id	sid	tid	token	lemma	pos
iajs-4047	1	1	425	425	NUM
iajs-4047	1	2	©	©	ADP
iajs-4047	1	3	2025	2025	NUM
iajs-4047	1	4	the	the	DET
iajs-4047	1	5	author(s	author(s	NOUN
iajs-4047	1	6	)	)	PUNCT
iajs-4047	1	7	.	.	PUNCT
iajs-4047	2	1	published	publish	VERB
iajs-4047	2	2	by	by	ADP
iajs-4047	2	3	college	college	NOUN
iajs-4047	2	4	of	of	ADP
iajs-4047	2	5	education	education	NOUN
iajs-4047	2	6	for	for	ADP
iajs-4047	2	7	pure	pure	ADJ
iajs-4047	2	8	science	science	NOUN
iajs-4047	2	9	(	(	PUNCT
iajs-4047	2	10	ibn	ibn	PROPN
iajs-4047	2	11	al	al	PROPN
iajs-4047	2	12	-	-	PUNCT
iajs-4047	2	13	haitham	haitham	PROPN
iajs-4047	2	14	)	)	PUNCT
iajs-4047	2	15	,	,	PUNCT
iajs-4047	2	16	university	university	NOUN
iajs-4047	2	17	of	of	ADP
iajs-4047	2	18	baghdad	baghdad	PROPN
iajs-4047	2	19	.	.	PUNCT
iajs-4047	3	1	this	this	PRON
iajs-4047	3	2	is	be	AUX
iajs-4047	3	3	an	an	DET
iajs-4047	3	4	open	open	ADJ
iajs-4047	3	5	-	-	PUNCT
iajs-4047	3	6	access	access	NOUN
iajs-4047	3	7	article	article	NOUN
iajs-4047	3	8	distributed	distribute	VERB
iajs-4047	3	9	under	under	ADP
iajs-4047	3	10	the	the	DET
iajs-4047	3	11	terms	term	NOUN
iajs-4047	3	12	of	of	ADP
iajs-4047	3	13	the	the	DET
iajs-4047	3	14	creative	creative	ADJ
iajs-4047	3	15	commons	common	NOUN
iajs-4047	3	16	attribution	attribution	NOUN
iajs-4047	3	17	4.0	4.0	NUM
iajs-4047	3	18	international	international	ADJ
iajs-4047	3	19	license	license	NOUN
iajs-4047	3	20	finding	find	VERB
iajs-4047	3	21	optimal	optimal	ADJ
iajs-4047	3	22	number	number	NOUN
iajs-4047	3	23	of	of	ADP
iajs-4047	3	24	clusters	cluster	NOUN
iajs-4047	3	25	using	use	VERB
iajs-4047	3	26	heuristic	heuristic	ADJ
iajs-4047	3	27	clustering	cluster	VERB
iajs-4047	3	28	algorithms	algorithms	NOUN
iajs-4047	3	29	hanin	hanin	PROPN
iajs-4047	3	30	haqi	haqi	PROPN
iajs-4047	4	1	ismail1	ismail1	PROPN
iajs-4047	4	2	*	*	PUNCT
iajs-4047	4	3	,	,	PUNCT
iajs-4047	4	4	tareef	tareef	NOUN
iajs-4047	4	5	kamil	kamil	PROPN
iajs-4047	4	6	mustafa2	mustafa2	PROPN
iajs-4047	4	7	1,2	1,2	NUM
iajs-4047	4	8	department	department	NOUN
iajs-4047	4	9	of	of	ADP
iajs-4047	4	10	computer	computer	NOUN
iajs-4047	4	11	science	science	NOUN
iajs-4047	4	12	,	,	PUNCT
iajs-4047	4	13	college	college	NOUN
iajs-4047	4	14	of	of	ADP
iajs-4047	4	15	science	science	NOUN
iajs-4047	4	16	,	,	PUNCT
iajs-4047	4	17	university	university	NOUN
iajs-4047	4	18	of	of	ADP
iajs-4047	4	19	baghdad	baghdad	PROPN
iajs-4047	4	20	,	,	PUNCT
iajs-4047	4	21	baghdad	baghdad	PROPN
iajs-4047	4	22	,	,	PUNCT
iajs-4047	4	23	iraq	iraq	PROPN
iajs-4047	4	24	.	.	PUNCT
iajs-4047	5	1	*	*	PUNCT
iajs-4047	5	2	corresponding	correspond	VERB
iajs-4047	5	3	author	author	NOUN
iajs-4047	5	4	.	.	PUNCT
iajs-4047	6	1	received	receive	VERB
iajs-4047	6	2	:	:	PUNCT
iajs-4047	6	3	13	13	NUM
iajs-4047	6	4	november	november	PROPN
iajs-4047	6	5	2024	2024	NUM
iajs-4047	6	6	accepted	accept	VERB
iajs-4047	6	7	:	:	PUNCT
iajs-4047	6	8	4	4	NUM
iajs-4047	6	9	february	february	NOUN
iajs-4047	6	10	2025	2025	NUM
iajs-4047	6	11	published	publish	VERB
iajs-4047	6	12	:	:	PUNCT
iajs-4047	6	13	20	20	NUM
iajs-4047	6	14	april	april	PROPN
iajs-4047	6	15	2025	2025	NUM
iajs-4047	6	16	doi.org/10.30526/38.2.4047	doi.org/10.30526/38.2.4047	NOUN
iajs-4047	6	17	abstract	abstract	ADJ
iajs-4047	6	18	the	the	DET
iajs-4047	6	19	problem	problem	NOUN
iajs-4047	6	20	of	of	ADP
iajs-4047	6	21	estimating	estimate	VERB
iajs-4047	6	22	the	the	DET
iajs-4047	6	23	number	number	NOUN
iajs-4047	6	24	of	of	ADP
iajs-4047	6	25	clusters	cluster	NOUN
iajs-4047	6	26	,	,	PUNCT
iajs-4047	6	27	k	k	PROPN
iajs-4047	6	28	,	,	PUNCT
iajs-4047	6	29	is	be	AUX
iajs-4047	6	30	considered	consider	VERB
iajs-4047	6	31	one	one	NUM
iajs-4047	6	32	of	of	ADP
iajs-4047	6	33	the	the	DET
iajs-4047	6	34	major	major	ADJ
iajs-4047	6	35	challenges	challenge	NOUN
iajs-4047	6	36	for	for	ADP
iajs-4047	6	37	partition	partition	NOUN
iajs-4047	6	38	clustering	clustering	NOUN
iajs-4047	6	39	.	.	PUNCT
iajs-4047	7	1	the	the	DET
iajs-4047	7	2	k	k	NOUN
iajs-4047	7	3	-	-	PUNCT
iajs-4047	7	4	means	means	NOUN
iajs-4047	7	5	algorithm	algorithm	NOUN
iajs-4047	7	6	is	be	AUX
iajs-4047	7	7	a	a	DET
iajs-4047	7	8	division	division	NOUN
iajs-4047	7	9	-	-	PUNCT
iajs-4047	7	10	based	base	VERB
iajs-4047	7	11	clustering	clustering	ADJ
iajs-4047	7	12	method	method	NOUN
iajs-4047	7	13	where	where	SCONJ
iajs-4047	7	14	only	only	ADJ
iajs-4047	7	15	objects	object	NOUN
iajs-4047	7	16	are	be	AUX
iajs-4047	7	17	entered	enter	VERB
iajs-4047	7	18	into	into	ADP
iajs-4047	7	19	a	a	DET
iajs-4047	7	20	set	set	NOUN
iajs-4047	7	21	of	of	ADP
iajs-4047	7	22	k	k	NOUN
iajs-4047	7	23	,	,	PUNCT
iajs-4047	7	24	and	and	CCONJ
iajs-4047	7	25	the	the	DET
iajs-4047	7	26	algorithm	algorithm	NOUN
iajs-4047	7	27	decides	decide	VERB
iajs-4047	7	28	the	the	DET
iajs-4047	7	29	number	number	NOUN
iajs-4047	7	30	group	group	NOUN
iajs-4047	7	31	initially	initially	ADV
iajs-4047	7	32	.	.	PUNCT
iajs-4047	8	1	still	still	ADV
iajs-4047	8	2	there	there	PRON
iajs-4047	8	3	is	be	VERB
iajs-4047	8	4	no	no	DET
iajs-4047	8	5	specific	specific	ADJ
iajs-4047	8	6	way	way	NOUN
iajs-4047	8	7	to	to	PART
iajs-4047	8	8	estimate	estimate	VERB
iajs-4047	8	9	the	the	DET
iajs-4047	8	10	best	good	ADJ
iajs-4047	8	11	number	number	NOUN
iajs-4047	8	12	for	for	ADP
iajs-4047	8	13	the	the	DET
iajs-4047	8	14	cluster	cluster	NOUN
iajs-4047	8	15	.	.	PUNCT
iajs-4047	9	1	the	the	DET
iajs-4047	9	2	outcome	outcome	NOUN
iajs-4047	9	3	of	of	ADP
iajs-4047	9	4	the	the	DET
iajs-4047	9	5	clustering	cluster	VERB
iajs-4047	9	6	process	process	NOUN
iajs-4047	9	7	can	can	AUX
iajs-4047	9	8	be	be	AUX
iajs-4047	9	9	better	well	ADJ
iajs-4047	9	10	after	after	ADP
iajs-4047	9	11	being	be	AUX
iajs-4047	9	12	performed	perform	VERB
iajs-4047	9	13	in	in	ADP
iajs-4047	9	14	more	more	ADJ
iajs-4047	9	15	than	than	ADP
iajs-4047	9	16	one	one	NUM
iajs-4047	9	17	attempt	attempt	NOUN
iajs-4047	9	18	.	.	PUNCT
iajs-4047	10	1	therefore	therefore	ADV
iajs-4047	10	2	,	,	PUNCT
iajs-4047	10	3	the	the	DET
iajs-4047	10	4	optimal	optimal	ADJ
iajs-4047	10	5	count	count	NOUN
iajs-4047	10	6	of	of	ADP
iajs-4047	10	7	iterations	iteration	NOUN
iajs-4047	10	8	can	can	AUX
iajs-4047	10	9	be	be	AUX
iajs-4047	10	10	identified	identify	VERB
iajs-4047	10	11	through	through	ADP
iajs-4047	10	12	a	a	DET
iajs-4047	10	13	steady	steady	ADJ
iajs-4047	10	14	method	method	NOUN
iajs-4047	10	15	in	in	ADP
iajs-4047	10	16	advance	advance	NOUN
iajs-4047	10	17	that	that	PRON
iajs-4047	10	18	can	can	AUX
iajs-4047	10	19	determine	determine	VERB
iajs-4047	10	20	the	the	DET
iajs-4047	10	21	time	time	NOUN
iajs-4047	10	22	and	and	CCONJ
