	bayes	bayes	NOUN
ijassa-751	25	8	model	model	NOUN
ijassa-751	25	9	for	for	ADP
ijassa-751	25	10	spam	spam	NOUN
ijassa-751	25	11	email	email	NOUN
ijassa-751	25	12	detection	detection	NOUN
ijassa-751	25	13	by	by	ADP
ijassa-751	25	14	applying	apply	VERB
ijassa-751	25	15	cost	cost	NOUN
ijassa-751	25	16	-	-	PUNCT
ijassa-751	25	17	sensitive	sensitive	ADJ
ijassa-751	25	18	multi	multi	ADJ
ijassa-751	25	19	-	-	ADJ
ijassa-751	25	20	objective	objective	ADJ
ijassa-751	25	21	genetic	genetic	ADJ
ijassa-751	25	22	programming	programming	NOUN
ijassa-751	25	23	for	for	ADP
ijassa-751	25	24	feature	feature	NOUN
ijassa-751	25	25	extraction	extraction	NOUN
ijassa-751	25	26	and	and	CCONJ
ijassa-751	25	27	achieved	achieve	VERB
ijassa-751	25	28	an	an	DET
ijassa-751	25	29	accuracy	accuracy	NOUN
ijassa-751	25	30	of	of	ADP
ijassa-751	25	31	79.3	79.3	NUM
ijassa-751	25	32	%	%	NOUN
ijassa-751	25	33	.	.	PUNCT
ijassa-751	26	1	renuka	renuka	PROPN
ijassa-751	26	2	et	et	PROPN
ijassa-751	26	3	al	al	PROPN
ijassa-751	26	4	.	.	PUNCT
ijassa-751	27	1	in	in	ADP
ijassa-751	27	2	[	[	X
ijassa-751	27	3	6	6	NUM
ijassa-751	27	4	]	]	PUNCT
ijassa-751	27	5	proposed	propose	VERB
ijassa-751	27	6	spam	spam	NOUN
ijassa-751	27	7	classification	classification	NOUN
ijassa-751	27	8	algorithm	algorithm	NOUN
ijassa-751	27	9	using	use	VERB
ijassa-751	27	10	hybrid	hybrid	ADJ
ijassa-751	27	11	ant	ant	ADJ
ijassa-751	27	12	colony	colony	NOUN
ijassa-751	27	13	optimization	optimization	NOUN
ijassa-751	27	14	and	and	CCONJ
ijassa-751	27	15	naive	naive	ADJ
ijassa-751	27	16	bayes	bayes	NOUN
ijassa-751	27	17	classifier	classifier	NOUN
ijassa-751	27	18	and	and	CCONJ
ijassa-751	27	19	applied	apply	VERB
ijassa-751	27	20	it	it	PRON
ijassa-751	27	21	on	on	ADP
ijassa-751	27	22	spambase	spambase	PROPN
ijassa-751	27	23	dataset	dataset	PROPN
ijassa-751	27	24	.	.	PUNCT
ijassa-751	28	1	the	the	DET
ijassa-751	28	2	accuracy	accuracy	NOUN
ijassa-751	28	3	obtained	obtain	VERB
ijassa-751	28	4	was	be	AUX
ijassa-751	28	5	84	84	NUM
ijassa-751	28	6	%	%	NOUN
ijassa-751	28	7	which	which	PRON
ijassa-751	28	8	indicated	indicate	VERB
ijassa-751	28	9	that	that	SCONJ
ijassa-751	28	10	the	the	DET
ijassa-751	28	11	hybrid	hybrid	ADJ
ijassa-751	28	12	algorithm	algorithm	NOUN
ijassa-751	28	13	outperformed	outperform	VERB
ijassa-751	28	14	hybrid	hybrid	ADJ
ijassa-751	28	15	genetic	genetic	ADJ
ijassa-751	28	16	algorithm	algorithm	NOUN
ijassa-751	28	17	and	and	CCONJ
ijassa-751	28	18	naive	naive	ADJ
ijassa-751	28	19	bayes	bayes	NOUN
ijassa-751	28	20	tested	test	VERB
ijassa-751	28	21	on	on	ADP
ijassa-751	28	22	the	the	DET
ijassa-751	28	23	same	same	ADJ
ijassa-751	28	24	dataset	dataset	NOUN
ijassa-751	28	25	.	.	PUNCT
ijassa-751	29	1	özgür	özgür	NUM
ijassa-751	29	2	et	et	PROPN
ijassa-751	29	3	al	al	PROPN
ijassa-751	29	4	.	.	PUNCT
ijassa-751	30	1	in	in	ADP
ijassa-751	30	2	[	[	X
ijassa-751	30	3	7	7	X
ijassa-751	30	4	]	]	PUNCT
ijassa-751	30	5	used	use	VERB
ijassa-751	30	6	artificial	artificial	ADJ
ijassa-751	30	7	neural	neural	ADJ
ijassa-751	30	8	network	network	NOUN
ijassa-751	30	9	and	and	CCONJ
ijassa-751	30	10	bayesian	bayesian	NOUN
ijassa-751	30	11	filter	filter	NOUN
ijassa-751	30	12	for	for	ADP
ijassa-751	30	13	spam	spam	NOUN
ijassa-751	30	14	email	email	NOUN
ijassa-751	30	15	detection	detection	NOUN
ijassa-751	30	16	.	.	PUNCT
ijassa-751	31	1	they	they	PRON
ijassa-751	31	2	considered	consider	VERB
ijassa-751	31	3	two	two	NUM
ijassa-751	31	4	artificial	artificial	ADJ
ijassa-751	31	5	neural	neural	ADJ
ijassa-751	31	6	network	network	NOUN
ijassa-751	31	7	structures	structure	NOUN
ijassa-751	31	8	,	,	PUNCT
ijassa-751	31	9	multi	multi	ADJ
ijassa-751	31	10	layer	layer	NOUN
ijassa-751	31	11	perceptron	perceptron	NOUN
ijassa-751	31	12	and	and	CCONJ
ijassa-751	31	13	single	single	ADJ
ijassa-751	31	14	layer	layer	NOUN
ijassa-751	31	15	and	and	CCONJ
ijassa-751	31	16	the	the	DET
ijassa-751	31	17	inputs	input	NOUN
ijassa-751	31	18	are	be	AUX
ijassa-751	31	19	specified	specify	VERB
ijassa-751	31	20	based	base	VERB
ijassa-751	31	21	on	on	ADP
ijassa-751	31	22	probabilistic	probabilistic	ADJ
ijassa-751	31	23	and	and	CCONJ
ijassa-751	31	24	binary	binary	ADJ
ijassa-751	31	25	models	model	NOUN
ijassa-751	31	26	.	.	PUNCT
ijassa-751	32	1	experimental	experimental	ADJ
ijassa-751	32	2	results	result	NOUN
ijassa-751	32	3	for	for	ADP
ijassa-751	32	4	750	750	NUM
ijassa-751	32	5	e	e	NOUN
ijassa-751	32	6	-	-	NOUN
ijassa-751	32	7	mails	mail	NOUN
ijassa-751	32	8	(	(	PUNCT
ijassa-751	32	9	410	410	NUM
ijassa-751	32	10	spams	spam	NOUN
ijassa-751	32	11	and	and	CCONJ
ijassa-751	32	12	340	340	NUM
ijassa-751	32	13	non	non	ADJ
ijassa-751	32	14	-	-	NOUN
ijassa-751	32	15	spam	spam	NOUN
ijassa-751	32	16	)	)	PUNCT
ijassa-751	32	17	,	,	PUNCT
ijassa-751	32	18	achieved	achieve	VERB
ijassa-751	32	19	90	90	NUM
ijassa-751	32	20	%	%	NOUN
ijassa-751	32	21	accuracy	accuracy	NOUN
ijassa-751	32	22	.	.	PUNCT
ijassa-751	33	1	temitayo	temitayo	PROPN
ijassa-751	33	2	et	et	PROPN
ijassa-751	33	3	al	al	PROPN
ijassa-751	33	4	.	.	PUNCT
ijassa-751	34	1	in	in	ADP
ijassa-751	34	2	[	[	X
ijassa-751	34	3	8	8	NUM
ijassa-751	34	4	]	]	PUNCT
ijassa-751	34	5	used	use	VERB
ijassa-751	34	6	genetic	genetic	ADJ
ijassa-751	34	7	algorithm	algorithm	NOUN
ijassa-751	34	8	to	to	PART
ijassa-751	34	9	optimize	optimize	VERB
ijassa-751	34	10	the	the	DET
ijassa-751	34	11	support	support	NOUN
ijassa-751	34	12	vector	vector	NOUN
ijassa-751	34	13	machines	machine	NOUN
ijassa-751	34	14	(	(	PUNCT
ijassa-751	34	15	svm	svm	ADJ
ijassa-751	34	16	)	)	PUNCT
ijassa-751	34	17	classification	classification	NOUN
ijassa-751	34	18	parameters	parameter	NOUN
ijassa-751	34	19	.	.	PUNCT
ijassa-751	35	1	the	the	DET
ijassa-751	35	2	hybrid	hybrid	ADJ
ijassa-751	35	3	algorithm	algorithm	NOUN
ijassa-751	35	4	achieved	achieve	VERB
ijassa-751	35	5	90	90	NUM
ijassa-751	35	6	%	%	NOUN
ijassa-751	35	7	accuracy	accuracy	NOUN
ijassa-751	35	8	for	for	ADP
ijassa-751	35	9	the	the	DET
ijassa-751	35	10	testing	testing	NOUN
ijassa-751	35	11	set	set	NOUN
ijassa-751	35	12	.	.	PUNCT
ijassa-751	36	1	liu	liu	PROPN
ijassa-751	36	2	et	et	PROPN
ijassa-751	36	3	al	al	PROPN
ijassa-751	36	4	.	.	PUNCT
ijassa-751	37	1	in	in	ADP
ijassa-751	37	2	[	[	X
ijassa-751	37	3	9	9	NUM
ijassa-751	37	4	]	]	PUNCT
ijassa-751	37	5	proposed	propose	VERB
ijassa-751	37	6	a	a	DET
ijassa-751	37	7	new	new	ADJ
ijassa-751	37	8	learning	learning	NOUN
ijassa-751	37	9	method	method	NOUN
ijassa-751	37	10	(	(	PUNCT
ijassa-751	37	11	pso	pso	NOUN
ijassa-751	37	12	-	-	PUNCT
ijassa-751	37	13	lm	lm	NOUN
ijassa-751	37	14	)	)	PUNCT
ijassa-751	37	15	for	for	ADP
ijassa-751	37	16	process	process	NOUN
ijassa-751	37	17	propagation	propagation	NOUN
ijassa-751	37	18	neural	neural	ADJ
ijassa-751	37	19	networks	network	NOUN
ijassa-751	37	20	(	(	PUNCT
ijassa-751	37	21	pnns	pnn	NOUN
ijassa-751	37	22	)	)	PUNCT
ijassa-751	37	23	based	base	VERB
ijassa-751	37	24	on	on	ADP
ijassa-751	37	25	particle	particle	NOUN
ijassa-751	37	26	swarm	swarm	NOUN
ijassa-751	37	27	optimization	optimization	NOUN
ijassa-751	37	28	(	(	PUNCT
ijassa-751	37	29	pso	pso	NOUN
ijassa-751	37	30	)	)	PUNCT
ijassa-751	37	31	and	and	CCONJ
ijassa-751	37	32	gaussian	gaussian	ADJ
ijassa-751	37	33	mixture	mixture	NOUN
ijassa-751	37	34	functions	function	NOUN
ijassa-751	37	35	.	.	PUNCT
ijassa-751	38	1	experiments	experiment	NOUN
ijassa-751	38	2	results	result	NOUN
ijassa-751	38	3	showed	show	VERB
ijassa-751	38	4	that	that	SCONJ
ijassa-751	38	5	applying	apply	VERB
ijassa-751	38	6	(	(	PUNCT
ijassa-751	38	7	pso	pso	NOUN
ijassa-751	38	8	-	-	PUNCT
ijassa-751	38	9	lm	lm	NOUN
ijassa-751	38	10	)	)	PUNCT
ijassa-751	38	11	on	on	ADP
ijassa-751	38	12	spambase	spambase	PROPN
ijassa-751	38	13	dataset	dataset	PROPN
ijassa-751	38	14	achieved	achieve	VERB
ijassa-751	38	15	90.5	90.5	NUM
ijassa-751	38	16	%	%	NOUN
ijassa-751	38	17	accuracy	accuracy	NOUN
ijassa-751	38	18	for	for	ADP
ijassa-751	38	19	the	the	DET
ijassa-751	38	20	testing	testing	NOUN
ijassa-751	38	21	set	set	NOUN
ijassa-751	38	22	which	which	PRON
ijassa-751	38	23	is	be	AUX
ijassa-751	38	24	better	well	ADJ
ijassa-751	38	25	than	than	ADP
ijassa-751	38	26	back	back	ADJ
ijassa-751	38	27	propagation	propagation	NOUN
ijassa-751	38	28	neural	neural	ADJ
ijassa-751	38	29	networks	network	NOUN
ijassa-751	38	30	(	(	PUNCT
ijassa-751	38	31	bpnns	bpnn	NOUN
ijassa-751	38	32	)	)	PUNCT
ijassa-751	38	33	and	and	CCONJ
ijassa-751	38	34	basis	basis	NOUN
ijassa-751	38	35	function	function	NOUN
ijassa-751	38	36	expansion	expansion	NOUN
ijassa-751	38	37	based	base	VERB
ijassa-751	38	38	learning	learning	NOUN
ijassa-751	38	39	method	method	NOUN
ijassa-751	38	40	(	(	PUNCT
ijassa-751	38	41	bfe	bfe	NOUN
ijassa-751	38	42	-	-	PUNCT
ijassa-751	38	43	lm	lm	NOUN
ijassa-751	38	44	)	)	PUNCT
ijassa-751	38	45	.	.	PUNCT
ijassa-751	39	1	moreover	moreover	ADV
ijassa-751	39	2	,	,	PUNCT
ijassa-751	39	3	idris	idris	PROPN
ijassa-751	39	4	and	and	CCONJ
ijassa-751	39	5	selamat	selamat	PROPN
ijassa-751	39	6	in	in	ADP
ijassa-751	39	7	[	[	X
ijassa-751	39	8	10	10	NUM
ijassa-751	39	9	]	]	PUNCT
ijassa-751	39	10	presented	present	VERB
ijassa-751	39	11	a	a	DET
ijassa-751	39	12	hybrid	hybrid	ADJ
ijassa-751	39	13	model	model	NOUN
ijassa-751	39	14	of	of	ADP
ijassa-751	39	15	negative	negative	ADJ
ijassa-751	39	16	selection	selection	NOUN
ijassa-751	39	17	algorithm	algorithm	NOUN
ijassa-751	39	18	(	(	PUNCT
ijassa-751	39	19	nsa	nsa	PROPN
ijassa-751	39	20	)	)	PUNCT
ijassa-751	39	21	and	and	CCONJ
ijassa-751	39	22	particle	particle	NOUN
ijassa-751	39	23	swarm	swarm	NOUN
ijassa-751	39	24	optimization	optimization	NOUN
ijassa-751	39	25	(	(	PUNCT
ijassa-751	39	26	pso	pso	NOUN
ijassa-751	39	27	)	)	PUNCT
ijassa-751	39	28	.	.	PUNCT
ijassa-751	40	1	they	they	PRON
ijassa-751	40	2	worked	work	VERB
ijassa-751	40	3	on	on	ADP
ijassa-751	40	4	spambase	spambase	PROPN
ijassa-751	40	5	dataset	dataset	NOUN
ijassa-751	40	6	and	and	CCONJ
ijassa-751	40	7	achieved	achieve	VERB
ijassa-751	40	8	91.22	91.22	NUM
ijassa-751	40	9	%	%	NOUN
ijassa-751	40	10	accuracy	accuracy	NOUN
ijassa-751	40	11	for	for	ADP
ijassa-751	40	12	the	the	DET
ijassa-751	40	13	testing	testing	NOUN
ijassa-751	40	14	set	set	VERB
ijassa-751	40	15	.	.	PUNCT
ijassa-751	41	1	awad	awad	PROPN
ijassa-751	41	2	and	and	CCONJ
ijassa-751	41	3	foqaha	foqaha	VERB
ijassa-751	41	4	in	in	ADP
ijassa-751	41	5	[	[	X
ijassa-751	41	6	1	1	NUM
ijassa-751	41	7	]	]	PUNCT
ijassa-751	41	8	proposed	propose	VERB
ijassa-751	41	9	a	a	DET
ijassa-751	41	10	hybrid	hybrid	ADJ
ijassa-751	41	11	algorithm	algorithm	NOUN
ijassa-751	41	12	of	of	ADP
ijassa-751	41	13	rbf	rbf	PROPN
ijassa-751	41	14	neural	neural	ADJ
ijassa-751	41	15	network	network	NOUN
ijassa-751	41	16	and	and	CCONJ
ijassa-751	41	17	particle	particle	NOUN
ijassa-751	41	18	swarm	swarm	NOUN
ijassa-751	41	19	optimization	optimization	NOUN
ijassa-751	41	20	(	(	PUNCT
ijassa-751	41	21	hc	hc	NOUN
ijassa-751	41	22	-	-	PUNCT
ijassa-751	41	23	rbfpso	rbfpso	NOUN
ijassa-751	41	24	)	)	PUNCT
ijassa-751	41	25	for	for	ADP
ijassa-751	41	26	spam	spam	NOUN
ijassa-751	41	27	email	email	NOUN
ijassa-751	41	28	classification	classification	NOUN
ijassa-751	41	29	.	.	PUNCT
ijassa-751	42	1	they	they	PRON
ijassa-751	42	2	used	use	VERB
ijassa-751	42	3	particle	particle	NOUN
ijassa-751	42	4	swarm	swarm	NOUN
ijassa-751	42	5	optimization	optimization	NOUN
ijassa-751	42	6	algorithm	algorithm	NOUN
ijassa-751	42	7	to	to	PART
ijassa-751	42	8	optimize	optimize	VERB
ijassa-751	42	9	the	the	DET
ijassa-751	42	10	parameters	parameter	NOUN
ijassa-751	42	11	of	of	ADP
ijassa-751	42	12	radial	radial	ADJ
ijassa-751	42	13	basis	basis	NOUN
ijassa-751	42	14	function	function	NOUN
ijassa-751	42	15	neural	neural	ADJ
ijassa-751	42	16	networks	network	NOUN
ijassa-751	42	17	(	(	PUNCT
ijassa-751	42	18	rbfnn	rbfnn	PROPN
ijassa-751	42	19	)	)	PUNCT
ijassa-751	42	20	based	base	VERB
ijassa-751	42	21	on	on	ADP
ijassa-751	42	22	the	the	DET
ijassa-751	42	23	evolutionary	evolutionary	ADJ
ijassa-751	42	24	heuristic	heuristic	ADJ
ijassa-751	42	25	search	search	NOUN
ijassa-751	42	26	of	of	ADP
ijassa-751	42	27	pso	pso	NOUN
ijassa-751	42	28	.	.	PUNCT
ijassa-751	43	1	they	they	PRON
ijassa-751	43	2	divided	divide	VERB
ijassa-751	43	3	spambase	spambase	NOUN
ijassa-751	43	4	dataset	dataset	VERB
ijassa-751	43	5	into	into	ADP
ijassa-751	43	6	70	70	NUM
ijassa-751	43	7	%	%	NOUN
ijassa-751	43	8	training	training	NOUN
ijassa-751	43	9	set	set	NOUN
ijassa-751	43	10	and	and	CCONJ
ijassa-751	43	11	30	30	NUM
ijassa-751	43	12	%	%	NOUN
ijassa-751	43	13	testing	testing	NOUN
ijassa-751	43	14	set	set	NOUN
ijassa-751	43	15	.	.	PUNCT
ijassa-751	44	1	experiments	experiment	NOUN
ijassa-751	44	2	are	be	AUX
ijassa-751	44	3	measured	measure	VERB
ijassa-751	44	4	by	by	ADP
ijassa-751	44	5	using	use	VERB
ijassa-751	44	6	a	a	DET
ijassa-751	44	7	different	different	ADJ
ijassa-751	44	8	number	number	NOUN
ijassa-751	44	9	of	of	ADP
ijassa-751	44	10	hidden	hide	VERB
ijassa-751	44	11	layer	layer	NOUN
ijassa-751	44	12	starting	start	VERB
ijassa-751	44	13	from	from	ADP
ijassa-751	44	14	10	10	NUM
ijassa-751	44	15	to	to	PART
ijassa-751	44	16	50	50	NUM
ijassa-751	44	17	.	.	PUNCT
ijassa-751	45	1	the	the	DET
ijassa-751	45	2	accuracy	accuracy	NOUN
ijassa-751	45	3	obtained	obtain	VERB
ijassa-751	45	4	was	be	AUX
ijassa-751	45	5	91.4	91.4	NUM
ijassa-751	45	6	%	%	NOUN
ijassa-751	45	7	for	for	ADP
ijassa-751	45	8	the	the	DET
ijassa-751	45	9	testing	testing	NOUN
ijassa-751	45	10	set	set	NOUN
ijassa-751	45	11	which	which	PRON
ijassa-751	45	12	was	be	AUX
ijassa-751	45	13	concluded	conclude	VERB
ijassa-751	45	14	that	that	SCONJ
ijassa-751	45	15	the	the	DET
ijassa-751	45	16	hybrid	hybrid	ADJ
ijassa-751	45	17	approach	approach	NOUN
ijassa-751	45	18	had	have	VERB
ijassa-751	45	19	good	good	ADJ
ijassa-751	45	20	performance	performance	NOUN
ijassa-751	45	21	compared	compare	VERB
ijassa-751	45	22	to	to	ADP
ijassa-751	45	23	other	other	ADJ
ijassa-751	45	24	algorithms	algorithm	NOUN
ijassa-751	45	25	tested	test	VERB
ijassa-751	45	26	on	on	ADP
ijassa-751	45	27	the	the	DET
ijassa-751	45	28	same	same	ADJ
ijassa-751	45	29	dataset	dataset	NOUN
ijassa-751	45	30	.	.	PUNCT
ijassa-751	46	1	olatunji	olatunji	NOUN
ijassa-751	46	2	in	in	ADP
ijassa-751	46	3	[	[	X
ijassa-751	46	4	11	11	NUM
ijassa-751	46	5	]	]	PUNCT
ijassa-751	46	6	proposed	propose	VERB
ijassa-751	46	7	support	support	NOUN
ijassa-751	46	8	vector	vector	NOUN
ijassa-751	46	9	machines	machine	NOUN
ijassa-751	46	10	-	-	PUNCT
ijassa-751	46	11	based	base	VERB
ijassa-751	46	12	model	model	NOUN
ijassa-751	46	13	for	for	ADP
ijassa-751	46	14	spam	spam	NOUN
ijassa-751	46	15	detection	detection	NOUN
ijassa-751	46	16	.	.	PUNCT
ijassa-751	47	1	he	he	PRON
ijassa-751	47	2	used	use	VERB
ijassa-751	47	3	a	a	DET
ijassa-751	47	4	systematic	systematic	ADJ
ijassa-751	47	5	parameter	parameter	NOUN
ijassa-751	47	6	search	search	NOUN
ijassa-751	47	7	in	in	ADP
ijassa-751	47	8	order	order	NOUN
ijassa-751	47	9	to	to	PART
ijassa-751	47	10	achieve	achieve	VERB
ijassa-751	47	11	better	well	ADJ
ijassa-751	47	12	spam	spam	NOUN
ijassa-751	47	13	detection	detection	NOUN
ijassa-751	47	14	accuracy	accuracy	NOUN
ijassa-751	47	15	.	.	PUNCT
ijassa-751	48	1	the	the	DET
ijassa-751	48	2	accuracy	accuracy	NOUN
ijassa-751	48	3	obtained	obtain	VERB
ijassa-751	48	4	was	be	AUX
ijassa-751	48	5	94.06	94.06	NUM
ijassa-751	48	6	%	%	NOUN
ijassa-751	48	7	for	for	ADP
ijassa-751	48	8	the	the	DET
ijassa-751	48	9	testing	testing	NOUN
ijassa-751	48	10	set	set	VERB
ijassa-751	48	11	.	.	PUNCT
ijassa-751	49	1	experimental	experimental	ADJ
ijassa-751	49	2	results	result	NOUN
ijassa-751	49	3	show	show	VERB
ijassa-751	49	4	that	that	SCONJ
ijassa-751	49	5	the	the	DET
ijassa-751	49	6	proposed	propose	VERB
ijassa-751	49	7	scheme	scheme	NOUN
ijassa-751	49	8	outperformed	outperform	VERB
ijassa-751	49	9	other	other	ADJ
ijassa-751	49	10	published	publish	VERB
ijassa-751	49	11	algorithms	algorithm	NOUN
ijassa-751	49	12	tested	test	VERB
ijassa-751	49	13	on	on	ADP
ijassa-751	49	14	spambase	spambase	PROPN
ijassa-751	49	15	dataset	dataset	NOUN
ijassa-751	49	16	used	use	VERB
ijassa-751	49	17	in	in	ADP
ijassa-751	49	18	this	this	DET
ijassa-751	49	19	work	work	NOUN
ijassa-751	49	20	.	.	PUNCT
ijassa-751	50	1	considering	consider	VERB
ijassa-751	50	2	the	the	DET
ijassa-751	50	3	performance	performance	NOUN
ijassa-751	50	4	accuracy	accuracy	NOUN
ijassa-751	50	5	achieved	achieve	VERB
ijassa-751	50	6	till	till	SCONJ
ijassa-751	50	7	now	now	ADV
ijassa-751	50	8	,	,	PUNCT
ijassa-751	50	9	there	there	PRON
ijassa-751	50	10	is	be	VERB
ijassa-751	50	11	still	still	ADV
ijassa-751	50	12	need	need	ADJ
ijassa-751	50	13	to	to	PART
ijassa-751	50	14	try	try	VERB
ijassa-751	50	15	to	to	PART
ijassa-751	50	16	achieve	achieve	VERB
ijassa-751	50	17	better	well	ADJ
ijassa-751	50	18	results	result	NOUN
ijassa-751	50	19	on	on	ADP
ijassa-751	50	20	the	the	DET
ijassa-751	50	21	same	same	ADJ
ijassa-751	50	22	dataset	dataset	NOUN
ijassa-751	50	23	.	.	PUNCT
ijassa-751	51	1	the	the	DET
ijassa-751	51	2	main	main	ADJ
ijassa-751	51	3	aim	aim	NOUN
ijassa-751	51	4	of	of	ADP
ijassa-751	51	5	this	this	DET
ijassa-751	51	6	paper	paper	NOUN
ijassa-751	51	7	is	be	AUX
ijassa-751	51	8	to	to	PART
ijassa-751	51	9	propose	propose	VERB
ijassa-751	51	10	an	an	DET
ijassa-751	51	11	alternative	alternative	ADJ
ijassa-751	51	12	algorithm	algorithm	NOUN
ijassa-751	51	13	that	that	PRON
ijassa-751	51	14	can	can	AUX
ijassa-751	51	15	accomplish	accomplish	VERB
ijassa-751	51	16	a	a	DET
ijassa-751	51	17	performance	performance	NOUN
ijassa-751	51	18	higher	high	ADJ
ijassa-751	51	19	than	than	ADP
ijassa-751	51	20	previous	previous	ADJ
ijassa-751	51	21	algorithms	algorithm	NOUN
ijassa-751	51	22	.	.	PUNCT
ijassa-751	52	1	in	in	ADP
ijassa-751	52	2	this	this	DET
ijassa-751	52	3	paper	paper	NOUN
ijassa-751	52	4	,	,	PUNCT
ijassa-751	52	5	hybrid	hybrid	ADJ
ijassa-751	52	6	particle	particle	NOUN
ijassa-751	52	7	swarm	swarm	NOUN
ijassa-751	52	8	optimization	optimization	NOUN
ijassa-751	52	9	and	and	CCONJ
ijassa-751	52	10	pegasos	pegasos	PROPN
ijassa-751	52	11	algorithm	algorithm	NOUN
ijassa-751	52	12	(	(	PUNCT
ijassa-751	52	13	pso	pso	NOUN
ijassa-751	52	14	-	-	PUNCT
ijassa-751	52	15	pegasos	pegasos	NOUN
ijassa-751	52	16	)	)	PUNCT
ijassa-751	52	17	is	be	AUX
ijassa-751	52	18	proposed	propose	VERB
ijassa-751	52	19	to	to	PART
ijassa-751	52	20	achieve	achieve	VERB
ijassa-751	52	21	better	well	ADJ
ijassa-751	52	22	accuracy	accuracy	NOUN
ijassa-751	52	23	of	of	ADP
ijassa-751	52	24	spam	spam	NOUN
ijassa-751	52	25	email	email	NOUN
ijassa-751	52	26	detection	detection	NOUN
ijassa-751	52	27	.	.	PUNCT
ijassa-751	53	1	pegasos	pegasos	PROPN
ijassa-751	53	2	algorithm	algorithm	PROPN
ijassa-751	53	3	is	be	AUX
ijassa-751	53	4	applied	apply	VERB
ijassa-751	53	5	to	to	PART
ijassa-751	53	6	solve	solve	VERB
ijassa-751	53	7	the	the	DET
ijassa-751	53	8	optimization	optimization	NOUN
ijassa-751	53	9	problem	problem	NOUN
ijassa-751	53	10	cast	cast	VERB
ijassa-751	53	11	by	by	ADP
ijassa-751	53	12	support	support	NOUN
ijassa-751	53	13	vector	vector	NOUN
ijassa-751	53	14	machines	machine	NOUN
ijassa-751	53	15	(	(	PUNCT
ijassa-751	53	16	svm	svm	PROPN
ijassa-751	53	17	)	)	PUNCT
ijassa-751	53	18	while	while	SCONJ
ijassa-751	53	19	particle	particle	NOUN
ijassa-751	53	20	swarm	swarm	NOUN
ijassa-751	53	21	optimization	optimization	NOUN
ijassa-751	53	22	is	be	AUX
ijassa-751	53	23	used	use	VERB
ijassa-751	53	24	as	as	ADP
ijassa-751	53	25	a	a	DET
ijassa-751	53	26	search	search	NOUN
ijassa-751	53	27	strategy	strategy	NOUN
ijassa-751	53	28	to	to	PART
ijassa-751	53	29	select	select	VERB
ijassa-751	53	30	the	the	DET
ijassa-751	53	31	optimal	optimal	ADJ
ijassa-751	53	32	parameters	parameter	NOUN
ijassa-751	53	33	(	(	PUNCT
ijassa-751	53	34	the	the	DET
ijassa-751	53	35	weights	weight	NOUN
ijassa-751	53	36	)	)	PUNCT
ijassa-751	53	37	for	for	ADP
ijassa-751	53	38	pegasos	pegasos	NOUN
ijassa-751	53	39	algorithm	algorithm	NOUN
ijassa-751	53	40	,	,	PUNCT
ijassa-751	53	41	which	which	PRON
ijassa-751	53	42	means	mean	VERB
ijassa-751	53	43	in	in	ADP
ijassa-751	53	44	each	each	DET
ijassa-751	53	45	iteration	iteration	NOUN
ijassa-751	53	46	of	of	ADP
ijassa-751	53	47	pso	pso	NOUN
ijassa-751	53	48	,	,	PUNCT
ijassa-751	53	49	the	the	DET
ijassa-751	53	50	weights	weight	NOUN
ijassa-751	53	51	(	(	PUNCT
ijassa-751	53	52	w	w	NOUN
ijassa-751	53	53	-	-	PUNCT
ijassa-751	53	54	parameters	parameter	NOUN
ijassa-751	53	55	)	)	PUNCT
ijassa-751	53	56	are	be	AUX
ijassa-751	53	57	changed	change	VERB
ijassa-751	53	58	based	base	VERB
ijassa-751	53	59	on	on	ADP
ijassa-751	53	60	the	the	DET
ijassa-751	53	61	fitness	fitness	NOUN
ijassa-751	53	62	function	function	NOUN
ijassa-751	53	63	(	(	PUNCT
ijassa-751	53	64	mean	mean	INTJ
ijassa-751	53	65	squared	square	VERB
ijassa-751	53	66	error	error	NOUN
ijassa-751	53	67	)	)	PUNCT
ijassa-751	53	68	.	.	PUNCT
ijassa-751	54	1	after	after	ADP
ijassa-751	54	2	running	run	VERB
ijassa-751	54	3	pso	pso	NOUN
ijassa-751	54	4	algorithm	algorithm	NOUN
ijassa-751	54	5	a	a	DET
ijassa-751	54	6	number	number	NOUN
ijassa-751	54	7	of	of	ADP
ijassa-751	54	8	iterations	iteration	NOUN
ijassa-751	54	9	,	,	PUNCT
ijassa-751	54	10	it	it	PRON
ijassa-751	54	11	will	will	AUX
ijassa-751	54	12	obtain	obtain	VERB
ijassa-751	54	13	the	the	DET
ijassa-751	54	14	best	good	ADJ
ijassa-751	54	15	optimal	optimal	ADJ
ijassa-751	54	16	w	w	NOUN
ijassa-751	54	17	-	-	PUNCT
ijassa-751	54	18	parameter	parameter	NOUN
ijassa-751	54	19	for	for	ADP
ijassa-751	54	20	pegasos	pegasos	NOUN
ijassa-751	54	21	algorithm	algorithm	NOUN
ijassa-751	54	22	.	.	PUNCT
ijassa-751	55	1	in	in	ADP
ijassa-751	55	2	this	this	DET
ijassa-751	55	3	paper	paper	NOUN
ijassa-751	55	4	,	,	PUNCT
ijassa-751	55	5	comparison	comparison	NOUN
ijassa-751	55	6	of	of	ADP
ijassa-751	55	7	performance	performance	NOUN
ijassa-751	55	8	measures	measure	NOUN
ijassa-751	55	9	of	of	ADP
ijassa-751	55	10	pegasos	pegasos	NOUN
ijassa-751	55	11	and	and	CCONJ
ijassa-751	55	12	hybrid	hybrid	ADJ
ijassa-751	55	13	algorithm	algorithm	NOUN
ijassa-751	55	14	(	(	PUNCT
ijassa-751	55	15	pso	pso	NOUN
ijassa-751	55	16	-	-	PUNCT
ijassa-751	55	17	pegasos	pegasos	NOUN
ijassa-751	55	18	)	)	PUNCT
ijassa-751	55	19	for	for	ADP
ijassa-751	55	20	training	training	NOUN
ijassa-751	55	21	and	and	CCONJ
ijassa-751	55	22	testing	testing	NOUN
ijassa-751	55	23	sets	set	NOUN
ijassa-751	55	24	is	be	AUX
ijassa-751	55	25	presented	present	VERB
ijassa-751	55	26	for	for	ADP
ijassa-751	55	27	spam	spam	NOUN
ijassa-751	55	28	email	email	NOUN
ijassa-751	55	29	detection	detection	NOUN
ijassa-751	55	30	.	.	PUNCT
ijassa-751	56	1	the	the	DET
ijassa-751	56	2	rest	rest	NOUN
ijassa-751	56	3	of	of	ADP
ijassa-751	56	4	this	this	DET
ijassa-751	56	5	paper	paper	NOUN
ijassa-751	56	6	is	be	AUX
ijassa-751	56	7	structured	structure	VERB
ijassa-751	56	8	as	as	SCONJ
ijassa-751	56	9	follows	follow	VERB
ijassa-751	56	10	:	:	PUNCT
ijassa-751	56	11	the	the	DET
ijassa-751	56	12	fundamentals	fundamental	NOUN
ijassa-751	56	13	of	of	ADP