iajs-4047	10	23	number	number	NOUN
iajs-4047	10	24	of	of	ADP
iajs-4047	10	25	rounds	round	NOUN
iajs-4047	10	26	.	.	PUNCT
iajs-4047	11	1	so	so	ADV
iajs-4047	11	2	,	,	PUNCT
iajs-4047	11	3	the	the	DET
iajs-4047	11	4	problem	problem	NOUN
iajs-4047	11	5	is	be	AUX
iajs-4047	11	6	finding	find	VERB
iajs-4047	11	7	the	the	DET
iajs-4047	11	8	optimal	optimal	ADJ
iajs-4047	11	9	number	number	NOUN
iajs-4047	11	10	(	(	PUNCT
iajs-4047	11	11	k	k	NOUN
iajs-4047	11	12	)	)	PUNCT
iajs-4047	11	13	in	in	ADP
iajs-4047	11	14	an	an	DET
iajs-4047	11	15	easy	easy	ADJ
iajs-4047	11	16	and	and	CCONJ
iajs-4047	11	17	fast	fast	ADJ
iajs-4047	11	18	way	way	NOUN
iajs-4047	11	19	.	.	PUNCT
iajs-4047	12	1	the	the	DET
iajs-4047	12	2	aim	aim	NOUN
iajs-4047	12	3	of	of	ADP
iajs-4047	12	4	this	this	DET
iajs-4047	12	5	paper	paper	NOUN
iajs-4047	12	6	is	be	AUX
iajs-4047	12	7	to	to	PART
iajs-4047	12	8	use	use	VERB
iajs-4047	12	9	a	a	DET
iajs-4047	12	10	genetic	genetic	ADJ
iajs-4047	12	11	algorithm	algorithm	NOUN
iajs-4047	12	12	(	(	PUNCT
iajs-4047	12	13	ga	ga	PROPN
iajs-4047	12	14	)	)	PUNCT
iajs-4047	12	15	with	with	ADP
iajs-4047	12	16	a	a	DET
iajs-4047	12	17	new	new	ADJ
iajs-4047	12	18	objective	objective	ADJ
iajs-4047	12	19	function	function	NOUN
iajs-4047	12	20	to	to	PART
iajs-4047	12	21	determine	determine	VERB
iajs-4047	12	22	the	the	DET
iajs-4047	12	23	best	good	ADJ
iajs-4047	12	24	number	number	NOUN
iajs-4047	12	25	of	of	ADP
iajs-4047	12	26	clusters	cluster	NOUN
iajs-4047	12	27	of	of	ADP
iajs-4047	12	28	different	different	ADJ
iajs-4047	12	29	types	type	NOUN
iajs-4047	12	30	of	of	ADP
iajs-4047	12	31	datasets	dataset	NOUN
iajs-4047	12	32	.	.	PUNCT
iajs-4047	13	1	the	the	DET
iajs-4047	13	2	fitness	fitness	NOUN
iajs-4047	13	3	function	function	NOUN
iajs-4047	13	4	optimizes	optimize	VERB
iajs-4047	13	5	the	the	DET
iajs-4047	13	6	heterogeneity	heterogeneity	NOUN
iajs-4047	13	7	among	among	ADP
iajs-4047	13	8	clusters	cluster	NOUN
iajs-4047	13	9	and	and	CCONJ
iajs-4047	13	10	homogeneity	homogeneity	NOUN
iajs-4047	13	11	within	within	ADP
iajs-4047	13	12	each	each	DET
iajs-4047	13	13	cluster	cluster	NOUN
iajs-4047	13	14	.	.	PUNCT
iajs-4047	14	1	utilizing	utilize	VERB
iajs-4047	14	2	the	the	DET
iajs-4047	14	3	gap	gap	NOUN
iajs-4047	14	4	statistic	statistic	NOUN
iajs-4047	14	5	equation	equation	NOUN
iajs-4047	14	6	,	,	PUNCT
iajs-4047	14	7	the	the	DET
iajs-4047	14	8	optimal	optimal	ADJ
iajs-4047	14	9	number	number	NOUN
iajs-4047	14	10	of	of	ADP
iajs-4047	14	11	clusters	cluster	NOUN
iajs-4047	14	12	is	be	AUX
iajs-4047	14	13	determined	determine	VERB
iajs-4047	14	14	in	in	ADP
iajs-4047	14	15	four	four	NUM
iajs-4047	14	16	standard	standard	ADJ
iajs-4047	14	17	datasets	dataset	NOUN
iajs-4047	14	18	.	.	PUNCT
iajs-4047	15	1	keywords	keyword	NOUN
iajs-4047	15	2	:	:	PUNCT
iajs-4047	15	3	clustering	cluster	VERB
iajs-4047	15	4	,	,	PUNCT
iajs-4047	15	5	k	k	NOUN
iajs-4047	15	6	-	-	PUNCT
iajs-4047	15	7	means	means	ADJ
iajs-4047	15	8	,	,	PUNCT
iajs-4047	15	9	heuristic	heuristic	ADJ
iajs-4047	15	10	,	,	PUNCT
iajs-4047	15	11	genetic	genetic	ADJ
iajs-4047	15	12	algorithm	algorithm	NOUN
iajs-4047	15	13	,	,	PUNCT
iajs-4047	15	14	gap	gap	NOUN
iajs-4047	15	15	statistic	statistic	NOUN
iajs-4047	15	16	.	.	PUNCT
iajs-4047	16	1	1	1	X
iajs-4047	16	2	.	.	X
iajs-4047	16	3	introduction	introduction	NOUN
iajs-4047	16	4	data	datum	NOUN
iajs-4047	16	5	mining	mining	NOUN
iajs-4047	16	6	is	be	AUX
iajs-4047	16	7	a	a	DET
iajs-4047	16	8	highly	highly	ADV
iajs-4047	16	9	powerful	powerful	ADJ
iajs-4047	16	10	technique	technique	NOUN
iajs-4047	16	11	for	for	ADP
iajs-4047	16	12	retracting	retract	VERB
iajs-4047	16	13	information	information	NOUN
iajs-4047	16	14	and	and	CCONJ
iajs-4047	16	15	is	be	AUX
iajs-4047	16	16	useful	useful	ADJ
iajs-4047	16	17	for	for	ADP
iajs-4047	16	18	a	a	DET
iajs-4047	16	19	large	large	ADJ
iajs-4047	16	20	amount	amount	NOUN
iajs-4047	16	21	of	of	ADP
iajs-4047	16	22	technical	technical	ADJ
iajs-4047	16	23	and	and	CCONJ
iajs-4047	16	24	commercial	commercial	ADJ
iajs-4047	16	25	data	datum	NOUN
iajs-4047	16	26	.	.	PUNCT
iajs-4047	17	1	this	this	PRON
iajs-4047	17	2	involves	involve	VERB
iajs-4047	17	3	using	use	VERB
iajs-4047	17	4	a	a	DET
iajs-4047	17	5	certain	certain	ADJ
iajs-4047	17	6	number	number	NOUN
iajs-4047	17	7	of	of	ADP
iajs-4047	17	8	methods	method	NOUN
iajs-4047	17	9	and	and	CCONJ
iajs-4047	17	10	strategies	strategy	NOUN
iajs-4047	17	11	to	to	PART
iajs-4047	17	12	check	check	VERB
iajs-4047	17	13	the	the	DET
iajs-4047	17	14	data	datum	NOUN
iajs-4047	17	15	with	with	ADP
iajs-4047	17	16	a	a	DET
iajs-4047	17	17	specified	specified	ADJ
iajs-4047	17	18	number	number	NOUN
iajs-4047	17	19	of	of	ADP
iajs-4047	17	20	classes	class	NOUN
iajs-4047	17	21	,	,	PUNCT
iajs-4047	17	22	clusters	cluster	NOUN
iajs-4047	17	23	,	,	PUNCT
iajs-4047	17	24	and	and	CCONJ
iajs-4047	17	25	associations	association	NOUN
iajs-4047	17	26	.	.	PUNCT
iajs-4047	18	1	technology	technology	NOUN
iajs-4047	18	2	and	and	CCONJ
iajs-4047	18	3	various	various	ADJ
iajs-4047	18	4	other	other	ADJ
iajs-4047	18	5	fields	field	NOUN
iajs-4047	18	6	widely	widely	ADV
iajs-4047	18	7	use	use	VERB
iajs-4047	18	8	clustering	cluster	VERB
iajs-4047	18	9	algorithms	algorithm	NOUN
iajs-4047	18	10	in	in	ADP
iajs-4047	18	11	many	many	ADJ
iajs-4047	18	12	applications	application	NOUN
iajs-4047	18	13	.	.	PUNCT
iajs-4047	19	1	for	for	ADP
iajs-4047	19	2	example	example	NOUN
iajs-4047	19	3	,	,	PUNCT
iajs-4047	19	4	marketing	marketing	NOUN
iajs-4047	19	5	,	,	PUNCT
iajs-4047	19	6	pattern	pattern	NOUN
iajs-4047	19	7	recognition	recognition	NOUN
iajs-4047	19	8	(	(	PUNCT
iajs-4047	19	9	pr	pr	NOUN
iajs-4047	19	10	)	)	PUNCT
iajs-4047	19	11	,	,	PUNCT
iajs-4047	19	12	information	information	NOUN
iajs-4047	19	13	technology	technology	NOUN
iajs-4047	19	14	(	(	PUNCT
iajs-4047	19	15	it	it	PRON
iajs-4047	19	16	)	)	PUNCT
iajs-4047	19	17	,	,	PUNCT
iajs-4047	19	18	information	information	NOUN
iajs-4047	19	19	retrieval	retrieval	NOUN
iajs-4047	19	20	(	(	PUNCT
iajs-4047	19	21	ir	ir	NOUN
iajs-4047	19	22	)	)	PUNCT
iajs-4047	19	23	,	,	PUNCT
iajs-4047	19	24	artificial	artificial	ADJ
iajs-4047	19	25	intelligence	intelligence	NOUN
iajs-4047	19	26	(	(	PUNCT
iajs-4047	19	27	ai	ai	NOUN
iajs-4047	19	28	)	)	PUNCT
iajs-4047	19	29	,	,	PUNCT
iajs-4047	19	30	image	image	NOUN
iajs-4047	19	31	processing	processing	NOUN
iajs-4047	19	32	,	,	PUNCT
iajs-4047	19	33	psychology	psychology	NOUN
iajs-4047	19	34	,	,	PUNCT
iajs-4047	19	35	biology	biology	NOUN
iajs-4047	19	36	,	,	PUNCT
iajs-4047	19	37	and	and	CCONJ
iajs-4047	19	38	bioinformatics	bioinformatics	NOUN