ijassa-751	56	14	particle	particle	NOUN
ijassa-751	56	15	swarm	swarm	NOUN
ijassa-751	56	16	optimization	optimization	NOUN
ijassa-751	56	17	and	and	CCONJ
ijassa-751	56	18	the	the	DET
ijassa-751	56	19	principles	principle	NOUN
ijassa-751	56	20	of	of	ADP
ijassa-751	56	21	the	the	DET
ijassa-751	56	22	original	original	ADJ
ijassa-751	56	23	pegasos	pegasos	NOUN
ijassa-751	56	24	algorithm	algorithm	NOUN
ijassa-751	56	25	are	be	AUX
ijassa-751	56	26	introduced	introduce	VERB
ijassa-751	56	27	in	in	ADP
ijassa-751	56	28	section	section	NOUN
ijassa-751	56	29	copyright	copyright	NOUN
ijassa-751	56	30	c	c	ADP
ijassa-751	56	31	©	©	PROPN
ijassa-751	56	32	2019	2019	NUM
ijassa-751	56	33	assa	assa	NOUN
ijassa-751	56	34	.	.	PUNCT
ijassa-751	57	1	adv	adv	PROPN
ijassa-751	57	2	.	.	PUNCT
ijassa-751	58	1	in	in	ADP
ijassa-751	58	2	systems	system	NOUN
ijassa-751	58	3	science	science	NOUN
ijassa-751	58	4	and	and	CCONJ
ijassa-751	58	5	appl.(2019	appl.(2019	NOUN
ijassa-751	58	6	)	)	PUNCT
ijassa-751	58	7	hybrid	hybrid	ADJ
ijassa-751	58	8	particle	particle	NOUN
ijassa-751	58	9	swarm	swarm	NOUN
ijassa-751	58	10	optimization	optimization	NOUN
ijassa-751	58	11	and	and	CCONJ
ijassa-751	58	12	pegasos	pegasos	NOUN
ijassa-751	58	13	algorithm	algorithm	NOUN
ijassa-751	58	14	for	for	ADP
ijassa-751	58	15	spam	spam	NOUN
ijassa-751	58	16	email	email	NOUN
ijassa-751	58	17	detection13	detection13	NOUN
ijassa-751	58	18	2	2	NUM
ijassa-751	58	19	.	.	PUNCT
ijassa-751	58	20	section	section	NOUN
ijassa-751	58	21	3	3	NUM
ijassa-751	58	22	describes	describe	VERB
ijassa-751	58	23	the	the	DET
ijassa-751	58	24	details	detail	NOUN
ijassa-751	58	25	of	of	ADP
ijassa-751	58	26	the	the	DET
ijassa-751	58	27	proposed	propose	VERB
ijassa-751	58	28	algorithm	algorithm	NOUN
ijassa-751	58	29	.	.	PUNCT
ijassa-751	59	1	experimental	experimental	ADJ
ijassa-751	59	2	results	result	NOUN
ijassa-751	59	3	and	and	CCONJ
ijassa-751	59	4	discussions	discussion	NOUN
ijassa-751	59	5	are	be	AUX
ijassa-751	59	6	demonstrated	demonstrate	VERB
ijassa-751	59	7	in	in	ADP
ijassa-751	59	8	section	section	NOUN
ijassa-751	59	9	4	4	NUM
ijassa-751	59	10	.	.	PUNCT
ijassa-751	60	1	finally	finally	ADV
ijassa-751	60	2	,	,	PUNCT
ijassa-751	60	3	section	section	NOUN
ijassa-751	60	4	5	5	NUM
ijassa-751	60	5	concludes	conclude	VERB
ijassa-751	60	6	the	the	DET
ijassa-751	60	7	paper	paper	NOUN
ijassa-751	60	8	.	.	PUNCT
ijassa-751	61	1	2	2	X
ijassa-751	61	2	.	.	NUM
ijassa-751	61	3	preliminaries	preliminary	NOUN
ijassa-751	61	4	2.1	2.1	NUM
ijassa-751	61	5	.	.	PUNCT
ijassa-751	61	6	particle	particle	NOUN
ijassa-751	61	7	swarm	swarm	NOUN
ijassa-751	61	8	optimization	optimization	NOUN
ijassa-751	61	9	particle	particle	NOUN
ijassa-751	61	10	swarm	swarm	NOUN
ijassa-751	61	11	optimization	optimization	NOUN
ijassa-751	61	12	(	(	PUNCT
ijassa-751	61	13	pso	pso	NOUN
ijassa-751	61	14	)	)	PUNCT
ijassa-751	61	15	was	be	AUX
ijassa-751	61	16	invented	invent	VERB
ijassa-751	61	17	by	by	ADP
ijassa-751	61	18	kennedy	kennedy	PROPN
ijassa-751	61	19	and	and	CCONJ
ijassa-751	61	20	eberhart	eberhart	NOUN
ijassa-751	61	21	in	in	ADP
ijassa-751	61	22	1995	1995	NUM
ijassa-751	61	23	[	[	X
ijassa-751	61	24	12	12	NUM
ijassa-751	61	25	]	]	PUNCT
ijassa-751	61	26	.	.	PUNCT
ijassa-751	62	1	pso	pso	NOUN
ijassa-751	62	2	is	be	AUX
ijassa-751	62	3	a	a	DET
ijassa-751	62	4	widely	widely	ADV
ijassa-751	62	5	used	use	VERB
ijassa-751	62	6	population	population	NOUN
ijassa-751	62	7	-	-	PUNCT
ijassa-751	62	8	based	base	VERB
ijassa-751	62	9	stochastic	stochastic	ADJ
ijassa-751	62	10	optimization	optimization	NOUN
ijassa-751	62	11	technique	technique	NOUN
ijassa-751	62	12	since	since	SCONJ
ijassa-751	62	13	it	it	PRON
ijassa-751	62	14	has	have	VERB
ijassa-751	62	15	strong	strong	ADJ
ijassa-751	62	16	global	global	ADJ
ijassa-751	62	17	search	search	NOUN
ijassa-751	62	18	capability	capability	NOUN
ijassa-751	62	19	,	,	PUNCT
ijassa-751	62	20	high	high	ADJ
ijassa-751	62	21	convergence	convergence	NOUN
ijassa-751	62	22	speed	speed	NOUN
ijassa-751	62	23	,	,	PUNCT
ijassa-751	62	24	high	high	ADJ
ijassa-751	62	25	robustness	robustness	NOUN
ijassa-751	62	26	and	and	CCONJ
ijassa-751	62	27	is	be	AUX
ijassa-751	62	28	conceptually	conceptually	ADV
ijassa-751	62	29	very	very	ADV
ijassa-751	62	30	simple	simple	ADJ
ijassa-751	63	1	[	[	X
ijassa-751	63	2	13	13	NUM
ijassa-751	63	3	,	,	PUNCT
ijassa-751	63	4	14	14	NUM
ijassa-751	63	5	,	,	PUNCT
ijassa-751	63	6	15	15	NUM
ijassa-751	63	7	]	]	PUNCT
ijassa-751	63	8	.	.	PUNCT
ijassa-751	64	1	pso	pso	NOUN
ijassa-751	64	2	is	be	AUX
ijassa-751	64	3	still	still	ADV
ijassa-751	64	4	attracted	attract	VERB
ijassa-751	64	5	the	the	DET
ijassa-751	64	6	attention	attention	NOUN
ijassa-751	64	7	of	of	ADP
ijassa-751	64	8	a	a	DET
ijassa-751	64	9	lot	lot	NOUN
ijassa-751	64	10	of	of	ADP
ijassa-751	64	11	researchers	researcher	NOUN
ijassa-751	64	12	over	over	ADP
ijassa-751	64	13	nearly	nearly	ADV
ijassa-751	64	14	a	a	DET
ijassa-751	64	15	quarter	quarter	NOUN
ijassa-751	64	16	century	century	NOUN
ijassa-751	64	17	.	.	PUNCT
ijassa-751	65	1	particle	particle	NOUN
ijassa-751	65	2	swarm	swarm	NOUN
ijassa-751	65	3	optimization	optimization	NOUN
ijassa-751	65	4	simulates	simulate	VERB
ijassa-751	65	5	the	the	DET
ijassa-751	65	6	social	social	ADJ
ijassa-751	65	7	behavior	behavior	NOUN
ijassa-751	65	8	among	among	ADP
ijassa-751	65	9	species	specie	NOUN
ijassa-751	65	10	such	such	ADJ
ijassa-751	65	11	as	as	ADP
ijassa-751	65	12	fish	fish	NOUN
ijassa-751	65	13	schools	school	NOUN
ijassa-751	65	14	,	,	PUNCT
ijassa-751	65	15	bird	bird	NOUN
ijassa-751	65	16	flocks	flock	NOUN
ijassa-751	65	17	.	.	PUNCT
ijassa-751	66	1	the	the	DET
ijassa-751	66	2	set	set	NOUN
ijassa-751	66	3	of	of	ADP
ijassa-751	66	4	particles	particle	NOUN
ijassa-751	66	5	represent	represent	VERB
ijassa-751	66	6	a	a	DET
ijassa-751	66	7	population	population	NOUN
ijassa-751	66	8	of	of	ADP
ijassa-751	66	9	the	the	DET
ijassa-751	66	10	possible	possible	ADJ
ijassa-751	66	11	solutions	solution	NOUN
ijassa-751	66	12	.	.	PUNCT
ijassa-751	67	1	in	in	ADP
ijassa-751	67	2	canonical	canonical	ADJ
ijassa-751	67	3	pso	pso	NOUN
ijassa-751	67	4	algorithm	algorithm	NOUN
ijassa-751	67	5	,	,	PUNCT
ijassa-751	67	6	particles	particle	NOUN
ijassa-751	67	7	are	be	AUX
ijassa-751	67	8	initialized	initialize	VERB
ijassa-751	67	9	with	with	ADP
ijassa-751	67	10	a	a	DET
ijassa-751	67	11	population	population	NOUN
ijassa-751	67	12	to	to	PART
ijassa-751	67	13	get	get	VERB
ijassa-751	67	14	a	a	DET
ijassa-751	67	15	random	random	ADJ
ijassa-751	67	16	solution	solution	NOUN
ijassa-751	67	17	.	.	PUNCT
ijassa-751	68	1	then	then	ADV
ijassa-751	68	2	,	,	PUNCT
ijassa-751	68	3	the	the	DET
ijassa-751	68	4	particles	particle	NOUN
ijassa-751	68	5	fly	fly	VERB
ijassa-751	68	6	iteratively	iteratively	ADV
ijassa-751	68	7	around	around	ADV
ijassa-751	68	8	in	in	ADP
ijassa-751	68	9	d	d	ADJ
ijassa-751	68	10	-	-	ADJ
ijassa-751	68	11	dimension	dimension	NOUN
ijassa-751	68	12	search	search	NOUN
ijassa-751	68	13	space	space	NOUN
ijassa-751	68	14	to	to	PART
ijassa-751	68	15	search	search	VERB
ijassa-751	68	16	the	the	DET
ijassa-751	68	17	optimal	optimal	ADJ
ijassa-751	68	18	solution	solution	NOUN
ijassa-751	68	19	,	,	PUNCT
ijassa-751	68	20	where	where	SCONJ
ijassa-751	68	21	the	the	DET
ijassa-751	68	22	proper	proper	ADJ
ijassa-751	68	23	fitness	fitness	NOUN
ijassa-751	68	24	function	function	NOUN
ijassa-751	68	25	can	can	AUX
ijassa-751	68	26	be	be	AUX
ijassa-751	68	27	calculated	calculate	VERB
ijassa-751	68	28	according	accord	VERB
ijassa-751	68	29	to	to	ADP
ijassa-751	68	30	the	the	DET
ijassa-751	68	31	problem	problem	NOUN
ijassa-751	68	32	.	.	PUNCT
ijassa-751	69	1	each	each	DET
ijassa-751	69	2	particle	particle	NOUN
ijassa-751	69	3	is	be	AUX
ijassa-751	69	4	indicated	indicate	VERB
ijassa-751	69	5	by	by	ADP
ijassa-751	69	6	a	a	DET
ijassa-751	69	7	row	row	NOUN
ijassa-751	69	8	vector	vector	NOUN
ijassa-751	69	9	~xi	~xi	PROPN
ijassa-751	69	10	,	,	PUNCT
ijassa-751	69	11	where	where	SCONJ
ijassa-751	69	12	i	i	PRON
ijassa-751	69	13	is	be	AUX
ijassa-751	69	14	the	the	DET
ijassa-751	69	15	index	index	NOUN
ijassa-751	69	16	of	of	ADP
ijassa-751	69	17	the	the	DET
ijassa-751	69	18	particle	particle	NOUN
ijassa-751	69	19	,	,	PUNCT
ijassa-751	69	20	and	and	CCONJ
ijassa-751	69	21	a	a	DET
ijassa-751	69	22	velocity	velocity	NOUN
ijassa-751	69	23	indicated	indicate	VERB
ijassa-751	69	24	by	by	ADP
ijassa-751	69	25	~vi	~vi	PROPN
ijassa-751	69	26	.	.	PUNCT
ijassa-751	70	1	the	the	DET
ijassa-751	70	2	best	good	ADJ
ijassa-751	70	3	position	position	NOUN
ijassa-751	70	4	of	of	ADP
ijassa-751	70	5	the	the	DET
ijassa-751	70	6	particle	particle	NOUN
ijassa-751	70	7	(	(	PUNCT
ijassa-751	70	8	pbest	pbest	NOUN
ijassa-751	70	9	)	)	PUNCT
ijassa-751	70	10	is	be	AUX
ijassa-751	70	11	indicated	indicate	VERB
ijassa-751	70	12	by	by	ADP
ijassa-751	70	13	vector	vector	NOUN
ijassa-751	70	14	~x#i	~x#i	PROPN
ijassa-751	70	15	,	,	PUNCT
ijassa-751	70	16	and	and	CCONJ
ijassa-751	70	17	its	its	PRON
ijassa-751	70	18	j	j	PROPN
ijassa-751	70	19	-	-	PUNCT
ijassa-751	70	20	th	th	VERB
ijassa-751	70	21	dimensional	dimensional	ADJ
ijassa-751	70	22	value	value	NOUN
ijassa-751	70	23	is	be	AUX
ijassa-751	70	24	x#ij	x#ij	ADJ
ijassa-751	70	25	,	,	PUNCT
ijassa-751	70	26	while	while	SCONJ
ijassa-751	70	27	the	the	DET
ijassa-751	70	28	best	good	ADJ
ijassa-751	70	29	position	position	NOUN
ijassa-751	70	30	among	among	ADP
ijassa-751	70	31	the	the	DET
ijassa-751	70	32	swarm	swarm	NOUN
ijassa-751	70	33	(	(	PUNCT
ijassa-751	70	34	gbest	gbest	NOUN
ijassa-751	70	35	)	)	PUNCT
ijassa-751	70	36	is	be	AUX
ijassa-751	70	37	indicated	indicate	VERB
ijassa-751	70	38	by	by	ADP
ijassa-751	70	39	a	a	DET
ijassa-751	70	40	vector	vector	NOUN
ijassa-751	70	41	~x∗	~x∗	NOUN
ijassa-751	70	42	,	,	PUNCT
ijassa-751	70	43	and	and	CCONJ
ijassa-751	70	44	its	its	PRON
ijassa-751	70	45	j	j	PROPN
ijassa-751	70	46	-	-	PUNCT
ijassa-751	70	47	th	th	VERB
ijassa-751	70	48	dimensional	dimensional	ADJ
ijassa-751	70	49	value	value	NOUN
ijassa-751	70	50	is	be	AUX
ijassa-751	70	51	x∗j	x∗j	PROPN
ijassa-751	70	52	.	.	PUNCT
ijassa-751	71	1	in	in	ADP
ijassa-751	71	2	each	each	DET
ijassa-751	71	3	iteration	iteration	NOUN
ijassa-751	71	4	t	t	PROPN
ijassa-751	71	5	,	,	PUNCT
ijassa-751	71	6	the	the	DET
ijassa-751	71	7	velocity	velocity	NOUN
ijassa-751	71	8	updating	update	VERB
ijassa-751	71	9	formula	formula	NOUN
ijassa-751	71	10	of	of	ADP
ijassa-751	71	11	particle	particle	NOUN
ijassa-751	71	12	is	be	AUX
ijassa-751	71	13	calculated	calculate	VERB
ijassa-751	71	14	by	by	ADP
ijassa-751	71	15	eq	eq	PROPN
ijassa-751	71	16	.	.	PUNCT
ijassa-751	72	1	(	(	PUNCT
ijassa-751	72	2	2.1	2.1	NUM
ijassa-751	72	3	)	)	PUNCT
ijassa-751	72	4	and	and	CCONJ
ijassa-751	72	5	the	the	DET
ijassa-751	72	6	position	position	NOUN
ijassa-751	72	7	updating	update	VERB
ijassa-751	72	8	formula	formula	NOUN
ijassa-751	72	9	of	of	ADP
ijassa-751	72	10	particle	particle	NOUN
ijassa-751	72	11	is	be	AUX
ijassa-751	72	12	determined	determine	VERB
ijassa-751	72	13	by	by	ADP
ijassa-751	72	14	the	the	DET
ijassa-751	72	15	sum	sum	NOUN
ijassa-751	72	16	of	of	ADP
ijassa-751	72	17	the	the	DET
ijassa-751	72	18	previous	previous	ADJ
ijassa-751	72	19	position	position	NOUN
ijassa-751	72	20	and	and	CCONJ
ijassa-751	72	21	the	the	DET
ijassa-751	72	22	new	new	ADJ
ijassa-751	72	23	velocity	velocity	NOUN
ijassa-751	72	24	by	by	ADP
ijassa-751	72	25	eq	eq	PROPN
ijassa-751	72	26	.	.	PUNCT
ijassa-751	73	1	(	(	PUNCT
ijassa-751	73	2	2.2	2.2	NUM
ijassa-751	73	3	)	)	PUNCT
ijassa-751	73	4	.	.	PUNCT
ijassa-751	74	1	vij(t+	vij(t+	NOUN
ijassa-751	74	2	1	1	NUM
ijassa-751	74	3	)	)	PUNCT
ijassa-751	74	4	=	=	PRON
ijassa-751	74	5	{	{	PUNCT
ijassa-751	74	6	wvij(t	wvij(t	PROPN
ijassa-751	74	7	)	)	PUNCT
ijassa-751	75	1	+	+	NUM
ijassa-751	75	2	c1r1(x	c1r1(x	NOUN
ijassa-751	75	3	#	#	NOUN
ijassa-751	75	4	ij(t)−	ij(t)−	PROPN
ijassa-751	75	5	xij(t	xij(t	PROPN
ijassa-751	75	6	)	)	PUNCT
ijassa-751	75	7	)	)	PUNCT
ijassa-751	76	1	+	+	X
ijassa-751	76	2	c2r2(x	c2r2(x	AUX
ijassa-751	76	3	∗	∗	VERB
ijassa-751	76	4	j(t)−	j(t)−	PROPN
ijassa-751	76	5	xij(t	xij(t	PROPN
ijassa-751	76	6	)	)	PUNCT
ijassa-751	76	7	)	)	PUNCT
ijassa-751	76	8	(	(	PUNCT
ijassa-751	76	9	2.1	2.1	NUM
ijassa-751	76	10	)	)	PUNCT
ijassa-751	76	11	xij(t+	xij(t+	NOUN
ijassa-751	76	12	1	1	NUM
ijassa-751	76	13	)	)	PUNCT
ijassa-751	76	14	=	=	SYM
ijassa-751	76	15	xij(t	xij(t	PROPN
ijassa-751	76	16	)	)	PUNCT
ijassa-751	76	17	+	+	CCONJ
ijassa-751	76	18	vij(t+	vij(t+	NOUN
ijassa-751	76	19	1	1	NUM
ijassa-751	76	20	)	)	PUNCT
ijassa-751	76	21	.	.	PUNCT
ijassa-751	77	1	(	(	PUNCT
ijassa-751	77	2	2.2	2.2	NUM
ijassa-751	77	3	)	)	PUNCT
ijassa-751	77	4	where	where	SCONJ
ijassa-751	77	5	c1	c1	PROPN
ijassa-751	77	6	and	and	CCONJ
ijassa-751	77	7	c2	c2	PROPN
ijassa-751	77	8	are	be	AUX
ijassa-751	77	9	nonnegative	nonnegative	ADJ
ijassa-751	77	10	constants	constant	NOUN
ijassa-751	77	11	called	call	VERB
ijassa-751	77	12	as	as	ADP
ijassa-751	77	13	learning	learn	VERB
ijassa-751	77	14	factors	factor	NOUN
ijassa-751	77	15	,	,	PUNCT
ijassa-751	77	16	r1	r1	PROPN
ijassa-751	77	17	and	and	CCONJ
ijassa-751	77	18	r2	r2	PROPN
ijassa-751	77	19	are	be	AUX
ijassa-751	77	20	random	random	ADJ
ijassa-751	77	21	numbers	number	NOUN
ijassa-751	77	22	uniformly	uniformly	ADV
ijassa-751	77	23	distributed	distribute	VERB
ijassa-751	77	24	in	in	ADP
ijassa-751	77	25	u(0,1	u(0,1	NOUN
ijassa-751	77	26	)	)	PUNCT
ijassa-751	77	27	for	for	ADP
ijassa-751	77	28	the	the	DET
ijassa-751	77	29	j	j	PROPN
ijassa-751	77	30	-	-	PUNCT
ijassa-751	77	31	th	th	VERB
ijassa-751	77	32	dimension	dimension	NOUN
ijassa-751	77	33	of	of	ADP
ijassa-751	77	34	the	the	DET
ijassa-751	77	35	i	i	PROPN
ijassa-751	77	36	-	-	PUNCT
ijassa-751	77	37	th	th	X
ijassa-751	77	38	particle	particle	NOUN
ijassa-751	77	39	.	.	PUNCT
ijassa-751	78	1	w	w	PROPN
ijassa-751	78	2	is	be	AUX
ijassa-751	78	3	the	the	DET
ijassa-751	78	4	inertia	inertia	NOUN
ijassa-751	78	5	weight	weight	NOUN
ijassa-751	78	6	,	,	PUNCT
ijassa-751	78	7	which	which	PRON
ijassa-751	78	8	can	can	AUX
ijassa-751	78	9	increase	increase	VERB
ijassa-751	78	10	the	the	DET
ijassa-751	78	11	algorithm	algorithm	NOUN
ijassa-751	78	12	search	search	NOUN
ijassa-751	78	13	capability	capability	NOUN
ijassa-751	78	14	and	and	CCONJ
ijassa-751	78	15	control	control	VERB
ijassa-751	78	16	the	the	DET
ijassa-751	78	17	process	process	NOUN
ijassa-751	78	18	of	of	ADP
ijassa-751	78	19	algorithms	algorithm	NOUN
ijassa-751	78	20	searching	search	VERB
ijassa-751	78	21	.	.	PUNCT
ijassa-751	79	1	eq	eq	ADP
ijassa-751	79	2	.	.	PUNCT
ijassa-751	80	1	(	(	PUNCT
ijassa-751	80	2	2.1	2.1	NUM
ijassa-751	80	3	)	)	PUNCT
ijassa-751	80	4	makes	make	VERB
ijassa-751	80	5	each	each	DET
ijassa-751	80	6	particle	particle	NOUN
ijassa-751	80	7	tends	tend	VERB
ijassa-751	80	8	to	to	PART
ijassa-751	80	9	move	move	VERB
ijassa-751	80	10	across	across	ADP
ijassa-751	80	11	the	the	DET
ijassa-751	80	12	design	design	NOUN
ijassa-751	80	13	space	space	NOUN
ijassa-751	80	14	,	,	PUNCT
ijassa-751	80	15	considering	consider	VERB
ijassa-751	80	16	its	its	PRON
ijassa-751	80	17	own	own	ADJ
ijassa-751	80	18	experience	experience	NOUN
ijassa-751	80	19	,	,	PUNCT
ijassa-751	80	20	which	which	PRON
ijassa-751	80	21	is	be	AUX
ijassa-751	80	22	the	the	DET
ijassa-751	80	23	memory	memory	NOUN
ijassa-751	80	24	of	of	ADP
ijassa-751	80	25	its	its	PRON
ijassa-751	80	26	best	good	ADJ
ijassa-751	80	27	fitness	fitness	NOUN
ijassa-751	80	28	function	function	NOUN
ijassa-751	80	29	value	value	NOUN
ijassa-751	80	30	achieved	achieve	VERB
ijassa-751	80	31	by	by	ADP
ijassa-751	80	32	the	the	DET
ijassa-751	80	33	particle	particle	NOUN
ijassa-751	80	34	in	in	ADP
ijassa-751	80	35	the	the	DET
ijassa-751	80	36	past	past	NOUN
ijassa-751	80	37	,	,	PUNCT
ijassa-751	80	38	and	and	CCONJ
ijassa-751	80	39	the	the	DET
ijassa-751	80	40	experience	experience	NOUN
ijassa-751	80	41	of	of	ADP
ijassa-751	80	42	its	its	PRON
ijassa-751	80	43	most	most	ADV
ijassa-751	80	44	successful	successful	ADJ
ijassa-751	80	45	particle	particle	NOUN
ijassa-751	80	46	in	in	ADP
ijassa-751	80	47	the	the	DET
ijassa-751	80	48	swarm	swarm	NOUN
ijassa-751	80	49	.	.	PUNCT
ijassa-751	81	1	in	in	ADP
ijassa-751	81	2	pso	pso	NOUN
ijassa-751	81	3	algorithm	algorithm	NOUN
ijassa-751	81	4	,	,	PUNCT
ijassa-751	81	5	the	the	DET
ijassa-751	81	6	particles	particle	NOUN
ijassa-751	81	7	tend	tend	VERB
ijassa-751	81	8	to	to	PART
ijassa-751	81	9	search	search	VERB
ijassa-751	81	10	the	the	DET
ijassa-751	81	11	solutions	solution	NOUN
ijassa-751	81	12	in	in	ADP
ijassa-751	81	13	the	the	DET
ijassa-751	81	14	problem	problem	NOUN
ijassa-751	81	15	space	space	NOUN
ijassa-751	81	16	with	with	ADP
ijassa-751	81	17	a	a	DET
ijassa-751	81	18	range	range	NOUN
ijassa-751	81	19	[	[	X
ijassa-751	81	20	−s	−s	NOUN
ijassa-751	81	21	,	,	PUNCT
ijassa-751	81	22	s	s	X
ijassa-751	81	23	]	]	PUNCT
ijassa-751	81	24	to	to	PART
ijassa-751	81	25	prevent	prevent	VERB
ijassa-751	81	26	the	the	DET
ijassa-751	81	27	particle	particle	NOUN
ijassa-751	81	28	from	from	ADP
ijassa-751	81	29	flying	fly	VERB
ijassa-751	81	30	away	away	ADV
ijassa-751	81	31	out	out	ADP
ijassa-751	81	32	of	of	ADP
ijassa-751	81	33	the	the	DET
ijassa-751	81	34	search	search	NOUN
ijassa-751	81	35	space	space	NOUN
ijassa-751	81	36	.	.	PUNCT
ijassa-751	82	1	if	if	SCONJ
ijassa-751	82	2	the	the	DET
ijassa-751	82	3	range	range	NOUN
ijassa-751	82	4	[	[	X
ijassa-751	82	5	−s	−s	NOUN
ijassa-751	82	6	,	,	PUNCT
ijassa-751	82	7	s	s	AUX
ijassa-751	82	8	]	]	X
ijassa-751	82	9	is	be	AUX
ijassa-751	82	10	not	not	PART
ijassa-751	82	11	symmetrical	symmetrical	ADJ
ijassa-751	82	12	,	,	PUNCT
ijassa-751	82	13	it	it	PRON
ijassa-751	82	14	will	will	AUX
ijassa-751	82	15	be	be	AUX
ijassa-751	82	16	changed	change	VERB
ijassa-751	82	17	to	to	ADP
ijassa-751	82	18	the	the	DET
ijassa-751	82	19	corresponding	corresponding	ADJ
ijassa-751	82	20	symmetrical	symmetrical	ADJ
ijassa-751	82	21	range	range	NOUN
ijassa-751	82	22	and	and	CCONJ
ijassa-751	82	23	the	the	DET
ijassa-751	82	24	maximum	maximum	ADJ
ijassa-751	82	25	velocity	velocity	NOUN
ijassa-751	82	26	during	during	ADP
ijassa-751	82	27	one	one	NUM
ijassa-751	82	28	iteration	iteration	NOUN
ijassa-751	82	29	must	must	AUX
ijassa-751	82	30	be	be	AUX
ijassa-751	82	31	limited	limit	VERB
ijassa-751	82	32	on	on	ADP
ijassa-751	82	33	the	the	DET
ijassa-751	82	34	interval	interval	NOUN
ijassa-751	82	35	[	[	X
ijassa-751	82	36	−vmax	−vmax	NOUN
ijassa-751	82	37	,	,	PUNCT
ijassa-751	82	38	vmax	vmax	PROPN
ijassa-751	82	39	]	]	PUNCT
ijassa-751	82	40	given	give	VERB
ijassa-751	82	41	in	in	ADP
ijassa-751	82	42	eq.(2.3	eq.(2.3	NOUN
ijassa-751	82	43	)	)	PUNCT
ijassa-751	82	44	vij	vij	NOUN
ijassa-751	82	45	=	=	PUNCT
ijassa-751	82	46	sign(vij)min(|vij|	sign(vij)min(|vij|	PROPN
ijassa-751	82	47	,	,	PUNCT
ijassa-751	82	48	vmax	vmax	PROPN
ijassa-751	82	49	)	)	PUNCT
ijassa-751	82	50	.	.	PUNCT
ijassa-751	83	1	(	(	PUNCT
ijassa-751	83	2	2.3	2.3	NUM
ijassa-751	83	3	)	)	PUNCT
ijassa-751	83	4	where	where	SCONJ
ijassa-751	83	5	the	the	DET
ijassa-751	83	6	value	value	NOUN
ijassa-751	83	7	of	of	ADP
ijassa-751	83	8	vmax	vmax	PROPN
ijassa-751	83	9	is	be	AUX
ijassa-751	83	10	p×	p×	NOUN
ijassa-751	83	11	s	s	NOUN
ijassa-751	83	12	,	,	PUNCT
ijassa-751	83	13	with	with	ADP
ijassa-751	83	14	p	p	PROPN
ijassa-751	83	15	∈	∈	PROPN
ijassa-751	83	16	[	[	X
ijassa-751	83	17	0.1	0.1	NUM
ijassa-751	83	18	,	,	PUNCT
ijassa-751	83	19	1	1	NUM
ijassa-751	83	20	]	]	PUNCT
ijassa-751	83	21	but	but	CCONJ
ijassa-751	83	22	vmax	vmax	PROPN
ijassa-751	83	23	is	be	AUX
ijassa-751	83	24	usually	usually	ADV
ijassa-751	83	25	selected	select	VERB
ijassa-751	83	26	to	to	PART
ijassa-751	83	27	be	be	AUX
ijassa-751	83	28	s	s	NOUN
ijassa-751	83	29	,	,	PUNCT
ijassa-751	83	30	i.e.	i.e.	X
ijassa-751	83	31	p	p	X
ijassa-751	83	32	=	=	NOUN
ijassa-751	83	33	1	1	X
ijassa-751	83	34	.	.	PUNCT
ijassa-751	84	1	the	the	DET
ijassa-751	84	2	termination	termination	NOUN
ijassa-751	84	3	criterion	criterion	NOUN
ijassa-751	84	4	for	for	ADP
ijassa-751	84	5	iterations	iteration	NOUN
ijassa-751	84	6	will	will	AUX
ijassa-751	84	7	be	be	AUX
ijassa-751	84	8	determined	determine	VERB
ijassa-751	84	9	according	accord	VERB
ijassa-751	84	10	to	to	ADP
ijassa-751	84	11	whether	whether	SCONJ
ijassa-751	84	12	the	the	DET
ijassa-751	84	13	maximum	maximum	ADJ
ijassa-751	84	14	number	number	NOUN
ijassa-751	84	15	of	of	ADP
ijassa-751	84	16	iterations	iteration	NOUN
ijassa-751	84	17	or	or	CCONJ
ijassa-751	84	18	minimum	minimum	NOUN
ijassa-751	84	19	fitness	fitness	NOUN
ijassa-751	84	20	function	function	NOUN
ijassa-751	84	21	error	error	NOUN
ijassa-751	84	22	is	be	AUX
ijassa-751	84	23	reached	reach	VERB
ijassa-751	84	24	.	.	PUNCT
ijassa-751	85	1	2.2	2.2	NUM
ijassa-751	85	2	.	.	PUNCT
ijassa-751	85	3	pegasos	pegasos	PROPN
ijassa-751	85	4	:	:	PUNCT
ijassa-751	85	5	primal	primal	ADJ
ijassa-751	85	6	estimated	estimate	VERB
ijassa-751	85	7	sub	sub	ADJ
ijassa-751	85	8	-	-	ADJ
ijassa-751	85	9	gradient	gradient	ADJ
ijassa-751	85	10	solver	solver	NOUN
ijassa-751	85	11	for	for	ADP
ijassa-751	85	12	svm	svm	ADJ
ijassa-751	85	13	pegasos	pegasos	PROPN
ijassa-751	85	14	was	be	AUX
ijassa-751	85	15	described	describe	VERB
ijassa-751	85	16	and	and	CCONJ
ijassa-751	85	17	analyzed	analyze	VERB
ijassa-751	85	18	by	by	ADP
ijassa-751	85	19	shalev	shalev	NOUN
ijassa-751	85	20	-	-	PUNCT
ijassa-751	85	21	shwartz	shwartz	NOUN
ijassa-751	85	22	et	et	PROPN
ijassa-751	85	23	al	al	PROPN
ijassa-751	85	24	.	.	PUNCT
ijassa-751	86	1	in	in	ADP
ijassa-751	86	2	[	[	X
ijassa-751	86	3	16	16	NUM
ijassa-751	86	4	]	]	PUNCT
ijassa-751	86	5	for	for	ADP
ijassa-751	86	6	solving	solve	VERB
ijassa-751	86	7	the	the	DET
ijassa-751	86	8	optimization	optimization	NOUN
ijassa-751	86	9	problem	problem	NOUN
ijassa-751	86	10	cast	cast	VERB
ijassa-751	86	11	by	by	ADP
ijassa-751	86	12	support	support	NOUN
ijassa-751	86	13	vector	vector	NOUN
ijassa-751	86	14	machine	machine	NOUN
ijassa-751	86	15	(	(	PUNCT
ijassa-751	86	16	svm	svm	PROPN
ijassa-751	86	17	)	)	PUNCT
ijassa-751	86	18	.	.	PUNCT
ijassa-751	87	1	it	it	PRON
ijassa-751	87	2	performed	perform	VERB
ijassa-751	87	3	a	a	DET
ijassa-751	87	4	stochastic	stochastic	ADJ
ijassa-751	87	5	subgradient	subgradient	ADJ
ijassa-751	87	6	descent	descent	NOUN
ijassa-751	87	7	based	base	VERB
ijassa-751	87	8	on	on	ADP
ijassa-751	87	9	the	the	DET
ijassa-751	87	10	primal	primal	ADJ
ijassa-751	87	11	objective	objective	NOUN
ijassa-751	87	12	by	by	ADP
ijassa-751	87	13	chosen	choose	VERB
ijassa-751	87	14	step	step	NOUN
ijassa-751	87	15	size	size	NOUN
ijassa-751	87	16	carefully	carefully	ADV
ijassa-751	87	17	to	to	PART
ijassa-751	87	18	improve	improve	VERB
ijassa-751	87	19	copyright	copyright	NOUN
ijassa-751	87	20	c	c	ADP
ijassa-751	87	21	©	©	PROPN
ijassa-751	87	22	2019	2019	NUM
ijassa-751	87	23	assa	assa	NOUN
ijassa-751	87	24	.	.	PUNCT
ijassa-751	88	1	adv	adv	PROPN
ijassa-751	88	2	.	.	PUNCT
ijassa-751	89	1	in	in	ADP
ijassa-751	89	2	systems	system	NOUN