iajs-4047	19	39	(	(	PUNCT
iajs-4047	19	40	gene	gene	NOUN
iajs-4047	19	41	expression	expression	NOUN
iajs-4047	19	42	analysis	analysis	NOUN
iajs-4047	19	43	)	)	PUNCT
iajs-4047	19	44	.	.	PUNCT
iajs-4047	20	1	several	several	ADJ
iajs-4047	20	2	clustering	clustering	ADJ
iajs-4047	20	3	techniques	technique	NOUN
iajs-4047	20	4	were	be	AUX
iajs-4047	20	5	proposed	propose	VERB
iajs-4047	20	6	to	to	PART
iajs-4047	20	7	work	work	VERB
iajs-4047	20	8	on	on	ADP
iajs-4047	20	9	a	a	DET
iajs-4047	20	10	range	range	NOUN
iajs-4047	20	11	of	of	ADP
iajs-4047	20	12	the	the	DET
iajs-4047	20	13	data	datum	NOUN
iajs-4047	20	14	.	.	PUNCT
iajs-4047	21	1	such	such	ADJ
iajs-4047	21	2	clustering	cluster	VERB
iajs-4047	21	3	algorithms	algorithm	NOUN
iajs-4047	21	4	could	could	AUX
iajs-4047	21	5	be	be	AUX
iajs-4047	21	6	defined	define	VERB
iajs-4047	21	7	on	on	ADP
iajs-4047	21	8	a	a	DET
iajs-4047	21	9	category	category	NOUN
iajs-4047	21	10	basis	basis	NOUN
iajs-4047	21	11	:	:	PUNCT
iajs-4047	21	12	clustering	cluster	VERB
iajs-4047	21	13	of	of	ADP
iajs-4047	21	14	portioning	portion	VERB
iajs-4047	21	15	algorithms	algorithm	NOUN
iajs-4047	21	16	,	,	PUNCT
iajs-4047	21	17	clustering	cluster	VERB
iajs-4047	21	18	of	of	ADP
iajs-4047	21	19	fuzzy	fuzzy	ADJ
iajs-4047	21	20	algorithms	algorithm	NOUN
iajs-4047	21	21	,	,	PUNCT
iajs-4047	21	22	clustering	cluster	VERB
iajs-4047	21	23	algorithms	algorithm	NOUN
iajs-4047	21	24	grid	grid	NOUN
iajs-4047	21	25	-	-	PUNCT
iajs-4047	21	26	based	base	VERB
iajs-4047	21	27	,	,	PUNCT
iajs-4047	21	28	clustering	cluster	VERB
iajs-4047	21	29	algorithms	algorithm	NOUN
iajs-4047	21	30	of	of	ADP
iajs-4047	21	31	hierarchy	hierarchy	NOUN
iajs-4047	21	32	,	,	PUNCT
iajs-4047	21	33	and	and	CCONJ
iajs-4047	21	34	clustering	cluster	VERB
iajs-4047	21	35	algorithms	algorithms	NOUN
iajs-4047	21	36	density	density	NOUN
iajs-4047	21	37	-	-	PUNCT
iajs-4047	21	38	based	base	VERB
iajs-4047	21	39	(	(	PUNCT
iajs-4047	21	40	1	1	NUM
iajs-4047	21	41	)	)	PUNCT
iajs-4047	21	42	.	.	PUNCT
iajs-4047	22	1	k	k	X
iajs-4047	22	2	-	-	PUNCT
iajs-4047	22	3	means	means	NOUN
iajs-4047	22	4	is	be	AUX
iajs-4047	22	5	one	one	NUM
iajs-4047	22	6	clustering	clustering	NOUN
iajs-4047	22	7	technique	technique	NOUN
iajs-4047	22	8	that	that	PRON
iajs-4047	22	9	may	may	AUX
iajs-4047	22	10	be	be	AUX
iajs-4047	22	11	employed	employ	VERB
iajs-4047	22	12	.	.	PUNCT
iajs-4047	23	1	clustering	clustering	NOUN
iajs-4047	23	2	falls	fall	VERB
iajs-4047	23	3	within	within	ADP
iajs-4047	23	4	the	the	DET
iajs-4047	23	5	domain	domain	NOUN
iajs-4047	23	6	of	of	ADP
iajs-4047	23	7	partitioning	partition	VERB
iajs-4047	23	8	algorithms	algorithm	NOUN
iajs-4047	23	9	.	.	PUNCT
iajs-4047	24	1	the	the	DET
iajs-4047	24	2	k	k	NOUN
iajs-4047	24	3	-	-	PUNCT
iajs-4047	24	4	means	mean	VERB
iajs-4047	24	5	clustering	cluster	VERB
iajs-4047	24	6	algorithm	algorithm	NOUN
iajs-4047	24	7	divides	divide	VERB
iajs-4047	24	8	objects	object	NOUN
iajs-4047	24	9	into	into	ADP
iajs-4047	24	10	k	k	PROPN
iajs-4047	24	11	groups	group	NOUN
iajs-4047	24	12	.	.	PUNCT
iajs-4047	25	1	to	to	PART
iajs-4047	25	2	accomplish	accomplish	VERB
iajs-4047	25	3	this	this	DET
iajs-4047	25	4	clustering	clustering	NOUN
iajs-4047	25	5	,	,	PUNCT
iajs-4047	25	6	the	the	DET
iajs-4047	25	7	value	value	NOUN
iajs-4047	25	8	of	of	ADP
iajs-4047	25	9	k	k	PROPN
iajs-4047	25	10	should	should	AUX
iajs-4047	25	11	be	be	AUX
iajs-4047	25	12	specified	specify	VERB
iajs-4047	25	13	in	in	ADP
iajs-4047	25	14	advance	advance	NOUN
iajs-4047	25	15	.	.	PUNCT
iajs-4047	26	1	the	the	DET
iajs-4047	26	2	next	next	ADJ
iajs-4047	26	3	step	step	NOUN
iajs-4047	26	4	is	be	AUX
iajs-4047	26	5	to	to	PART
iajs-4047	26	6	calculate	calculate	VERB
iajs-4047	26	7	the	the	DET
iajs-4047	26	8	cluster	cluster	NOUN
iajs-4047	26	9	centroid	centroid	NOUN
iajs-4047	26	10	about	about	ADP
iajs-4047	26	11	:	:	PUNCT
iajs-4047	26	12	blank	blank	ADJ
iajs-4047	26	13	about	about	ADP
iajs-4047	26	14	:	:	PUNCT
iajs-4047	26	15	blank	blank	PROPN
iajs-4047	26	16	https://orcid.org/0009-0003-5920-5035	https://orcid.org/0009-0003-5920-5035	PROPN
iajs-4047	26	17	mailto:haninhaqi25@hahoo.com	mailto:haninhaqi25@hahoo.com	PROPN
iajs-4047	26	18	https://orcid.org/0000-0001-6291-5976	https://orcid.org/0000-0001-6291-5976	PROPN
iajs-4047	26	19	mailto:tareef.mustafa@sc.uobaghdad.edu.iq	mailto:tareef.mustafa@sc.uobaghdad.edu.iq	NOUN
iajs-4047	26	20	ihjpas	ihjpas	PROPN
iajs-4047	26	21	.	.	PUNCT
iajs-4047	27	1	2025	2025	NUM
iajs-4047	27	2	,	,	PUNCT
iajs-4047	27	3	38	38	NUM
iajs-4047	27	4	(	(	PUNCT
iajs-4047	27	5	2	2	NUM
iajs-4047	27	6	)	)	PUNCT
iajs-4047	27	7	426	426	NUM
iajs-4047	27	8	(	(	PUNCT
iajs-4047	27	9	2	2	NUM
iajs-4047	27	10	-	-	SYM
iajs-4047	27	11	4	4	NUM
iajs-4047	27	12	)	)	PUNCT
iajs-4047	27	13	.	.	PUNCT
iajs-4047	28	1	among	among	ADP
iajs-4047	28	2	the	the	DET
iajs-4047	28	3	several	several	ADJ
iajs-4047	28	4	broad	broad	ADJ
iajs-4047	28	5	clustering	clustering	ADJ
iajs-4047	28	6	methods	method	NOUN
iajs-4047	28	7	,	,	PUNCT
iajs-4047	28	8	k	k	NOUN
iajs-4047	28	9	-	-	PUNCT
iajs-4047	28	10	means	means	NOUN
iajs-4047	28	11	is	be	AUX
iajs-4047	28	12	perhaps	perhaps	ADV
iajs-4047	28	13	the	the	DET
iajs-4047	28	14	best	well	ADV
iajs-4047	28	15	used	use	VERB
iajs-4047	28	16	.	.	PUNCT
iajs-4047	29	1	it	it	PRON
iajs-4047	29	2	still	still	ADV
iajs-4047	29	3	,	,	PUNCT
iajs-4047	29	4	however	however	ADV
iajs-4047	29	5	,	,	PUNCT
iajs-4047	29	6	has	have	VERB
iajs-4047	29	7	certain	certain	ADJ
iajs-4047	29	8	intrinsic	intrinsic	ADJ
iajs-4047	29	9	limitations	limitation	NOUN
iajs-4047	29	10	.	.	PUNCT
iajs-4047	30	1	one	one	NUM
iajs-4047	30	2	of	of	ADP
iajs-4047	30	3	the	the	DET
iajs-4047	30	4	most	most	ADV
iajs-4047	30	5	difficult	difficult	ADJ
iajs-4047	30	6	issues	issue	NOUN
iajs-4047	30	7	when	when	SCONJ
iajs-4047	30	8	utilizing	utilize	VERB
iajs-4047	30	9	k	k	NOUN
iajs-4047	30	10	-	-	PUNCT
iajs-4047	30	11	means	means	PROPN
iajs-4047	30	12	is	be	AUX
iajs-4047	30	13	identifying	identify	VERB
iajs-4047	30	14	the	the	DET
iajs-4047	30	15	best	good	ADJ
iajs-4047	30	16	cluster	cluster	NOUN
iajs-4047	30	17	number	number	NOUN
iajs-4047	30	18	symbolized	symbolize	VERB
iajs-4047	30	19	by	by	ADP
iajs-4047	30	20	k	k	PROPN
iajs-4047	30	21	(	(	PUNCT
iajs-4047	30	22	5	5	NUM
iajs-4047	30	23	)	)	PUNCT
iajs-4047	30	24	,	,	PUNCT
iajs-4047	30	25	where	where	SCONJ
iajs-4047	30	26	k	k	PROPN
iajs-4047	30	27	represents	represent	VERB
iajs-4047	30	28	a	a	DET
iajs-4047	30	29	positive	positive	ADJ
iajs-4047	30	30	integer	integer	NOUN
iajs-4047	30	31	.	.	PUNCT
iajs-4047	31	1	however	however	ADV