ijassa-751	89	3	science	science	NOUN
ijassa-751	89	4	and	and	CCONJ
ijassa-751	89	5	appl.(2019	appl.(2019	NOUN
ijassa-751	89	6	)	)	PUNCT
ijassa-751	89	7	14	14	NUM
ijassa-751	89	8	l.m	l.m	PROPN
ijassa-751	89	9	.	.	PROPN
ijassa-751	89	10	el	el	PROPN
ijassa-751	89	11	bakrawy	bakrawy	PROPN
ijassa-751	89	12	convergence	convergence	PROPN
ijassa-751	89	13	[	[	X
ijassa-751	89	14	17	17	NUM
ijassa-751	89	15	,	,	PUNCT
ijassa-751	89	16	18	18	NUM
ijassa-751	89	17	,	,	PUNCT
ijassa-751	89	18	19	19	NUM
ijassa-751	89	19	]	]	PUNCT
ijassa-751	89	20	.	.	PUNCT
ijassa-751	90	1	pegasos	pegasos	PROPN
ijassa-751	90	2	has	have	AUX
ijassa-751	90	3	attracted	attract	VERB
ijassa-751	90	4	research	research	NOUN
ijassa-751	90	5	interest	interest	NOUN
ijassa-751	90	6	because	because	SCONJ
ijassa-751	90	7	it	it	PRON
ijassa-751	90	8	has	have	VERB
ijassa-751	90	9	better	well	ADJ
ijassa-751	90	10	convergence	convergence	NOUN
ijassa-751	90	11	bounds	bound	NOUN
ijassa-751	90	12	and	and	CCONJ
ijassa-751	90	13	robustly	robustly	ADV
ijassa-751	90	14	convex	convex	VERB
ijassa-751	90	15	optimization	optimization	NOUN
ijassa-751	90	16	objective	objective	NOUN
ijassa-751	90	17	.	.	PUNCT
ijassa-751	91	1	it	it	PRON
ijassa-751	91	2	uses	use	VERB
ijassa-751	91	3	theory	theory	NOUN
ijassa-751	91	4	of	of	ADP
ijassa-751	91	5	strongly	strongly	ADV
ijassa-751	91	6	convex	convex	VERB
ijassa-751	91	7	optimization	optimization	NOUN
ijassa-751	91	8	problems	problem	NOUN
ijassa-751	91	9	and	and	CCONJ
ijassa-751	91	10	hinge	hinge	NOUN
ijassa-751	91	11	loss	loss	NOUN
ijassa-751	91	12	instead	instead	ADV
ijassa-751	91	13	of	of	ADP
ijassa-751	91	14	the	the	DET
ijassa-751	91	15	original	original	ADJ
ijassa-751	91	16	linear	linear	NOUN
ijassa-751	91	17	constraints	constraint	NOUN
ijassa-751	91	18	which	which	PRON
ijassa-751	91	19	makes	make	VERB
ijassa-751	91	20	the	the	DET
ijassa-751	91	21	objective	objective	NOUN
ijassa-751	91	22	of	of	ADP
ijassa-751	91	23	svm	svm	PROPN
ijassa-751	91	24	unconstrained	unconstraine	VERB
ijassa-751	91	25	.	.	PUNCT
ijassa-751	92	1	given	give	VERB
ijassa-751	92	2	a	a	DET
ijassa-751	92	3	binary	binary	ADJ
ijassa-751	92	4	classification	classification	NOUN
ijassa-751	92	5	problem	problem	NOUN
ijassa-751	92	6	with	with	ADP
ijassa-751	92	7	training	training	NOUN
ijassa-751	92	8	set	set	NOUN
ijassa-751	92	9	s	s	PART
ijassa-751	92	10	=	=	PUNCT
ijassa-751	92	11	(	(	PUNCT
ijassa-751	92	12	xi	xi	PROPN
ijassa-751	92	13	,	,	PUNCT
ijassa-751	92	14	yi	yi	PROPN
ijassa-751	92	15	)	)	PUNCT
ijassa-751	92	16	,	,	PUNCT
ijassa-751	92	17	(	(	PUNCT
ijassa-751	92	18	i	i	NOUN
ijassa-751	92	19	=	=	NOUN
ijassa-751	92	20	1	1	NUM
ijassa-751	92	21	,	,	PUNCT
ijassa-751	92	22	.	.	PUNCT
ijassa-751	92	23	.	.	PUNCT
ijassa-751	92	24	.	.	PUNCT
ijassa-751	92	25	,	,	PUNCT
ijassa-751	92	26	n	n	CCONJ
ijassa-751	92	27	)	)	PUNCT
ijassa-751	92	28	,	,	PUNCT
ijassa-751	92	29	where	where	SCONJ
ijassa-751	92	30	xi	xi	PROPN
ijassa-751	92	31	is	be	AUX
ijassa-751	92	32	a	a	DET
ijassa-751	92	33	d	d	ADJ
ijassa-751	92	34	-	-	ADJ
ijassa-751	92	35	dimensional	dimensional	ADJ
ijassa-751	92	36	feature	feature	NOUN
ijassa-751	92	37	vector	vector	NOUN
ijassa-751	92	38	and	and	CCONJ
ijassa-751	92	39	yi	yi	NOUN
ijassa-751	92	40	=	=	PUNCT
ijassa-751	92	41	±1	±1	VERB
ijassa-751	92	42	is	be	AUX
ijassa-751	92	43	the	the	DET
ijassa-751	92	44	class	class	NOUN
ijassa-751	92	45	label	label	NOUN
ijassa-751	92	46	.	.	PUNCT
ijassa-751	93	1	the	the	DET
ijassa-751	93	2	goal	goal	NOUN
ijassa-751	93	3	of	of	ADP
ijassa-751	93	4	linear	linear	ADJ
ijassa-751	93	5	support	support	NOUN
ijassa-751	93	6	vector	vector	NOUN
ijassa-751	93	7	machines	machine	NOUN
ijassa-751	93	8	is	be	AUX
ijassa-751	93	9	to	to	PART
ijassa-751	93	10	find	find	VERB
ijassa-751	93	11	a	a	DET
ijassa-751	93	12	classifier	classifier	NOUN
ijassa-751	93	13	in	in	ADP
ijassa-751	93	14	the	the	DET
ijassa-751	93	15	following	follow	VERB
ijassa-751	93	16	form	form	NOUN
ijassa-751	93	17	h(x	h(x	PROPN
ijassa-751	93	18	)	)	PUNCT
ijassa-751	93	19	=	=	SYM
ijassa-751	93	20	sign(wtx	sign(wtx	NOUN
ijassa-751	93	21	)	)	PUNCT
ijassa-751	93	22	,	,	PUNCT
ijassa-751	93	23	(	(	PUNCT
ijassa-751	93	24	2.4	2.4	NUM
ijassa-751	93	25	)	)	PUNCT
ijassa-751	93	26	where	where	SCONJ
ijassa-751	93	27	w	w	NOUN
ijassa-751	93	28	is	be	AUX
ijassa-751	93	29	the	the	DET
ijassa-751	93	30	weight	weight	NOUN
ijassa-751	93	31	vector	vector	NOUN
ijassa-751	93	32	which	which	PRON
ijassa-751	93	33	can	can	AUX
ijassa-751	93	34	be	be	AUX
ijassa-751	93	35	learnt	learn	VERB
ijassa-751	93	36	from	from	ADP
ijassa-751	93	37	training	training	NOUN
ijassa-751	93	38	set	set	VERB
ijassa-751	93	39	to	to	PART
ijassa-751	93	40	solve	solve	VERB
ijassa-751	93	41	the	the	DET
ijassa-751	93	42	following	follow	VERB
ijassa-751	93	43	optimization	optimization	NOUN
ijassa-751	93	44	problem	problem	NOUN
ijassa-751	93	45	after	after	ADP
ijassa-751	93	46	number	number	NOUN
ijassa-751	93	47	of	of	ADP
ijassa-751	93	48	iterations	iteration	NOUN
ijassa-751	93	49	t	t	NOUN
ijassa-751	93	50	.	.	PUNCT
ijassa-751	94	1	min	min	PROPN
ijassa-751	94	2	w	w	PROPN
ijassa-751	94	3	=	=	PUNCT
ijassa-751	94	4	λ	λ	PROPN
ijassa-751	94	5	2	2	NUM
ijassa-751	94	6	‖w‖2	‖w‖2	NOUN
ijassa-751	95	1	+	+	CCONJ
ijassa-751	95	2	1	1	NUM
ijassa-751	95	3	n	n	NUM
ijassa-751	95	4	∑	∑	DET
ijassa-751	95	5	(	(	PUNCT
ijassa-751	95	6	x	x	NOUN
ijassa-751	95	7	,	,	PUNCT
ijassa-751	95	8	y)∈s	y)∈s	NUM
ijassa-751	96	1	l(w	l(w	PROPN
ijassa-751	96	2	,	,	PUNCT
ijassa-751	96	3	(	(	PUNCT
ijassa-751	96	4	x	x	NOUN
ijassa-751	96	5	,	,	PUNCT
ijassa-751	96	6	y	y	NOUN
ijassa-751	96	7	)	)	PUNCT
ijassa-751	96	8	)	)	PUNCT
ijassa-751	96	9	,	,	PUNCT
ijassa-751	96	10	(	(	PUNCT
ijassa-751	96	11	2.5	2.5	NUM
ijassa-751	96	12	)	)	PUNCT
ijassa-751	96	13	where	where	SCONJ
ijassa-751	96	14	l(w	l(w	PROPN
ijassa-751	96	15	,	,	PUNCT
ijassa-751	96	16	(	(	PUNCT
ijassa-751	96	17	x	x	NOUN
ijassa-751	96	18	,	,	PUNCT
ijassa-751	96	19	y	y	NOUN
ijassa-751	96	20	)	)	PUNCT
ijassa-751	96	21	)	)	PUNCT
ijassa-751	97	1	=	=	SYM
ijassa-751	97	2	max(0	max(0	NOUN
ijassa-751	97	3	,	,	PUNCT
ijassa-751	97	4	1−	1−	NUM
ijassa-751	97	5	y(w	y(w	PROPN
ijassa-751	97	6	,	,	PUNCT
ijassa-751	97	7	x	x	NOUN
ijassa-751	97	8	)	)	PUNCT
ijassa-751	97	9	)	)	PUNCT
ijassa-751	97	10	,	,	PUNCT
ijassa-751	97	11	and	and	CCONJ
ijassa-751	97	12	λ	λ	X
ijassa-751	97	13	≥	≥	X
ijassa-751	97	14	0	0	NUM
ijassa-751	97	15	is	be	AUX
ijassa-751	97	16	the	the	DET
ijassa-751	97	17	regularization	regularization	NOUN
ijassa-751	97	18	parameter	parameter	NOUN
ijassa-751	97	19	.	.	PUNCT
ijassa-751	98	1	in	in	ADP
ijassa-751	98	2	each	each	DET
ijassa-751	98	3	iteration	iteration	NOUN
ijassa-751	98	4	t	t	NOUN
ijassa-751	98	5	,	,	PUNCT
ijassa-751	98	6	pegasos	pegasos	PROPN
ijassa-751	98	7	algorithm	algorithm	PROPN
ijassa-751	98	8	aims	aim	VERB
ijassa-751	98	9	to	to	PART
ijassa-751	98	10	update	update	VERB
ijassa-751	98	11	w	w	NOUN
ijassa-751	98	12	by	by	ADP
ijassa-751	98	13	choosing	choose	VERB
ijassa-751	98	14	a	a	DET
ijassa-751	98	15	random	random	ADJ
ijassa-751	98	16	training	training	NOUN
ijassa-751	98	17	set	set	VERB
ijassa-751	98	18	at	at	ADP
ijassa-751	98	19	⊆	⊆	NUM
ijassa-751	98	20	s	s	NOUN
ijassa-751	98	21	with	with	ADP
ijassa-751	98	22	size	size	NOUN
ijassa-751	98	23	k	k	PROPN
ijassa-751	98	24	,	,	PUNCT
ijassa-751	98	25	where	where	SCONJ
ijassa-751	98	26	k	k	PROPN
ijassa-751	98	27	is	be	AUX
ijassa-751	98	28	the	the	DET
ijassa-751	98	29	number	number	NOUN
ijassa-751	98	30	of	of	ADP
ijassa-751	98	31	training	training	NOUN
ijassa-751	98	32	examples	example	NOUN
ijassa-751	98	33	used	use	VERB
ijassa-751	98	34	for	for	ADP
ijassa-751	98	35	calculating	calculate	VERB
ijassa-751	98	36	sub	sub	NOUN
ijassa-751	98	37	-	-	NOUN
ijassa-751	98	38	gradient	gradient	ADJ
ijassa-751	98	39	through	through	ADP
ijassa-751	98	40	the	the	DET
ijassa-751	98	41	following	following	ADJ
ijassa-751	98	42	approximate	approximate	ADJ
ijassa-751	98	43	objective	objective	ADJ
ijassa-751	98	44	function	function	NOUN
ijassa-751	98	45	f(w	f(w	PROPN
ijassa-751	98	46	,	,	PUNCT
ijassa-751	98	47	at	at	ADP
ijassa-751	98	48	)	)	PUNCT
ijassa-751	99	1	=	=	SYM
ijassa-751	99	2	λ	λ	NOUN
ijassa-751	99	3	2	2	NUM
ijassa-751	99	4	‖w‖2	‖w‖2	NOUN
ijassa-751	100	1	+	+	CCONJ
ijassa-751	100	2	1	1	NUM
ijassa-751	100	3	k	k	X
ijassa-751	100	4	∑	∑	PUNCT
ijassa-751	100	5	(	(	PUNCT
ijassa-751	100	6	x	x	NOUN
ijassa-751	100	7	,	,	PUNCT
ijassa-751	100	8	y)∈at	y)∈at	PROPN
ijassa-751	100	9	l(w	l(w	PROPN
ijassa-751	100	10	,	,	PUNCT
ijassa-751	100	11	(	(	PUNCT
ijassa-751	100	12	x	x	NOUN
ijassa-751	100	13	,	,	PUNCT
ijassa-751	100	14	y	y	NOUN
ijassa-751	100	15	)	)	PUNCT
ijassa-751	100	16	)	)	PUNCT
ijassa-751	100	17	.	.	PUNCT
ijassa-751	101	1	(	(	PUNCT
ijassa-751	101	2	2.6	2.6	NUM
ijassa-751	101	3	)	)	PUNCT
ijassa-751	101	4	the	the	DET
ijassa-751	101	5	sub	sub	NOUN
ijassa-751	101	6	-	-	NOUN
ijassa-751	101	7	gradient	gradient	NOUN
ijassa-751	101	8	of	of	ADP
ijassa-751	101	9	the	the	DET
ijassa-751	101	10	approximate	approximate	ADJ
ijassa-751	101	11	objective	objective	ADJ
ijassa-751	101	12	function	function	NOUN
ijassa-751	101	13	f(w	f(w	PROPN
ijassa-751	101	14	,	,	PUNCT
ijassa-751	101	15	at	at	ADP
ijassa-751	101	16	)	)	PUNCT
ijassa-751	101	17	at	at	ADP
ijassa-751	101	18	wt	wt	PROPN
ijassa-751	101	19	is	be	AUX
ijassa-751	101	20	calculated	calculate	VERB
ijassa-751	101	21	by	by	ADP
ijassa-751	101	22	∇t	∇t	PROPN
ijassa-751	101	23	=	=	PROPN
ijassa-751	101	24	λwt	λwt	PROPN
ijassa-751	101	25	−	−	PROPN
ijassa-751	101	26	1	1	NUM
ijassa-751	101	27	|at|	|at|	NUM
ijassa-751	101	28	∑	∑	PUNCT
ijassa-751	101	29	(	(	PUNCT
ijassa-751	101	30	x	x	NOUN
ijassa-751	101	31	,	,	PUNCT
ijassa-751	101	32	y)∈a+	y)∈a+	PROPN
ijassa-751	101	33	t	t	PROPN
ijassa-751	101	34	yx	yx	PROPN
ijassa-751	101	35	,	,	PUNCT
ijassa-751	101	36	(	(	PUNCT
ijassa-751	101	37	2.7	2.7	NUM
ijassa-751	101	38	)	)	PUNCT
ijassa-751	101	39	where	where	SCONJ
ijassa-751	101	40	a+	a+	PUNCT
ijassa-751	101	41	t	t	PROPN
ijassa-751	101	42	is	be	AUX
ijassa-751	101	43	the	the	DET
ijassa-751	101	44	set	set	NOUN
ijassa-751	101	45	of	of	ADP
ijassa-751	101	46	examples	example	NOUN
ijassa-751	101	47	when	when	SCONJ
ijassa-751	101	48	w	w	PROPN
ijassa-751	101	49	suffers	suffer	VERB
ijassa-751	101	50	a	a	DET
ijassa-751	101	51	non	non	ADJ
ijassa-751	101	52	-	-	ADJ
ijassa-751	101	53	zero	zero	NUM
ijassa-751	101	54	loss	loss	NOUN
ijassa-751	101	55	.	.	PUNCT
ijassa-751	102	1	finally	finally	ADV
ijassa-751	102	2	,	,	PUNCT
ijassa-751	102	3	the	the	DET
ijassa-751	102	4	sub	sub	NOUN
ijassa-751	102	5	-	-	ADJ
ijassa-751	102	6	gradient	gradient	ADJ
ijassa-751	102	7	is	be	AUX
ijassa-751	102	8	used	use	VERB
ijassa-751	102	9	to	to	PART
ijassa-751	102	10	update	update	VERB
ijassa-751	102	11	the	the	DET
ijassa-751	102	12	weight	weight	NOUN
ijassa-751	102	13	by	by	ADP
ijassa-751	102	14	using	use	VERB
ijassa-751	102	15	a	a	DET
ijassa-751	102	16	step	step	NOUN
ijassa-751	102	17	size	size	NOUN
ijassa-751	102	18	of	of	ADP
ijassa-751	102	19	ηt	ηt	ADV
ijassa-751	102	20	=	=	SYM
ijassa-751	102	21	1	1	NUM
ijassa-751	102	22	|λt|	|λt|	NOUN
ijassa-751	102	23	as	as	ADP
ijassa-751	102	24	wt+1	wt+1	PROPN
ijassa-751	102	25	=	=	NOUN
ijassa-751	102	26	wt	wt	NOUN
ijassa-751	102	27	−	−	PROPN
ijassa-751	102	28	ηt∇t	ηt∇t	PROPN
ijassa-751	102	29	,	,	PUNCT
ijassa-751	102	30	(	(	PUNCT
ijassa-751	102	31	2.8	2.8	NUM
ijassa-751	102	32	)	)	PUNCT
ijassa-751	102	33	where	where	SCONJ
ijassa-751	102	34	ηt	ηt	ADV
ijassa-751	102	35	is	be	AUX
ijassa-751	102	36	the	the	DET
ijassa-751	102	37	learning	learning	NOUN
ijassa-751	102	38	rate	rate	NOUN
ijassa-751	102	39	.	.	PUNCT
ijassa-751	103	1	the	the	DET
ijassa-751	103	2	last	last	ADJ
ijassa-751	103	3	vector	vector	NOUN
ijassa-751	103	4	wt+1	wt+1	PROPN
ijassa-751	103	5	is	be	AUX
ijassa-751	103	6	the	the	DET
ijassa-751	103	7	output	output	NOUN
ijassa-751	103	8	of	of	ADP
ijassa-751	103	9	pegasos	pegasos	NOUN
ijassa-751	103	10	algorithm	algorithm	NOUN
ijassa-751	103	11	after	after	ADP
ijassa-751	103	12	number	number	NOUN
ijassa-751	103	13	of	of	ADP
ijassa-751	103	14	iterations	iteration	NOUN
ijassa-751	103	15	t	t	NOUN
ijassa-751	103	16	.	.	PUNCT
ijassa-751	104	1	3	3	X
ijassa-751	104	2	.	.	X
ijassa-751	104	3	the	the	DET
ijassa-751	104	4	proposed	propose	VERB
ijassa-751	104	5	algorithm	algorithm	NOUN
ijassa-751	104	6	in	in	ADP
ijassa-751	104	7	this	this	DET
ijassa-751	104	8	section	section	NOUN
ijassa-751	104	9	,	,	PUNCT
ijassa-751	104	10	we	we	PRON
ijassa-751	104	11	describe	describe	VERB
ijassa-751	104	12	the	the	DET
ijassa-751	104	13	proposed	propose	VERB
ijassa-751	104	14	pso	pso	NOUN
ijassa-751	104	15	-	-	PUNCT
ijassa-751	104	16	pegasos	pegasos	NOUN
ijassa-751	104	17	algorithm	algorithm	NOUN
ijassa-751	104	18	to	to	PART
ijassa-751	104	19	determine	determine	VERB
ijassa-751	104	20	the	the	DET
ijassa-751	104	21	optimal	optimal	ADJ
ijassa-751	104	22	values	value	NOUN
ijassa-751	104	23	of	of	ADP
ijassa-751	104	24	pegasos	pegasos	NOUN
ijassa-751	104	25	parameters	parameter	NOUN
ijassa-751	104	26	as	as	SCONJ
ijassa-751	104	27	shown	show	VERB
ijassa-751	104	28	in	in	ADP
ijassa-751	104	29	figure	figure	NOUN
ijassa-751	104	30	3.1	3.1	NUM
ijassa-751	104	31	.	.	PUNCT
ijassa-751	105	1	the	the	DET
ijassa-751	105	2	detailed	detailed	ADJ
ijassa-751	105	3	description	description	NOUN
ijassa-751	105	4	is	be	AUX
ijassa-751	105	5	as	as	SCONJ
ijassa-751	105	6	follows	follow	VERB
ijassa-751	105	7	:	:	PUNCT
ijassa-751	105	8	3.1	3.1	NUM
ijassa-751	105	9	.	.	PUNCT
ijassa-751	105	10	data	datum	NOUN
ijassa-751	105	11	preprocessing	preprocessing	NOUN
ijassa-751	105	12	in	in	ADP
ijassa-751	105	13	this	this	DET
ijassa-751	105	14	paper	paper	NOUN
ijassa-751	105	15	,	,	PUNCT
ijassa-751	105	16	the	the	DET
ijassa-751	105	17	popular	popular	ADJ
ijassa-751	105	18	and	and	CCONJ
ijassa-751	105	19	often	often	ADV
ijassa-751	105	20	used	use	VERB
ijassa-751	105	21	corpus	corpus	NOUN
ijassa-751	105	22	benchmark	benchmark	NOUN
ijassa-751	105	23	spambase	spambase	PROPN
ijassa-751	105	24	dataset	dataset	NOUN
ijassa-751	105	25	is	be	AUX
ijassa-751	105	26	utilized	utilize	VERB
ijassa-751	105	27	to	to	PART
ijassa-751	105	28	classify	classify	VERB
ijassa-751	105	29	email	email	NOUN
ijassa-751	105	30	as	as	ADP
ijassa-751	105	31	spam	spam	NOUN
ijassa-751	105	32	or	or	CCONJ
ijassa-751	105	33	non	non	ADJ
ijassa-751	105	34	-	-	NOUN
ijassa-751	105	35	spam	spam	NOUN
ijassa-751	105	36	.	.	PUNCT
ijassa-751	106	1	the	the	DET
ijassa-751	106	2	dataset	dataset	NOUN
ijassa-751	106	3	is	be	AUX
ijassa-751	106	4	available	available	ADJ
ijassa-751	106	5	in	in	ADP
ijassa-751	106	6	numeric	numeric	ADJ
ijassa-751	106	7	form	form	NOUN
ijassa-751	106	8	and	and	CCONJ
ijassa-751	106	9	the	the	DET
ijassa-751	106	10	features	feature	NOUN
ijassa-751	106	11	are	be	AUX
ijassa-751	106	12	frequencies	frequency	NOUN
ijassa-751	106	13	of	of	ADP
ijassa-751	106	14	various	various	ADJ
ijassa-751	106	15	characters	character	NOUN
ijassa-751	106	16	and	and	CCONJ
ijassa-751	106	17	words	word	NOUN
ijassa-751	106	18	in	in	ADP
ijassa-751	106	19	emails	email	NOUN
ijassa-751	106	20	.	.	PUNCT
ijassa-751	107	1	the	the	DET
ijassa-751	107	2	main	main	ADJ
ijassa-751	107	3	tasks	task	NOUN
ijassa-751	107	4	in	in	ADP
ijassa-751	107	5	preprocessing	preprocessing	NOUN
ijassa-751	107	6	are	be	AUX
ijassa-751	107	7	transformation	transformation	NOUN
ijassa-751	107	8	,	,	PUNCT
ijassa-751	107	9	reduction	reduction	NOUN
ijassa-751	107	10	,	,	PUNCT
ijassa-751	107	11	cleaning	cleaning	NOUN
ijassa-751	107	12	,	,	PUNCT
ijassa-751	107	13	integration	integration	NOUN
ijassa-751	107	14	and	and	CCONJ
ijassa-751	107	15	normalization	normalization	NOUN
ijassa-751	107	16	.	.	PUNCT
ijassa-751	108	1	normalization	normalization	NOUN
ijassa-751	108	2	is	be	AUX
ijassa-751	108	3	an	an	DET
ijassa-751	108	4	important	important	ADJ
ijassa-751	108	5	pahse	pahse	NOUN
ijassa-751	108	6	to	to	PART
ijassa-751	108	7	fast	fast	VERB
ijassa-751	108	8	the	the	DET
ijassa-751	108	9	algorithm	algorithm	NOUN
ijassa-751	108	10	,	,	PUNCT
ijassa-751	108	11	convergence	convergence	NOUN
ijassa-751	108	12	and	and	CCONJ
ijassa-751	108	13	decrease	decrease	VERB
ijassa-751	108	14	the	the	DET
ijassa-751	108	15	influence	influence	NOUN
ijassa-751	108	16	of	of	ADP
ijassa-751	108	17	imbalance	imbalance	NOUN
ijassa-751	108	18	in	in	ADP
ijassa-751	108	19	data	datum	NOUN
ijassa-751	108	20	.	.	PUNCT
ijassa-751	109	1	in	in	ADP
ijassa-751	109	2	spambase	spambase	PROPN
ijassa-751	109	3	dataset	dataset	PROPN
ijassa-751	109	4	,	,	PUNCT
ijassa-751	109	5	normalization	normalization	NOUN
ijassa-751	109	6	is	be	AUX
ijassa-751	109	7	done	do	VERB
ijassa-751	109	8	before	before	ADP
ijassa-751	109	9	running	run	VERB
ijassa-751	109	10	pso	pso	NOUN
ijassa-751	109	11	-	-	PUNCT
ijassa-751	109	12	pegasos	pegasos	NOUN
ijassa-751	109	13	algorithm	algorithm	NOUN
ijassa-751	109	14	.	.	PUNCT
ijassa-751	110	1	each	each	DET
ijassa-751	110	2	feature	feature	NOUN
ijassa-751	110	3	of	of	ADP
ijassa-751	110	4	spambase	spambase	NOUN
ijassa-751	110	5	dataset	dataset	NOUN
ijassa-751	110	6	is	be	AUX
ijassa-751	110	7	normalized	normalize	VERB
ijassa-751	110	8	in	in	ADP
ijassa-751	110	9	the	the	DET
ijassa-751	110	10	range	range	NOUN
ijassa-751	110	11	[	[	X
ijassa-751	110	12	0	0	NUM
ijassa-751	110	13	,	,	PUNCT
ijassa-751	110	14	1	1	NUM
ijassa-751	110	15	]	]	PUNCT
ijassa-751	110	16	through	through	ADP
ijassa-751	110	17	the	the	DET
ijassa-751	110	18	following	follow	VERB
ijassa-751	110	19	function	function	NOUN
ijassa-751	110	20	copyright	copyright	NOUN
ijassa-751	110	21	c	c	ADP
ijassa-751	110	22	©	©	PROPN
ijassa-751	110	23	2019	2019	NUM
ijassa-751	110	24	assa	assa	NOUN
ijassa-751	110	25	.	.	PUNCT
ijassa-751	111	1	adv	adv	PROPN
ijassa-751	111	2	.	.	PUNCT
ijassa-751	112	1	in	in	ADP
ijassa-751	112	2	systems	system	NOUN
ijassa-751	112	3	science	science	NOUN
ijassa-751	112	4	and	and	CCONJ
ijassa-751	112	5	appl.(2019	appl.(2019	NOUN
ijassa-751	112	6	)	)	PUNCT
ijassa-751	112	7	hybrid	hybrid	ADJ
ijassa-751	112	8	particle	particle	NOUN
ijassa-751	112	9	swarm	swarm	NOUN
ijassa-751	112	10	optimization	optimization	NOUN
ijassa-751	112	11	and	and	CCONJ
ijassa-751	112	12	pegasos	pegasos	NOUN
ijassa-751	112	13	algorithm	algorithm	NOUN
ijassa-751	112	14	for	for	ADP
ijassa-751	112	15	spam	spam	NOUN
ijassa-751	112	16	email	email	NOUN
ijassa-751	112	17	detection15	detection15	NOUN
ijassa-751	112	18	figure	figure	VERB
ijassa-751	112	19	3.1	3.1	NUM
ijassa-751	112	20	:	:	PUNCT
ijassa-751	112	21	flowchart	flowchart	NOUN
ijassa-751	112	22	of	of	ADP
ijassa-751	112	23	the	the	DET
ijassa-751	112	24	proposed	propose	VERB
ijassa-751	112	25	algorithm	algorithm	NOUN
ijassa-751	112	26	.	.	PUNCT
ijassa-751	113	1	a	a	DET
ijassa-751	113	2	=	=	NOUN
ijassa-751	113	3	a−min	a−min	NOUN
ijassa-751	113	4	max−min	max−min	NOUN
ijassa-751	113	5	(	(	PUNCT
ijassa-751	113	6	3.9	3.9	NUM
ijassa-751	113	7	)	)	PUNCT
ijassa-751	113	8	where	where	SCONJ
ijassa-751	113	9	a	a	PRON
ijassa-751	113	10	is	be	AUX
ijassa-751	113	11	the	the	DET
ijassa-751	113	12	scaled	scale	VERB
ijassa-751	113	13	value	value	NOUN
ijassa-751	113	14	,	,	PUNCT
ijassa-751	113	15	a	a	PRON
ijassa-751	113	16	is	be	AUX
ijassa-751	113	17	the	the	DET
ijassa-751	113	18	original	original	ADJ
ijassa-751	113	19	value	value	NOUN
ijassa-751	113	20	,	,	PUNCT
ijassa-751	113	21	max	max	PROPN
ijassa-751	113	22	and	and	CCONJ
ijassa-751	113	23	min	min	PROPN
ijassa-751	113	24	are	be	AUX
ijassa-751	113	25	the	the	DET
ijassa-751	113	26	maximum	maximum	ADJ
ijassa-751	113	27	and	and	CCONJ
ijassa-751	113	28	minimum	minimum	ADJ
ijassa-751	113	29	bounds	bound	NOUN
ijassa-751	113	30	of	of	ADP
ijassa-751	113	31	the	the	DET
ijassa-751	113	32	feature	feature	NOUN
ijassa-751	113	33	value	value	NOUN
ijassa-751	113	34	.	.	PUNCT
ijassa-751	114	1	3.2	3.2	NUM
ijassa-751	114	2	.	.	PUNCT
ijassa-751	114	3	pso	pso	NOUN
ijassa-751	114	4	-	-	PUNCT
ijassa-751	114	5	pegasos	pegasos	NOUN
ijassa-751	114	6	algorithm	algorithm	NOUN
ijassa-751	114	7	in	in	ADP
ijassa-751	114	8	this	this	DET
ijassa-751	114	9	research	research	NOUN
ijassa-751	114	10	,	,	PUNCT
ijassa-751	114	11	hybrid	hybrid	ADJ
ijassa-751	114	12	particle	particle	NOUN
ijassa-751	114	13	swarm	swarm	NOUN
ijassa-751	114	14	optimization	optimization	NOUN
ijassa-751	114	15	and	and	CCONJ
ijassa-751	114	16	pegasos	pegasos	PROPN
ijassa-751	114	17	algorithm	algorithm	NOUN
ijassa-751	114	18	(	(	PUNCT
ijassa-751	114	19	pso	pso	NOUN
ijassa-751	114	20	-	-	PUNCT
ijassa-751	114	21	pegasos	pegasos	NOUN
ijassa-751	114	22	)	)	PUNCT
ijassa-751	114	23	is	be	AUX
ijassa-751	114	24	proposed	propose	VERB
ijassa-751	114	25	for	for	ADP
ijassa-751	114	26	spam	spam	NOUN
ijassa-751	114	27	email	email	NOUN
ijassa-751	114	28	detection	detection	NOUN
ijassa-751	114	29	.	.	PUNCT
ijassa-751	115	1	particle	particle	NOUN
ijassa-751	115	2	swarm	swarm	NOUN
ijassa-751	115	3	optimization	optimization	NOUN
ijassa-751	115	4	has	have	AUX
ijassa-751	115	5	been	be	AUX
ijassa-751	115	6	utilized	utilize	VERB
ijassa-751	115	7	to	to	PART
ijassa-751	115	8	optimize	optimize	VERB
ijassa-751	115	9	the	the	DET
ijassa-751	115	10	parameters	parameter	NOUN
ijassa-751	115	11	of	of	ADP
ijassa-751	115	12	pegasos	pegasos	PROPN
ijassa-751	115	13	algorithm	algorithm	PROPN
ijassa-751	115	14	.	.	PUNCT
ijassa-751	116	1	in	in	ADP
ijassa-751	116	2	pso	pso	NOUN
ijassa-751	116	3	each	each	DET
ijassa-751	116	4	solution	solution	NOUN
ijassa-751	116	5	is	be	AUX
ijassa-751	116	6	called	call	VERB
ijassa-751	116	7	a	a	DET
ijassa-751	116	8	particle	particle	NOUN
ijassa-751	116	9	.	.	PUNCT
ijassa-751	117	1	fitness	fitness	NOUN
ijassa-751	117	2	function	function	NOUN
ijassa-751	117	3	(	(	PUNCT
ijassa-751	117	4	mean	mean	VERB
ijassa-751	117	5	squared	square	VERB
ijassa-751	117	6	error	error	NOUN
ijassa-751	117	7	)	)	PUNCT
ijassa-751	117	8	is	be	AUX
ijassa-751	117	9	used	use	VERB
ijassa-751	117	10	to	to	PART
ijassa-751	117	11	evaluate	evaluate	VERB
ijassa-751	117	12	the	the	DET
ijassa-751	117	13	particles	particle	NOUN
ijassa-751	117	14	for	for	ADP
ijassa-751	117	15	the	the	DET
ijassa-751	117	16	optimal	optimal	ADJ
ijassa-751	117	17	solution	solution	NOUN
ijassa-751	117	18	.	.	PUNCT
ijassa-751	118	1	particle	particle	NOUN
ijassa-751	118	2	swarm	swarm	NOUN
ijassa-751	118	3	optimization	optimization	NOUN
ijassa-751	118	4	is	be	AUX
ijassa-751	118	5	used	use	VERB
ijassa-751	118	6	as	as	ADP
ijassa-751	118	7	a	a	DET
ijassa-751	118	8	search	search	NOUN
ijassa-751	118	9	strategy	strategy	NOUN
ijassa-751	118	10	to	to	PART
ijassa-751	118	11	determine	determine	VERB
ijassa-751	118	12	the	the	DET
ijassa-751	118	13	optimal	optimal	ADJ
ijassa-751	118	14	parameters	parameter	NOUN
ijassa-751	118	15	(	(	PUNCT
ijassa-751	118	16	weights	weight	NOUN
ijassa-751	118	17	)	)	PUNCT
ijassa-751	118	18	for	for	ADP
ijassa-751	118	19	pegasos	pegasos	NOUN
ijassa-751	118	20	algorithm	algorithm	NOUN
ijassa-751	118	21	,	,	PUNCT
ijassa-751	118	22	which	which	PRON
ijassa-751	118	23	means	mean	VERB
ijassa-751	118	24	in	in	ADP
ijassa-751	118	25	each	each	DET
ijassa-751	118	26	iteration	iteration	NOUN
ijassa-751	118	27	of	of	ADP
ijassa-751	118	28	pso	pso	NOUN
ijassa-751	118	29	,	,	PUNCT
ijassa-751	118	30	the	the	DET
ijassa-751	118	31	weights	weight	NOUN
ijassa-751	118	32	(	(	PUNCT
ijassa-751	118	33	w	w	NOUN
ijassa-751	118	34	-	-	PUNCT
ijassa-751	118	35	parameters	parameter	NOUN
ijassa-751	118	36	)	)	PUNCT
ijassa-751	118	37	are	be	AUX
ijassa-751	118	38	updated	update	VERB
ijassa-751	118	39	depending	depend	VERB
ijassa-751	118	40	the	the	DET
ijassa-751	118	41	fitness	fitness	NOUN
ijassa-751	118	42	function	function	NOUN
ijassa-751	118	43	.	.	PUNCT
ijassa-751	119	1	no	no	DET
ijassa-751	119	2	assumptions	assumption	NOUN
ijassa-751	119	3	are	be	AUX
ijassa-751	119	4	needed	need	VERB
ijassa-751	119	5	about	about	ADP
ijassa-751	119	6	the	the	DET
ijassa-751	119	7	w	w	NOUN
ijassa-751	119	8	-	-	PUNCT
ijassa-751	119	9	parameter	parameter	NOUN
ijassa-751	119	10	in	in	ADP
ijassa-751	119	11	pegasos	pegasos	PROPN
ijassa-751	119	12	algorithm	algorithm	NOUN
ijassa-751	119	13	since	since	SCONJ
ijassa-751	119	14	pso	pso	NOUN
ijassa-751	119	15	algorithm	algorithm	NOUN
ijassa-751	119	16	can	can	AUX
ijassa-751	119	17	help	help	VERB
ijassa-751	119	18	us	we	PRON
ijassa-751	119	19	to	to	PART
ijassa-751	119	20	identify	identify	VERB
ijassa-751	119	21	automatically	automatically	ADV
ijassa-751	119	22	the	the	DET
ijassa-751	119	23	best	well	ADV
ijassa-751	119	24	optimal	optimal	ADJ
ijassa-751	119	25	w	w	NOUN
ijassa-751	119	26	-	-	PUNCT
ijassa-751	119	27	parameter	parameter	NOUN
ijassa-751	119	28	(	(	PUNCT
ijassa-751	119	29	bw	bw	NOUN
ijassa-751	119	30	)	)	PUNCT
ijassa-751	119	31	that	that	PRON
ijassa-751	119	32	utilized	utilize	VERB
ijassa-751	119	33	to	to	PART
ijassa-751	119	34	obtain	obtain	VERB
ijassa-751	119	35	the	the	DET
ijassa-751	119	36	highest	high	ADJ
ijassa-751	119	37	classification	classification	NOUN
ijassa-751	119	38	accuracy	accuracy	NOUN
ijassa-751	119	39	for	for	ADP
ijassa-751	119	40	pegasos	pegasos	NOUN
ijassa-751	119	41	algorithm	algorithm	NOUN
ijassa-751	119	42	.	.	PUNCT
ijassa-751	120	1	the	the	DET
ijassa-751	120	2	major	major	ADJ
ijassa-751	120	3	steps	step	NOUN
ijassa-751	120	4	of	of	ADP
ijassa-751	120	5	the	the	DET
ijassa-751	120	6	hybrid	hybrid	ADJ
ijassa-751	120	7	particle	particle	NOUN
ijassa-751	120	8	swarm	swarm	NOUN
ijassa-751	120	9	optimization	optimization	NOUN
ijassa-751	120	10	and	and	CCONJ
ijassa-751	120	11	pegasos	pegasos	PROPN
ijassa-751	120	12	algorithm	algorithm	NOUN
ijassa-751	120	13	(	(	PUNCT
ijassa-751	120	14	pso	pso	NOUN
ijassa-751	120	15	-	-	PUNCT
ijassa-751	120	16	pegasos	pegasos	NOUN
ijassa-751	120	17	)	)	PUNCT
ijassa-751	120	18	are	be	AUX
ijassa-751	120	19	shown	show	VERB
ijassa-751	120	20	as	as	SCONJ
ijassa-751	120	21	follows	follow	VERB
ijassa-751	120	22	:	:	PUNCT
ijassa-751	120	23	copyright	copyright	NOUN
ijassa-751	120	24	c	c	ADP
ijassa-751	120	25	©	©	PROPN
ijassa-751	120	26	2019	2019	NUM
ijassa-751	120	27	assa	assa	NOUN
ijassa-751	120	28	.	.	PUNCT
ijassa-751	121	1	adv	adv	PROPN
ijassa-751	121	2	.	.	PUNCT
ijassa-751	122	1	in	in	ADP
ijassa-751	122	2	systems	system	NOUN
ijassa-751	122	3	science	science	NOUN
ijassa-751	122	4	and	and	CCONJ
ijassa-751	122	5	appl.(2019	appl.(2019	NOUN
ijassa-751	122	6	)	)	PUNCT
ijassa-751	122	7	16	16	NUM
ijassa-751	122	8	l.m	l.m	PROPN
ijassa-751	122	9	.	.	PROPN
ijassa-751	122	10	el	el	PROPN
ijassa-751	122	11	bakrawy	bakrawy	PROPN
ijassa-751	122	12	1	1	NUM
ijassa-751	122	13	.	.	PUNCT
ijassa-751	122	14	initialize	initialize	VERB
ijassa-751	122	15	the	the	DET
ijassa-751	122	16	population	population	NOUN
ijassa-751	122	17	for	for	ADP
ijassa-751	122	18	w	w	NOUN
ijassa-751	122	19	-	-	PUNCT
ijassa-751	122	20	parameter	parameter	NOUN
ijassa-751	122	21	individuals	individual	NOUN
ijassa-751	122	22	(	(	PUNCT
ijassa-751	122	23	particles	particle	NOUN
ijassa-751	122	24	)	)	PUNCT
ijassa-751	122	25	in	in	ADP
ijassa-751	122	26	a	a	DET
ijassa-751	122	27	random	random	ADJ
ijassa-751	122	28	manner	manner	NOUN
ijassa-751	122	29	from	from	ADP
ijassa-751	122	30	spambase	spambase	PROPN
ijassa-751	122	31	dataset	dataset	PROPN
ijassa-751	122	32	.	.	PUNCT
ijassa-751	123	1	suppose	suppose	VERB
ijassa-751	123	2	that	that	SCONJ
ijassa-751	123	3	,	,	PUNCT
ijassa-751	123	4	each	each	DET
ijassa-751	123	5	particle	particle	NOUN
ijassa-751	123	6	swarm	swarm	NOUN
ijassa-751	123	7	position	position	NOUN
ijassa-751	123	8	is	be	AUX
ijassa-751	123	9	xi	xi	ADP
ijassa-751	123	10	=	=	PUNCT
ijassa-751	123	11	{	{	PUNCT
ijassa-751	123	12	ai	ai	PROPN
ijassa-751	123	13	,	,	PUNCT
ijassa-751	123	14	j	j	PROPN
ijassa-751	123	15	,	,	PUNCT
ijassa-751	123	16	j	j	PROPN
ijassa-751	123	17	=	=	SYM
ijassa-751	123	18	1	1	NUM
ijassa-751	123	19	,	,	PUNCT
ijassa-751	123	20	2	2	NUM
ijassa-751	123	21	,	,	PUNCT
ijassa-751	123	22	...	...	PUNCT
ijassa-751	123	23	,	,	PUNCT
ijassa-751	123	24	k	k	X
ijassa-751	123	25	}	}	PUNCT
ijassa-751	123	26	,	,	PUNCT
ijassa-751	123	27	where	where	SCONJ
ijassa-751	123	28	ai	ai	VERB
ijassa-751	123	29	,	,	PUNCT
ijassa-751	123	30	j	j	PROPN
ijassa-751	123	31	is	be	AUX
ijassa-751	123	32	j	j	PROPN
ijassa-751	123	33	th	th	INTJ
ijassa-751	123	34	w	w	NOUN
ijassa-751	123	35	-	-	PUNCT
ijassa-751	123	36	parameter	parameter	NOUN
ijassa-751	123	37	for	for	ADP
ijassa-751	123	38	the	the	DET
ijassa-751	123	39	i	i	PROPN
ijassa-751	123	40	th	th	PROPN
ijassa-751	123	41	individual	individual	NOUN
ijassa-751	123	42	,	,	PUNCT
ijassa-751	123	43	k	k	PROPN
ijassa-751	123	44	is	be	AUX
ijassa-751	123	45	the	the	DET
ijassa-751	123	46	number	number	NOUN
ijassa-751	123	47	of	of	ADP
ijassa-751	123	48	features	feature	NOUN
ijassa-751	123	49	(	(	PUNCT
ijassa-751	123	50	attributes	attribute	NOUN
ijassa-751	123	51	)	)	PUNCT
ijassa-751	123	52	of	of	ADP
ijassa-751	123	53	spambase	spambase	NOUN
ijassa-751	123	54	dataset	dataset	NOUN
ijassa-751	123	55	and	and	CCONJ
ijassa-751	123	56	the	the	DET
ijassa-751	123	57	value	value	NOUN
ijassa-751	123	58	of	of	ADP
ijassa-751	123	59	the	the	DET
ijassa-751	123	60	w	w	NOUN
ijassa-751	123	61	-	-	PUNCT
ijassa-751	123	62	parameter	parameter	NOUN
ijassa-751	123	63	for	for	ADP
ijassa-751	123	64	each	each	DET
ijassa-751	123	65	individual	individual	NOUN
ijassa-751	123	66	is	be	AUX
ijassa-751	123	67	vector	vector	NOUN
ijassa-751	123	68	of	of	ADP
ijassa-751	123	69	k	k	X
ijassa-751	123	70	random	random	ADJ
ijassa-751	123	71	numbers	number	NOUN
ijassa-751	123	72	in	in	ADP
ijassa-751	123	73	range	range	NOUN
ijassa-751	123	74	from	from	ADP
ijassa-751	123	75	-10	-10	PUNCT
ijassa-751	123	76	to	to	ADP
ijassa-751	123	77	10	10	NUM
ijassa-751	123	78	.	.	PUNCT
ijassa-751	124	1	2	2	NUM
ijassa-751	124	2	.	.	X
ijassa-751	124	3	initialize	initialize	VERB
ijassa-751	124	4	velocity	velocity	NOUN
ijassa-751	124	5	of	of	ADP
ijassa-751	124	6	particle	particle	NOUN
ijassa-751	124	7	swarm	swarm	NOUN
ijassa-751	124	8	optimization	optimization	NOUN
ijassa-751	124	9	randomly	randomly	ADV
ijassa-751	124	10	in	in	ADP
ijassa-751	124	11	range	range	NOUN
ijassa-751	124	12	from	from	ADP
ijassa-751	124	13	-100	-100	PROPN
ijassa-751	124	14	to	to	ADP
ijassa-751	124	15	100	100	NUM
ijassa-751	124	16	3	3	NUM
ijassa-751	124	17	.	.	PUNCT
ijassa-751	124	18	calculate	calculate	VERB
ijassa-751	124	19	the	the	DET
ijassa-751	124	20	fitness	fitness	NOUN
ijassa-751	124	21	function	function	NOUN
ijassa-751	124	22	for	for	ADP
ijassa-751	124	23	each	each	DET
ijassa-751	124	24	particle	particle	NOUN
ijassa-751	124	25	which	which	PRON
ijassa-751	124	26	is	be	AUX
ijassa-751	124	27	acquired	acquire	VERB
ijassa-751	124	28	by	by	ADP
ijassa-751	124	29	pegasos	pegasos	PROPN
ijassa-751	124	30	algorithm	algorithm	NOUN
ijassa-751	124	31	to	to	PART
ijassa-751	124	32	classify	classify	VERB
ijassa-751	124	33	non	non	ADJ
ijassa-751	124	34	-	-	ADJ
ijassa-751	124	35	spam	spam	ADJ
ijassa-751	124	36	and	and	CCONJ
ijassa-751	124	37	spam	spam	NOUN
ijassa-751	124	38	emails	email	NOUN
ijassa-751	124	39	correctly	correctly	ADV
ijassa-751	124	40	by	by	ADP
ijassa-751	124	41	fitness	fitness	NOUN
ijassa-751	124	42	=	=	SYM
ijassa-751	124	43	mse	mse	NOUN
ijassa-751	124	44	=	=	SYM
ijassa-751	124	45	1	1	NUM
ijassa-751	124	46	n	n	NUM
ijassa-751	124	47	n∑	n∑	NOUN
ijassa-751	124	48	i=1	i=1	PROPN
ijassa-751	125	1	(	(	PUNCT
ijassa-751	125	2	xi	xi	X
ijassa-751	125	3	−	−	PROPN
ijassa-751	126	1	yi)2	yi)2	PROPN
ijassa-751	126	2	.	.	PUNCT
ijassa-751	127	1	(	(	PUNCT
ijassa-751	127	2	3.10	3.10	NUM
ijassa-751	127	3	)	)	PUNCT
ijassa-751	127	4	where	where	SCONJ
ijassa-751	127	5	mse	mse	PROPN
ijassa-751	127	6	is	be	AUX
ijassa-751	127	7	the	the	DET
ijassa-751	127	8	mean	mean	ADJ
ijassa-751	127	9	squared	square	VERB
ijassa-751	127	10	error	error	NOUN
ijassa-751	127	11	,	,	PUNCT
ijassa-751	127	12	x	x	X
ijassa-751	127	13	is	be	AUX
ijassa-751	127	14	a	a	DET
ijassa-751	127	15	vector	vector	NOUN
ijassa-751	127	16	of	of	ADP
ijassa-751	127	17	n	n	DET
ijassa-751	127	18	predictions	prediction	NOUN
ijassa-751	127	19	,	,	PUNCT
ijassa-751	127	20	and	and	CCONJ
ijassa-751	127	21	y	y	PROPN
ijassa-751	127	22	is	be	AUX
ijassa-751	127	23	the	the	DET
ijassa-751	127	24	vector	vector	NOUN
ijassa-751	127	25	of	of	ADP
ijassa-751	127	26	true	true	ADJ
ijassa-751	127	27	values	value	NOUN
ijassa-751	127	28	.	.	PUNCT
ijassa-751	128	1	4	4	X
ijassa-751	128	2	.	.	X
ijassa-751	128	3	if	if	SCONJ
ijassa-751	128	4	the	the	DET
ijassa-751	128	5	fitness	fitness	NOUN
ijassa-751	128	6	function	function	NOUN
ijassa-751	128	7	is	be	AUX
ijassa-751	128	8	better	well	ADJ
ijassa-751	128	9	than	than	ADP
ijassa-751	128	10	the	the	DET
ijassa-751	128	11	best	good	ADJ
ijassa-751	128	12	fitness	fitness	NOUN
ijassa-751	128	13	function	function	NOUN
ijassa-751	128	14	of	of	ADP
ijassa-751	128	15	the	the	DET
ijassa-751	128	16	particle	particle	NOUN
ijassa-751	128	17	(	(	PUNCT
ijassa-751	128	18	pbest	pbest	NOUN
ijassa-751	128	19	)	)	PUNCT
ijassa-751	128	20	then	then	ADV
ijassa-751	128	21	the	the	DET
ijassa-751	128	22	current	current	ADJ
ijassa-751	128	23	position	position	NOUN
ijassa-751	128	24	will	will	AUX
ijassa-751	128	25	be	be	AUX
ijassa-751	128	26	(	(	PUNCT
ijassa-751	128	27	pbest	pb	ADJ
ijassa-751	128	28	)	)	PUNCT
ijassa-751	128	29	5	5	X
ijassa-751	128	30	.	.	X
ijassa-751	128	31	select	select	VERB
ijassa-751	128	32	the	the	DET
ijassa-751	128	33	best	good	ADJ
ijassa-751	128	34	position	position	NOUN
ijassa-751	128	35	among	among	ADP
ijassa-751	128	36	all	all	DET
ijassa-751	128	37	particles	particle	NOUN
ijassa-751	128	38	(	(	PUNCT
ijassa-751	128	39	gbest	gbest	NOUN
ijassa-751	128	40	)	)	PUNCT
ijassa-751	128	41	in	in	ADP
ijassa-751	128	42	current	current	ADJ
ijassa-751	128	43	iteration	iteration	NOUN
ijassa-751	128	44	6	6	NUM
ijassa-751	128	45	.	.	PUNCT
ijassa-751	129	1	update	update	VERB
ijassa-751	129	2	the	the	DET
ijassa-751	129	3	velocity	velocity	NOUN
ijassa-751	129	4	of	of	ADP
ijassa-751	129	5	each	each	DET
ijassa-751	129	6	particle	particle	NOUN
ijassa-751	129	7	depending	depend	VERB
ijassa-751	129	8	on	on	ADP
ijassa-751	129	9	eq	eq	ADP
ijassa-751	129	10	.	.	PUNCT
ijassa-751	130	1	(	(	PUNCT
ijassa-751	130	2	2.1	2.1	NUM
ijassa-751	130	3	)	)	PUNCT
ijassa-751	130	4	.	.	PUNCT
ijassa-751	131	1	7	7	X
ijassa-751	131	2	.	.	X
ijassa-751	131	3	update	update	VERB
ijassa-751	131	4	the	the	DET
ijassa-751	131	5	position	position	NOUN
ijassa-751	131	6	of	of	ADP
ijassa-751	131	7	each	each	DET
ijassa-751	131	8	particle	particle	NOUN
ijassa-751	131	9	(	(	PUNCT
ijassa-751	131	10	w	w	NOUN
ijassa-751	131	11	-	-	PUNCT
ijassa-751	131	12	parameter	parameter	NOUN
ijassa-751	131	13	)	)	PUNCT
ijassa-751	131	14	depending	depend	VERB
ijassa-751	131	15	on	on	ADP
ijassa-751	131	16	eq	eq	ADP
ijassa-751	131	17	.	.	PUNCT
ijassa-751	132	1	(	(	PUNCT
ijassa-751	132	2	2.2	2.2	NUM
ijassa-751	132	3	)	)	PUNCT
ijassa-751	132	4	.	.	PUNCT
ijassa-751	133	1	8	8	X
ijassa-751	133	2	.	.	X
ijassa-751	133	3	search	search	VERB
ijassa-751	133	4	the	the	DET
ijassa-751	133	5	the	the	DET
ijassa-751	133	6	pbest	pbest	NOUN
ijassa-751	133	7	of	of	ADP
ijassa-751	133	8	particle	particle	NOUN
ijassa-751	133	9	as	as	ADP
ijassa-751	133	10	(	(	PUNCT
ijassa-751	133	11	w	w	NOUN
ijassa-751	133	12	-	-	PUNCT
ijassa-751	133	13	parameter	parameter	NOUN
ijassa-751	133	14	)	)	PUNCT
ijassa-751	133	15	of	of	ADP
ijassa-751	133	16	pegasos	pegasos	PROPN
ijassa-751	133	17	algorithm	algorithm	PROPN
ijassa-751	133	18	in	in	ADP
ijassa-751	133	19	same	same	ADJ
ijassa-751	133	20	iteration	iteration	NOUN
ijassa-751	133	21	.	.	PUNCT
ijassa-751	134	1	9	9	X
ijassa-751	134	2	.	.	X
ijassa-751	134	3	repeat	repeat	NOUN
ijassa-751	134	4	steps	step	NOUN
ijassa-751	134	5	3	3	NUM
ijassa-751	134	6	to	to	PART
ijassa-751	134	7	8	8	NUM
ijassa-751	134	8	until	until	ADP
ijassa-751	134	9	obtaining	obtain	VERB
ijassa-751	134	10	the	the	DET
ijassa-751	134	11	best	good	ADJ
ijassa-751	134	12	optimal	optimal	ADJ
ijassa-751	134	13	w	w	NOUN
ijassa-751	134	14	-	-	PUNCT
ijassa-751	134	15	parameter	parameter	NOUN
ijassa-751	134	16	(	(	PUNCT
ijassa-751	134	17	bw	bw	NOUN
ijassa-751	134	18	)	)	PUNCT
ijassa-751	134	19	which	which	PRON
ijassa-751	134	20	leads	lead	VERB
ijassa-751	134	21	to	to	PART
ijassa-751	134	22	get	get	VERB
ijassa-751	134	23	the	the	DET
ijassa-751	134	24	highest	high	ADJ
ijassa-751	134	25	accuracy	accuracy	NOUN
ijassa-751	134	26	for	for	ADP
ijassa-751	134	27	spam	spam	NOUN
ijassa-751	134	28	email	email	NOUN
ijassa-751	134	29	detection	detection	NOUN
ijassa-751	134	30	with	with	ADP
ijassa-751	134	31	more	more	ADJ
ijassa-751	134	32	exploration	exploration	NOUN
ijassa-751	134	33	in	in	ADP
ijassa-751	134	34	the	the	DET
ijassa-751	134	35	search	search	NOUN
ijassa-751	134	36	space	space	NOUN
ijassa-751	134	37	.	.	PUNCT
ijassa-751	135	1	4	4	X
ijassa-751	135	2	.	.	X
ijassa-751	135	3	experimental	experimental	ADJ
ijassa-751	135	4	results	result	NOUN
ijassa-751	135	5	and	and	CCONJ
ijassa-751	135	6	discussions	discussion	NOUN
ijassa-751	135	7	in	in	ADP
ijassa-751	135	8	this	this	DET
ijassa-751	135	9	paper	paper	NOUN
ijassa-751	135	10	,	,	PUNCT
ijassa-751	135	11	the	the	DET
ijassa-751	135	12	experiments	experiment	NOUN
ijassa-751	135	13	were	be	AUX
ijassa-751	135	14	performed	perform	VERB
ijassa-751	135	15	on	on	ADP
ijassa-751	135	16	a	a	DET
ijassa-751	135	17	system	system	NOUN
ijassa-751	135	18	with	with	ADP
ijassa-751	135	19	a	a	DET
ijassa-751	135	20	2.40	2.40	NUM
ijassa-751	135	21	ghz	ghz	NOUN
ijassa-751	135	22	intel(r	intel(r	NOUN
ijassa-751	135	23	)	)	PUNCT
ijassa-751	135	24	core(tm)i7	core(tm)i7	PROPN
ijassa-751	135	25	processor	processor	NOUN
ijassa-751	135	26	and	and	CCONJ
ijassa-751	135	27	16	16	NUM
ijassa-751	135	28	gb	gb	NOUN
ijassa-751	135	29	memory	memory	NOUN
ijassa-751	135	30	using	use	VERB
ijassa-751	135	31	written	write	VERB
ijassa-751	135	32	codes	code	NOUN
ijassa-751	135	33	in	in	ADP
ijassa-751	135	34	matlab	matlab	PROPN
ijassa-751	135	35	15	15	NUM
ijassa-751	135	36	.	.	NOUN
ijassa-751	136	1	4.1	4.1	NUM
ijassa-751	136	2	.	.	PUNCT
ijassa-751	137	1	dataset	dataset	ADJ
ijassa-751	137	2	description	description	NOUN
ijassa-751	137	3	in	in	ADP
ijassa-751	137	4	this	this	DET
ijassa-751	137	5	work	work	NOUN
ijassa-751	137	6	,	,	PUNCT
ijassa-751	137	7	the	the	DET
ijassa-751	137	8	dataset	dataset	NOUN
ijassa-751	137	9	utilized	utilize	VERB
ijassa-751	137	10	is	be	AUX
ijassa-751	137	11	spambase	spambase	NOUN
ijassa-751	137	12	dataset	dataset	NOUN
ijassa-751	137	13	which	which	PRON
ijassa-751	137	14	is	be	AUX
ijassa-751	137	15	used	use	VERB
ijassa-751	137	16	to	to	PART
ijassa-751	137	17	evaluate	evaluate	VERB
ijassa-751	137	18	the	the	DET
ijassa-751	137	19	proposed	propose	VERB
ijassa-751	137	20	algorithm	algorithm	NOUN
ijassa-751	137	21	.	.	PUNCT
ijassa-751	138	1	hopkins	hopkin	NOUN
ijassa-751	138	2	et	et	PROPN
ijassa-751	138	3	al	al	PROPN
ijassa-751	138	4	.	.	PUNCT
ijassa-751	139	1	[	[	X
ijassa-751	139	2	20	20	NUM
ijassa-751	139	3	]	]	PUNCT
ijassa-751	139	4	presented	present	VERB
ijassa-751	139	5	spambase	spambase	PROPN
ijassa-751	139	6	dataset	dataset	VERB
ijassa-751	139	7	in	in	ADP
ijassa-751	139	8	their	their	PRON
ijassa-751	139	9	colleagues	colleague	NOUN
ijassa-751	139	10	.	.	PUNCT
ijassa-751	140	1	it	it	PRON
ijassa-751	140	2	has	have	AUX
ijassa-751	140	3	been	be	AUX
ijassa-751	140	4	collected	collect	VERB
ijassa-751	140	5	from	from	ADP
ijassa-751	140	6	uci	uci	PROPN
ijassa-751	140	7	machine	machine	NOUN
ijassa-751	140	8	learning	learn	VERB
ijassa-751	140	9	repository	repository	NOUN
ijassa-751	140	10	site	site	NOUN
ijassa-751	140	11	.	.	PUNCT
ijassa-751	141	1	in	in	ADP
ijassa-751	141	2	the	the	DET
ijassa-751	141	3	spambase	spambase	PROPN
ijassa-751	141	4	dataset	dataset	NOUN
ijassa-751	141	5	,	,	PUNCT
ijassa-751	141	6	the	the	DET
ijassa-751	141	7	total	total	ADJ
ijassa-751	141	8	email	email	NOUN
ijassa-751	141	9	instances	instance	NOUN
ijassa-751	141	10	is	be	AUX
ijassa-751	141	11	4601	4601	NUM
ijassa-751	141	12	.	.	PUNCT
ijassa-751	142	1	1813	1813	NUM
ijassa-751	142	2	from	from	ADP
ijassa-751	142	3	these	these	DET
ijassa-751	142	4	email	email	NOUN
ijassa-751	142	5	instances	instance	NOUN
ijassa-751	142	6	are	be	AUX
ijassa-751	142	7	characterized	characterize	VERB
ijassa-751	142	8	as	as	ADP
ijassa-751	142	9	spam	spam	NOUN
ijassa-751	142	10	(	(	PUNCT
ijassa-751	142	11	39.4	39.4	NUM
ijassa-751	142	12	%	%	NOUN
ijassa-751	142	13	)	)	PUNCT
ijassa-751	142	14	and	and	CCONJ
ijassa-751	142	15	the	the	DET
ijassa-751	142	16	remaining	remain	VERB
ijassa-751	142	17	are	be	AUX
ijassa-751	142	18	non	non	ADJ
ijassa-751	142	19	-	-	ADJ
ijassa-751	142	20	spam	spam	NOUN
ijassa-751	142	21	.	.	PUNCT
ijassa-751	143	1	spambase	spambase	PROPN
ijassa-751	143	2	dataset	dataset	PROPN
ijassa-751	143	3	consists	consist	VERB
ijassa-751	143	4	of	of	ADP
ijassa-751	143	5	57	57	NUM
ijassa-751	143	6	features	feature	NOUN
ijassa-751	143	7	and	and	CCONJ
ijassa-751	143	8	1	1	NUM
ijassa-751	143	9	classification	classification	NOUN
ijassa-751	143	10	attribute	attribute	NOUN
ijassa-751	143	11	,	,	PUNCT
ijassa-751	143	12	which	which	PRON
ijassa-751	143	13	is	be	AUX
ijassa-751	143	14	the	the	DET
ijassa-751	143	15	label	label	NOUN
ijassa-751	143	16	of	of	ADP
ijassa-751	143	17	class	class	NOUN
ijassa-751	143	18	indicating	indicate	VERB
ijassa-751	143	19	the	the	DET
ijassa-751	143	20	status	status	NOUN
ijassa-751	143	21	of	of	ADP
ijassa-751	143	22	each	each	DET
ijassa-751	143	23	email	email	NOUN
ijassa-751	143	24	instance	instance	NOUN
ijassa-751	143	25	whether	whether	SCONJ
ijassa-751	143	26	it	it	PRON
ijassa-751	143	27	is	be	AUX
ijassa-751	143	28	spam	spam	NOUN
ijassa-751	143	29	(	(	PUNCT
ijassa-751	143	30	1	1	NUM
ijassa-751	143	31	)	)	PUNCT
ijassa-751	143	32	or	or	CCONJ
ijassa-751	143	33	non	non	ADJ
ijassa-751	143	34	-	-	ADJ
ijassa-751	143	35	spam	spam	ADJ
ijassa-751	143	36	(	(	PUNCT
ijassa-751	143	37	0	0	NUM
ijassa-751	143	38	)	)	PUNCT
ijassa-751	143	39	.	.	PUNCT
ijassa-751	144	1	most	most	ADJ
ijassa-751	144	2	of	of	ADP
ijassa-751	144	3	the	the	DET
ijassa-751	144	4	features	feature	NOUN
ijassa-751	144	5	(	(	PUNCT
ijassa-751	144	6	1	1	NUM
ijassa-751	144	7	-	-	SYM
ijassa-751	144	8	54	54	NUM
ijassa-751	144	9	)	)	PUNCT
ijassa-751	144	10	show	show	VERB
ijassa-751	144	11	particular	particular	ADJ
ijassa-751	144	12	characters	character	NOUN
ijassa-751	144	13	or	or	CCONJ
ijassa-751	144	14	words	word	NOUN
ijassa-751	144	15	were	be	AUX
ijassa-751	144	16	repeatedly	repeatedly	ADV
ijassa-751	144	17	occurring	occur	VERB
ijassa-751	144	18	in	in	ADP
ijassa-751	144	19	an	an	DET
ijassa-751	144	20	email	email	NOUN
ijassa-751	144	21	or	or	CCONJ
ijassa-751	144	22	not	not	PART
ijassa-751	144	23	.	.	PUNCT
ijassa-751	145	1	the	the	DET
ijassa-751	145	2	features	feature	NOUN
ijassa-751	145	3	from	from	ADP
ijassa-751	145	4	55	55	NUM
ijassa-751	145	5	to	to	PART
ijassa-751	145	6	57	57	NUM
ijassa-751	145	7	present	present	ADJ
ijassa-751	145	8	the	the	DET
ijassa-751	145	9	measurement	measurement	NOUN
ijassa-751	145	10	for	for	ADP
ijassa-751	145	11	length	length	NOUN
ijassa-751	145	12	of	of	ADP
ijassa-751	145	13	consecutive	consecutive	ADJ
ijassa-751	145	14	capital	capital	NOUN
ijassa-751	145	15	letters	letter	NOUN
ijassa-751	145	16	.	.	PUNCT
ijassa-751	146	1	the	the	DET
ijassa-751	146	2	definitions	definition	NOUN
ijassa-751	146	3	of	of	ADP
ijassa-751	146	4	the	the	DET
ijassa-751	146	5	features	feature	NOUN
ijassa-751	146	6	can	can	AUX
ijassa-751	146	7	be	be	AUX
ijassa-751	146	8	shown	show	VERB
ijassa-751	146	9	as	as	SCONJ
ijassa-751	146	10	follows	follow	VERB
ijassa-751	146	11	•	•	NUM
ijassa-751	146	12	features	feature	NOUN
ijassa-751	146	13	from	from	ADP
ijassa-751	146	14	1	1	NUM
ijassa-751	146	15	to	to	ADP
ijassa-751	146	16	48	48	NUM
ijassa-751	146	17	are	be	AUX
ijassa-751	146	18	real	real	ADJ
ijassa-751	146	19	continuous	continuous	ADJ
ijassa-751	146	20	features	feature	NOUN
ijassa-751	146	21	which	which	PRON
ijassa-751	146	22	are	be	AUX
ijassa-751	146	23	equal	equal	ADJ
ijassa-751	146	24	to	to	ADP
ijassa-751	146	25	the	the	DET
ijassa-751	146	26	percentage	percentage	NOUN
ijassa-751	146	27	of	of	ADP
ijassa-751	146	28	words	word	NOUN
ijassa-751	146	29	in	in	ADP
ijassa-751	146	30	the	the	DET
ijassa-751	146	31	e	e	NOUN
ijassa-751	146	32	-	-	NOUN
ijassa-751	146	33	mail	mail	NOUN
ijassa-751	146	34	that	that	PRON
ijassa-751	146	35	match	match	VERB
ijassa-751	146	36	word	word	NOUN
ijassa-751	146	37	.	.	PUNCT
ijassa-751	147	1	•	•	NOUN
ijassa-751	147	2	features	feature	NOUN
ijassa-751	147	3	from	from	ADP
ijassa-751	147	4	49	49	NUM
ijassa-751	147	5	to	to	PART
ijassa-751	147	6	54	54	NUM
ijassa-751	147	7	are	be	AUX
ijassa-751	147	8	real	real	ADV
ijassa-751	147	9	continuous	continuous	ADJ
ijassa-751	147	10	features	feature	NOUN
ijassa-751	147	11	which	which	PRON
ijassa-751	147	12	are	be	AUX
ijassa-751	147	13	equal	equal	ADJ
ijassa-751	147	14	to	to	ADP
ijassa-751	147	15	the	the	DET
ijassa-751	147	16	percentage	percentage	NOUN
ijassa-751	147	17	of	of	ADP
ijassa-751	147	18	characters	character	NOUN
ijassa-751	147	19	in	in	ADP
ijassa-751	147	20	the	the	DET
ijassa-751	147	21	e	e	NOUN
ijassa-751	147	22	-	-	NOUN
ijassa-751	147	23	mail	mail	NOUN
ijassa-751	147	24	that	that	PRON
ijassa-751	147	25	match	match	VERB
ijassa-751	147	26	char	char	NOUN
ijassa-751	147	27	.	.	PUNCT
ijassa-751	148	1	•	•	NUM
ijassa-751	148	2	feature	feature	NOUN
ijassa-751	148	3	55	55	NUM
ijassa-751	148	4	is	be	AUX
ijassa-751	148	5	real	real	ADV
ijassa-751	148	6	continuous	continuous	ADJ
ijassa-751	148	7	feature	feature	NOUN
ijassa-751	148	8	which	which	PRON
ijassa-751	148	9	is	be	AUX
ijassa-751	148	10	equal	equal	ADJ
ijassa-751	148	11	to	to	ADP
ijassa-751	148	12	the	the	DET
ijassa-751	148	13	average	average	ADJ
ijassa-751	148	14	length	length	NOUN
ijassa-751	148	15	of	of	ADP
ijassa-751	148	16	continuous	continuous	ADJ
ijassa-751	148	17	sequences	sequence	NOUN
ijassa-751	148	18	of	of	ADP
ijassa-751	148	19	capital	capital	NOUN
ijassa-751	148	20	letters	letter	NOUN