iajs-4047	31	2	,	,	PUNCT
iajs-4047	31	3	k	k	X
iajs-4047	31	4	-	-	PUNCT
iajs-4047	31	5	means	means	NOUN
iajs-4047	31	6	has	have	VERB
iajs-4047	31	7	a	a	DET
iajs-4047	31	8	significant	significant	ADJ
iajs-4047	31	9	drawback	drawback	NOUN
iajs-4047	31	10	:	:	PUNCT
iajs-4047	31	11	it	it	PRON
iajs-4047	31	12	frequently	frequently	ADV
iajs-4047	31	13	converges	converge	VERB
iajs-4047	31	14	to	to	ADP
iajs-4047	31	15	a	a	DET
iajs-4047	31	16	suboptimal	suboptimal	ADJ
iajs-4047	31	17	solution	solution	NOUN
iajs-4047	31	18	due	due	ADP
iajs-4047	31	19	to	to	ADP
iajs-4047	31	20	the	the	DET
iajs-4047	31	21	huge	huge	ADJ
iajs-4047	31	22	clustering	clustering	ADJ
iajs-4047	31	23	search	search	NOUN
iajs-4047	31	24	space	space	NOUN
iajs-4047	31	25	.	.	PUNCT
iajs-4047	32	1	thus	thus	ADV
iajs-4047	32	2	,	,	PUNCT
iajs-4047	32	3	evolutionary	evolutionary	ADJ
iajs-4047	32	4	methods	method	NOUN
iajs-4047	32	5	such	such	ADJ
iajs-4047	32	6	as	as	ADP
iajs-4047	32	7	the	the	DET
iajs-4047	32	8	genetic	genetic	ADJ
iajs-4047	32	9	algorithm	algorithm	NOUN
iajs-4047	32	10	are	be	AUX
iajs-4047	32	11	appropriate	appropriate	ADJ
iajs-4047	32	12	for	for	ADP
iajs-4047	32	13	grouping	group	VERB
iajs-4047	32	14	tasks	task	NOUN
iajs-4047	32	15	.	.	PUNCT
iajs-4047	33	1	a	a	DET
iajs-4047	33	2	good	good	ADJ
iajs-4047	33	3	ga	ga	PROPN
iajs-4047	33	4	examines	examine	VERB
iajs-4047	33	5	the	the	DET
iajs-4047	33	6	search	search	NOUN
iajs-4047	33	7	space	space	NOUN
iajs-4047	33	8	appropriately	appropriately	ADV
iajs-4047	33	9	while	while	SCONJ
iajs-4047	33	10	also	also	ADV
iajs-4047	33	11	using	use	VERB
iajs-4047	33	12	superior	superior	ADJ
iajs-4047	33	13	solutions	solution	NOUN
iajs-4047	33	14	to	to	PART
iajs-4047	33	15	obtain	obtain	VERB
iajs-4047	33	16	the	the	DET
iajs-4047	33	17	globally	globally	ADV
iajs-4047	33	18	optimum	optimum	ADJ
iajs-4047	33	19	solution	solution	NOUN
iajs-4047	33	20	(	(	PUNCT
iajs-4047	33	21	6	6	NUM
iajs-4047	33	22	)	)	PUNCT
iajs-4047	33	23	.	.	PUNCT
iajs-4047	34	1	a	a	DET
iajs-4047	34	2	typical	typical	ADJ
iajs-4047	34	3	explanation	explanation	NOUN
iajs-4047	34	4	of	of	ADP
iajs-4047	34	5	the	the	DET
iajs-4047	34	6	clustering	clustering	ADJ
iajs-4047	34	7	aim	aim	NOUN
iajs-4047	34	8	is	be	AUX
iajs-4047	34	9	to	to	PART
iajs-4047	34	10	maintain	maintain	VERB
iajs-4047	34	11	homogeneity	homogeneity	NOUN
iajs-4047	34	12	within	within	ADP
iajs-4047	34	13	each	each	DET
iajs-4047	34	14	cluster	cluster	NOUN
iajs-4047	34	15	while	while	SCONJ
iajs-4047	34	16	increasing	increase	VERB
iajs-4047	34	17	variability	variability	NOUN
iajs-4047	34	18	between	between	ADP
iajs-4047	34	19	clusters	cluster	NOUN
iajs-4047	34	20	.	.	PUNCT
iajs-4047	35	1	the	the	DET
iajs-4047	35	2	ga	ga	PROPN
iajs-4047	35	3	method	method	NOUN
iajs-4047	35	4	will	will	AUX
iajs-4047	35	5	stop	stop	VERB
iajs-4047	35	6	the	the	DET
iajs-4047	35	7	maximum	maximum	ADJ
iajs-4047	35	8	number	number	NOUN
iajs-4047	35	9	of	of	ADP
iajs-4047	35	10	generations	generation	NOUN
iajs-4047	35	11	is	be	AUX
iajs-4047	35	12	created	create	VERB
iajs-4047	35	13	or	or	CCONJ
iajs-4047	35	14	when	when	SCONJ
iajs-4047	35	15	the	the	DET
iajs-4047	35	16	maximum	maximum	ADJ
iajs-4047	35	17	number	number	NOUN
iajs-4047	35	18	of	of	ADP
iajs-4047	35	19	objective	objective	ADJ
iajs-4047	35	20	function	function	NOUN
iajs-4047	35	21	evaluations	evaluation	NOUN
iajs-4047	35	22	is	be	AUX
iajs-4047	35	23	reached	reach	VERB
iajs-4047	35	24	.	.	PUNCT
iajs-4047	36	1	this	this	DET
iajs-4047	36	2	paper	paper	NOUN
iajs-4047	36	3	suggests	suggest	VERB
iajs-4047	36	4	a	a	DET
iajs-4047	36	5	new	new	ADJ
iajs-4047	36	6	objective	objective	ADJ
iajs-4047	36	7	method	method	NOUN
iajs-4047	36	8	to	to	PART
iajs-4047	36	9	find	find	VERB
iajs-4047	36	10	the	the	DET
iajs-4047	36	11	optimal	optimal	ADJ
iajs-4047	36	12	number	number	NOUN
iajs-4047	36	13	of	of	ADP
iajs-4047	36	14	clusters	cluster	NOUN
iajs-4047	36	15	using	use	VERB
iajs-4047	36	16	a	a	DET
iajs-4047	36	17	genetic	genetic	ADJ
iajs-4047	36	18	algorithm	algorithm	NOUN
iajs-4047	36	19	(	(	PUNCT
iajs-4047	36	20	ga	ga	NOUN
iajs-4047	36	21	)	)	PUNCT
iajs-4047	36	22	and	and	CCONJ
iajs-4047	36	23	solve	solve	VERB
iajs-4047	36	24	the	the	DET
iajs-4047	36	25	problem	problem	NOUN
iajs-4047	36	26	of	of	ADP
iajs-4047	36	27	many	many	ADJ
iajs-4047	36	28	traditional	traditional	ADJ
iajs-4047	36	29	methods	method	NOUN
iajs-4047	36	30	used	use	VERB
iajs-4047	36	31	to	to	PART
iajs-4047	36	32	find	find	VERB
iajs-4047	36	33	the	the	DET
iajs-4047	36	34	best	good	ADJ
iajs-4047	36	35	k	k	NOUN
iajs-4047	36	36	,	,	PUNCT
iajs-4047	36	37	as	as	SCONJ
iajs-4047	36	38	each	each	DET
iajs-4047	36	39	method	method	NOUN
iajs-4047	36	40	gives	give	VERB
iajs-4047	36	41	different	different	ADJ
iajs-4047	36	42	results	result	NOUN
iajs-4047	36	43	from	from	ADP
iajs-4047	36	44	those	those	PRON
iajs-4047	36	45	applied	apply	VERB
iajs-4047	36	46	to	to	ADP
iajs-4047	36	47	the	the	DET
iajs-4047	36	48	same	same	ADJ
iajs-4047	36	49	dataset	dataset	NOUN
iajs-4047	36	50	.	.	PUNCT
iajs-4047	37	1	1.1	1.1	NUM
iajs-4047	37	2	.	.	PUNCT
iajs-4047	38	1	literature	literature	NOUN
iajs-4047	38	2	review	review	VERB
iajs-4047	38	3	there	there	PRON
iajs-4047	38	4	is	be	VERB
iajs-4047	38	5	no	no	DET
iajs-4047	38	6	specific	specific	ADJ
iajs-4047	38	7	rule	rule	NOUN
iajs-4047	38	8	for	for	ADP
iajs-4047	38	9	determining	determine	VERB
iajs-4047	38	10	the	the	DET
iajs-4047	38	11	appropriate	appropriate	ADJ
iajs-4047	38	12	cluster	cluster	NOUN
iajs-4047	38	13	number	number	NOUN
iajs-4047	38	14	.	.	PUNCT
iajs-4047	39	1	due	due	ADP
iajs-4047	39	2	to	to	ADP
iajs-4047	39	3	these	these	DET
iajs-4047	39	4	limitations	limitation	NOUN
iajs-4047	39	5	,	,	PUNCT
iajs-4047	39	6	the	the	DET
iajs-4047	39	7	researchers	researcher	NOUN
iajs-4047	39	8	used	use	VERB
iajs-4047	39	9	the	the	DET
iajs-4047	39	10	evolutionary	evolutionary	ADJ
iajs-4047	39	11	methods	method	NOUN
iajs-4047	39	12	to	to	PART
iajs-4047	39	13	solve	solve	VERB
iajs-4047	39	14	the	the	DET
iajs-4047	39	15	clustering	clustering	ADJ
iajs-4047	39	16	problem	problem	NOUN
iajs-4047	39	17	,	,	PUNCT
iajs-4047	39	18	as	as	SCONJ
iajs-4047	39	19	follows	follow	VERB
iajs-4047	39	20	:	:	PUNCT
iajs-4047	39	21	elshorbagy	elshorbagy	NOUN
iajs-4047	39	22	et	et	PROPN
iajs-4047	39	23	al	al	PROPN
iajs-4047	39	24	.	.	PROPN
iajs-4047	40	1	(	(	PUNCT
iajs-4047	40	2	7	7	NUM
iajs-4047	40	3	)	)	PUNCT
iajs-4047	40	4	,	,	PUNCT
iajs-4047	40	5	research	research	NOUN
iajs-4047	40	6	on	on	ADP
iajs-4047	40	7	combining	combine	VERB
iajs-4047	40	8	k	k	NOUN
iajs-4047	40	9	-	-	PUNCT