ijassa-751	148	21	.	.	PUNCT
ijassa-751	149	1	•	•	NUM
ijassa-751	149	2	feature	feature	NOUN
ijassa-751	149	3	56	56	NUM
ijassa-751	149	4	is	be	AUX
ijassa-751	149	5	an	an	DET
ijassa-751	149	6	integer	integer	NOUN
ijassa-751	149	7	continuous	continuous	ADJ
ijassa-751	149	8	feature	feature	NOUN
ijassa-751	149	9	which	which	PRON
ijassa-751	149	10	is	be	AUX
ijassa-751	149	11	equal	equal	ADJ
ijassa-751	149	12	to	to	ADP
ijassa-751	149	13	the	the	DET
ijassa-751	149	14	length	length	NOUN
ijassa-751	149	15	of	of	ADP
ijassa-751	149	16	longest	long	ADJ
ijassa-751	149	17	continuous	continuous	ADJ
ijassa-751	149	18	sequence	sequence	NOUN
ijassa-751	149	19	of	of	ADP
ijassa-751	149	20	capital	capital	NOUN
ijassa-751	149	21	letters	letter	NOUN
ijassa-751	149	22	.	.	PUNCT
ijassa-751	150	1	•	•	NUM
ijassa-751	150	2	feature	feature	NOUN
ijassa-751	150	3	57	57	NUM
ijassa-751	150	4	is	be	AUX
ijassa-751	150	5	an	an	DET
ijassa-751	150	6	integer	integer	NOUN
ijassa-751	150	7	continuous	continuous	ADJ
ijassa-751	150	8	feature	feature	NOUN
ijassa-751	150	9	which	which	PRON
ijassa-751	150	10	is	be	AUX
ijassa-751	150	11	equal	equal	ADJ
ijassa-751	150	12	to	to	ADP
ijassa-751	150	13	the	the	DET
ijassa-751	150	14	total	total	ADJ
ijassa-751	150	15	number	number	NOUN
ijassa-751	150	16	of	of	ADP
ijassa-751	150	17	capital	capital	NOUN
ijassa-751	150	18	letters	letter	NOUN
ijassa-751	150	19	in	in	ADP
ijassa-751	150	20	the	the	DET
ijassa-751	150	21	e	e	NOUN
ijassa-751	150	22	-	-	NOUN
ijassa-751	150	23	mail	mail	NOUN
ijassa-751	150	24	.	.	PUNCT
ijassa-751	151	1	copyright	copyright	NOUN
ijassa-751	151	2	c	c	ADP
ijassa-751	151	3	©	©	PROPN
ijassa-751	151	4	2019	2019	NUM
ijassa-751	151	5	assa	assa	NOUN
ijassa-751	151	6	.	.	PUNCT
ijassa-751	152	1	adv	adv	PROPN
ijassa-751	152	2	.	.	PUNCT
ijassa-751	153	1	in	in	ADP
ijassa-751	153	2	systems	system	NOUN
ijassa-751	153	3	science	science	NOUN
ijassa-751	153	4	and	and	CCONJ
ijassa-751	153	5	appl.(2019	appl.(2019	NOUN
ijassa-751	153	6	)	)	PUNCT
ijassa-751	153	7	hybrid	hybrid	ADJ
ijassa-751	153	8	particle	particle	NOUN
ijassa-751	153	9	swarm	swarm	NOUN
ijassa-751	153	10	optimization	optimization	NOUN
ijassa-751	153	11	and	and	CCONJ
ijassa-751	153	12	pegasos	pegasos	NOUN
ijassa-751	153	13	algorithm	algorithm	NOUN
ijassa-751	153	14	for	for	ADP
ijassa-751	153	15	spam	spam	NOUN
ijassa-751	153	16	email	email	NOUN
ijassa-751	153	17	detection17	detection17	NOUN
ijassa-751	153	18	4.2	4.2	NUM
ijassa-751	153	19	.	.	PUNCT
ijassa-751	154	1	evaluation	evaluation	NOUN
ijassa-751	154	2	measures	measure	NOUN
ijassa-751	154	3	in	in	ADP
ijassa-751	154	4	this	this	DET
ijassa-751	154	5	research	research	NOUN
ijassa-751	154	6	,	,	PUNCT
ijassa-751	154	7	the	the	DET
ijassa-751	154	8	evaluation	evaluation	NOUN
ijassa-751	154	9	of	of	ADP
ijassa-751	154	10	the	the	DET
ijassa-751	154	11	proposed	propose	VERB
ijassa-751	154	12	algorithm	algorithm	NOUN
ijassa-751	154	13	is	be	AUX
ijassa-751	154	14	carried	carry	VERB
ijassa-751	154	15	out	out	ADP
ijassa-751	154	16	based	base	VERB
ijassa-751	154	17	on	on	ADP
ijassa-751	154	18	popular	popular	ADJ
ijassa-751	154	19	and	and	CCONJ
ijassa-751	154	20	commonly	commonly	ADV
ijassa-751	154	21	performance	performance	NOUN
ijassa-751	154	22	measures	measure	NOUN
ijassa-751	154	23	such	such	ADJ
ijassa-751	154	24	as	as	ADP
ijassa-751	154	25	accuracy	accuracy	NOUN
ijassa-751	154	26	,	,	PUNCT
ijassa-751	154	27	recall	recall	NOUN
ijassa-751	154	28	,	,	PUNCT
ijassa-751	154	29	precision	precision	NOUN
ijassa-751	154	30	,	,	PUNCT
ijassa-751	154	31	f	f	X
ijassa-751	154	32	-	-	PUNCT
ijassa-751	154	33	measure	measure	NOUN
ijassa-751	154	34	[	[	X
ijassa-751	154	35	21	21	NUM
ijassa-751	154	36	,	,	PUNCT
ijassa-751	154	37	22	22	NUM
ijassa-751	154	38	]	]	PUNCT
ijassa-751	154	39	.	.	PUNCT
ijassa-751	155	1	the	the	DET
ijassa-751	155	2	information	information	NOUN
ijassa-751	155	3	about	about	ADP
ijassa-751	155	4	these	these	DET
ijassa-751	155	5	measures	measure	NOUN
ijassa-751	155	6	is	be	AUX
ijassa-751	155	7	done	do	VERB
ijassa-751	155	8	depending	depend	VERB
ijassa-751	155	9	on	on	ADP
ijassa-751	155	10	the	the	DET
ijassa-751	155	11	confusion	confusion	NOUN
ijassa-751	155	12	matrix	matrix	NOUN
ijassa-751	155	13	presented	present	VERB
ijassa-751	155	14	in	in	ADP
ijassa-751	155	15	table	table	NOUN
ijassa-751	155	16	4.1	4.1	NUM
ijassa-751	155	17	.	.	PUNCT
ijassa-751	155	18	table	table	NOUN
ijassa-751	155	19	4.1	4.1	NUM
ijassa-751	155	20	:	:	PUNCT
ijassa-751	155	21	confusion	confusion	NOUN
ijassa-751	155	22	matrix	matrix	NOUN
ijassa-751	155	23	actual	actual	ADJ
ijassa-751	155	24	class	class	NOUN
ijassa-751	155	25	spam	spam	NOUN
ijassa-751	155	26	non	non	ADJ
ijassa-751	155	27	-	-	ADJ
ijassa-751	155	28	spam	spam	ADJ
ijassa-751	155	29	predicted	predict	VERB
ijassa-751	155	30	class	class	NOUN
ijassa-751	155	31	spam	spam	NOUN
ijassa-751	155	32	tp	tp	ADP
ijassa-751	155	33	fp	fp	DET
ijassa-751	155	34	non	non	ADJ
ijassa-751	155	35	-	-	ADJ
ijassa-751	155	36	spam	spam	ADJ
ijassa-751	155	37	fn	fn	PROPN
ijassa-751	155	38	tn	tn	PROPN
ijassa-751	155	39	brief	brief	ADJ
ijassa-751	155	40	overview	overview	NOUN
ijassa-751	155	41	of	of	ADP
ijassa-751	155	42	each	each	DET
ijassa-751	155	43	performance	performance	NOUN
ijassa-751	155	44	measure	measure	NOUN
ijassa-751	155	45	is	be	AUX
ijassa-751	155	46	shown	show	VERB
ijassa-751	155	47	below	below	ADP
ijassa-751	155	48	.	.	PUNCT
ijassa-751	156	1	•	•	NUM
ijassa-751	156	2	accuracy	accuracy	NOUN
ijassa-751	156	3	is	be	AUX
ijassa-751	156	4	defined	define	VERB
ijassa-751	156	5	as	as	ADP
ijassa-751	156	6	the	the	DET
ijassa-751	156	7	fraction	fraction	NOUN
ijassa-751	156	8	of	of	ADP
ijassa-751	156	9	all	all	DET
ijassa-751	156	10	emails	email	NOUN
ijassa-751	156	11	(	(	PUNCT
ijassa-751	156	12	non	non	ADJ
ijassa-751	156	13	-	-	ADJ
ijassa-751	156	14	spam	spam	ADJ
ijassa-751	156	15	and	and	CCONJ
ijassa-751	156	16	spam	spam	NOUN
ijassa-751	156	17	emails	email	NOUN
ijassa-751	156	18	)	)	PUNCT
ijassa-751	156	19	that	that	PRON
ijassa-751	156	20	are	be	AUX
ijassa-751	156	21	classified	classify	VERB
ijassa-751	156	22	correctly	correctly	ADV
ijassa-751	156	23	by	by	ADP
ijassa-751	156	24	the	the	DET
ijassa-751	156	25	algorithm	algorithm	NOUN
ijassa-751	156	26	.	.	PUNCT
ijassa-751	157	1	it	it	PRON
ijassa-751	157	2	can	can	AUX
ijassa-751	157	3	be	be	AUX
ijassa-751	157	4	represented	represent	VERB
ijassa-751	157	5	by	by	ADP
ijassa-751	157	6	the	the	DET
ijassa-751	157	7	following	follow	VERB
ijassa-751	157	8	equation	equation	NOUN
ijassa-751	157	9	:	:	PUNCT
ijassa-751	157	10	accuracy	accuracy	NOUN
ijassa-751	157	11	=	=	SYM
ijassa-751	158	1	tp+tn	tp+tn	INTJ
ijassa-751	158	2	fp+fn+tp+tn	fp+fn+tp+tn	INTJ
ijassa-751	158	3	(	(	PUNCT
ijassa-751	158	4	4.11	4.11	NUM
ijassa-751	158	5	)	)	PUNCT
ijassa-751	158	6	where	where	SCONJ
ijassa-751	158	7	tp	tp	NOUN
ijassa-751	158	8	and	and	CCONJ
ijassa-751	158	9	tn	tn	PROPN
ijassa-751	158	10	are	be	AUX
ijassa-751	158	11	the	the	DET
ijassa-751	158	12	number	number	NOUN
ijassa-751	158	13	of	of	ADP
ijassa-751	158	14	spam	spam	NOUN
ijassa-751	158	15	emails	email	NOUN
ijassa-751	158	16	and	and	CCONJ
ijassa-751	158	17	non	non	ADJ
ijassa-751	158	18	-	-	ADJ
ijassa-751	158	19	spam	spam	ADJ
ijassa-751	158	20	emails	email	NOUN
ijassa-751	158	21	correctly	correctly	ADV
ijassa-751	158	22	classified	classify	VERB
ijassa-751	158	23	,	,	PUNCT
ijassa-751	158	24	respectively	respectively	ADV
ijassa-751	158	25	.	.	PUNCT
ijassa-751	159	1	fp	fp	NOUN
ijassa-751	159	2	and	and	CCONJ
ijassa-751	159	3	fn	fn	PROPN
ijassa-751	159	4	are	be	AUX
ijassa-751	159	5	the	the	DET
ijassa-751	159	6	number	number	NOUN
ijassa-751	159	7	of	of	ADP
ijassa-751	159	8	spam	spam	NOUN
ijassa-751	159	9	emails	email	NOUN
ijassa-751	159	10	and	and	CCONJ
ijassa-751	159	11	non	non	ADJ
ijassa-751	159	12	-	-	ADJ
ijassa-751	159	13	spam	spam	ADJ
ijassa-751	159	14	emails	email	NOUN
ijassa-751	159	15	incorrectly	incorrectly	ADV
ijassa-751	159	16	classified	classify	VERB
ijassa-751	159	17	,	,	PUNCT
ijassa-751	159	18	respectively	respectively	ADV
ijassa-751	159	19	.	.	PUNCT
ijassa-751	160	1	•	•	NUM
ijassa-751	160	2	recall	recall	NOUN
ijassa-751	160	3	stands	stand	VERB
ijassa-751	160	4	for	for	ADP
ijassa-751	160	5	the	the	DET
ijassa-751	160	6	proportion	proportion	NOUN
ijassa-751	160	7	of	of	ADP
ijassa-751	160	8	spam	spam	NOUN
ijassa-751	160	9	emails	email	NOUN
ijassa-751	160	10	being	be	AUX
ijassa-751	160	11	recognized	recognize	VERB
ijassa-751	160	12	and	and	CCONJ
ijassa-751	160	13	can	can	AUX
ijassa-751	160	14	be	be	AUX
ijassa-751	160	15	represented	represent	VERB
ijassa-751	160	16	as	as	SCONJ
ijassa-751	160	17	follows	follow	VERB
ijassa-751	160	18	:	:	PUNCT
ijassa-751	160	19	recall	recall	VERB
ijassa-751	160	20	=	=	PRON
ijassa-751	160	21	tp	tp	NOUN
ijassa-751	160	22	fn+tp	fn+tp	NUM
ijassa-751	160	23	(	(	PUNCT
ijassa-751	160	24	4.12	4.12	NUM
ijassa-751	160	25	)	)	PUNCT
ijassa-751	160	26	•	•	NUM
ijassa-751	161	1	precision	precision	NOUN
ijassa-751	161	2	stands	stand	VERB
ijassa-751	161	3	for	for	ADP
ijassa-751	161	4	the	the	DET
ijassa-751	161	5	fraction	fraction	NOUN
ijassa-751	161	6	of	of	ADP
ijassa-751	161	7	spam	spam	NOUN
ijassa-751	161	8	emails	email	NOUN
ijassa-751	161	9	that	that	PRON
ijassa-751	161	10	are	be	AUX
ijassa-751	161	11	correctly	correctly	ADV
ijassa-751	161	12	classified	classify	VERB
ijassa-751	161	13	as	as	ADP
ijassa-751	161	14	spam	spam	NOUN
ijassa-751	161	15	.	.	PUNCT
ijassa-751	162	1	precision	precision	NOUN
ijassa-751	162	2	=	=	SYM
ijassa-751	162	3	tp	tp	X
ijassa-751	162	4	fp+tp	fp+tp	VERB
ijassa-751	162	5	(	(	PUNCT
ijassa-751	162	6	4.13	4.13	NUM
ijassa-751	162	7	)	)	PUNCT
ijassa-751	162	8	•	•	NOUN
ijassa-751	162	9	f	f	X
ijassa-751	162	10	-	-	PUNCT
ijassa-751	162	11	measure	measure	NOUN
ijassa-751	162	12	(	(	PUNCT
ijassa-751	162	13	f	f	X
ijassa-751	162	14	-	-	PUNCT
ijassa-751	162	15	score	score	NOUN
ijassa-751	162	16	)	)	PUNCT
ijassa-751	162	17	,	,	PUNCT
ijassa-751	162	18	denotes	denote	VERB
ijassa-751	162	19	the	the	DET
ijassa-751	162	20	harmonic	harmonic	ADJ
ijassa-751	162	21	average	average	NOUN
ijassa-751	162	22	of	of	ADP
ijassa-751	162	23	precision	precision	NOUN
ijassa-751	162	24	and	and	CCONJ
ijassa-751	162	25	recall	recall	NOUN
ijassa-751	162	26	and	and	CCONJ
ijassa-751	162	27	can	can	AUX
ijassa-751	162	28	be	be	AUX
ijassa-751	162	29	written	write	VERB
ijassa-751	162	30	as	as	SCONJ
ijassa-751	162	31	follows	follow	VERB
ijassa-751	162	32	:	:	PUNCT
ijassa-751	162	33	f	f	X
ijassa-751	162	34	−measure	−measure	NOUN
ijassa-751	162	35	=	=	SYM
ijassa-751	162	36	2∗precision∗recall	2∗precision∗recall	NUM
ijassa-751	162	37	precision+recall	precision+recall	PROPN
ijassa-751	162	38	(	(	PUNCT
ijassa-751	162	39	4.14	4.14	NUM
ijassa-751	162	40	)	)	PUNCT
ijassa-751	162	41	4.3	4.3	NUM
ijassa-751	162	42	.	.	PUNCT
ijassa-751	162	43	results	result	NOUN
ijassa-751	162	44	and	and	CCONJ
ijassa-751	162	45	discussion	discussion	NOUN
ijassa-751	162	46	the	the	DET
ijassa-751	162	47	experimental	experimental	ADJ
ijassa-751	162	48	method	method	NOUN
ijassa-751	162	49	applied	apply	VERB
ijassa-751	162	50	here	here	ADV
ijassa-751	162	51	followed	follow	VERB
ijassa-751	162	52	carefully	carefully	ADV
ijassa-751	162	53	the	the	DET
ijassa-751	162	54	computational	computational	ADJ
ijassa-751	162	55	intelligence	intelligence	NOUN
ijassa-751	162	56	technique	technique	NOUN
ijassa-751	162	57	.	.	PUNCT
ijassa-751	163	1	spambase	spambase	PROPN
ijassa-751	163	2	dataset	dataset	PROPN
ijassa-751	163	3	was	be	AUX
ijassa-751	163	4	first	first	ADV
ijassa-751	163	5	divided	divide	VERB
ijassa-751	163	6	into	into	ADP
ijassa-751	163	7	two	two	NUM
ijassa-751	163	8	phases	phase	NOUN
ijassa-751	163	9	,	,	PUNCT
ijassa-751	163	10	training	training	NOUN
ijassa-751	163	11	set	set	NOUN
ijassa-751	163	12	and	and	CCONJ
ijassa-751	163	13	testing	testing	NOUN
ijassa-751	163	14	set	set	VERB
ijassa-751	163	15	in	in	ADP
ijassa-751	163	16	the	the	DET
ijassa-751	163	17	ratio	ratio	NOUN
ijassa-751	163	18	7:3	7:3	NUM
ijassa-751	163	19	,	,	PUNCT
ijassa-751	163	20	respectively	respectively	ADV
ijassa-751	163	21	.	.	PUNCT
ijassa-751	164	1	the	the	DET
ijassa-751	164	2	data	datum	NOUN
ijassa-751	164	3	was	be	AUX
ijassa-751	164	4	chosen	choose	VERB
ijassa-751	164	5	randomly	randomly	ADV
ijassa-751	164	6	for	for	ADP
ijassa-751	164	7	training	training	NOUN
ijassa-751	164	8	and	and	CCONJ
ijassa-751	164	9	testing	testing	NOUN
ijassa-751	164	10	sets	set	NOUN
ijassa-751	164	11	in	in	ADP
ijassa-751	164	12	order	order	NOUN
ijassa-751	164	13	to	to	PART
ijassa-751	164	14	exclude	exclude	VERB
ijassa-751	164	15	any	any	DET
ijassa-751	164	16	particular	particular	ADJ
ijassa-751	164	17	behavior	behavior	NOUN
ijassa-751	164	18	of	of	ADP
ijassa-751	164	19	the	the	DET
ijassa-751	164	20	dataset	dataset	NOUN
ijassa-751	164	21	.	.	PUNCT
ijassa-751	165	1	then	then	ADV
ijassa-751	165	2	,	,	PUNCT
ijassa-751	165	3	the	the	DET
ijassa-751	165	4	training	training	NOUN
ijassa-751	165	5	set	set	NOUN
ijassa-751	165	6	(	(	PUNCT
ijassa-751	165	7	70	70	NUM
ijassa-751	165	8	%	%	NOUN
ijassa-751	165	9	of	of	ADP
ijassa-751	165	10	data	datum	NOUN
ijassa-751	165	11	)	)	PUNCT
ijassa-751	165	12	was	be	AUX
ijassa-751	165	13	first	first	ADV
ijassa-751	165	14	entered	enter	VERB
ijassa-751	165	15	to	to	ADP
ijassa-751	165	16	the	the	DET
ijassa-751	165	17	algorithm	algorithm	NOUN
ijassa-751	165	18	for	for	ADP
ijassa-751	165	19	training	training	NOUN
ijassa-751	165	20	and	and	CCONJ
ijassa-751	165	21	validation	validation	NOUN
ijassa-751	165	22	and	and	CCONJ
ijassa-751	165	23	the	the	DET
ijassa-751	165	24	rest	rest	NOUN
ijassa-751	165	25	of	of	ADP
ijassa-751	165	26	dataset	dataset	NOUN
ijassa-751	165	27	(	(	PUNCT
ijassa-751	165	28	30	30	NUM
ijassa-751	165	29	%	%	NOUN
ijassa-751	165	30	of	of	ADP
ijassa-751	165	31	data	datum	NOUN
ijassa-751	165	32	)	)	PUNCT
ijassa-751	165	33	was	be	AUX
ijassa-751	165	34	used	use	VERB
ijassa-751	165	35	to	to	PART
ijassa-751	165	36	test	test	VERB
ijassa-751	165	37	the	the	DET
ijassa-751	165	38	algorithm	algorithm	NOUN
ijassa-751	165	39	to	to	PART
ijassa-751	165	40	ensure	ensure	VERB
ijassa-751	165	41	the	the	DET
ijassa-751	165	42	performance	performance	NOUN
ijassa-751	165	43	accuracy	accuracy	NOUN
ijassa-751	165	44	of	of	ADP
ijassa-751	165	45	the	the	DET
ijassa-751	165	46	proposed	propose	VERB
ijassa-751	165	47	algorithm	algorithm	NOUN
ijassa-751	165	48	.	.	PUNCT
ijassa-751	166	1	to	to	PART
ijassa-751	166	2	evaluate	evaluate	VERB
ijassa-751	166	3	the	the	DET
ijassa-751	166	4	proposed	propose	VERB
ijassa-751	166	5	algorithm	algorithm	NOUN
ijassa-751	166	6	,	,	PUNCT
ijassa-751	166	7	the	the	DET
ijassa-751	166	8	parameters	parameter	NOUN
ijassa-751	166	9	settings	setting	VERB
ijassa-751	166	10	for	for	ADP
ijassa-751	166	11	original	original	ADJ
ijassa-751	166	12	pegasos	pegasos	NOUN
ijassa-751	166	13	algorithm	algorithm	NOUN
ijassa-751	166	14	are	be	AUX
ijassa-751	166	15	regularization	regularization	NOUN
ijassa-751	166	16	parameter	parameter	NOUN
ijassa-751	166	17	(	(	PUNCT
ijassa-751	166	18	λ	λ	NOUN
ijassa-751	166	19	)	)	PUNCT
ijassa-751	166	20	with	with	ADP
ijassa-751	166	21	different	different	ADJ
ijassa-751	166	22	values	value	NOUN
ijassa-751	166	23	from	from	ADP
ijassa-751	166	24	0.0001	0.0001	NUM
ijassa-751	166	25	to	to	ADP
ijassa-751	166	26	0.1	0.1	NUM
ijassa-751	166	27	and	and	CCONJ
ijassa-751	166	28	number	number	NOUN
ijassa-751	166	29	of	of	ADP
ijassa-751	166	30	iterations	iteration	NOUN
ijassa-751	166	31	t	t	NOUN
ijassa-751	166	32	=	=	SYM
ijassa-751	166	33	1000	1000	NUM
ijassa-751	166	34	.	.	PUNCT
ijassa-751	167	1	the	the	DET
ijassa-751	167	2	original	original	ADJ
ijassa-751	167	3	pegasos	pegasos	NOUN
ijassa-751	167	4	algorithm	algorithm	NOUN
ijassa-751	167	5	is	be	AUX
ijassa-751	167	6	applied	apply	VERB
ijassa-751	167	7	on	on	ADP
ijassa-751	167	8	spambase	spambase	PROPN
ijassa-751	167	9	dataset	dataset	VERB
ijassa-751	167	10	with	with	ADP
ijassa-751	167	11	different	different	ADJ
ijassa-751	167	12	values	value	NOUN
ijassa-751	167	13	of	of	ADP
ijassa-751	167	14	λ	λ	PROPN
ijassa-751	167	15	and	and	CCONJ
ijassa-751	167	16	the	the	DET
ijassa-751	167	17	four	four	NUM
ijassa-751	167	18	performance	performance	NOUN
ijassa-751	167	19	measures	measure	NOUN
ijassa-751	167	20	are	be	AUX
ijassa-751	167	21	recorded	record	VERB
ijassa-751	167	22	for	for	ADP
ijassa-751	167	23	training	training	NOUN
ijassa-751	167	24	and	and	CCONJ
ijassa-751	167	25	testing	testing	NOUN
ijassa-751	167	26	sets	set	NOUN
ijassa-751	167	27	as	as	SCONJ
ijassa-751	167	28	shown	show	VERB
ijassa-751	167	29	in	in	ADP
ijassa-751	167	30	table	table	NOUN
ijassa-751	167	31	4.2	4.2	NUM
ijassa-751	167	32	.	.	PUNCT
ijassa-751	168	1	it	it	PRON
ijassa-751	168	2	can	can	AUX
ijassa-751	168	3	be	be	AUX
ijassa-751	168	4	observed	observe	VERB
ijassa-751	168	5	in	in	ADP
ijassa-751	168	6	table	table	NOUN
ijassa-751	168	7	4.2	4.2	NUM
ijassa-751	168	8	that	that	PRON
ijassa-751	168	9	using	use	VERB
ijassa-751	168	10	a	a	DET
ijassa-751	168	11	small	small	ADJ
ijassa-751	168	12	value	value	NOUN
ijassa-751	168	13	of	of	ADP
ijassa-751	168	14	λ	λ	PROPN
ijassa-751	168	15	(	(	PUNCT
ijassa-751	168	16	0.0001	0.0001	NUM
ijassa-751	168	17	)	)	PUNCT
ijassa-751	168	18	in	in	ADP
ijassa-751	168	19	a	a	DET
ijassa-751	168	20	large	large	ADJ
ijassa-751	168	21	dataset	dataset	NOUN
ijassa-751	168	22	increases	increase	NOUN
ijassa-751	168	23	the	the	DET
ijassa-751	168	24	accuracy	accuracy	NOUN
ijassa-751	168	25	,	,	PUNCT
ijassa-751	168	26	recall	recall	NOUN
ijassa-751	168	27	,	,	PUNCT
ijassa-751	168	28	precision	precision	NOUN
ijassa-751	168	29	and	and	CCONJ
ijassa-751	168	30	f	f	NOUN
ijassa-751	168	31	-	-	PUNCT
ijassa-751	168	32	measure	measure	NOUN
ijassa-751	168	33	,	,	PUNCT
ijassa-751	168	34	respectively	respectively	ADV
ijassa-751	168	35	for	for	ADP
ijassa-751	168	36	spam	spam	NOUN
ijassa-751	168	37	detection	detection	NOUN
ijassa-751	168	38	by	by	ADP
ijassa-751	168	39	pegasos	pegasos	PROPN
ijassa-751	168	40	algorithm	algorithm	PROPN
ijassa-751	168	41	.	.	PUNCT
ijassa-751	169	1	according	accord	VERB
ijassa-751	169	2	to	to	ADP
ijassa-751	169	3	this	this	DET
ijassa-751	169	4	result	result	NOUN
ijassa-751	169	5	,	,	PUNCT
ijassa-751	169	6	we	we	PRON
ijassa-751	169	7	fixed	fix	VERB
ijassa-751	169	8	the	the	DET
ijassa-751	169	9	copyright	copyright	NOUN
ijassa-751	169	10	c	c	ADP
ijassa-751	169	11	©	©	PROPN
ijassa-751	169	12	2019	2019	NUM
ijassa-751	169	13	assa	assa	NOUN
ijassa-751	169	14	.	.	PUNCT
ijassa-751	170	1	adv	adv	PROPN
ijassa-751	170	2	.	.	PUNCT
ijassa-751	171	1	in	in	ADP
ijassa-751	171	2	systems	system	NOUN
ijassa-751	171	3	science	science	NOUN
ijassa-751	171	4	and	and	CCONJ
ijassa-751	171	5	appl.(2019	appl.(2019	NOUN
ijassa-751	171	6	)	)	PUNCT
ijassa-751	171	7	18	18	NUM
ijassa-751	171	8	l.m	l.m	PROPN
ijassa-751	171	9	.	.	PROPN
ijassa-751	171	10	el	el	PROPN
ijassa-751	171	11	bakrawy	bakrawy	PROPN
ijassa-751	171	12	table	table	PROPN
ijassa-751	171	13	4.2	4.2	NUM
ijassa-751	171	14	:	:	PUNCT
ijassa-751	171	15	performance	performance	NOUN
ijassa-751	171	16	measures	measure	NOUN
ijassa-751	171	17	for	for	ADP
ijassa-751	171	18	pegasos	pegasos	NOUN
ijassa-751	171	19	algorithm	algorithm	NOUN
ijassa-751	171	20	with	with	ADP
ijassa-751	171	21	different	different	ADJ
ijassa-751	171	22	values	value	NOUN
ijassa-751	171	23	of	of	ADP
ijassa-751	171	24	λ	λ	PROPN
ijassa-751	171	25	for	for	ADP
ijassa-751	171	26	spambase	spambase	NOUN
ijassa-751	171	27	dataset	dataset	NOUN
ijassa-751	171	28	(	(	PUNCT
ijassa-751	171	29	λ	λ	NOUN
ijassa-751	171	30	)	)	PUNCT
ijassa-751	171	31	accuracy	accuracy	NOUN
ijassa-751	171	32	recall	recall	NOUN
ijassa-751	171	33	precision	precision	PROPN
ijassa-751	171	34	f	f	NOUN
ijassa-751	171	35	-	-	PUNCT
ijassa-751	171	36	measure	measure	NOUN
ijassa-751	171	37	0.0001	0.0001	NUM
ijassa-751	171	38	training	training	NOUN
ijassa-751	171	39	set	set	NOUN
ijassa-751	171	40	93.62	93.62	NUM
ijassa-751	171	41	%	%	NOUN
ijassa-751	171	42	0.9360	0.9360	NUM
ijassa-751	171	43	0.9370	0.9370	NUM
ijassa-751	171	44	0.9360	0.9360	NUM
ijassa-751	171	45	testing	testing	NOUN
ijassa-751	171	46	set	set	VERB
ijassa-751	171	47	92.71	92.71	NUM
ijassa-751	171	48	%	%	NOUN
ijassa-751	172	1	0.9270	0.9270	NUM
ijassa-751	172	2	0.9280	0.9280	NUM
ijassa-751	172	3	0.9270	0.9270	NUM
ijassa-751	172	4	0.001	0.001	NUM
ijassa-751	172	5	training	training	NOUN
ijassa-751	172	6	set	set	VERB
ijassa-751	172	7	93.04	93.04	NUM
ijassa-751	172	8	%	%	NOUN
ijassa-751	172	9	0.9300	0.9300	NUM
ijassa-751	172	10	0.9310	0.9310	NUM
ijassa-751	172	11	0.9310	0.9310	NUM
ijassa-751	172	12	testing	testing	NOUN
ijassa-751	172	13	set	set	VERB
ijassa-751	172	14	92.51	92.51	NUM
ijassa-751	172	15	%	%	NOUN
ijassa-751	173	1	0.9250	0.9250	NUM
ijassa-751	173	2	0.9250	0.9250	NUM
ijassa-751	173	3	0.9250	0.9250	NUM
ijassa-751	173	4	0.01	0.01	NUM
ijassa-751	173	5	training	training	NOUN
ijassa-751	173	6	set	set	VERB
ijassa-751	173	7	92.60	92.60	NUM
ijassa-751	173	8	%	%	NOUN
ijassa-751	173	9	0.9260	0.9260	NUM
ijassa-751	173	10	0.926	0.926	NUM
ijassa-751	173	11	0.926	0.926	NUM
ijassa-751	173	12	testing	testing	NOUN
ijassa-751	173	13	set	set	VERB
ijassa-751	173	14	91.67	91.67	NUM
ijassa-751	173	15	%	%	NOUN
ijassa-751	173	16	0.9170	0.9170	NUM
ijassa-751	173	17	0.9180	0.9180	NUM
ijassa-751	173	18	0.9160	0.9160	NUM
ijassa-751	173	19	0.1	0.1	NUM
ijassa-751	173	20	training	training	NOUN
ijassa-751	173	21	set	set	NOUN
ijassa-751	173	22	90.43	90.43	NUM
ijassa-751	173	23	%	%	NOUN
ijassa-751	173	24	0.9040	0.9040	NUM
ijassa-751	173	25	0.9060	0.9060	NUM
ijassa-751	173	26	0.903	0.903	NUM
ijassa-751	173	27	testing	testing	NOUN
ijassa-751	173	28	set	set	VERB
ijassa-751	173	29	89.19	89.19	NUM
ijassa-751	173	30	%	%	NOUN
ijassa-751	173	31	0.8920	0.8920	NUM
ijassa-751	173	32	0.8970	0.8970	NUM
ijassa-751	173	33	0.8900	0.8900	NUM
ijassa-751	173	34	value	value	NOUN
ijassa-751	173	35	of	of	ADP
ijassa-751	173	36	λ	λ	PROPN
ijassa-751	173	37	as	as	ADP
ijassa-751	173	38	0.0001	0.0001	NUM
ijassa-751	173	39	in	in	ADP
ijassa-751	173	40	proposed	propose	VERB
ijassa-751	173	41	algorithm	algorithm	NOUN
ijassa-751	173	42	(	(	PUNCT
ijassa-751	173	43	pso	pso	NOUN
ijassa-751	173	44	-	-	PUNCT
ijassa-751	173	45	pegasos	pegasos	NOUN
ijassa-751	173	46	)	)	PUNCT
ijassa-751	173	47	.	.	PUNCT
ijassa-751	174	1	in	in	ADP
ijassa-751	174	2	pso	pso	NOUN
ijassa-751	174	3	-	-	PUNCT
ijassa-751	174	4	pegasos	pegasos	NOUN
ijassa-751	174	5	,	,	PUNCT
ijassa-751	174	6	the	the	DET
ijassa-751	174	7	parameters	parameter	NOUN
ijassa-751	174	8	of	of	ADP
ijassa-751	174	9	particle	particle	NOUN
ijassa-751	174	10	swarm	swarm	NOUN
ijassa-751	174	11	optimization	optimization	NOUN
ijassa-751	174	12	were	be	AUX
ijassa-751	174	13	set	set	VERB
ijassa-751	174	14	as	as	ADP
ijassa-751	174	15	learning	learn	VERB
ijassa-751	174	16	factors	factor	NOUN
ijassa-751	174	17	c1	c1	NOUN
ijassa-751	174	18	=	=	PROPN
ijassa-751	174	19	c2	c2	PROPN
ijassa-751	174	20	=	=	SYM
ijassa-751	174	21	1.4	1.4	NUM
ijassa-751	174	22	,	,	PUNCT
ijassa-751	174	23	vmax	vmax	PROPN
ijassa-751	174	24	=	=	SYM
ijassa-751	174	25	4	4	NUM
ijassa-751	174	26	and	and	CCONJ
ijassa-751	174	27	inertia	inertia	NOUN
ijassa-751	174	28	weight	weight	NOUN
ijassa-751	174	29	(	(	PUNCT
ijassa-751	174	30	w	w	NOUN
ijassa-751	174	31	)	)	PUNCT
ijassa-751	174	32	was	be	AUX
ijassa-751	174	33	linearly	linearly	ADV
ijassa-751	174	34	decreased	decrease	VERB
ijassa-751	174	35	from	from	ADP
ijassa-751	174	36	0.9	0.9	NUM
ijassa-751	174	37	to	to	ADP
ijassa-751	174	38	0.4	0.4	NUM
ijassa-751	174	39	.	.	PUNCT
ijassa-751	175	1	the	the	DET
ijassa-751	175	2	population	population	NOUN
ijassa-751	175	3	size	size	NOUN
ijassa-751	175	4	was	be	AUX
ijassa-751	175	5	fixed	fix	VERB
ijassa-751	175	6	to	to	ADP
ijassa-751	175	7	20	20	NUM
ijassa-751	175	8	particles	particle	NOUN
ijassa-751	175	9	to	to	PART
ijassa-751	175	10	reduce	reduce	VERB
ijassa-751	175	11	the	the	DET
ijassa-751	175	12	computational	computational	ADJ
ijassa-751	175	13	cost	cost	NOUN
ijassa-751	175	14	and	and	CCONJ
ijassa-751	175	15	fast	fast	VERB
ijassa-751	175	16	the	the	DET
ijassa-751	175	17	convergence	convergence	NOUN
ijassa-751	175	18	process	process	NOUN
ijassa-751	175	19	of	of	ADP
ijassa-751	175	20	the	the	DET
ijassa-751	175	21	algorithm	algorithm	NOUN
ijassa-751	175	22	.	.	PUNCT
ijassa-751	176	1	tuning	tune	VERB
ijassa-751	176	2	the	the	DET
ijassa-751	176	3	parameters	parameter	NOUN
ijassa-751	176	4	for	for	ADP
ijassa-751	176	5	particle	particle	NOUN
ijassa-751	176	6	swarm	swarm	NOUN
ijassa-751	176	7	optimization	optimization	NOUN
ijassa-751	176	8	is	be	AUX
ijassa-751	176	9	important	important	ADJ
ijassa-751	176	10	in	in	ADP
ijassa-751	176	11	designing	design	VERB
ijassa-751	176	12	the	the	DET
ijassa-751	176	13	algorithm	algorithm	NOUN
ijassa-751	176	14	.	.	PUNCT
ijassa-751	177	1	figure	figure	VERB
ijassa-751	177	2	4.2	4.2	NUM
ijassa-751	177	3	shows	show	VERB
ijassa-751	177	4	the	the	DET
ijassa-751	177	5	effect	effect	NOUN
ijassa-751	177	6	of	of	ADP
ijassa-751	177	7	the	the	DET
ijassa-751	177	8	number	number	NOUN
ijassa-751	177	9	of	of	ADP
ijassa-751	177	10	iterations	iteration	NOUN
ijassa-751	177	11	on	on	ADP
ijassa-751	177	12	the	the	DET
ijassa-751	177	13	accuracy	accuracy	NOUN
ijassa-751	177	14	of	of	ADP
ijassa-751	177	15	the	the	DET
ijassa-751	177	16	proposed	propose	VERB
ijassa-751	177	17	algorithm	algorithm	NOUN
ijassa-751	177	18	pso	pso	NOUN
ijassa-751	177	19	-	-	PUNCT
ijassa-751	177	20	pegasos	pegasos	NOUN
ijassa-751	177	21	using	use	VERB
ijassa-751	177	22	different	different	ADJ
ijassa-751	177	23	number	number	NOUN
ijassa-751	177	24	of	of	ADP
ijassa-751	177	25	iterations	iteration	NOUN
ijassa-751	177	26	from	from	ADP
ijassa-751	177	27	5	5	NUM
ijassa-751	177	28	to	to	PART
ijassa-751	177	29	30	30	NUM
ijassa-751	177	30	.	.	PUNCT
ijassa-751	178	1	as	as	SCONJ
ijassa-751	178	2	shown	show	VERB
ijassa-751	178	3	in	in	ADP
ijassa-751	178	4	fig	fig	NOUN
ijassa-751	178	5	.	.	PUNCT
ijassa-751	179	1	4.2	4.2	NUM
ijassa-751	179	2	,	,	PUNCT
ijassa-751	179	3	we	we	PRON
ijassa-751	179	4	can	can	AUX
ijassa-751	179	5	observe	observe	VERB
ijassa-751	179	6	that	that	SCONJ
ijassa-751	179	7	when	when	SCONJ
ijassa-751	179	8	the	the	DET
ijassa-751	179	9	number	number	NOUN
ijassa-751	179	10	of	of	ADP
ijassa-751	179	11	iterations	iteration	NOUN
ijassa-751	179	12	was	be	AUX
ijassa-751	179	13	increased	increase	VERB
ijassa-751	179	14	,	,	PUNCT
ijassa-751	179	15	the	the	DET
ijassa-751	179	16	accuracy	accuracy	NOUN
ijassa-751	179	17	was	be	AUX
ijassa-751	179	18	increased	increase	VERB
ijassa-751	179	19	until	until	SCONJ
ijassa-751	179	20	it	it	PRON
ijassa-751	179	21	accomplished	accomplish	VERB
ijassa-751	179	22	an	an	DET
ijassa-751	179	23	extent	extent	NOUN
ijassa-751	179	24	(	(	PUNCT
ijassa-751	179	25	number	number	NOUN
ijassa-751	179	26	of	of	ADP
ijassa-751	179	27	iterations	iteration	NOUN
ijassa-751	179	28	=	=	NOUN
ijassa-751	179	29	20	20	NUM
ijassa-751	179	30	)	)	PUNCT
ijassa-751	179	31	at	at	ADP
ijassa-751	179	32	which	which	PRON
ijassa-751	179	33	increasing	increase	VERB
ijassa-751	179	34	the	the	DET
ijassa-751	179	35	number	number	NOUN
ijassa-751	179	36	of	of	ADP
ijassa-751	179	37	iterations	iteration	NOUN
ijassa-751	179	38	did	do	AUX
ijassa-751	179	39	not	not	PART
ijassa-751	179	40	affect	affect	VERB
ijassa-751	179	41	the	the	DET
ijassa-751	179	42	accuracy	accuracy	NOUN
ijassa-751	179	43	of	of	ADP
ijassa-751	179	44	the	the	DET
ijassa-751	179	45	proposed	propose	VERB
ijassa-751	179	46	algorithm	algorithm	NOUN
ijassa-751	179	47	.	.	PUNCT
ijassa-751	180	1	figure	figure	VERB
ijassa-751	180	2	4.2	4.2	NUM
ijassa-751	180	3	:	:	PUNCT
ijassa-751	180	4	effect	effect	NOUN
ijassa-751	180	5	of	of	ADP
ijassa-751	180	6	the	the	DET
ijassa-751	180	7	number	number	NOUN
ijassa-751	180	8	of	of	ADP
ijassa-751	180	9	iterations	iteration	NOUN
ijassa-751	180	10	on	on	ADP
ijassa-751	180	11	the	the	DET
ijassa-751	180	12	accuracy	accuracy	NOUN
ijassa-751	180	13	of	of	ADP
ijassa-751	180	14	pso	pso	NOUN
ijassa-751	180	15	-	-	PUNCT
ijassa-751	180	16	pegasos	pegasos	NOUN
ijassa-751	180	17	algorithm	algorithm	NOUN
ijassa-751	180	18	for	for	ADP
ijassa-751	180	19	training	training	NOUN
ijassa-751	180	20	and	and	CCONJ
ijassa-751	180	21	testing	testing	NOUN
ijassa-751	180	22	sets	set	NOUN
ijassa-751	180	23	.	.	PUNCT
ijassa-751	181	1	according	accord	VERB
ijassa-751	181	2	to	to	ADP
ijassa-751	181	3	parameter	parameter	NOUN
ijassa-751	181	4	analysis	analysis	NOUN
ijassa-751	181	5	and	and	CCONJ
ijassa-751	181	6	paper	paper	NOUN
ijassa-751	181	7	results	result	NOUN
ijassa-751	181	8	,	,	PUNCT
ijassa-751	181	9	we	we	PRON
ijassa-751	181	10	put	put	VERB
ijassa-751	181	11	number	number	NOUN
ijassa-751	181	12	of	of	ADP
ijassa-751	181	13	iterations	iteration	NOUN
ijassa-751	181	14	in	in	ADP
ijassa-751	181	15	pso	pso	NOUN
ijassa-751	181	16	=	=	NOUN
ijassa-751	181	17	20	20	NUM
ijassa-751	181	18	to	to	PART
ijassa-751	181	19	run	run	VERB
ijassa-751	181	20	the	the	DET
ijassa-751	181	21	proposed	propose	VERB
ijassa-751	181	22	algorithm	algorithm	NOUN
ijassa-751	181	23	,	,	PUNCT
ijassa-751	181	24	therefore	therefore	ADV
ijassa-751	181	25	,	,	PUNCT
ijassa-751	181	26	the	the	DET
ijassa-751	181	27	computational	computational	ADJ
ijassa-751	181	28	cost	cost	NOUN
ijassa-751	181	29	is	be	AUX
ijassa-751	181	30	small	small	ADJ
ijassa-751	181	31	.	.	PUNCT
ijassa-751	182	1	figures	figure	NOUN
ijassa-751	182	2	4.3	4.3	NUM
ijassa-751	182	3	and	and	CCONJ
ijassa-751	182	4	4.4	4.4	NUM
ijassa-751	182	5	show	show	VERB
ijassa-751	182	6	the	the	DET
ijassa-751	182	7	performance	performance	NOUN
ijassa-751	182	8	measures	measure	NOUN
ijassa-751	182	9	accuracy	accuracy	NOUN
ijassa-751	182	10	,	,	PUNCT
ijassa-751	182	11	recall	recall	NOUN
ijassa-751	182	12	,	,	PUNCT
ijassa-751	182	13	precision	precision	NOUN
ijassa-751	182	14	and	and	CCONJ
ijassa-751	182	15	f	f	NOUN
ijassa-751	182	16	-	-	PUNCT
ijassa-751	182	17	measure	measure	NOUN
ijassa-751	182	18	of	of	ADP
ijassa-751	182	19	pegasos	pegasos	NOUN
ijassa-751	182	20	and	and	CCONJ
ijassa-751	182	21	pso	pso	NOUN
ijassa-751	182	22	-	-	PUNCT
ijassa-751	182	23	pegasos	pegasos	NOUN
ijassa-751	182	24	algorithms	algorithm	NOUN
ijassa-751	182	25	for	for	ADP
ijassa-751	182	26	training	training	NOUN
ijassa-751	182	27	and	and	CCONJ
ijassa-751	182	28	testing	testing	NOUN
ijassa-751	182	29	sets	set	NOUN
ijassa-751	182	30	,	,	PUNCT
ijassa-751	182	31	respectively	respectively	ADV
ijassa-751	182	32	.	.	PUNCT
ijassa-751	183	1	experimental	experimental	ADJ
ijassa-751	183	2	results	result	NOUN
ijassa-751	183	3	in	in	ADP
ijassa-751	183	4	figures	figure	NOUN
ijassa-751	183	5	4.3	4.3	NUM
ijassa-751	183	6	and	and	CCONJ
ijassa-751	183	7	4.4	4.4	NUM
ijassa-751	183	8	show	show	VERB
ijassa-751	183	9	that	that	SCONJ
ijassa-751	183	10	the	the	DET
ijassa-751	183	11	accuracy	accuracy	NOUN
ijassa-751	183	12	of	of	ADP
ijassa-751	183	13	the	the	DET
ijassa-751	183	14	proposed	propose	VERB
ijassa-751	183	15	algorithm	algorithm	NOUN
ijassa-751	183	16	(	(	PUNCT
ijassa-751	183	17	pso	pso	NOUN
ijassa-751	183	18	-	-	PUNCT
ijassa-751	183	19	pegasos	pegasos	NOUN
ijassa-751	183	20	)	)	PUNCT
ijassa-751	183	21	for	for	ADP
ijassa-751	183	22	training	training	NOUN
ijassa-751	183	23	and	and	CCONJ
ijassa-751	183	24	testing	testing	NOUN
ijassa-751	183	25	sets	set	NOUN
ijassa-751	183	26	are	be	AUX
ijassa-751	183	27	higher	high	ADJ
ijassa-751	183	28	than	than	ADP
ijassa-751	183	29	the	the	DET
ijassa-751	183	30	accuracy	accuracy	NOUN
ijassa-751	183	31	of	of	ADP
ijassa-751	183	32	pegasos	pegasos	NOUN
ijassa-751	183	33	algorithm	algorithm	NOUN
ijassa-751	183	34	by	by	ADP
ijassa-751	183	35	about	about	ADV
ijassa-751	183	36	3.39	3.39	NUM
ijassa-751	183	37	and	and	CCONJ
ijassa-751	183	38	3.48	3.48	NUM
ijassa-751	183	39	respectively	respectively	ADV
ijassa-751	183	40	.	.	PUNCT
ijassa-751	184	1	it	it	PRON
ijassa-751	184	2	also	also	ADV
ijassa-751	184	3	shows	show	VERB
ijassa-751	184	4	that	that	SCONJ
ijassa-751	184	5	the	the	DET
ijassa-751	184	6	proposed	propose	VERB
ijassa-751	184	7	algorithm	algorithm	NOUN
ijassa-751	184	8	outperforms	outperform	NOUN
ijassa-751	184	9	pegasos	pegasos	PROPN
ijassa-751	184	10	copyright	copyright	NOUN
ijassa-751	184	11	c	c	ADP
ijassa-751	184	12	©	©	PROPN
ijassa-751	184	13	2019	2019	NUM
ijassa-751	184	14	assa	assa	NOUN
ijassa-751	184	15	.	.	PUNCT
ijassa-751	185	1	adv	adv	PROPN
ijassa-751	185	2	.	.	PUNCT
ijassa-751	186	1	in	in	ADP
ijassa-751	186	2	systems	system	NOUN
ijassa-751	186	3	science	science	NOUN
ijassa-751	186	4	and	and	CCONJ
ijassa-751	186	5	appl.(2019	appl.(2019	NOUN
ijassa-751	186	6	)	)	PUNCT
ijassa-751	186	7	hybrid	hybrid	ADJ
ijassa-751	186	8	particle	particle	NOUN
ijassa-751	186	9	swarm	swarm	NOUN
ijassa-751	186	10	optimization	optimization	NOUN
ijassa-751	186	11	and	and	CCONJ
ijassa-751	186	12	pegasos	pegasos	NOUN
ijassa-751	186	13	algorithm	algorithm	NOUN
ijassa-751	186	14	for	for	ADP
ijassa-751	186	15	spam	spam	NOUN
ijassa-751	186	16	email	email	NOUN
ijassa-751	186	17	detection19	detection19	PROPN
ijassa-751	186	18	algorithm	algorithm	PROPN
ijassa-751	186	19	in	in	ADP
ijassa-751	186	20	terms	term	NOUN
ijassa-751	186	21	of	of	ADP
ijassa-751	186	22	recall	recall	NOUN
ijassa-751	186	23	,	,	PUNCT
ijassa-751	186	24	precision	precision	NOUN
ijassa-751	186	25	and	and	CCONJ
ijassa-751	186	26	f	f	NOUN
ijassa-751	186	27	-	-	PUNCT
ijassa-751	186	28	measure	measure	NOUN
ijassa-751	186	29	for	for	ADP
ijassa-751	186	30	training	training	NOUN
ijassa-751	186	31	and	and	CCONJ
ijassa-751	186	32	testing	testing	NOUN
ijassa-751	186	33	sets	set	NOUN
ijassa-751	186	34	due	due	ADP
ijassa-751	186	35	to	to	ADP
ijassa-751	186	36	the	the	DET
ijassa-751	186	37	existence	existence	NOUN
ijassa-751	186	38	of	of	ADP
ijassa-751	186	39	particle	particle	NOUN
ijassa-751	186	40	swarm	swarm	NOUN
ijassa-751	186	41	optimization	optimization	NOUN
ijassa-751	186	42	,	,	PUNCT
ijassa-751	186	43	which	which	PRON
ijassa-751	186	44	has	have	VERB
ijassa-751	186	45	strong	strong	ADJ
ijassa-751	186	46	global	global	ADJ
ijassa-751	186	47	search	search	NOUN
ijassa-751	186	48	capability	capability	NOUN
ijassa-751	186	49	and	and	CCONJ
ijassa-751	186	50	high	high	ADJ
ijassa-751	186	51	convergence	convergence	NOUN
ijassa-751	186	52	speed	speed	NOUN
ijassa-751	186	53	to	to	ADP
ijassa-751	186	54	optimal	optimal	ADJ
ijassa-751	186	55	solution	solution	NOUN
ijassa-751	186	56	.	.	PUNCT
ijassa-751	187	1	figure	figure	VERB
ijassa-751	187	2	4.3	4.3	NUM
ijassa-751	187	3	:	:	PUNCT
ijassa-751	187	4	comparison	comparison	NOUN
ijassa-751	187	5	of	of	ADP
ijassa-751	187	6	performance	performance	NOUN
ijassa-751	187	7	measures	measure	NOUN
ijassa-751	187	8	of	of	ADP
ijassa-751	187	9	pegasos	pegasos	NOUN
ijassa-751	187	10	and	and	CCONJ
ijassa-751	187	11	pso	pso	NOUN
ijassa-751	187	12	-	-	PUNCT
ijassa-751	187	13	pegasos	pegasos	NOUN
ijassa-751	187	14	for	for	ADP
ijassa-751	187	15	training	training	NOUN
ijassa-751	187	16	set	set	NOUN
ijassa-751	187	17	.	.	PUNCT
ijassa-751	188	1	figure	figure	VERB
ijassa-751	188	2	4.4	4.4	NUM
ijassa-751	188	3	:	:	PUNCT
ijassa-751	188	4	comparison	comparison	NOUN
ijassa-751	188	5	of	of	ADP
ijassa-751	188	6	performance	performance	NOUN
ijassa-751	188	7	measures	measure	NOUN
ijassa-751	188	8	of	of	ADP
ijassa-751	188	9	pegasos	pegasos	NOUN
ijassa-751	188	10	and	and	CCONJ
ijassa-751	188	11	pso	pso	NOUN
ijassa-751	188	12	-	-	PUNCT
ijassa-751	188	13	pegasos	pegasos	NOUN
ijassa-751	188	14	for	for	ADP
ijassa-751	188	15	testing	testing	NOUN
ijassa-751	188	16	set	set	NOUN
ijassa-751	188	17	.	.	PUNCT
ijassa-751	189	1	finally	finally	ADV
ijassa-751	189	2	,	,	PUNCT
ijassa-751	189	3	in	in	ADP
ijassa-751	189	4	order	order	NOUN
ijassa-751	189	5	to	to	PART
ijassa-751	189	6	indicate	indicate	VERB
ijassa-751	189	7	that	that	SCONJ
ijassa-751	189	8	the	the	DET
ijassa-751	189	9	improvement	improvement	NOUN
ijassa-751	189	10	obtained	obtain	VERB
ijassa-751	189	11	by	by	ADP
ijassa-751	189	12	the	the	DET
ijassa-751	189	13	proposed	propose	VERB
ijassa-751	189	14	algorithm	algorithm	NOUN
ijassa-751	189	15	(	(	PUNCT
ijassa-751	189	16	pso	pso	NOUN
ijassa-751	189	17	-	-	PUNCT
ijassa-751	189	18	pegasos	pegasos	NOUN
ijassa-751	189	19	)	)	PUNCT
ijassa-751	189	20	clearer	clear	ADJ
ijassa-751	189	21	,	,	PUNCT
ijassa-751	189	22	its	its	PRON
ijassa-751	189	23	accuracy	accuracy	NOUN
ijassa-751	189	24	compared	compare	VERB
ijassa-751	189	25	with	with	ADP
ijassa-751	189	26	earlier	early	ADV
ijassa-751	189	27	used	use	VERB
ijassa-751	189	28	algorithms	algorithm	NOUN
ijassa-751	189	29	implemented	implement	VERB
ijassa-751	189	30	on	on	ADP
ijassa-751	189	31	the	the	DET
ijassa-751	189	32	same	same	ADJ
ijassa-751	189	33	dataset	dataset	NOUN
ijassa-751	189	34	is	be	AUX
ijassa-751	189	35	presented	present	VERB
ijassa-751	189	36	below	below	ADV
ijassa-751	189	37	.	.	PUNCT
ijassa-751	190	1	experimental	experimental	ADJ
ijassa-751	190	2	results	result	NOUN
ijassa-751	190	3	in	in	ADP
ijassa-751	190	4	table	table	NOUN
ijassa-751	190	5	4.3	4.3	NUM
ijassa-751	190	6	show	show	VERB
ijassa-751	190	7	that	that	SCONJ
ijassa-751	190	8	the	the	DET
ijassa-751	190	9	results	result	NOUN
ijassa-751	190	10	of	of	ADP
ijassa-751	190	11	the	the	DET
ijassa-751	190	12	proposed	propose	VERB
ijassa-751	190	13	algorithm	algorithm	NOUN
ijassa-751	190	14	outperforms	outperform	VERB
ijassa-751	190	15	the	the	DET
ijassa-751	190	16	results	result	NOUN
ijassa-751	190	17	of	of	ADP
ijassa-751	190	18	other	other	ADJ
ijassa-751	190	19	published	publish	VERB
ijassa-751	190	20	classifier	classifier	NOUN
ijassa-751	190	21	called	call	VERB
ijassa-751	190	22	svm	svm	PROPN
ijassa-751	190	23	-	-	PUNCT
ijassa-751	190	24	based	base	VERB
ijassa-751	190	25	spam	spam	NOUN
ijassa-751	190	26	detector	detector	NOUN
ijassa-751	190	27	[	[	X
ijassa-751	190	28	11	11	NUM
ijassa-751	190	29	]	]	PUNCT
ijassa-751	190	30	.	.	PUNCT
ijassa-751	191	1	the	the	DET
ijassa-751	191	2	proposed	propose	VERB
ijassa-751	191	3	pso	pso	NOUN
ijassa-751	191	4	-	-	PUNCT
ijassa-751	191	5	pegasos	pegasos	NOUN
ijassa-751	191	6	presented	present	VERB
ijassa-751	191	7	improvement	improvement	NOUN
ijassa-751	191	8	of	of	ADP
ijassa-751	191	9	2.13	2.13	NUM
ijassa-751	191	10	%	%	NOUN
ijassa-751	191	11	over	over	ADP
ijassa-751	191	12	svm	svm	ADJ
ijassa-751	191	13	-	-	PUNCT
ijassa-751	191	14	based	base	VERB
ijassa-751	191	15	spam	spam	NOUN
ijassa-751	191	16	detector	detector	NOUN
ijassa-751	191	17	model	model	NOUN
ijassa-751	191	18	,	,	PUNCT
ijassa-751	191	19	which	which	PRON
ijassa-751	191	20	is	be	AUX
ijassa-751	191	21	the	the	DET
ijassa-751	191	22	best	good	ADJ
ijassa-751	191	23	among	among	ADP
ijassa-751	191	24	the	the	DET
ijassa-751	191	25	other	other	ADJ
ijassa-751	191	26	earlier	early	ADV
ijassa-751	191	27	published	publish	VERB
ijassa-751	191	28	classifiers	classifier	NOUN
ijassa-751	191	29	for	for	ADP
ijassa-751	191	30	spam	spam	NOUN
ijassa-751	191	31	email	email	NOUN
ijassa-751	191	32	copyright	copyright	NOUN
ijassa-751	191	33	c	c	ADP
ijassa-751	191	34	©	©	PROPN
ijassa-751	191	35	2019	2019	NUM
ijassa-751	191	36	assa	assa	NOUN
ijassa-751	191	37	.	.	PUNCT
ijassa-751	192	1	adv	adv	PROPN
ijassa-751	192	2	.	.	PUNCT
ijassa-751	193	1	in	in	ADP
ijassa-751	193	2	systems	system	NOUN
ijassa-751	193	3	science	science	NOUN
ijassa-751	193	4	and	and	CCONJ
ijassa-751	193	5	appl.(2019	appl.(2019	NOUN
ijassa-751	193	6	)	)	PUNCT
ijassa-751	193	7	20	20	NUM
ijassa-751	193	8	l.m	l.m	PROPN
ijassa-751	193	9	.	.	PROPN
ijassa-751	193	10	el	el	PROPN
ijassa-751	193	11	bakrawy	bakrawy	PROPN
ijassa-751	193	12	table	table	PROPN
ijassa-751	193	13	4.3	4.3	NUM
ijassa-751	193	14	:	:	PUNCT
ijassa-751	193	15	comparison	comparison	NOUN
ijassa-751	193	16	of	of	ADP
ijassa-751	193	17	accuracy	accuracy	NOUN
ijassa-751	193	18	of	of	ADP
ijassa-751	193	19	the	the	DET
ijassa-751	193	20	proposed	propose	VERB
ijassa-751	193	21	algorithm	algorithm	NOUN
ijassa-751	193	22	and	and	CCONJ
ijassa-751	193	23	other	other	ADJ
ijassa-751	193	24	published	publish	VERB
ijassa-751	193	25	classifiers	classifier	NOUN
ijassa-751	193	26	on	on	ADP
ijassa-751	193	27	spambase	spambase	PROPN
ijassa-751	193	28	dataset	dataset	PROPN
ijassa-751	193	29	classifiers	classifier	NOUN
ijassa-751	193	30	classification	classification	NOUN
ijassa-751	193	31	accuracy	accuracy	NOUN
ijassa-751	193	32	ga	ga	NOUN
ijassa-751	193	33	-	-	PUNCT
ijassa-751	193	34	naive	naive	ADJ
ijassa-751	193	35	bayes	bayes	NOUN
ijassa-751	194	1	[	[	X
ijassa-751	194	2	6	6	NUM
ijassa-751	194	3	]	]	SYM
ijassa-751	194	4	77	77	NUM
ijassa-751	194	5	%	%	NOUN
ijassa-751	194	6	aco	aco	NOUN
ijassa-751	194	7	-	-	PUNCT
ijassa-751	194	8	naive	naive	ADJ
ijassa-751	194	9	baye	baye	NOUN
ijassa-751	194	10	[	[	X
ijassa-751	194	11	6	6	NUM
ijassa-751	194	12	]	]	SYM
ijassa-751	194	13	84	84	NUM
ijassa-751	194	14	%	%	NOUN
ijassa-751	194	15	pso	pso	NOUN
ijassa-751	194	16	-	-	PUNCT
ijassa-751	194	17	lm	lm	PROPN
ijassa-751	195	1	[	[	X
ijassa-751	195	2	9	9	NUM
ijassa-751	195	3	]	]	SYM
ijassa-751	195	4	90.5	90.5	NUM
ijassa-751	195	5	%	%	NOUN
ijassa-751	195	6	nsa	nsa	PROPN
ijassa-751	196	1	[	[	X
ijassa-751	196	2	10	10	NUM
ijassa-751	196	3	]	]	SYM
ijassa-751	196	4	68.86	68.86	NUM
ijassa-751	196	5	%	%	NOUN
ijassa-751	196	6	pso	pso	NOUN
ijassa-751	196	7	[	[	X
ijassa-751	196	8	10	10	NUM
ijassa-751	196	9	]	]	PUNCT
ijassa-751	196	10	81.32	81.32	NUM
ijassa-751	196	11	%	%	NOUN
ijassa-751	196	12	nsa	nsa	PROPN
ijassa-751	196	13	-	-	PUNCT
ijassa-751	196	14	pso	pso	NOUN
ijassa-751	196	15	[	[	NOUN
ijassa-751	196	16	10	10	NUM
ijassa-751	196	17	]	]	SYM
ijassa-751	196	18	91.22	91.22	NUM
ijassa-751	196	19	%	%	NOUN
ijassa-751	196	20	hc	hc	NOUN
ijassa-751	196	21	-	-	NOUN
ijassa-751	196	22	rbfpso	rbfpso	NOUN
ijassa-751	196	23	[	[	X
ijassa-751	196	24	1	1	NUM
ijassa-751	196	25	]	]	SYM
ijassa-751	196	26	91.4	91.4	NUM
ijassa-751	196	27	%	%	NOUN
ijassa-751	196	28	svm	svm	ADJ
ijassa-751	196	29	-	-	PUNCT
ijassa-751	196	30	based	base	VERB
ijassa-751	196	31	spam	spam	NOUN
ijassa-751	196	32	detector	detector	NOUN
ijassa-751	196	33	[	[	X
ijassa-751	196	34	11	11	NUM
ijassa-751	196	35	]	]	SYM
ijassa-751	196	36	94.06	94.06	NUM
ijassa-751	196	37	%	%	NOUN
ijassa-751	196	38	pso	pso	NOUN
ijassa-751	196	39	-	-	PUNCT
ijassa-751	196	40	pegasos	pegasos	NOUN
ijassa-751	196	41	(	(	PUNCT
ijassa-751	196	42	proposed	propose	VERB
ijassa-751	196	43	)	)	PUNCT
ijassa-751	196	44	96.19	96.19	NUM
ijassa-751	196	45	%	%	NOUN
ijassa-751	196	46	detection	detection	NOUN
ijassa-751	196	47	.	.	PUNCT
ijassa-751	197	1	it	it	PRON
ijassa-751	197	2	also	also	ADV
ijassa-751	197	3	presented	present	VERB
ijassa-751	197	4	an	an	DET
ijassa-751	197	5	accuracy	accuracy	NOUN
ijassa-751	197	6	improvement	improvement	NOUN
ijassa-751	197	7	of	of	ADP
ijassa-751	197	8	4.79	4.79	NUM
ijassa-751	197	9	%	%	NOUN
ijassa-751	197	10	over	over	ADP
ijassa-751	197	11	a	a	DET
ijassa-751	197	12	hybrid	hybrid	ADJ
ijassa-751	197	13	approach	approach	NOUN
ijassa-751	197	14	(	(	PUNCT
ijassa-751	197	15	hcrbfpso	hcrbfpso	PROPN
ijassa-751	197	16	)	)	PUNCT
ijassa-751	197	17	,	,	PUNCT
ijassa-751	197	18	that	that	PRON
ijassa-751	197	19	combines	combine	VERB
ijassa-751	197	20	radial	radial	ADJ
ijassa-751	197	21	basis	basis	NOUN
ijassa-751	197	22	function	function	NOUN
ijassa-751	197	23	neural	neural	ADJ
ijassa-751	197	24	network	network	NOUN
ijassa-751	197	25	(	(	PUNCT
ijassa-751	197	26	rbfnn	rbfnn	PROPN
ijassa-751	197	27	)	)	PUNCT
ijassa-751	197	28	and	and	CCONJ
ijassa-751	197	29	particle	particle	NOUN
ijassa-751	197	30	swarm	swarm	NOUN
ijassa-751	197	31	optimization	optimization	NOUN
ijassa-751	197	32	(	(	PUNCT
ijassa-751	197	33	pso	pso	NOUN
ijassa-751	197	34	)	)	PUNCT
ijassa-751	197	35	algorithm	algorithm	NOUN
ijassa-751	197	36	[	[	X
ijassa-751	197	37	1	1	NUM
ijassa-751	197	38	]	]	PUNCT
ijassa-751	197	39	.	.	PUNCT
ijassa-751	198	1	the	the	DET
ijassa-751	198	2	proposed	propose	VERB
ijassa-751	198	3	algorithm	algorithm	NOUN
ijassa-751	198	4	also	also	ADV
ijassa-751	198	5	presented	present	VERB
ijassa-751	198	6	improvement	improvement	NOUN
ijassa-751	198	7	of	of	ADP
ijassa-751	198	8	4.97	4.97	NUM
ijassa-751	198	9	%	%	NOUN
ijassa-751	198	10	over	over	ADP
ijassa-751	198	11	a	a	DET
ijassa-751	198	12	hybridized	hybridize	VERB
ijassa-751	198	13	negative	negative	ADJ
ijassa-751	198	14	selection	selection	NOUN
ijassa-751	198	15	algorithm	algorithm	NOUN
ijassa-751	198	16	and	and	CCONJ
ijassa-751	198	17	particle	particle	NOUN
ijassa-751	198	18	swarm	swarm	NOUN
ijassa-751	198	19	optimization	optimization	NOUN
ijassa-751	198	20	(	(	PUNCT
ijassa-751	198	21	nsapso	nsapso	NOUN
ijassa-751	198	22	)	)	PUNCT
ijassa-751	199	1	[	[	X
ijassa-751	199	2	10	10	NUM
ijassa-751	199	3	]	]	PUNCT
ijassa-751	199	4	,	,	PUNCT
ijassa-751	199	5	yet	yet	CCONJ
ijassa-751	199	6	the	the	DET
ijassa-751	199	7	proposed	propose	VERB
ijassa-751	199	8	algorithm	algorithm	NOUN
ijassa-751	199	9	in	in	ADP
ijassa-751	199	10	this	this	DET
ijassa-751	199	11	paper	paper	NOUN
ijassa-751	199	12	outperformed	outperform	VERB
ijassa-751	199	13	all	all	DET
ijassa-751	199	14	the	the	DET
ijassa-751	199	15	three	three	NUM
ijassa-751	199	16	algorithms	algorithm	NOUN
ijassa-751	199	17	nsa	nsa	PROPN
ijassa-751	199	18	-	-	PUNCT
ijassa-751	199	19	pso	pso	NOUN
ijassa-751	199	20	,	,	PUNCT
ijassa-751	199	21	nsa	nsa	PROPN
ijassa-751	199	22	and	and	CCONJ
ijassa-751	199	23	pso	pso	NOUN
ijassa-751	199	24	including	include	VERB
ijassa-751	199	25	the	the	DET
ijassa-751	199	26	hybrid	hybrid	ADJ
ijassa-751	199	27	schemes	scheme	NOUN
ijassa-751	199	28	.	.	PUNCT
ijassa-751	200	1	it	it	PRON
ijassa-751	200	2	also	also	ADV
ijassa-751	200	3	presented	present	VERB
ijassa-751	200	4	an	an	DET
ijassa-751	200	5	accuracy	accuracy	NOUN
ijassa-751	200	6	improvement	improvement	NOUN
ijassa-751	200	7	of	of	ADP
ijassa-751	200	8	5.69	5.69	NUM
ijassa-751	200	9	%	%	NOUN
ijassa-751	200	10	over	over	ADP