iajs-4047	40	10	means	means	NOUN
iajs-4047	40	11	with	with	ADP
iajs-4047	40	12	the	the	DET
iajs-4047	40	13	genetic	genetic	ADJ
iajs-4047	40	14	method	method	NOUN
iajs-4047	40	15	has	have	AUX
iajs-4047	40	16	executed	execute	VERB
iajs-4047	40	17	clustering	clustering	NOUN
iajs-4047	40	18	using	use	VERB
iajs-4047	40	19	this	this	DET
iajs-4047	40	20	combined	combine	VERB
iajs-4047	40	21	technique	technique	NOUN
iajs-4047	40	22	.	.	PUNCT
iajs-4047	41	1	it	it	PRON
iajs-4047	41	2	was	be	AUX
iajs-4047	41	3	discovered	discover	VERB
iajs-4047	41	4	that	that	SCONJ
iajs-4047	41	5	genetic	genetic	ADJ
iajs-4047	41	6	algorithms	algorithm	NOUN
iajs-4047	41	7	have	have	VERB
iajs-4047	41	8	the	the	DET
iajs-4047	41	9	potential	potential	NOUN
iajs-4047	41	10	to	to	PART
iajs-4047	41	11	split	split	VERB
iajs-4047	41	12	datasets	dataset	NOUN
iajs-4047	41	13	into	into	ADP
iajs-4047	41	14	a	a	DET
iajs-4047	41	15	variety	variety	NOUN
iajs-4047	41	16	of	of	ADP
iajs-4047	41	17	groups	group	NOUN
iajs-4047	41	18	that	that	PRON
iajs-4047	41	19	were	be	AUX
iajs-4047	41	20	not	not	PART
iajs-4047	41	21	recognized	recognize	VERB
iajs-4047	41	22	previously	previously	ADV
iajs-4047	41	23	.	.	PUNCT
iajs-4047	42	1	by	by	ADP
iajs-4047	42	2	using	use	VERB
iajs-4047	42	3	label	label	NOUN
iajs-4047	42	4	-	-	PUNCT
iajs-4047	42	5	based	base	VERB
iajs-4047	42	6	representation	representation	NOUN
iajs-4047	42	7	and	and	CCONJ
iajs-4047	42	8	k	k	ADJ
iajs-4047	42	9	-	-	PUNCT
iajs-4047	42	10	means	mean	NOUN
iajs-4047	42	11	methods	method	NOUN
iajs-4047	42	12	,	,	PUNCT
iajs-4047	42	13	which	which	PRON
iajs-4047	42	14	will	will	AUX
iajs-4047	42	15	enhance	enhance	VERB
iajs-4047	42	16	the	the	DET
iajs-4047	42	17	offspring	offspring	NOUN
iajs-4047	42	18	generated	generate	VERB
iajs-4047	42	19	by	by	ADP
iajs-4047	42	20	cluster	cluster	NOUN
iajs-4047	42	21	-	-	PUNCT
iajs-4047	42	22	based	base	VERB
iajs-4047	42	23	crossover	crossover	NOUN
iajs-4047	42	24	,	,	PUNCT
iajs-4047	42	25	there	there	PRON
iajs-4047	42	26	will	will	AUX
iajs-4047	42	27	be	be	AUX
iajs-4047	42	28	no	no	DET
iajs-4047	42	29	need	need	NOUN
iajs-4047	42	30	to	to	PART
iajs-4047	42	31	set	set	VERB
iajs-4047	42	32	the	the	DET
iajs-4047	42	33	number	number	NOUN
iajs-4047	42	34	of	of	ADP
iajs-4047	42	35	clusters	cluster	NOUN
iajs-4047	42	36	.	.	PUNCT
iajs-4047	43	1	the	the	DET
iajs-4047	43	2	clustering	cluster	VERB
iajs-4047	43	3	process	process	NOUN
iajs-4047	43	4	is	be	AUX
iajs-4047	43	5	employed	employ	VERB
iajs-4047	43	6	to	to	PART
iajs-4047	43	7	get	get	VERB
iajs-4047	43	8	the	the	DET
iajs-4047	43	9	central	central	ADJ
iajs-4047	43	10	point	point	NOUN
iajs-4047	43	11	,	,	PUNCT
iajs-4047	43	12	which	which	PRON
iajs-4047	43	13	decreases	decrease	VERB
iajs-4047	43	14	the	the	DET
iajs-4047	43	15	complexity	complexity	NOUN
iajs-4047	43	16	of	of	ADP
iajs-4047	43	17	the	the	DET
iajs-4047	43	18	problem	problem	NOUN
iajs-4047	43	19	.	.	PUNCT
iajs-4047	44	1	a	a	DET
iajs-4047	44	2	large	large	ADJ
iajs-4047	44	3	-	-	PUNCT
iajs-4047	44	4	scale	scale	NOUN
iajs-4047	44	5	problem	problem	NOUN
iajs-4047	44	6	is	be	AUX
iajs-4047	44	7	divided	divide	VERB
iajs-4047	44	8	into	into	ADP
iajs-4047	44	9	multiple	multiple	ADJ
iajs-4047	44	10	minor	minor	ADJ
iajs-4047	44	11	issues	issue	NOUN
iajs-4047	44	12	,	,	PUNCT
iajs-4047	44	13	so	so	SCONJ
iajs-4047	44	14	these	these	DET
iajs-4047	44	15	methods	method	NOUN
iajs-4047	44	16	represent	represent	VERB
iajs-4047	44	17	that	that	SCONJ
iajs-4047	44	18	ga	ga	PROPN
iajs-4047	44	19	is	be	AUX
iajs-4047	44	20	good	good	ADJ
iajs-4047	44	21	for	for	ADP
iajs-4047	44	22	subproblems	subproblem	NOUN
iajs-4047	44	23	to	to	PART
iajs-4047	44	24	increase	increase	VERB
iajs-4047	44	25	speed	speed	NOUN
iajs-4047	44	26	and	and	CCONJ
iajs-4047	44	27	performance	performance	NOUN
iajs-4047	44	28	while	while	SCONJ
iajs-4047	44	29	handling	handle	VERB
iajs-4047	44	30	tiny	tiny	ADJ
iajs-4047	44	31	-	-	PUNCT
iajs-4047	44	32	scale	scale	NOUN
iajs-4047	44	33	combinatorial	combinatorial	ADJ
iajs-4047	44	34	optimization	optimization	NOUN
iajs-4047	44	35	.	.	PUNCT
iajs-4047	45	1	some	some	PRON
iajs-4047	45	2	of	of	ADP
iajs-4047	45	3	the	the	DET
iajs-4047	45	4	proposed	propose	VERB
iajs-4047	45	5	techniques	technique	NOUN
iajs-4047	45	6	work	work	VERB
iajs-4047	45	7	more	more	ADV
iajs-4047	45	8	effectively	effectively	ADV
iajs-4047	45	9	and	and	CCONJ
iajs-4047	45	10	efficiently	efficiently	ADV
iajs-4047	45	11	in	in	ADP
iajs-4047	45	12	terms	term	NOUN
iajs-4047	45	13	of	of	ADP
iajs-4047	45	14	complexity	complexity	NOUN
iajs-4047	45	15	and	and	CCONJ
iajs-4047	45	16	converge	converge	VERB
iajs-4047	45	17	to	to	ADP
iajs-4047	45	18	the	the	DET
iajs-4047	45	19	global	global	ADJ
iajs-4047	45	20	optimum	optimum	NOUN
iajs-4047	45	21	.	.	PUNCT
iajs-4047	46	1	in	in	ADP
iajs-4047	46	2	hruschka	hruschka	PROPN
iajs-4047	46	3	,	,	PUNCT
iajs-4047	46	4	e.r	e.r	PROPN
iajs-4047	46	5	.	.	PROPN
iajs-4047	46	6	and	and	CCONJ
iajs-4047	46	7	ebecken	ebecken	VERB
iajs-4047	46	8	,	,	PUNCT
iajs-4047	46	9	n.f	n.f	PROPN
iajs-4047	46	10	.	.	PROPN
iajs-4047	46	11	(	(	PUNCT
iajs-4047	46	12	8)	8)	NUM
iajs-4047	46	13	,	,	PUNCT
iajs-4047	46	14	the	the	DET
iajs-4047	46	15	study	study	NOUN
iajs-4047	46	16	provided	provide	VERB
iajs-4047	46	17	a	a	DET
iajs-4047	46	18	way	way	NOUN
iajs-4047	46	19	to	to	PART
iajs-4047	46	20	find	find	VERB
iajs-4047	46	21	the	the	DET
iajs-4047	46	22	ideal	ideal	ADJ
iajs-4047	46	23	number	number	NOUN
iajs-4047	46	24	for	for	ADP
iajs-4047	46	25	clustering	cluster	VERB
iajs-4047	46	26	a	a	DET
iajs-4047	46	27	dataset	dataset	NOUN
iajs-4047	46	28	.	.	PUNCT
iajs-4047	47	1	it	it	PRON
iajs-4047	47	2	created	create	VERB
iajs-4047	47	3	a	a	DET
iajs-4047	47	4	genetic	genetic	ADJ
iajs-4047	47	5	algorithm	algorithm	NOUN
iajs-4047	47	6	to	to	PART
iajs-4047	47	7	perform	perform	VERB
iajs-4047	47	8	this	this	DET
iajs-4047	47	9	task	task	NOUN
iajs-4047	47	10	.	.	PUNCT
iajs-4047	48	1	a	a	DET
iajs-4047	48	2	simple	simple	ADJ
iajs-4047	48	3	encoding	encoding	NOUN
iajs-4047	48	4	approach	approach	NOUN
iajs-4047	48	5	that	that	PRON
iajs-4047	48	6	results	result	VERB
iajs-4047	48	7	in	in	ADP
iajs-4047	48	8	constant	constant	ADJ
iajs-4047	48	9	-	-	PUNCT
iajs-4047	48	10	length	length	NOUN
iajs-4047	48	11	chromosomes	chromosome	NOUN
iajs-4047	48	12	is	be	AUX
iajs-4047	48	13	utilized	utilize	VERB
iajs-4047	48	14	.	.	PUNCT
iajs-4047	49	1	the	the	DET
iajs-4047	49	2	homogeneity	homogeneity	NOUN
iajs-4047	49	3	between	between	ADP
iajs-4047	49	4	and	and	CCONJ
iajs-4047	49	5	within	within	ADP
iajs-4047	49	6	each	each	DET