ijassa-751	200	11	learning	learn	VERB
ijassa-751	200	12	method	method	NOUN
ijassa-751	200	13	for	for	ADP
ijassa-751	200	14	process	process	NOUN
ijassa-751	200	15	neural	neural	ADJ
ijassa-751	200	16	networks	network	NOUN
ijassa-751	200	17	based	base	VERB
ijassa-751	200	18	on	on	ADP
ijassa-751	200	19	particle	particle	NOUN
ijassa-751	200	20	swarm	swarm	NOUN
ijassa-751	200	21	optimization	optimization	NOUN
ijassa-751	200	22	(	(	PUNCT
ijassa-751	200	23	pso	pso	NOUN
ijassa-751	200	24	-	-	PUNCT
ijassa-751	200	25	lm	lm	NOUN
ijassa-751	200	26	)	)	PUNCT
ijassa-751	201	1	[	[	X
ijassa-751	201	2	9	9	NUM
ijassa-751	201	3	]	]	PUNCT
ijassa-751	201	4	and	and	CCONJ
ijassa-751	201	5	an	an	DET
ijassa-751	201	6	accuracy	accuracy	NOUN
ijassa-751	201	7	improvement	improvement	NOUN
ijassa-751	201	8	of	of	ADP
ijassa-751	201	9	12.19	12.19	NUM
ijassa-751	201	10	%	%	NOUN
ijassa-751	201	11	over	over	ADP
ijassa-751	201	12	hybrid	hybrid	ADJ
ijassa-751	201	13	ant	ant	ADJ
ijassa-751	201	14	colony	colony	NOUN
ijassa-751	201	15	optimization	optimization	NOUN
ijassa-751	201	16	and	and	CCONJ
ijassa-751	201	17	naive	naive	ADJ
ijassa-751	201	18	bayes	bayes	NOUN
ijassa-751	201	19	(	(	PUNCT
ijassa-751	201	20	aconaive	aconaive	ADJ
ijassa-751	201	21	bayes	bayes	PROPN
ijassa-751	201	22	)	)	PUNCT
ijassa-751	201	23	,	,	PUNCT
ijassa-751	201	24	while	while	SCONJ
ijassa-751	201	25	presenting	present	VERB
ijassa-751	201	26	an	an	DET
ijassa-751	201	27	accuracy	accuracy	NOUN
ijassa-751	201	28	improvement	improvement	NOUN
ijassa-751	201	29	of	of	ADP
ijassa-751	201	30	19.19	19.19	NUM
ijassa-751	201	31	%	%	NOUN
ijassa-751	201	32	over	over	ADP
ijassa-751	201	33	hybrid	hybrid	ADJ
ijassa-751	201	34	genetic	genetic	ADJ
ijassa-751	201	35	algorithm	algorithm	NOUN
ijassa-751	201	36	and	and	CCONJ
ijassa-751	201	37	naive	naive	ADJ
ijassa-751	201	38	bayes	bayes	NOUN
ijassa-751	201	39	(	(	PUNCT
ijassa-751	201	40	ganaive	ganaive	ADJ
ijassa-751	201	41	bayes	baye	NOUN
ijassa-751	201	42	)	)	PUNCT
ijassa-751	202	1	[	[	X
ijassa-751	202	2	6	6	NUM
ijassa-751	202	3	]	]	PUNCT
ijassa-751	202	4	.	.	PUNCT
ijassa-751	203	1	5	5	X
ijassa-751	203	2	.	.	X
ijassa-751	203	3	conclusion	conclusion	NOUN
ijassa-751	203	4	primal	primal	ADJ
ijassa-751	203	5	estimated	estimate	VERB
ijassa-751	203	6	sub	sub	ADJ
ijassa-751	203	7	-	-	ADJ
ijassa-751	203	8	gradient	gradient	ADJ
ijassa-751	203	9	solver	solver	NOUN
ijassa-751	203	10	for	for	ADP
ijassa-751	203	11	svm	svm	PROPN
ijassa-751	203	12	(	(	PUNCT
ijassa-751	203	13	pegasos	pegasos	PROPN
ijassa-751	203	14	)	)	PUNCT
ijassa-751	203	15	algorithm	algorithm	NOUN
ijassa-751	203	16	was	be	AUX
ijassa-751	203	17	utilized	utilize	VERB
ijassa-751	203	18	to	to	PART
ijassa-751	203	19	solve	solve	VERB
ijassa-751	203	20	the	the	DET
ijassa-751	203	21	optimization	optimization	NOUN
ijassa-751	203	22	problem	problem	NOUN
ijassa-751	203	23	cast	cast	VERB
ijassa-751	203	24	by	by	ADP
ijassa-751	203	25	support	support	NOUN
ijassa-751	203	26	vector	vector	NOUN
ijassa-751	203	27	machines	machine	NOUN
ijassa-751	203	28	(	(	PUNCT
ijassa-751	203	29	svm	svm	PROPN
ijassa-751	203	30	)	)	PUNCT
ijassa-751	203	31	.	.	PUNCT
ijassa-751	204	1	it	it	PRON
ijassa-751	204	2	is	be	AUX
ijassa-751	204	3	characterized	characterize	VERB
ijassa-751	204	4	by	by	ADP
ijassa-751	204	5	better	well	ADJ
ijassa-751	204	6	convergence	convergence	NOUN
ijassa-751	204	7	bounds	bound	NOUN
ijassa-751	204	8	and	and	CCONJ
ijassa-751	204	9	robustly	robustly	ADV
ijassa-751	204	10	convex	convex	VERB
ijassa-751	204	11	optimization	optimization	NOUN
ijassa-751	204	12	objective	objective	NOUN
ijassa-751	204	13	.	.	PUNCT
ijassa-751	205	1	in	in	ADP
ijassa-751	205	2	this	this	DET
ijassa-751	205	3	paper	paper	NOUN
ijassa-751	205	4	,	,	PUNCT
ijassa-751	205	5	hybrid	hybrid	ADJ
ijassa-751	205	6	particle	particle	NOUN
ijassa-751	205	7	swarm	swarm	NOUN
ijassa-751	205	8	optimization	optimization	NOUN
ijassa-751	205	9	(	(	PUNCT
ijassa-751	205	10	pso	pso	NOUN
ijassa-751	205	11	)	)	PUNCT
ijassa-751	205	12	and	and	CCONJ
ijassa-751	205	13	pegasos	pegasos	PROPN
ijassa-751	205	14	algorithm	algorithm	PROPN
ijassa-751	205	15	,	,	PUNCT
ijassa-751	205	16	called	call	VERB
ijassa-751	205	17	(	(	PUNCT
ijassa-751	205	18	pso	pso	NOUN
ijassa-751	205	19	-	-	PUNCT
ijassa-751	205	20	pegasos	pegasos	NOUN
ijassa-751	205	21	)	)	PUNCT
ijassa-751	205	22	is	be	AUX
ijassa-751	205	23	proposed	propose	VERB
ijassa-751	205	24	for	for	ADP
ijassa-751	205	25	spam	spam	NOUN
ijassa-751	205	26	email	email	NOUN
ijassa-751	205	27	detection	detection	NOUN
ijassa-751	205	28	.	.	PUNCT
ijassa-751	206	1	pso	pso	NOUN
ijassa-751	206	2	is	be	AUX
ijassa-751	206	3	used	use	VERB
ijassa-751	206	4	to	to	PART
ijassa-751	206	5	identify	identify	VERB
ijassa-751	206	6	automatically	automatically	ADV
ijassa-751	206	7	the	the	DET
ijassa-751	206	8	best	well	ADV
ijassa-751	206	9	optimal	optimal	ADJ
ijassa-751	206	10	w	w	NOUN
ijassa-751	206	11	-	-	PUNCT
ijassa-751	206	12	parameter	parameter	NOUN
ijassa-751	206	13	for	for	ADP
ijassa-751	206	14	original	original	ADJ
ijassa-751	206	15	pegasos	pegasos	NOUN
ijassa-751	206	16	algorithm	algorithm	NOUN
ijassa-751	206	17	.	.	PUNCT
ijassa-751	207	1	the	the	DET
ijassa-751	207	2	proposed	propose	VERB
ijassa-751	207	3	algorithm	algorithm	NOUN
ijassa-751	207	4	has	have	AUX
ijassa-751	207	5	been	be	AUX
ijassa-751	207	6	trained	train	VERB
ijassa-751	207	7	and	and	CCONJ
ijassa-751	207	8	tested	test	VERB
ijassa-751	207	9	using	use	VERB
ijassa-751	207	10	popular	popular	ADJ
ijassa-751	207	11	and	and	CCONJ
ijassa-751	207	12	often	often	ADV
ijassa-751	207	13	used	use	VERB
ijassa-751	207	14	spambase	spambase	NOUN
ijassa-751	207	15	dataset	dataset	NOUN
ijassa-751	207	16	,	,	PUNCT
ijassa-751	207	17	which	which	PRON
ijassa-751	207	18	consists	consist	VERB
ijassa-751	207	19	of	of	ADP
ijassa-751	207	20	collection	collection	NOUN
ijassa-751	207	21	of	of	ADP
ijassa-751	207	22	spam	spam	NOUN
ijassa-751	207	23	and	and	CCONJ
ijassa-751	207	24	non	non	ADJ
ijassa-751	207	25	-	-	ADJ
ijassa-751	207	26	spam	spam	ADJ
ijassa-751	207	27	emails	email	NOUN
ijassa-751	207	28	with	with	ADP
ijassa-751	207	29	57	57	NUM
ijassa-751	207	30	features	feature	NOUN
ijassa-751	207	31	and	and	CCONJ
ijassa-751	207	32	1	1	NUM
ijassa-751	207	33	classification	classification	NOUN
ijassa-751	207	34	attribute	attribute	NOUN
ijassa-751	207	35	.	.	PUNCT
ijassa-751	208	1	excremental	excremental	PROPN
ijassa-751	208	2	results	result	NOUN
ijassa-751	208	3	indicated	indicate	VERB
ijassa-751	208	4	that	that	SCONJ
ijassa-751	208	5	the	the	DET
ijassa-751	208	6	proposed	propose	VERB
ijassa-751	208	7	pso	pso	NOUN
ijassa-751	208	8	-	-	PUNCT
ijassa-751	208	9	pegasos	pegasos	NOUN
ijassa-751	208	10	algorithm	algorithm	NOUN
ijassa-751	208	11	outperformed	outperform	VERB
ijassa-751	208	12	original	original	ADJ
ijassa-751	208	13	pegasos	pegasos	NOUN
ijassa-751	208	14	algorithm	algorithm	NOUN
ijassa-751	208	15	and	and	CCONJ
ijassa-751	208	16	other	other	ADJ
ijassa-751	208	17	recently	recently	ADV
ijassa-751	208	18	published	publish	VERB
ijassa-751	208	19	algorithms	algorithm	NOUN
ijassa-751	208	20	tested	test	VERB
ijassa-751	208	21	on	on	ADP
ijassa-751	208	22	the	the	DET
ijassa-751	208	23	same	same	ADJ
ijassa-751	208	24	popular	popular	ADJ
ijassa-751	208	25	dataset	dataset	NOUN
ijassa-751	208	26	used	use	VERB
ijassa-751	208	27	in	in	ADP
ijassa-751	208	28	this	this	DET
ijassa-751	208	29	paper	paper	NOUN
ijassa-751	208	30	.	.	PUNCT
ijassa-751	209	1	the	the	DET
ijassa-751	209	2	need	need	NOUN
ijassa-751	209	3	for	for	ADP
ijassa-751	209	4	more	more	ADV
ijassa-751	209	5	accurate	accurate	ADJ
ijassa-751	209	6	spam	spam	NOUN
ijassa-751	209	7	email	email	NOUN
ijassa-751	209	8	detection	detection	NOUN
ijassa-751	209	9	method	method	NOUN
ijassa-751	209	10	can	can	AUX
ijassa-751	209	11	not	not	PART
ijassa-751	209	12	be	be	AUX
ijassa-751	209	13	overemphasized	overemphasize	VERB
ijassa-751	209	14	,	,	PUNCT
ijassa-751	209	15	the	the	DET
ijassa-751	209	16	proposed	propose	VERB
ijassa-751	209	17	pso	pso	NOUN
ijassa-751	209	18	-	-	PUNCT
ijassa-751	209	19	pegasos	pegasos	NOUN
ijassa-751	209	20	algorithm	algorithm	NOUN
ijassa-751	209	21	provides	provide	VERB
ijassa-751	209	22	improvement	improvement	NOUN
ijassa-751	209	23	of	of	ADP
ijassa-751	209	24	2.13	2.13	NUM
ijassa-751	209	25	%	%	NOUN
ijassa-751	209	26	over	over	ADP
ijassa-751	209	27	svm	svm	ADJ
ijassa-751	209	28	-	-	PUNCT
ijassa-751	209	29	based	base	VERB
ijassa-751	209	30	spam	spam	NOUN
ijassa-751	209	31	detector	detector	NOUN
ijassa-751	209	32	model	model	NOUN
ijassa-751	209	33	,	,	PUNCT
ijassa-751	209	34	which	which	PRON
ijassa-751	209	35	is	be	AUX
ijassa-751	209	36	the	the	DET
ijassa-751	209	37	best	good	ADJ
ijassa-751	209	38	among	among	ADP
ijassa-751	209	39	the	the	DET
ijassa-751	209	40	previous	previous	ADJ
ijassa-751	209	41	reported	report	VERB
ijassa-751	209	42	schemes	scheme	NOUN
ijassa-751	209	43	for	for	ADP
ijassa-751	209	44	spam	spam	NOUN
ijassa-751	209	45	email	email	NOUN
ijassa-751	209	46	detection	detection	NOUN
ijassa-751	209	47	.	.	PUNCT
ijassa-751	210	1	the	the	DET
ijassa-751	210	2	results	result	NOUN
ijassa-751	210	3	show	show	VERB
ijassa-751	210	4	that	that	SCONJ
ijassa-751	210	5	pso	pso	NOUN
ijassa-751	210	6	-	-	PUNCT
ijassa-751	210	7	pegasos	pegasos	NOUN
ijassa-751	210	8	improves	improve	VERB
ijassa-751	210	9	the	the	DET
ijassa-751	210	10	convergence	convergence	NOUN
ijassa-751	210	11	accuracy	accuracy	NOUN
ijassa-751	210	12	and	and	CCONJ
ijassa-751	210	13	it	it	PRON
ijassa-751	210	14	is	be	AUX
ijassa-751	210	15	an	an	DET
ijassa-751	210	16	effective	effective	ADJ
ijassa-751	210	17	algorithm	algorithm	NOUN
ijassa-751	210	18	,	,	PUNCT
ijassa-751	210	19	which	which	PRON
ijassa-751	210	20	is	be	AUX
ijassa-751	210	21	a	a	DET
ijassa-751	210	22	powerful	powerful	ADJ
ijassa-751	210	23	alternative	alternative	NOUN
ijassa-751	210	24	for	for	ADP
ijassa-751	210	25	spam	spam	NOUN
ijassa-751	210	26	email	email	NOUN
ijassa-751	210	27	detection	detection	NOUN
ijassa-751	210	28	.	.	PUNCT
ijassa-751	211	1	we	we	PRON
ijassa-751	211	2	can	can	AUX
ijassa-751	211	3	conclude	conclude	VERB
ijassa-751	211	4	that	that	SCONJ
ijassa-751	211	5	the	the	DET
ijassa-751	211	6	aim	aim	NOUN
ijassa-751	211	7	of	of	ADP
ijassa-751	211	8	this	this	DET
ijassa-751	211	9	paper	paper	NOUN
ijassa-751	211	10	has	have	AUX
ijassa-751	211	11	been	be	AUX
ijassa-751	211	12	achieved	achieve	VERB
ijassa-751	211	13	through	through	ADP
ijassa-751	211	14	training	training	NOUN
ijassa-751	211	15	and	and	CCONJ
ijassa-751	211	16	testing	testing	NOUN
ijassa-751	211	17	proposed	propose	VERB
ijassa-751	211	18	pso	pso	NOUN
ijassa-751	211	19	-	-	PUNCT
ijassa-751	211	20	pegasos	pegasos	NOUN
ijassa-751	211	21	algorithm	algorithm	NOUN
ijassa-751	211	22	on	on	ADP
ijassa-751	211	23	spambase	spambase	PROPN
ijassa-751	211	24	dataset	dataset	PROPN
ijassa-751	211	25	.	.	PUNCT
ijassa-751	212	1	this	this	DET
ijassa-751	212	2	algorithm	algorithm	NOUN
ijassa-751	212	3	has	have	AUX
ijassa-751	212	4	enabled	enable	VERB
ijassa-751	212	5	build	build	VERB
ijassa-751	212	6	an	an	DET
ijassa-751	212	7	improved	improve	VERB
ijassa-751	212	8	spam	spam	NOUN
ijassa-751	212	9	email	email	NOUN
ijassa-751	212	10	detection	detection	NOUN
ijassa-751	212	11	system	system	NOUN
ijassa-751	212	12	based	base	VERB
ijassa-751	212	13	on	on	ADP
ijassa-751	212	14	hybridization	hybridization	NOUN
ijassa-751	212	15	of	of	ADP
ijassa-751	212	16	particle	particle	NOUN
ijassa-751	212	17	swarm	swarm	NOUN
ijassa-751	212	18	optimization	optimization	NOUN
ijassa-751	212	19	and	and	CCONJ
ijassa-751	212	20	pegasos	pegasos	PROPN
ijassa-751	212	21	algorithm	algorithm	PROPN
ijassa-751	212	22	.	.	PUNCT
ijassa-751	213	1	references	reference	NOUN
ijassa-751	213	2	copyright	copyright	NOUN
ijassa-751	213	3	c	c	ADP
ijassa-751	213	4	©	©	PROPN
ijassa-751	213	5	2019	2019	NUM
ijassa-751	213	6	assa	assa	NOUN
ijassa-751	213	7	.	.	PUNCT
ijassa-751	214	1	adv	adv	PROPN
ijassa-751	214	2	.	.	PUNCT
ijassa-751	215	1	in	in	ADP
ijassa-751	215	2	systems	system	NOUN
ijassa-751	215	3	science	science	NOUN
ijassa-751	215	4	and	and	CCONJ
ijassa-751	215	5	appl.(2019	appl.(2019	NOUN
ijassa-751	215	6	)	)	PUNCT
ijassa-751	215	7	hybrid	hybrid	ADJ
ijassa-751	215	8	particle	particle	NOUN
ijassa-751	215	9	swarm	swarm	NOUN
ijassa-751	215	10	optimization	optimization	NOUN
ijassa-751	215	11	and	and	CCONJ
ijassa-751	215	12	pegasos	pegasos	NOUN
ijassa-751	215	13	algorithm	algorithm	NOUN
ijassa-751	215	14	for	for	ADP
ijassa-751	215	15	spam	spam	NOUN
ijassa-751	215	16	email	email	NOUN
ijassa-751	215	17	detection21	detection21	NOUN
ijassa-751	215	18	1	1	NUM
ijassa-751	215	19	.	.	PUNCT
ijassa-751	215	20	awad	awad	PROPN
ijassa-751	215	21	m	m	PROPN
ijassa-751	215	22	,	,	PUNCT
ijassa-751	215	23	foqaha	foqaha	NOUN
ijassa-751	215	24	m	m	PROPN
ijassa-751	215	25	(	(	PUNCT
ijassa-751	215	26	2016	2016	NUM
ijassa-751	215	27	)	)	PUNCT
ijassa-751	215	28	email	email	NOUN
ijassa-751	215	29	spam	spam	NOUN
ijassa-751	215	30	classification	classification	NOUN
ijassa-751	215	31	using	use	VERB
ijassa-751	215	32	hybrid	hybrid	ADJ
ijassa-751	215	33	approach	approach	NOUN
ijassa-751	215	34	of	of	ADP
ijassa-751	215	35	rbf	rbf	PROPN
ijassa-751	215	36	neural	neural	ADJ
ijassa-751	215	37	network	network	NOUN
ijassa-751	215	38	and	and	CCONJ
ijassa-751	215	39	particle	particle	NOUN
ijassa-751	215	40	swarm	swarm	NOUN
ijassa-751	215	41	optimization	optimization	NOUN
ijassa-751	215	42	,	,	PUNCT
ijassa-751	215	43	international	international	ADJ
ijassa-751	215	44	journal	journal	NOUN
ijassa-751	215	45	of	of	ADP
ijassa-751	215	46	network	network	NOUN
ijassa-751	215	47	security	security	NOUN
ijassa-751	215	48	and	and	CCONJ
ijassa-751	215	49	its	its	PRON
ijassa-751	215	50	applications	application	NOUN
ijassa-751	215	51	(	(	PUNCT
ijassa-751	215	52	ijnsa	ijnsa	PROPN
ijassa-751	215	53	)	)	PUNCT
ijassa-751	215	54	vol.8	vol.8	PROPN
ijassa-751	215	55	,	,	PUNCT
ijassa-751	215	56	no.4	no.4	PROPN
ijassa-751	215	57	,	,	PUNCT
ijassa-751	215	58	pp	pp	X
ijassa-751	215	59	.	.	PUNCT
ijassa-751	216	1	17	17	NUM
ijassa-751	216	2	-	-	SYM
ijassa-751	216	3	28	28	NUM
ijassa-751	216	4	.	.	PUNCT
ijassa-751	217	1	2	2	X
ijassa-751	217	2	.	.	X
ijassa-751	217	3	saad	saad	PROPN
ijassa-751	217	4	o	o	PROPN
ijassa-751	217	5	,	,	PUNCT
ijassa-751	217	6	hassanien	hassanien	NOUN
ijassa-751	217	7	a	a	PRON
ijassa-751	217	8	,	,	PUNCT
ijassa-751	217	9	darwish	darwish	PROPN
ijassa-751	217	10	a	a	DET
ijassa-751	217	11	,	,	PUNCT
ijassa-751	217	12	faraj	faraj	ADJ
ijassa-751	217	13	r	r	NOUN
ijassa-751	217	14	(	(	PUNCT
ijassa-751	217	15	2013	2013	NUM
ijassa-751	217	16	)	)	PUNCT
ijassa-751	217	17	a	a	DET
ijassa-751	217	18	survey	survey	NOUN
ijassa-751	217	19	of	of	ADP
ijassa-751	217	20	machine	machine	NOUN
ijassa-751	217	21	learning	learn	VERB
ijassa-751	217	22	techniques	technique	NOUN
ijassa-751	217	23	for	for	ADP
ijassa-751	217	24	spam	spam	NOUN
ijassa-751	217	25	filtering	filter	VERB
ijassa-751	217	26	,	,	PUNCT
ijassa-751	217	27	ijcsns	ijcsns	ADJ
ijassa-751	217	28	international	international	ADJ
ijassa-751	217	29	journal	journal	NOUN
ijassa-751	217	30	of	of	ADP
ijassa-751	217	31	computer	computer	NOUN
ijassa-751	217	32	science	science	NOUN
ijassa-751	217	33	and	and	CCONJ
ijassa-751	217	34	network	network	NOUN
ijassa-751	217	35	security	security	NOUN
ijassa-751	217	36	,	,	PUNCT
ijassa-751	217	37	vol.13	vol.13	NOUN
ijassa-751	217	38	no.1	no.1	PROPN
ijassa-751	217	39	,	,	PUNCT
ijassa-751	217	40	pp	pp	ADP
ijassa-751	217	41	.	.	PUNCT
ijassa-751	218	1	103	103	NUM
ijassa-751	218	2	-	-	SYM
ijassa-751	218	3	110	110	NUM
ijassa-751	218	4	.	.	PUNCT
ijassa-751	219	1	3	3	X
ijassa-751	219	2	.	.	X
ijassa-751	219	3	zhiwei	zhiwei	PROPN
ijassa-751	219	4	m	m	PROPN
ijassa-751	219	5	,	,	PUNCT
ijassa-751	219	6	singh	singh	PROPN
ijassa-751	219	7	m	m	PROPN
ijassa-751	219	8	,	,	PUNCT
ijassa-751	219	9	zaaba	zaaba	PROPN
ijassa-751	219	10	z	z	PROPN
ijassa-751	219	11	(	(	PUNCT
ijassa-751	219	12	2017	2017	NUM
ijassa-751	219	13	)	)	PUNCT
ijassa-751	219	14	email	email	NOUN
ijassa-751	219	15	spam	spam	NOUN
ijassa-751	219	16	detection	detection	PROPN
ijassa-751	219	17	:	:	PUNCT
ijassa-751	219	18	a	a	DET
ijassa-751	219	19	method	method	NOUN
ijassa-751	219	20	of	of	ADP
ijassa-751	219	21	metaclassifiers	metaclassifier	NOUN
ijassa-751	219	22	stacking	stacking	NOUN
ijassa-751	219	23	,	,	PUNCT
ijassa-751	219	24	proceedings	proceeding	NOUN
ijassa-751	219	25	of	of	ADP
ijassa-751	219	26	the	the	DET
ijassa-751	219	27	6th	6th	ADJ
ijassa-751	219	28	international	international	ADJ
ijassa-751	219	29	conference	conference	NOUN
ijassa-751	219	30	on	on	ADP
ijassa-751	219	31	computing	computing	NOUN
ijassa-751	219	32	and	and	CCONJ
ijassa-751	219	33	informatics	informatic	NOUN
ijassa-751	219	34	,	,	PUNCT
ijassa-751	219	35	icoci	icoci	PROPN
ijassa-751	219	36	,	,	PUNCT
ijassa-751	219	37	pp	pp	ADJ
ijassa-751	219	38	.	.	PUNCT
ijassa-751	220	1	750	750	NUM
ijassa-751	220	2	-	-	SYM
ijassa-751	220	3	757.757	757.757	NUM
ijassa-751	220	4	.	.	PUNCT
ijassa-751	221	1	4	4	NUM
ijassa-751	221	2	.	.	X
ijassa-751	221	3	sabri	sabri	PROPN
ijassa-751	221	4	a	a	PROPN
ijassa-751	221	5	,	,	PUNCT
ijassa-751	221	6	mohammads	mohammad	NOUN
ijassa-751	221	7	a	a	PRON
ijassa-751	221	8	,	,	PUNCT
ijassa-751	221	9	al	al	PROPN
ijassa-751	221	10	-	-	PUNCT
ijassa-751	221	11	shargabi	shargabi	PROPN
ijassa-751	221	12	b	b	PROPN
ijassa-751	221	13	,	,	PUNCT
ijassa-751	221	14	hamdeh	hamdeh	NOUN
ijassa-751	221	15	m	m	PROPN
ijassa-751	221	16	(	(	PUNCT
ijassa-751	221	17	2010	2010	NUM
ijassa-751	221	18	)	)	PUNCT
ijassa-751	221	19	developing	develop	VERB
ijassa-751	221	20	new	new	ADJ
ijassa-751	221	21	continuous	continuous	ADJ
ijassa-751	221	22	learning	learning	NOUN
ijassa-751	221	23	approach	approach	NOUN
ijassa-751	221	24	for	for	ADP
ijassa-751	221	25	spam	spam	NOUN
ijassa-751	221	26	detection	detection	NOUN
ijassa-751	221	27	using	use	VERB
ijassa-751	221	28	artificial	artificial	ADJ
ijassa-751	221	29	neural	neural	ADJ
ijassa-751	221	30	network	network	NOUN
ijassa-751	221	31	(	(	PUNCT
ijassa-751	221	32	cla	cla	PROPN
ijassa-751	221	33	ann	ann	PROPN
ijassa-751	221	34	)	)	PUNCT
ijassa-751	221	35	,	,	PUNCT
ijassa-751	221	36	european	european	PROPN
ijassa-751	221	37	journal	journal	PROPN
ijassa-751	221	38	of	of	ADP
ijassa-751	221	39	scientific	scientific	ADJ
ijassa-751	221	40	research	research	NOUN
ijassa-751	221	41	,	,	PUNCT
ijassa-751	221	42	42(3	42(3	NUM
ijassa-751	221	43	)	)	PUNCT
ijassa-751	221	44	,	,	PUNCT
ijassa-751	221	45	pp	pp	PROPN
ijassa-751	221	46	.	.	PUNCT
ijassa-751	222	1	525	525	NUM
ijassa-751	222	2	-	-	SYM
ijassa-751	222	3	535	535	NUM
ijassa-751	222	4	.	.	PUNCT
ijassa-751	223	1	5	5	NUM
ijassa-751	223	2	.	.	X
ijassa-751	224	1	zhang	zhang	PROPN
ijassa-751	224	2	y	y	PROPN
ijassa-751	224	3	,	,	PUNCT
ijassa-751	224	4	li	li	PROPN
ijassa-751	224	5	h	h	PROPN
ijassa-751	224	6	,	,	PUNCT
ijassa-751	224	7	niranjan	niranjan	PROPN
ijassa-751	224	8	m	m	PROPN
ijassa-751	224	9	,	,	PUNCT
ijassa-751	224	10	rockett	rockett	PROPN
ijassa-751	224	11	p	p	PROPN
ijassa-751	224	12	(	(	PUNCT
ijassa-751	224	13	2008	2008	NUM
ijassa-751	224	14	)	)	PUNCT
ijassa-751	224	15	applying	apply	VERB
ijassa-751	224	16	costsensitive	costsensitive	ADJ
ijassa-751	224	17	multiobjective	multiobjective	ADJ
ijassa-751	224	18	genetic	genetic	ADJ
ijassa-751	224	19	programming	programming	NOUN
ijassa-751	224	20	to	to	PART
ijassa-751	224	21	feature	feature	VERB
ijassa-751	224	22	extraction	extraction	NOUN
ijassa-751	224	23	for	for	ADP
ijassa-751	224	24	spam	spam	NOUN
ijassa-751	224	25	e	e	NOUN
ijassa-751	224	26	-	-	NOUN
ijassa-751	224	27	mail	mail	NOUN
ijassa-751	224	28	filtering	filtering	NOUN
ijassa-751	224	29	.	.	PUNCT
ijassa-751	224	30	springer	springer	PROPN
ijassa-751	224	31	,	,	PUNCT
ijassa-751	224	32	berlin	berlin	PROPN
ijassa-751	224	33	,	,	PUNCT
ijassa-751	224	34	pp	pp	ADJ
ijassa-751	224	35	.	.	PUNCT
ijassa-751	225	1	325	325	NUM
ijassa-751	225	2	-	-	SYM
ijassa-751	225	3	336	336	NUM
ijassa-751	225	4	.	.	PUNCT
ijassa-751	226	1	doi:10.1007/978	doi:10.1007/978	NOUN
ijassa-751	226	2	-	-	PUNCT
ijassa-751	226	3	3	3	NUM
ijassa-751	226	4	-	-	PUNCT
ijassa-751	226	5	540	540	NUM
ijassa-751	226	6	-	-	PUNCT
ijassa-751	226	7	78671	78671	NUM
ijassa-751	226	8	-	-	SYM
ijassa-751	226	9	9	9	NUM
ijassa-751	226	10	28	28	NUM
ijassa-751	226	11	6	6	NUM
ijassa-751	226	12	.	.	PUNCT
ijassa-751	227	1	renuka	renuka	PROPN
ijassa-751	227	2	d	d	PROPN
ijassa-751	227	3	,	,	PUNCT
ijassa-751	227	4	visalakshi	visalakshi	PROPN
ijassa-751	227	5	p	p	NOUN
ijassa-751	227	6	,	,	PUNCT
ijassa-751	227	7	sankar	sankar	PROPN
ijassa-751	227	8	t	t	PROPN
ijassa-751	227	9	,	,	PUNCT
ijassa-751	227	10	improving	improve	VERB
ijassa-751	227	11	e	e	NOUN
ijassa-751	227	12	-	-	NOUN
ijassa-751	227	13	mail	mail	NOUN
ijassa-751	227	14	spam	spam	NOUN
ijassa-751	227	15	classification	classification	NOUN
ijassa-751	227	16	using	use	VERB
ijassa-751	227	17	ant	ant	ADJ
ijassa-751	227	18	colony	colony	NOUN
ijassa-751	227	19	optimization	optimization	NOUN
ijassa-751	227	20	algorithm	algorithm	NOUN
ijassa-751	227	21	,	,	PUNCT
ijassa-751	227	22	international	international	ADJ
ijassa-751	227	23	journal	journal	NOUN
ijassa-751	227	24	of	of	ADP
ijassa-751	227	25	computer	computer	NOUN
ijassa-751	227	26	applications	application	NOUN
ijassa-751	227	27	(	(	PUNCT
ijassa-751	227	28	0975	0975	NUM
ijassa-751	227	29	8887)international	8887)international	NUM
ijassa-751	227	30	conference	conference	NOUN
ijassa-751	227	31	on	on	ADP
ijassa-751	227	32	innovations	innovation	NOUN
ijassa-751	227	33	in	in	ADP
ijassa-751	227	34	computing	compute	VERB
ijassa-751	227	35	techniques	technique	NOUN
ijassa-751	227	36	(	(	PUNCT
ijassa-751	227	37	icict	icict	NOUN
ijassa-751	227	38	2015	2015	NUM
ijassa-751	227	39	)	)	PUNCT
ijassa-751	227	40	7	7	NUM
ijassa-751	227	41	.	.	PUNCT
ijassa-751	227	42	özgür	özgür	NUM
ijassa-751	227	43	l	l	NOUN
ijassa-751	227	44	,	,	PUNCT
ijassa-751	227	45	güngör	güngör	PROPN
ijassa-751	227	46	t	t	PROPN
ijassa-751	227	47	,	,	PUNCT
ijassa-751	227	48	gürgen	gürgen	NOUN
ijassa-751	227	49	f	f	PROPN
ijassa-751	227	50	(	(	PUNCT
ijassa-751	227	51	2004	2004	NUM
ijassa-751	227	52	)	)	PUNCT
ijassa-751	227	53	spam	spam	NOUN
ijassa-751	227	54	mail	mail	NOUN
ijassa-751	227	55	detection	detection	NOUN
ijassa-751	227	56	using	use	VERB
ijassa-751	227	57	artificial	artificial	ADJ
ijassa-751	227	58	neural	neural	ADJ
ijassa-751	227	59	network	network	NOUN
ijassa-751	227	60	and	and	CCONJ
ijassa-751	227	61	bayesian	bayesian	NOUN
ijassa-751	227	62	filter	filter	NOUN
ijassa-751	227	63	.	.	PUNCT
ijassa-751	228	1	pp	pp	ADJ
ijassa-751	228	2	.	.	PUNCT
ijassa-751	229	1	505	505	NUM
ijassa-751	229	2	-	-	SYM
ijassa-751	229	3	510	510	NUM
ijassa-751	229	4	.	.	PUNCT
ijassa-751	230	1	doi:10.1007/978	doi:10.1007/978	PROPN
ijassa-751	230	2	-	-	PUNCT
ijassa-751	230	3	3	3	NUM
ijassa-751	230	4	-	-	PUNCT
ijassa-751	230	5	540	540	NUM
ijassa-751	230	6	-	-	PUNCT
ijassa-751	230	7	28651	28651	NUM
ijassa-751	230	8	-	-	SYM
ijassa-751	230	9	6	6	NUM
ijassa-751	230	10	74	74	NUM
ijassa-751	230	11	.	.	PUNCT
ijassa-751	230	12	8	8	NUM
ijassa-751	230	13	.	.	PUNCT
ijassa-751	231	1	temitayo	temitayo	PROPN
ijassa-751	231	2	f	f	PROPN
ijassa-751	231	3	,	,	PUNCT
ijassa-751	231	4	stephen	stephen	PROPN
ijassa-751	231	5	o	o	PROPN
ijassa-751	231	6	,	,	PUNCT
ijassa-751	231	7	abimbola	abimbola	VERB
ijassa-751	231	8	a	a	DET
ijassa-751	231	9	(	(	PUNCT
ijassa-751	231	10	2012	2012	NUM
ijassa-751	231	11	)	)	PUNCT
ijassa-751	231	12	hybrid	hybrid	ADJ
ijassa-751	231	13	ga	ga	NOUN
ijassa-751	231	14	-	-	PUNCT
ijassa-751	231	15	svm	svm	PROPN
ijassa-751	231	16	for	for	ADP
ijassa-751	231	17	efficient	efficient	ADJ
ijassa-751	231	18	feature	feature	NOUN
ijassa-751	231	19	selection	selection	NOUN
ijassa-751	231	20	in	in	ADP
ijassa-751	231	21	e	e	NOUN
ijassa-751	231	22	-	-	NOUN
ijassa-751	231	23	mail	mail	NOUN
ijassa-751	231	24	classification	classification	NOUN
ijassa-751	231	25	,	,	PUNCT
ijassa-751	231	26	computer	computer	NOUN
ijassa-751	231	27	engineering	engineering	NOUN
ijassa-751	231	28	and	and	CCONJ
ijassa-751	231	29	intelligent	intelligent	ADJ
ijassa-751	231	30	systems	system	NOUN
ijassa-751	231	31	,	,	PUNCT
ijassa-751	231	32	vol	vol	NOUN
ijassa-751	231	33	3	3	NUM
ijassa-751	231	34	,	,	PUNCT
ijassa-751	231	35	no.3	no.3	VERB
ijassa-751	231	36	,	,	PUNCT
ijassa-751	231	37	pp	pp	ADJ
ijassa-751	231	38	.	.	PUNCT
ijassa-751	232	1	17	17	NUM
ijassa-751	232	2	-	-	SYM
ijassa-751	232	3	29	29	NUM
ijassa-751	232	4	9	9	NUM
ijassa-751	232	5	.	.	PUNCT
ijassa-751	233	1	liu	liu	PROPN
ijassa-751	233	2	k	k	PROPN
ijassa-751	233	3	,	,	PUNCT
ijassa-751	233	4	tan	tan	PROPN
ijassa-751	233	5	y	y	PROPN
ijassa-751	233	6	,	,	PUNCT
ijassa-751	233	7	he	he	PRON
ijassa-751	233	8	x	x	X
ijassa-751	233	9	(	(	PUNCT
ijassa-751	233	10	2010	2010	NUM
ijassa-751	233	11	)	)	PUNCT
ijassa-751	233	12	particle	particle	NOUN
ijassa-751	233	13	swarm	swarm	NOUN
ijassa-751	233	14	optimization	optimization	NOUN
ijassa-751	233	15	based	base	VERB
ijassa-751	233	16	learning	learning	NOUN
ijassa-751	233	17	method	method	NOUN
ijassa-751	233	18	for	for	ADP
ijassa-751	233	19	process	process	NOUN
ijassa-751	233	20	neural	neural	ADJ
ijassa-751	233	21	networks	network	NOUN
ijassa-751	233	22	,	,	PUNCT
ijassa-751	233	23	in	in	ADP
ijassa-751	233	24	advances	advance	NOUN
ijassa-751	233	25	in	in	ADP
ijassa-751	233	26	neural	neural	ADJ
ijassa-751	233	27	networks	network	NOUN
ijassa-751	233	28	-	-	PUNCT
ijassa-751	233	29	isnn	isnn	NOUN
ijassa-751	233	30	2010	2010	NUM
ijassa-751	233	31	(	(	PUNCT
ijassa-751	233	32	pp	pp	ADJ
ijassa-751	233	33	.	.	PUNCT
ijassa-751	234	1	280	280	NUM
ijassa-751	234	2	-	-	SYM
ijassa-751	234	3	287	287	NUM
ijassa-751	234	4	)	)	PUNCT
ijassa-751	234	5	.	.	PUNCT
ijassa-751	235	1	springer	springer	PROPN
ijassa-751	235	2	berlin	berlin	PROPN
ijassa-751	235	3	heidelberg	heidelberg	PROPN
ijassa-751	235	4	.	.	PUNCT
ijassa-751	236	1	10	10	NUM
ijassa-751	236	2	.	.	PUNCT
ijassa-751	237	1	idris	idris	PROPN
ijassa-751	237	2	i	i	PRON
ijassa-751	237	3	,	,	PUNCT
ijassa-751	237	4	selamat	selamat	PROPN
ijassa-751	237	5	a	a	DET
ijassa-751	237	6	(	(	PUNCT
ijassa-751	237	7	2014	2014	NUM
ijassa-751	237	8	)	)	PUNCT
ijassa-751	237	9	improved	improve	VERB
ijassa-751	237	10	email	email	NOUN
ijassa-751	237	11	spam	spam	NOUN
ijassa-751	237	12	detection	detection	NOUN
ijassa-751	237	13	model	model	NOUN
ijassa-751	237	14	with	with	ADP
ijassa-751	237	15	negative	negative	ADJ
ijassa-751	237	16	selection	selection	NOUN
ijassa-751	237	17	algorithm	algorithm	NOUN
ijassa-751	237	18	and	and	CCONJ
ijassa-751	237	19	particle	particle	NOUN
ijassa-751	237	20	swarm	swarm	NOUN
ijassa-751	237	21	optimization	optimization	NOUN
ijassa-751	237	22	,	,	PUNCT
ijassa-751	237	23	applied	apply	VERB
ijassa-751	237	24	soft	soft	ADJ
ijassa-751	237	25	computing	computing	NOUN
ijassa-751	237	26	,	,	PUNCT
ijassa-751	237	27	22	22	NUM
ijassa-751	237	28	,	,	PUNCT
ijassa-751	237	29	pp	pp	ADJ
ijassa-751	237	30	.	.	PUNCT
ijassa-751	238	1	11	11	NUM
ijassa-751	238	2	-	-	SYM
ijassa-751	238	3	27	27	NUM
ijassa-751	238	4	.	.	PUNCT
ijassa-751	239	1	11	11	NUM
ijassa-751	239	2	.	.	PUNCT
ijassa-751	239	3	olatunji	olatunji	NOUN
ijassa-751	239	4	s	s	PART
ijassa-751	239	5	(	(	PUNCT
ijassa-751	239	6	2017	2017	NUM
ijassa-751	239	7	)	)	PUNCT
ijassa-751	239	8	improved	improve	VERB
ijassa-751	239	9	email	email	NOUN
ijassa-751	239	10	spam	spam	NOUN
ijassa-751	239	11	detection	detection	NOUN
ijassa-751	239	12	model	model	NOUN
ijassa-751	239	13	based	base	VERB
ijassa-751	239	14	on	on	ADP
ijassa-751	239	15	support	support	NOUN
ijassa-751	239	16	vector	vector	NOUN
ijassa-751	239	17	machines	machine	NOUN
ijassa-751	239	18	,	,	PUNCT
ijassa-751	239	19	neural	neural	ADJ
ijassa-751	239	20	computing	computing	NOUN
ijassa-751	239	21	and	and	CCONJ
ijassa-751	239	22	applications	application	NOUN
ijassa-751	239	23	,	,	PUNCT
ijassa-751	239	24	20131(3	20131(3	NUM
ijassa-751	239	25	)	)	PUNCT
ijassa-751	239	26	,	,	PUNCT
ijassa-751	239	27	pp	pp	PROPN
ijassa-751	239	28	.	.	PUNCT
ijassa-751	240	1	691	691	NUM
ijassa-751	240	2	-	-	SYM
ijassa-751	240	3	699	699	NUM
ijassa-751	240	4	.	.	PUNCT
ijassa-751	240	5	12	12	NUM
ijassa-751	240	6	.	.	PUNCT
ijassa-751	241	1	kennedy	kennedy	PROPN
ijassa-751	241	2	j	j	PROPN
ijassa-751	241	3	,	,	PUNCT
ijassa-751	241	4	eberhart	eberhart	NOUN
ijassa-751	241	5	r	r	NOUN
ijassa-751	241	6	(	(	PUNCT
ijassa-751	241	7	1995)”particle	1995)”particle	NUM
ijassa-751	241	8	swarm	swarm	NOUN
ijassa-751	241	9	optimization	optimization	NOUN
ijassa-751	241	10	”	"	PUNCT
ijassa-751	241	11	.	.	PUNCT
ijassa-751	242	1	in	in	ADP
ijassa-751	242	2	proceedings	proceeding	NOUN
ijassa-751	242	3	international	international	ADJ
ijassa-751	242	4	conference	conference	NOUN
ijassa-751	242	5	on	on	ADP
ijassa-751	242	6	neural	neural	ADJ
ijassa-751	242	7	networks	network	NOUN
ijassa-751	242	8	(	(	PUNCT
ijassa-751	242	9	icnn	icnn	PROPN
ijassa-751	242	10	95	95	NUM
ijassa-751	242	11	)	)	PUNCT
ijassa-751	242	12	perth	perth	PROPN
ijassa-751	242	13	,	,	PUNCT
ijassa-751	242	14	australia	australia	PROPN
ijassa-751	242	15	,	,	PUNCT
ijassa-751	242	16	pp	pp	X
ijassa-751	242	17	.	.	PUNCT
ijassa-751	242	18	19421948	19421948	NUM
ijassa-751	242	19	.	.	PUNCT
ijassa-751	243	1	13	13	NUM
ijassa-751	243	2	.	.	PUNCT
ijassa-751	244	1	modares	modare	NOUN
ijassa-751	244	2	h	h	PROPN
ijassa-751	244	3	,	,	PUNCT
ijassa-751	244	4	alfi	alfi	X
ijassa-751	244	5	a	a	PRON
ijassa-751	244	6	,	,	PUNCT
ijassa-751	244	7	sistani	sistani	PROPN
ijassa-751	244	8	m	m	PROPN
ijassa-751	244	9	(	(	PUNCT
ijassa-751	244	10	2010	2010	NUM
ijassa-751	244	11	)	)	PUNCT
ijassa-751	244	12	parameter	parameter	NOUN
ijassa-751	244	13	estimation	estimation	NOUN
ijassa-751	244	14	of	of	ADP
ijassa-751	244	15	bilinear	bilinear	NOUN
ijassa-751	244	16	systems	system	NOUN
ijassa-751	244	17	based	base	VERB
ijassa-751	244	18	on	on	ADP
ijassa-751	244	19	an	an	DET
ijassa-751	244	20	adaptive	adaptive	ADJ
ijassa-751	244	21	particle	particle	NOUN
ijassa-751	244	22	swarm	swarm	NOUN
ijassa-751	244	23	optimization	optimization	NOUN
ijassa-751	244	24	,	,	PUNCT
ijassa-751	244	25	engineering	engineering	NOUN
ijassa-751	244	26	applications	application	NOUN
ijassa-751	244	27	of	of	ADP
ijassa-751	244	28	artificial	artificial	ADJ
ijassa-751	244	29	intelligence	intelligence	NOUN
ijassa-751	244	30	,	,	PUNCT
ijassa-751	244	31	23(7	23(7	NUM
ijassa-751	244	32	)	)	PUNCT
ijassa-751	244	33	,	,	PUNCT
ijassa-751	244	34	pp	pp	ADJ
ijassa-751	244	35	.	.	PUNCT
ijassa-751	245	1	1105	1105	NUM
ijassa-751	245	2	-	-	SYM
ijassa-751	245	3	1111	1111	NUM
ijassa-751	245	4	.	.	PUNCT
ijassa-751	246	1	14	14	NUM
ijassa-751	246	2	.	.	PUNCT
ijassa-751	247	1	liu	liu	PROPN
ijassa-751	247	2	z	z	PROPN
ijassa-751	247	3	,	,	PUNCT
ijassa-751	247	4	li	li	PROPN
ijassa-751	247	5	h	h	PROPN
ijassa-751	247	6	,	,	PUNCT
ijassa-751	247	7	zhu	zhu	PROPN
ijassa-751	247	8	p	p	NOUN
ijassa-751	247	9	(	(	PUNCT
ijassa-751	247	10	2019	2019	NUM
ijassa-751	247	11	)	)	PUNCT
ijassa-751	247	12	diversity	diversity	NOUN
ijassa-751	247	13	enhanced	enhance	VERB
ijassa-751	247	14	particle	particle	NOUN
ijassa-751	247	15	swarm	swarm	NOUN
ijassa-751	247	16	optimization	optimization	NOUN
ijassa-751	247	17	algorithm	algorithm	NOUN
ijassa-751	247	18	and	and	CCONJ
ijassa-751	247	19	its	its	PRON
ijassa-751	247	20	application	application	NOUN
ijassa-751	247	21	in	in	ADP
ijassa-751	247	22	vehicle	vehicle	NOUN
ijassa-751	247	23	lightweight	lightweight	ADJ
ijassa-751	247	24	design	design	NOUN
ijassa-751	247	25	,	,	PUNCT
ijassa-751	247	26	journal	journal	NOUN
ijassa-751	247	27	of	of	ADP
ijassa-751	247	28	mechanical	mechanical	ADJ
ijassa-751	247	29	science	science	NOUN
ijassa-751	247	30	and	and	CCONJ
ijassa-751	247	31	technology	technology	NOUN
ijassa-751	247	32	,	,	PUNCT
ijassa-751	247	33	33	33	NUM
ijassa-751	247	34	(	(	PUNCT
ijassa-751	247	35	2	2	NUM
ijassa-751	247	36	)	)	PUNCT
ijassa-751	247	37	,	,	PUNCT
ijassa-751	247	38	pp	pp	ADJ
ijassa-751	247	39	.	.	PUNCT
ijassa-751	248	1	695	695	NUM
ijassa-751	248	2	-	-	SYM
ijassa-751	248	3	709	709	NUM
ijassa-751	248	4	.	.	PUNCT
ijassa-751	249	1	15	15	NUM
ijassa-751	249	2	.	.	PUNCT
ijassa-751	250	1	cheng	cheng	PROPN
ijassa-751	250	2	s	s	PROPN
ijassa-751	250	3	,	,	PUNCT
ijassa-751	250	4	lu	lu	PROPN
ijassa-751	250	5	h	h	NOUN
ijassa-751	250	6	,	,	PUNCT
ijassa-751	250	7	lei	lei	X
ijassa-751	250	8	x	x	NOUN
ijassa-751	250	9	,	,	PUNCT
ijassa-751	250	10	hi	hi	INTJ
ijassa-751	250	11	y	y	PROPN
ijassa-751	250	12	(	(	PUNCT
ijassa-751	250	13	2018	2018	NUM
ijassa-751	250	14	)	)	PUNCT
ijassa-751	250	15	a	a	DET
ijassa-751	250	16	quarter	quarter	NOUN
ijassa-751	250	17	century	century	NOUN
ijassa-751	250	18	of	of	ADP
ijassa-751	250	19	particle	particle	NOUN
ijassa-751	250	20	swarm	swarm	NOUN
ijassa-751	250	21	optimization	optimization	NOUN
ijassa-751	250	22	,	,	PUNCT
ijassa-751	250	23	complex	complex	ADJ
ijassa-751	250	24	and	and	CCONJ
ijassa-751	250	25	intelligent	intelligent	ADJ
ijassa-751	250	26	systems	system	NOUN
ijassa-751	250	27	,	,	PUNCT
ijassa-751	250	28	january	january	PROPN
ijassa-751	250	29	2018	2018	NUM
ijassa-751	250	30	,	,	PUNCT
ijassa-751	250	31	accepted	accept	VERB
ijassa-751	250	32	,	,	PUNCT
ijassa-751	250	33	22	22	NUM
ijassa-751	250	34	march	march	NOUN
ijassa-751	250	35	2018	2018	NUM
ijassa-751	250	36	16	16	NUM
ijassa-751	250	37	.	.	PUNCT
ijassa-751	251	1	shalev	shalev	NOUN
ijassa-751	251	2	-	-	PUNCT
ijassa-751	251	3	shwartz	shwartz	PROPN
ijassa-751	251	4	s	s	PROPN
ijassa-751	251	5	,	,	PUNCT
ijassa-751	251	6	singer	singer	NOUN
ijassa-751	251	7	y	y	PROPN
ijassa-751	251	8	,	,	PUNCT
ijassa-751	251	9	srebro	srebro	NOUN
ijassa-751	251	10	n	n	PRON
ijassa-751	251	11	,	,	PUNCT
ijassa-751	251	12	(	(	PUNCT
ijassa-751	251	13	2007	2007	NUM
ijassa-751	251	14	)	)	PUNCT
ijassa-751	251	15	pegasos	pegaso	NOUN
ijassa-751	251	16	:	:	PUNCT
ijassa-751	251	17	primal	primal	ADJ
ijassa-751	251	18	estimated	estimate	VERB
ijassa-751	251	19	sub	sub	ADJ
ijassa-751	251	20	-	-	ADJ
ijassa-751	251	21	gradient	gradient	ADJ
ijassa-751	251	22	solver	solver	NOUN
ijassa-751	251	23	for	for	ADP
ijassa-751	251	24	svm	svm	PROPN
ijassa-751	251	25	,	,	PUNCT
ijassa-751	251	26	in	in	ADP
ijassa-751	251	27	proceedings	proceeding	NOUN
ijassa-751	251	28	of	of	ADP
ijassa-751	251	29	the	the	DET
ijassa-751	251	30	24th	24th	ADJ
ijassa-751	251	31	international	international	ADJ
ijassa-751	251	32	conference	conference	NOUN
ijassa-751	251	33	on	on	ADP
ijassa-751	251	34	machine	machine	NOUN
ijassa-751	251	35	learning	learning	NOUN
ijassa-751	251	36	,	,	PUNCT
ijassa-751	251	37	pp	pp	PROPN
ijassa-751	251	38	.	.	PUNCT
ijassa-751	252	1	807	807	NUM
ijassa-751	253	1	-814	-814	PROPN
ijassa-751	253	2	.	.	PROPN
ijassa-751	253	3	17	17	NUM
ijassa-751	253	4	.	.	PUNCT
ijassa-751	254	1	shalev	shalev	NOUN
ijassa-751	254	2	-	-	PUNCT
ijassa-751	254	3	shwartz	shwartz	PROPN
ijassa-751	254	4	s	s	PROPN
ijassa-751	254	5	,	,	PUNCT
ijassa-751	254	6	singer	singer	NOUN
ijassa-751	254	7	y	y	PROPN
ijassa-751	254	8	,	,	PUNCT
ijassa-751	254	9	srebro	srebro	PROPN
ijassa-751	254	10	n	n	PROPN
ijassa-751	254	11	,	,	PUNCT
ijassa-751	254	12	cotter	cotter	NOUN
ijassa-751	254	13	a	a	DET
ijassa-751	254	14	(	(	PUNCT
ijassa-751	254	15	2011	2011	NUM
ijassa-751	254	16	)	)	PUNCT
ijassa-751	254	17	extended	extend	VERB
ijassa-751	254	18	version	version	NOUN
ijassa-751	254	19	:	:	PUNCT
ijassa-751	254	20	pegasos	pegaso	NOUN
ijassa-751	254	21	:	:	PUNCT
ijassa-751	254	22	primal	primal	ADJ
ijassa-751	254	23	estimated	estimate	VERB
ijassa-751	254	24	sub	sub	ADJ
ijassa-751	254	25	-	-	ADJ
ijassa-751	254	26	gradient	gradient	ADJ
ijassa-751	254	27	solver	solver	NOUN
ijassa-751	254	28	for	for	ADP
ijassa-751	254	29	svm	svm	ADJ
ijassa-751	254	30	,	,	PUNCT
ijassa-751	254	31	mathematical	mathematical	ADJ
ijassa-751	254	32	programming	programming	NOUN
ijassa-751	254	33	,	,	PUNCT
ijassa-751	254	34	series	series	NOUN
ijassa-751	254	35	b	b	PROPN
ijassa-751	254	36	,	,	PUNCT
ijassa-751	254	37	127(1	127(1	NUM
ijassa-751	254	38	)	)	PUNCT
ijassa-751	254	39	,	,	PUNCT
ijassa-751	255	1	pp	pp	ADP
ijassa-751	255	2	.	.	PUNCT
ijassa-751	256	1	3	3	NUM
ijassa-751	256	2	-	-	SYM
ijassa-751	256	3	30	30	NUM
ijassa-751	256	4	,	,	PUNCT
ijassa-751	256	5	springer	springer	NOUN
ijassa-751	256	6	and	and	CCONJ
ijassa-751	256	7	mathematical	mathematical	ADJ
ijassa-751	256	8	optimization	optimization	NOUN
ijassa-751	256	9	society	society	NOUN
ijassa-751	256	10	.	.	PUNCT
ijassa-751	257	1	18	18	NUM
ijassa-751	257	2	.	.	X
ijassa-751	257	3	lu	lu	PROPN
ijassa-751	257	4	s	s	PROPN
ijassa-751	257	5	,	,	PUNCT
ijassa-751	257	6	jin	jin	PROPN
ijassa-751	257	7	z	z	PROPN
ijassa-751	257	8	(	(	PUNCT
ijassa-751	257	9	2017	2017	NUM
ijassa-751	257	10	)	)	PUNCT
ijassa-751	257	11	improved	improve	VERB
ijassa-751	257	12	stochastic	stochastic	ADJ
ijassa-751	257	13	gradient	gradient	ADJ
ijassa-751	257	14	descent	descent	NOUN
ijassa-751	257	15	algorithm	algorithm	NOUN
ijassa-751	257	16	for	for	ADP
ijassa-751	257	17	svm	svm	PROPN
ijassa-751	257	18	,	,	PUNCT
ijassa-751	257	19	international	international	ADJ
ijassa-751	257	20	journal	journal	NOUN
ijassa-751	257	21	of	of	ADP
ijassa-751	257	22	recent	recent	ADJ
ijassa-751	257	23	engineering	engineering	NOUN
ijassa-751	257	24	science	science	NOUN
ijassa-751	257	25	(	(	PUNCT
ijassa-751	257	26	ijres	ijre	NOUN
ijassa-751	257	27	)	)	PUNCT
ijassa-751	257	28	,	,	PUNCT
ijassa-751	257	29	issn	issn	PROPN
ijassa-751	257	30	2349	2349	NUM
ijassa-751	257	31	-	-	SYM
ijassa-751	257	32	7157	7157	NUM
ijassa-751	257	33	,	,	PUNCT
ijassa-751	257	34	vol	vol	NOUN
ijassa-751	257	35	4	4	NUM
ijassa-751	257	36	,	,	PUNCT
ijassa-751	257	37	pp	pp	ADJ
ijassa-751	257	38	.	.	PUNCT
ijassa-751	258	1	39	39	NUM
ijassa-751	258	2	-	-	SYM
ijassa-751	258	3	42	42	NUM
ijassa-751	258	4	.	.	PUNCT
ijassa-751	259	1	19	19	NUM
ijassa-751	259	2	.	.	PUNCT
ijassa-751	260	1	v.	v.	PROPN
ijassa-751	260	2	jumutc	jumutc	PROPN
ijassa-751	260	3	,	,	PUNCT
ijassa-751	260	4	x.	x.	PROPN
ijassa-751	260	5	huang	huang	PROPN
ijassa-751	260	6	,	,	PUNCT
ijassa-751	260	7	j.	j.	PROPN
ijassa-751	260	8	a.	a.	PROPN
ijassa-751	260	9	k.	k.	PROPN
ijassa-751	260	10	suykens,(2013	suykens,(2013	PROPN
ijassa-751	260	11	)	)	PUNCT
ijassa-751	260	12	fixed	fix	VERB
ijassa-751	260	13	-	-	PUNCT
ijassa-751	260	14	size	size	NOUN
ijassa-751	260	15	pegasos	pegasos	NOUN
ijassa-751	260	16	for	for	ADP
ijassa-751	260	17	hinge	hinge	NOUN
ijassa-751	260	18	and	and	CCONJ
ijassa-751	260	19	pinball	pinball	NOUN
ijassa-751	260	20	loss	loss	NOUN
ijassa-751	260	21	svm	svm	NOUN
ijassa-751	260	22	,	,	PUNCT
ijassa-751	260	23	in	in	ADP
ijassa-751	260	24	proceedings	proceeding	NOUN
ijassa-751	260	25	of	of	ADP
ijassa-751	260	26	the	the	DET
ijassa-751	260	27	2013	2013	NUM
ijassa-751	260	28	international	international	ADJ
ijassa-751	260	29	joint	joint	ADJ
ijassa-751	260	30	conference	conference	NOUN
ijassa-751	260	31	on	on	ADP
ijassa-751	260	32	neural	neural	ADJ
ijassa-751	260	33	networks	network	NOUN
ijassa-751	260	34	(	(	PUNCT
ijassa-751	260	35	ijcnn	ijcnn	PROPN
ijassa-751	260	36	)	)	PUNCT
ijassa-751	260	37	,	,	PUNCT
ijassa-751	261	1	pp	pp	PROPN
ijassa-751	261	2	.	.	PUNCT
ijassa-751	262	1	1122	1122	NUM
ijassa-751	262	2	-	-	SYM
ijassa-751	262	3	1128	1128	NUM
ijassa-751	262	4	,	,	PUNCT
ijassa-751	262	5	2013	2013	NUM
ijassa-751	262	6	.	.	PUNCT
ijassa-751	263	1	copyright	copyright	NOUN
ijassa-751	263	2	c	c	ADP
ijassa-751	263	3	©	©	PROPN
ijassa-751	263	4	2019	2019	NUM
ijassa-751	263	5	assa	assa	NOUN
ijassa-751	263	6	.	.	PUNCT
ijassa-751	264	1	adv	adv	PROPN
ijassa-751	264	2	.	.	PUNCT
ijassa-751	265	1	in	in	ADP
ijassa-751	265	2	systems	system	NOUN
ijassa-751	265	3	science	science	NOUN
ijassa-751	265	4	and	and	CCONJ
ijassa-751	265	5	appl.(2019	appl.(2019	NOUN
ijassa-751	265	6	)	)	PUNCT
ijassa-751	265	7	22	22	NUM
ijassa-751	265	8	l.m	l.m	PROPN
ijassa-751	265	9	.	.	PROPN
ijassa-751	265	10	el	el	PROPN
ijassa-751	265	11	bakrawy	bakrawy	PROPN
ijassa-751	265	12	20	20	NUM
ijassa-751	265	13	.	.	PUNCT
ijassa-751	266	1	hopkins	hopkins	PROPN
ijassa-751	266	2	m	m	PROPN
ijassa-751	266	3	,	,	PUNCT
ijassa-751	266	4	reeber	reeber	PROPN
ijassa-751	266	5	e	e	PROPN
ijassa-751	266	6	,	,	PUNCT
ijassa-751	266	7	forman	forman	NOUN
ijassa-751	266	8	g	g	PROPN
ijassa-751	266	9	,	,	PUNCT
ijassa-751	266	10	suermondt	suermondt	PROPN
ijassa-751	266	11	j	j	PROPN
ijassa-751	266	12	(	(	PUNCT
ijassa-751	266	13	1999	1999	NUM
ijassa-751	266	14	)	)	PUNCT
ijassa-751	266	15	spambase	spambase	PROPN
ijassa-751	266	16	dataset	dataset	NOUN
ijassa-751	266	17	.	.	PUNCT
ijassa-751	267	1	hewlett	hewlett	PROPN
ijassa-751	267	2	-	-	PUNCT
ijassa-751	267	3	packard	packard	PROPN
ijassa-751	267	4	labs	lab	NOUN
ijassa-751	267	5	,	,	PUNCT
ijassa-751	267	6	1501	1501	NUM
ijassa-751	267	7	page	page	NOUN
ijassa-751	267	8	mill	mill	PROPN
ijassa-751	267	9	rd	rd	PROPN
ijassa-751	267	10	.	.	PROPN
ijassa-751	267	11	,	,	PUNCT
ijassa-751	267	12	palo	palo	PROPN
ijassa-751	267	13	alto	alto	PROPN
ijassa-751	267	14	,	,	PUNCT
ijassa-751	267	15	ca	ca	PROPN
ijassa-751	267	16	94304	94304	NUM
ijassa-751	267	17	.	.	PUNCT
ijassa-751	268	1	https://archive.ics.uci.edu/ml/datasets/spambase	https://archive.ics.uci.edu/ml/datasets/spambase	PROPN
ijassa-751	268	2	.	.	PUNCT
ijassa-751	269	1	21	21	NUM
ijassa-751	269	2	.	.	PUNCT
ijassa-751	270	1	el	el	PROPN
ijassa-751	270	2	bakrawy	bakrawy	PROPN
ijassa-751	270	3	l	l	PROPN
ijassa-751	270	4	(	(	PUNCT
ijassa-751	270	5	2017	2017	NUM
ijassa-751	270	6	)	)	PUNCT
ijassa-751	270	7	grey	grey	PROPN
ijassa-751	270	8	wolf	wolf	PROPN
ijassa-751	270	9	optimization	optimization	NOUN
ijassa-751	270	10	and	and	CCONJ
ijassa-751	270	11	naive	naive	ADJ
ijassa-751	270	12	bayes	bayes	NOUN
ijassa-751	270	13	classifier	classifier	NOUN
ijassa-751	270	14	incorporation	incorporation	NOUN
ijassa-751	270	15	for	for	ADP
ijassa-751	270	16	heart	heart	NOUN
ijassa-751	270	17	disease	disease	NOUN
ijassa-751	270	18	diagnosis	diagnosis	NOUN
ijassa-751	270	19	,	,	PUNCT
ijassa-751	270	20	australian	australian	ADJ
ijassa-751	270	21	journal	journal	NOUN
ijassa-751	270	22	of	of	ADP
ijassa-751	270	23	basic	basic	ADJ
ijassa-751	270	24	and	and	CCONJ
ijassa-751	270	25	applied	applied	ADJ
ijassa-751	270	26	sciences	science	NOUN
ijassa-751	270	27	,	,	PUNCT
ijassa-751	270	28	11(7	11(7	NUM
ijassa-751	270	29	)	)	PUNCT
ijassa-751	270	30	m	m	PROPN
ijassa-751	270	31	,	,	PUNCT
ijassa-751	270	32	pp	pp	ADJ
ijassa-751	270	33	.	.	PUNCT
ijassa-751	271	1	64	64	NUM
ijassa-751	271	2	-	-	SYM
ijassa-751	271	3	70	70	NUM
ijassa-751	271	4	.	.	PUNCT
ijassa-751	272	1	22	22	NUM
ijassa-751	272	2	.	.	PUNCT
ijassa-751	273	1	liu	liu	PROPN
ijassa-751	273	2	p	p	PROPN
ijassa-751	273	3	,	,	PUNCT
ijassa-751	273	4	moh	moh	PROPN
ijassa-751	273	5	t	t	PROPN
ijassa-751	273	6	(	(	PUNCT
ijassa-751	273	7	2016	2016	NUM
ijassa-751	273	8	)	)	PUNCT
ijassa-751	273	9	content	content	NOUN
ijassa-751	273	10	based	base	VERB
ijassa-751	273	11	spam	spam	NOUN
ijassa-751	273	12	e	e	NOUN
ijassa-751	273	13	-	-	NOUN
ijassa-751	273	14	mail	mail	NOUN
ijassa-751	273	15	filtering	filtering	NOUN
ijassa-751	273	16	,	,	PUNCT
ijassa-751	273	17	in	in	ADP
ijassa-751	273	18	proceedings	proceeding	NOUN
ijassa-751	273	19	of	of	ADP
ijassa-751	273	20	the	the	DET
ijassa-751	273	21	international	international	ADJ
ijassa-751	273	22	conference	conference	NOUN
ijassa-751	273	23	on	on	ADP
ijassa-751	273	24	collaboration	collaboration	NOUN
ijassa-751	273	25	technologies	technology	NOUN
ijassa-751	273	26	and	and	CCONJ
ijassa-751	273	27	systems	system	NOUN
ijassa-751	273	28	,	,	PUNCT
ijassa-751	273	29	978	978	NUM
ijassa-751	273	30	-	-	SYM
ijassa-751	273	31	1	1	NUM
ijassa-751	273	32	-	-	PUNCT
ijassa-751	273	33	5090	5090	NUM
ijassa-751	273	34	-	-	NUM
ijassa-751	273	35	23004/16	23004/16	NUM
ijassa-751	273	36	31.00	31.00	NUM
ijassa-751	273	37	,	,	PUNCT
ijassa-751	273	38	ieee	ieee	NOUN
ijassa-751	273	39	,	,	PUNCT
ijassa-751	273	40	pp	pp	ADJ
ijassa-751	273	41	.	.	PUNCT
ijassa-751	274	1	2018	2018	NUM
ijassa-751	274	2	-	-	SYM
ijassa-751	274	3	2024	2024	NUM
ijassa-751	274	4	.	.	PUNCT
ijassa-751	275	1	copyright	copyright	NOUN
ijassa-751	275	2	c	c	ADP
ijassa-751	275	3	©	©	PROPN
ijassa-751	275	4	2019	2019	NUM
ijassa-751	275	5	assa	assa	NOUN
ijassa-751	275	6	.	.	PUNCT
ijassa-751	276	1	adv	adv	PROPN
ijassa-751	276	2	.	.	PUNCT
ijassa-751	277	1	in	in	ADP
ijassa-751	277	2	systems	system	NOUN
ijassa-751	277	3	science	science	NOUN
ijassa-751	277	4	and	and	CCONJ
ijassa-751	277	5	appl.(2019	appl.(2019	PROPN
ijassa-751	277	6	)	)	PUNCT
ijassa-751	277	7	introduction	introduction	NOUN
ijassa-751	277	8	preliminaries	preliminary	NOUN
ijassa-751	277	9	particle	particle	NOUN
ijassa-751	277	10	swarm	swarm	NOUN
ijassa-751	277	11	optimization	optimization	NOUN
ijassa-751	277	12	pegasos	pegasos	NOUN
ijassa-751	277	13	:	:	PUNCT
ijassa-751	277	14	primal	primal	ADJ
ijassa-751	277	15	estimated	estimate	VERB
ijassa-751	277	16	sub	sub	ADJ
ijassa-751	277	17	-	-	ADJ
ijassa-751	277	18	gradient	gradient	ADJ
ijassa-751	277	19	solver	solver	NOUN
ijassa-751	277	20	for	for	ADP
ijassa-751	277	21	svm	svm	ADJ
ijassa-751	277	22	the	the	DET
ijassa-751	277	23	proposed	propose	VERB
ijassa-751	277	24	algorithm	algorithm	NOUN
ijassa-751	277	25	data	datum	NOUN
ijassa-751	277	26	preprocessing	preprocesse	VERB
ijassa-751	277	27	pso	pso	NOUN
ijassa-751	277	28	-	-	PUNCT
ijassa-751	277	29	pegasos	pegasos	NOUN
ijassa-751	277	30	algorithm	algorithm	NOUN
ijassa-751	277	31	experimental	experimental	ADJ
ijassa-751	277	32	results	result	NOUN
ijassa-751	277	33	and	and	CCONJ
ijassa-751	277	34	discussions	discussion	NOUN
ijassa-751	277	35	dataset	dataset	VERB
ijassa-751	277	36	description	description	NOUN
ijassa-751	277	37	evaluation	evaluation	NOUN
ijassa-751	277	38	measures	measure	NOUN
ijassa-751	277	39	results	result	NOUN
ijassa-751	277	40	and	and	CCONJ
ijassa-751	277	41	discussion	discussion	NOUN
ijassa-751	277	42	conclusion	conclusion	NOUN