iajs-4047	49	7	cluster	cluster	NOUN
iajs-4047	49	8	is	be	AUX
iajs-4047	49	9	optimized	optimize	VERB
iajs-4047	49	10	by	by	ADP
iajs-4047	49	11	the	the	DET
iajs-4047	49	12	objective	objective	ADJ
iajs-4047	49	13	method	method	NOUN
iajs-4047	49	14	.	.	PUNCT
iajs-4047	50	1	besides	besides	SCONJ
iajs-4047	50	2	,	,	PUNCT
iajs-4047	50	3	the	the	DET
iajs-4047	50	4	clustering	clustering	ADJ
iajs-4047	50	5	genetic	genetic	ADJ
iajs-4047	50	6	algorithm	algorithm	NOUN
iajs-4047	50	7	also	also	ADV
iajs-4047	50	8	determines	determine	VERB
iajs-4047	50	9	the	the	DET
iajs-4047	50	10	appropriate	appropriate	ADJ
iajs-4047	50	11	group	group	NOUN
iajs-4047	50	12	number	number	NOUN
iajs-4047	50	13	based	base	VERB
iajs-4047	50	14	on	on	ADP
iajs-4047	50	15	the	the	DET
iajs-4047	50	16	average	average	ADJ
iajs-4047	50	17	silhouette	silhouette	NOUN
iajs-4047	50	18	width	width	NOUN
iajs-4047	50	19	requirement	requirement	NOUN
iajs-4047	50	20	.	.	PUNCT
iajs-4047	51	1	it	it	PRON
iajs-4047	51	2	also	also	ADV
iajs-4047	51	3	created	create	VERB
iajs-4047	51	4	genetic	genetic	ADJ
iajs-4047	51	5	operators	operator	NOUN
iajs-4047	51	6	that	that	PRON
iajs-4047	51	7	are	be	AUX
iajs-4047	51	8	context	context	NOUN
iajs-4047	51	9	-	-	PUNCT
iajs-4047	51	10	sensitive	sensitive	ADJ
iajs-4047	51	11	.	.	PUNCT
iajs-4047	52	1	four	four	NUM
iajs-4047	52	2	examples	example	NOUN
iajs-4047	52	3	are	be	AUX
iajs-4047	52	4	supplied	supply	VERB
iajs-4047	52	5	to	to	PART
iajs-4047	52	6	show	show	VERB
iajs-4047	52	7	the	the	DET
iajs-4047	52	8	effectiveness	effectiveness	NOUN
iajs-4047	52	9	of	of	ADP
iajs-4047	52	10	the	the	DET
iajs-4047	52	11	suggested	suggest	VERB
iajs-4047	52	12	strategy	strategy	NOUN
iajs-4047	52	13	.	.	PUNCT
iajs-4047	53	1	the	the	DET
iajs-4047	53	2	efficacy	efficacy	NOUN
iajs-4047	53	3	of	of	ADP
iajs-4047	53	4	the	the	DET
iajs-4047	53	5	suggested	suggest	VERB
iajs-4047	53	6	method	method	NOUN
iajs-4047	53	7	is	be	AUX
iajs-4047	53	8	illustrated	illustrate	VERB
iajs-4047	53	9	by	by	ADP
iajs-4047	53	10	presenting	present	VERB
iajs-4047	53	11	the	the	DET
iajs-4047	53	12	results	result	NOUN
iajs-4047	53	13	obtained	obtain	VERB
iajs-4047	53	14	from	from	ADP
iajs-4047	53	15	four	four	NUM
iajs-4047	53	16	different	different	ADJ
iajs-4047	53	17	data	data	NOUN
iajs-4047	53	18	sets	set	NOUN
iajs-4047	53	19	:	:	PUNCT
iajs-4047	53	20	data	datum	NOUN
iajs-4047	53	21	that	that	PRON
iajs-4047	53	22	is	be	AUX
iajs-4047	53	23	generated	generate	VERB
iajs-4047	53	24	randomly	randomly	ADV
iajs-4047	53	25	,	,	PUNCT
iajs-4047	53	26	data	datum	NOUN
iajs-4047	53	27	on	on	ADP
iajs-4047	53	28	breast	breast	NOUN
iajs-4047	53	29	cancer	cancer	NOUN
iajs-4047	53	30	,	,	PUNCT
iajs-4047	53	31	data	datum	NOUN
iajs-4047	53	32	from	from	ADP
iajs-4047	53	33	ruspini	ruspini	NOUN
iajs-4047	53	34	,	,	PUNCT
iajs-4047	53	35	and	and	CCONJ
iajs-4047	53	36	data	datum	NOUN
iajs-4047	53	37	from	from	ADP
iajs-4047	53	38	the	the	DET
iajs-4047	53	39	iris	iris	NOUN
iajs-4047	53	40	plant	plant	NOUN
iajs-4047	53	41	.	.	PUNCT
iajs-4047	54	1	in	in	ADP
iajs-4047	54	2	each	each	DET
iajs-4047	54	3	simulation	simulation	NOUN
iajs-4047	54	4	,	,	PUNCT
iajs-4047	54	5	a	a	DET
iajs-4047	54	6	population	population	NOUN
iajs-4047	54	7	of	of	ADP
iajs-4047	54	8	20	20	NUM
iajs-4047	54	9	genotypes	genotype	NOUN
iajs-4047	54	10	was	be	AUX
iajs-4047	54	11	examined	examine	VERB
iajs-4047	54	12	,	,	PUNCT
iajs-4047	54	13	which	which	PRON
iajs-4047	54	14	,	,	PUNCT
iajs-4047	54	15	in	in	ADP
iajs-4047	54	16	turn	turn	NOUN
iajs-4047	54	17	,	,	PUNCT
iajs-4047	54	18	reflected	reflect	VERB
iajs-4047	54	19	the	the	DET
iajs-4047	54	20	use	use	NOUN
iajs-4047	54	21	of	of	ADP
iajs-4047	54	22	21	21	NUM
iajs-4047	54	23	clusters	cluster	NOUN
iajs-4047	54	24	.	.	PUNCT
iajs-4047	55	1	besides	besides	SCONJ
iajs-4047	55	2	,	,	PUNCT
iajs-4047	55	3	200	200	NUM
iajs-4047	55	4	is	be	AUX
iajs-4047	55	5	set	set	VERB
iajs-4047	55	6	to	to	PART
iajs-4047	55	7	be	be	AUX
iajs-4047	55	8	the	the	DET
iajs-4047	55	9	maximum	maximum	ADJ
iajs-4047	55	10	number	number	NOUN
iajs-4047	55	11	of	of	ADP
iajs-4047	55	12	generations	generation	NOUN
iajs-4047	55	13	.	.	PUNCT
iajs-4047	56	1	the	the	DET
iajs-4047	56	2	dissimilarities	dissimilarity	NOUN
iajs-4047	56	3	between	between	ADP
iajs-4047	56	4	items	item	NOUN
iajs-4047	56	5	were	be	AUX
iajs-4047	56	6	calculated	calculate	VERB
iajs-4047	56	7	using	use	VERB
iajs-4047	56	8	the	the	DET
iajs-4047	56	9	euclidean	euclidean	ADJ
iajs-4047	56	10	distance	distance	NOUN
iajs-4047	56	11	measure	measure	NOUN
iajs-4047	56	12	.	.	PUNCT
iajs-4047	57	1	it	it	PRON
iajs-4047	57	2	simulated	simulate	VERB
iajs-4047	57	3	ten	ten	NUM
iajs-4047	57	4	tests	test	NOUN
iajs-4047	57	5	on	on	ADP
iajs-4047	57	6	each	each	DET
iajs-4047	57	7	dataset	dataset	NOUN
iajs-4047	57	8	;	;	PUNCT
iajs-4047	57	9	the	the	DET
iajs-4047	57	10	best	good	ADJ
iajs-4047	57	11	objective	objective	ADJ
iajs-4047	57	12	function	function	NOUN
iajs-4047	57	13	value	value	NOUN
iajs-4047	57	14	was	be	AUX
iajs-4047	57	15	first	first	ADV
iajs-4047	57	16	found	find	VERB
iajs-4047	57	17	.	.	PUNCT
iajs-4047	58	1	in	in	ADP
iajs-4047	58	2	a	a	DET
iajs-4047	58	3	study	study	NOUN
iajs-4047	58	4	by	by	ADP
iajs-4047	58	5	liu	liu	PROPN
iajs-4047	58	6	et	et	PROPN
iajs-4047	58	7	al	al	PROPN
iajs-4047	58	8	.	.	PROPN
iajs-4047	59	1	(	(	PUNCT
iajs-4047	59	2	9	9	NUM
iajs-4047	59	3	)	)	PUNCT
iajs-4047	59	4	,	,	PUNCT
iajs-4047	59	5	the	the	DET
iajs-4047	59	6	so	so	ADV
iajs-4047	59	7	-	-	PUNCT
iajs-4047	59	8	called	call	VERB
iajs-4047	59	9	clustering	clustering	NOUN
iajs-4047	59	10	of	of	ADP
iajs-4047	59	11	automatic	automatic	ADJ
iajs-4047	59	12	genetics	genetic	NOUN
iajs-4047	59	13	,	,	PUNCT
iajs-4047	59	14	which	which	PRON
iajs-4047	59	15	is	be	AUX
iajs-4047	59	16	basically	basically	ADV
iajs-4047	59	17	genetic	genetic	ADJ
iajs-4047	59	18	algorithm	algorithm	NOUN
iajs-4047	59	19	-	-	PUNCT
iajs-4047	59	20	based	base	VERB
iajs-4047	59	21	clustering	clustering	NOUN
iajs-4047	59	22	,	,	PUNCT
iajs-4047	59	23	is	be	AUX
iajs-4047	59	24	presented	present	VERB
iajs-4047	59	25	in	in	ADP
iajs-4047	59	26	this	this	DET
iajs-4047	59	27	paper	paper	NOUN
iajs-4047	59	28	approach	approach	NOUN
iajs-4047	59	29	to	to	ADP
iajs-4047	59	30	genetic	genetic	ADJ
iajs-4047	59	31	clustering	clustering	NOUN
iajs-4047	59	32	for	for	ADP
iajs-4047	59	33	unknown	unknown	ADJ
iajs-4047	59	34	k	k	PROPN
iajs-4047	59	35	(	(	PUNCT
iajs-4047	59	36	agcuk	agcuk	NOUN
iajs-4047	59	37	)	)	PUNCT
iajs-4047	59	38	.	.	PUNCT
iajs-4047	60	1	the	the	DET
iajs-4047	60	2	agcuk	agcuk	NOUN
iajs-4047	60	3	technique	technique	NOUN
iajs-4047	60	4	could	could	AUX
iajs-4047	60	5	automatically	automatically	ADV
iajs-4047	60	6	give	give	VERB
iajs-4047	60	7	the	the	DET
iajs-4047	60	8	cluster	cluster	NOUN
iajs-4047	60	9	number	number	NOUN
iajs-4047	60	10	to	to	PART
iajs-4047	60	11	define	define	VERB
iajs-4047	60	12	the	the	DET
iajs-4047	60	13	division	division	NOUN
iajs-4047	60	14	of	of	ADP
iajs-4047	60	15	clustering	clustering	NOUN
iajs-4047	60	16	.	.	PUNCT
iajs-4047	61	1	davies	davy	NOUN
iajs-4047	61	2	-	-	PUNCT
iajs-4047	61	3	bouldin	bouldin	NOUN
iajs-4047	61	4	's	's	PART
iajs-4047	61	5	index	index	NOUN
iajs-4047	61	6	is	be	AUX
iajs-4047	61	7	used	use	VERB
iajs-4047	61	8	to	to	PART
iajs-4047	61	9	evaluate	evaluate	VERB
iajs-4047	61	10	the	the	DET
iajs-4047	61	11	cluster	cluster	NOUN
iajs-4047	61	12	's	's	PART
iajs-4047	61	13	accuracy	accuracy	NOUN
iajs-4047	61	14	.	.	PUNCT
iajs-4047	62	1	real	real	ADJ
iajs-4047	62	2	-	-	PUNCT
iajs-4047	62	3	world	world	NOUN
iajs-4047	62	4	and	and	CCONJ
iajs-4047	62	5	simulated	simulated	ADJ
iajs-4047	62	6	datasets	dataset	NOUN
iajs-4047	62	7	are	be	AUX
iajs-4047	62	8	experimented	experiment	VERB
iajs-4047	62	9	with	with	ADP
iajs-4047	62	10	to	to	PART
iajs-4047	62	11	demonstrate	demonstrate	VERB
iajs-4047	62	12	the	the	DET
iajs-4047	62	13	performance	performance	NOUN
iajs-4047	62	14	of	of	ADP
iajs-4047	62	15	the	the	DET
iajs-4047	62	16	agcuk	agcuk	NOUN
iajs-4047	62	17	algorithm	algorithm	NOUN
iajs-4047	62	18	.	.	PUNCT
iajs-4047	63	1	in	in	ADP
iajs-4047	63	2	a	a	DET
iajs-4047	63	3	study	study	NOUN
iajs-4047	63	4	by	by	ADP
iajs-4047	63	5	rahman	rahman	PROPN
iajs-4047	63	6	and	and	CCONJ
iajs-4047	63	7	islam	islam	PROPN
iajs-4047	63	8	(	(	PUNCT
iajs-4047	63	9	10	10	NUM
iajs-4047	63	10	)	)	PUNCT
iajs-4047	63	11	,	,	PUNCT
iajs-4047	63	12	a	a	DET
iajs-4047	63	13	novel	novel	ADJ
iajs-4047	63	14	ga	ga	NOUN
iajs-4047	63	15	-	-	PUNCT
iajs-4047	63	16	based	base	VERB
iajs-4047	63	17	clustering	clustering	ADJ
iajs-4047	63	18	study	study	NOUN
iajs-4047	63	19	strategy	strategy	NOUN
iajs-4047	63	20	has	have	AUX
iajs-4047	63	21	ihjpas	ihjpa	VERB
iajs-4047	63	22	.	.	PUNCT
iajs-4047	64	1	2025	2025	NUM
iajs-4047	64	2	,	,	PUNCT
iajs-4047	64	3	38	38	NUM
iajs-4047	64	4	(	(	PUNCT
iajs-4047	64	5	2	2	NUM
iajs-4047	64	6	)	)	PUNCT
iajs-4047	64	7	427	427	NUM
iajs-4047	64	8	the	the	DET
iajs-4047	64	9	capability	capability	NOUN
iajs-4047	64	10	of	of	ADP
iajs-4047	64	11	choosing	choose	VERB
iajs-4047	64	12	the	the	DET
iajs-4047	64	13	ideal	ideal	ADJ
iajs-4047	64	14	number	number	NOUN
iajs-4047	64	15	of	of	ADP
iajs-4047	64	16	clusters	cluster	NOUN
iajs-4047	64	17	and	and	CCONJ
iajs-4047	64	18	genes	gene	NOUN
iajs-4047	64	19	using	use	VERB
iajs-4047	64	20	a	a	DET
iajs-4047	64	21	selection	selection	NOUN
iajs-4047	64	22	approach	approach	NOUN
iajs-4047	64	23	of	of	ADP
iajs-4047	64	24	a	a	DET
iajs-4047	64	25	novel	novel	ADJ
iajs-4047	64	26	initial	initial	ADJ
iajs-4047	64	27	population	population	NOUN
iajs-4047	64	28	.	.	PUNCT
iajs-4047	65	1	the	the	DET
iajs-4047	65	2	objective	objective	ADJ
iajs-4047	65	3	function	function	NOUN
iajs-4047	65	4	and	and	CCONJ
iajs-4047	65	5	gene	gene	NOUN
iajs-4047	65	6	modification	modification	NOUN
iajs-4047	65	7	operation	operation	NOUN
iajs-4047	65	8	create	create	VERB
iajs-4047	65	9	highquality	highquality	NOUN
iajs-4047	65	10	cluster	cluster	NOUN
iajs-4047	65	11	centers	center	NOUN
iajs-4047	65	12	.	.	PUNCT
iajs-4047	66	1	the	the	DET
iajs-4047	66	2	centers	center	NOUN
iajs-4047	66	3	are	be	AUX
iajs-4047	66	4	then	then	ADV
iajs-4047	66	5	passed	pass	VERB
iajs-4047	66	6	to	to	ADP
iajs-4047	66	7	k	k	X
iajs-4047	66	8	-	-	PUNCT
iajs-4047	66	9	means	means	NOUN
iajs-4047	66	10	as	as	ADP
iajs-4047	66	11	initial	initial	ADJ
iajs-4047	66	12	seeds	seed	NOUN
iajs-4047	66	13	,	,	PUNCT
iajs-4047	66	14	resulting	result	VERB
iajs-4047	66	15	in	in	ADP
iajs-4047	66	16	an	an	DET
iajs-4047	66	17	even	even	ADV
iajs-4047	66	18	higher	high	ADJ
iajs-4047	66	19	quality	quality	NOUN
iajs-4047	66	20	clustering	clustering	NOUN
iajs-4047	66	21	solution	solution	NOUN
iajs-4047	66	22	by	by	ADP
iajs-4047	66	23	enabling	enable	VERB
iajs-4047	66	24	the	the	DET
iajs-4047	66	25	original	original	ADJ
iajs-4047	66	26	seeds	seed	NOUN
iajs-4047	66	27	to	to	PART
iajs-4047	66	28	change	change	VERB
iajs-4047	66	29	as	as	ADP
iajs-4047	66	30	necessary	necessary	ADJ
iajs-4047	66	31	.	.	PUNCT
iajs-4047	67	1	the	the	DET
iajs-4047	67	2	results	result	NOUN
iajs-4047	67	3	show	show	VERB
iajs-4047	67	4	that	that	SCONJ
iajs-4047	67	5	the	the	DET
iajs-4047	67	6	approach	approach	NOUN
iajs-4047	67	7	outperforms	outperform	VERB
iajs-4047	67	8	five	five	NUM
iajs-4047	67	9	contemporary	contemporary	ADJ
iajs-4047	67	10	techniques	technique	NOUN
iajs-4047	67	11	on	on	ADP
iajs-4047	67	12	twenty	twenty	NUM
iajs-4047	67	13	natural	natural	ADJ
iajs-4047	67	14	data	datum	NOUN
iajs-4047	67	15	sets	set	NOUN
iajs-4047	67	16	included	include	VERB
iajs-4047	67	17	in	in	ADP
iajs-4047	67	18	this	this	DET
iajs-4047	67	19	study	study	NOUN
iajs-4047	67	20	,	,	PUNCT
iajs-4047	67	21	according	accord	VERB
iajs-4047	67	22	to	to	ADP
iajs-4047	67	23	six	six	NUM
iajs-4047	67	24	evaluation	evaluation	NOUN
iajs-4047	67	25	criteria	criterion	NOUN
iajs-4047	67	26	.	.	PUNCT
iajs-4047	68	1	roy	roy	PROPN
iajs-4047	68	2	and	and	CCONJ
iajs-4047	68	3	sharma	sharma	PROPN
iajs-4047	68	4	(	(	PUNCT
iajs-4047	68	5	11	11	NUM
iajs-4047	68	6	)	)	PUNCT
iajs-4047	68	7	described	describe	VERB
iajs-4047	68	8	a	a	DET
iajs-4047	68	9	clustering	clustering	ADJ
iajs-4047	68	10	technique	technique	NOUN
iajs-4047	68	11	based	base	VERB
iajs-4047	68	12	on	on	ADP
iajs-4047	68	13	the	the	DET
iajs-4047	68	14	genetic	genetic	ADJ
iajs-4047	68	15	k	k	ADJ
iajs-4047	68	16	-	-	PUNCT
iajs-4047	68	17	means	mean	NOUN
iajs-4047	68	18	paradigm	paradigm	NOUN
iajs-4047	68	19	that	that	PRON
iajs-4047	68	20	works	work	VERB
iajs-4047	68	21	well	well	ADV
iajs-4047	68	22	with	with	ADP
iajs-4047	68	23	data	datum	NOUN
iajs-4047	68	24	that	that	PRON
iajs-4047	68	25	contains	contain	VERB
iajs-4047	68	26	both	both	DET
iajs-4047	68	27	numerical	numerical	ADJ
iajs-4047	68	28	and	and	CCONJ
iajs-4047	68	29	categorical	categorical	ADJ
iajs-4047	68	30	variables	variable	NOUN
iajs-4047	68	31	.	.	PUNCT
iajs-4047	69	1	this	this	DET
iajs-4047	69	2	study	study	NOUN
iajs-4047	69	3	proposed	propose	VERB
iajs-4047	69	4	a	a	DET
iajs-4047	69	5	modified	modify	VERB
iajs-4047	69	6	cluster	cluster	NOUN
iajs-4047	69	7	center	center	NOUN
iajs-4047	69	8	description	description	NOUN
iajs-4047	69	9	to	to	PART
iajs-4047	69	10	overcome	overcome	VERB
iajs-4047	69	11	the	the	DET
iajs-4047	69	12	genetic	genetic	ADJ
iajs-4047	69	13	k	k	ADJ
iajs-4047	69	14	-	-	PUNCT
iajs-4047	69	15	means	mean	NOUN
iajs-4047	69	16	algorithm	algorithm	NOUN
iajs-4047	69	17	's	's	PART
iajs-4047	69	18	numeric	numeric	ADJ
iajs-4047	69	19	data	datum	NOUN
iajs-4047	69	20	constraint	constraint	NOUN
iajs-4047	69	21	and	and	CCONJ
iajs-4047	69	22	give	give	VERB
iajs-4047	69	23	a	a	DET
iajs-4047	69	24	more	more	ADV
iajs-4047	69	25	complete	complete	ADJ
iajs-4047	69	26	definition	definition	NOUN
iajs-4047	69	27	of	of	ADP
iajs-4047	69	28	clusters	cluster	NOUN
iajs-4047	69	29	.	.	PUNCT
iajs-4047	70	1	the	the	DET
iajs-4047	70	2	performance	performance	NOUN
iajs-4047	70	3	of	of	ADP
iajs-4047	70	4	this	this	DET
iajs-4047	70	5	method	method	NOUN
iajs-4047	70	6	was	be	AUX
iajs-4047	70	7	investigated	investigate	VERB
iajs-4047	70	8	using	use	VERB
iajs-4047	70	9	benchmark	benchmark	ADJ
iajs-4047	70	10	data	data	NOUN
iajs-4047	70	11	sets	set	NOUN
iajs-4047	70	12	.	.	PUNCT
iajs-4047	71	1	han	han	PROPN
iajs-4047	71	2	and	and	CCONJ
iajs-4047	71	3	xiao	xiao	PROPN
iajs-4047	71	4	(	(	PUNCT
iajs-4047	71	5	12	12	NUM
iajs-4047	71	6	)	)	PUNCT
iajs-4047	71	7	explain	explain	VERB
iajs-4047	71	8	the	the	DET
iajs-4047	71	9	fundamental	fundamental	ADJ
iajs-4047	71	10	premise	premise	NOUN
iajs-4047	71	11	of	of	ADP
iajs-4047	71	12	the	the	DET
iajs-4047	71	13	genetic	genetic	ADJ
iajs-4047	71	14	algorithm	algorithm	NOUN
iajs-4047	71	15	,	,	PUNCT
iajs-4047	71	16	which	which	PRON
iajs-4047	71	17	is	be	AUX
iajs-4047	71	18	based	base	VERB
iajs-4047	71	19	on	on	ADP
iajs-4047	71	20	darwin	darwin	PROPN
iajs-4047	71	21	's	's	PART
iajs-4047	71	22	theory	theory	NOUN
iajs-4047	71	23	of	of	ADP
iajs-4047	71	24	evolution	evolution	NOUN
iajs-4047	71	25	's	's	PART
iajs-4047	71	26	"	"	PUNCT
iajs-4047	71	27	survival	survival	NOUN
iajs-4047	71	28	of	of	ADP
iajs-4047	71	29	the	the	DET
iajs-4047	71	30	fittest	fit	ADJ
iajs-4047	71	31	"	"	PUNCT
iajs-4047	71	32	,	,	PUNCT
iajs-4047	71	33	describes	describe	VERB
iajs-4047	71	34	the	the	DET
iajs-4047	71	35	algorithm	algorithm	NOUN
iajs-4047	71	36	's	's	PART
iajs-4047	71	37	primary	primary	ADJ
iajs-4047	71	38	characteristics	characteristic	NOUN
iajs-4047	71	39	,	,	PUNCT
iajs-4047	71	40	and	and	CCONJ
iajs-4047	71	41	analyzes	analyze	VERB
iajs-4047	71	42	its	its	PRON
iajs-4047	71	43	weaknesses	weakness	NOUN
iajs-4047	71	44	.	.	PUNCT
iajs-4047	72	1	an	an	DET
iajs-4047	72	2	enhanced	enhance	VERB
iajs-4047	72	3	adaptive	adaptive	ADJ
iajs-4047	72	4	genetic	genetic	ADJ
iajs-4047	72	5	algorithm	algorithm	NOUN
iajs-4047	72	6	is	be	AUX
iajs-4047	72	7	developed	develop	VERB
iajs-4047	72	8	based	base	VERB
iajs-4047	72	9	on	on	ADP
iajs-4047	72	10	the	the	DET
iajs-4047	72	11	specific	specific	ADJ
iajs-4047	72	12	running	running	NOUN
iajs-4047	72	13	phases	phase	NOUN
iajs-4047	72	14	of	of	ADP
iajs-4047	72	15	the	the	DET
iajs-4047	72	16	genetic	genetic	ADJ
iajs-4047	72	17	algorithm	algorithm	NOUN
iajs-4047	72	18	,	,	PUNCT
iajs-4047	72	19	to	to	PART
iajs-4047	72	20	address	address	VERB
iajs-4047	72	21	its	its	PRON
iajs-4047	72	22	inadequacies	inadequacy	NOUN
iajs-4047	72	23	.	.	PUNCT
iajs-4047	73	1	finally	finally	ADV
iajs-4047	73	2	,	,	PUNCT
iajs-4047	73	3	an	an	DET
iajs-4047	73	4	example	example	NOUN
iajs-4047	73	5	is	be	AUX
iajs-4047	73	6	provided	provide	VERB
iajs-4047	73	7	for	for	ADP
iajs-4047	73	8	simulation	simulation	NOUN
iajs-4047	73	9	.	.	PUNCT
iajs-4047	74	1	the	the	DET
iajs-4047	74	2	simulation	simulation	NOUN
iajs-4047	74	3	results	result	NOUN
iajs-4047	74	4	demonstrated	demonstrate	VERB
iajs-4047	74	5	that	that	SCONJ
iajs-4047	74	6	the	the	DET
iajs-4047	74	7	enhanced	enhanced	ADJ
iajs-4047	74	8	method	method	NOUN
iajs-4047	74	9	has	have	VERB
iajs-4047	74	10	some	some	DET
iajs-4047	74	11	advantages	advantage	NOUN
iajs-4047	74	12	.	.	PUNCT
iajs-4047	75	1	in	in	ADP
iajs-4047	75	2	the	the	DET
iajs-4047	75	3	current	current	ADJ
iajs-4047	75	4	paper	paper	NOUN
iajs-4047	75	5	,	,	PUNCT
iajs-4047	75	6	we	we	PRON
iajs-4047	75	7	use	use	VERB
iajs-4047	75	8	the	the	DET
iajs-4047	75	9	genetic	genetic	ADJ
iajs-4047	75	10	algorithm	algorithm	NOUN
iajs-4047	75	11	with	with	ADP
iajs-4047	75	12	the	the	DET
iajs-4047	75	13	negative	negative	ADJ
iajs-4047	75	14	equation	equation	NOUN
iajs-4047	75	15	of	of	ADP
iajs-4047	75	16	the	the	DET
iajs-4047	75	17	gap	gap	NOUN
iajs-4047	75	18	statistic	statistic	NOUN
iajs-4047	75	19	as	as	SCONJ
iajs-4047	75	20	the	the	DET
iajs-4047	75	21	objective	objective	ADJ
iajs-4047	75	22	function	function	NOUN
iajs-4047	75	23	to	to	PART
iajs-4047	75	24	find	find	VERB
iajs-4047	75	25	the	the	DET
iajs-4047	75	26	optimal	optimal	ADJ
iajs-4047	75	27	number	number	NOUN
iajs-4047	75	28	of	of	ADP
iajs-4047	75	29	clusters	cluster	NOUN
iajs-4047	75	30	.	.	PUNCT
iajs-4047	76	1	2	2	X
iajs-4047	76	2	.	.	X
iajs-4047	76	3	materials	material	NOUN
iajs-4047	76	4	and	and	CCONJ
iajs-4047	76	5	methods	method	NOUN
iajs-4047	76	6	this	this	DET
iajs-4047	76	7	section	section	NOUN
iajs-4047	76	8	will	will	AUX
iajs-4047	76	9	present	present	VERB
iajs-4047	76	10	the	the	DET
iajs-4047	76	11	types	type	NOUN
iajs-4047	76	12	of	of	ADP
iajs-4047	76	13	clusters	cluster	NOUN
iajs-4047	76	14	and	and	CCONJ
iajs-4047	76	15	algorithms	algorithm	NOUN
iajs-4047	76	16	used	use	VERB
iajs-4047	76	17	for	for	ADP
iajs-4047	76	18	them	they	PRON
iajs-4047	76	19	,	,	PUNCT
iajs-4047	76	20	as	as	ADV
iajs-4047	76	21	well	well	ADV
iajs-4047	76	22	as	as	ADP
iajs-4047	76	23	the	the	DET
iajs-4047	76	24	algorithms	algorithm	NOUN
iajs-4047	76	25	used	use	VERB
iajs-4047	76	26	in	in	ADP
iajs-4047	76	27	this	this	DET
iajs-4047	76	28	paper	paper	NOUN
iajs-4047	76	29	.	.	PUNCT
iajs-4047	77	1	2.1	2.1	NUM
iajs-4047	77	2	.	.	PUNCT
iajs-4047	77	3	clustering	cluster	VERB
iajs-4047	77	4	types	type	NOUN
iajs-4047	77	5	a	a	DET
iajs-4047	77	6	clustering	clustering	ADJ
iajs-4047	77	7	approach	approach	NOUN
iajs-4047	77	8	seeks	seek	VERB
iajs-4047	77	9	to	to	PART
iajs-4047	77	10	group	group	VERB
iajs-4047	77	11	comparable	comparable	ADJ
iajs-4047	77	12	data	datum	NOUN
iajs-4047	77	13	items	item	NOUN
iajs-4047	77	14	and	and	CCONJ
iajs-4047	77	15	allocate	allocate	VERB
iajs-4047	77	16	heterogeneous	heterogeneous	ADJ
iajs-4047	77	17	data	datum	NOUN
iajs-4047	77	18	to	to	ADP
iajs-4047	77	19	various	various	ADJ
iajs-4047	77	20	clusters	cluster	NOUN
iajs-4047	77	21	using	use	VERB
iajs-4047	77	22	an	an	DET
iajs-4047	77	23	objective	objective	ADJ
iajs-4047	77	24	function	function	NOUN
iajs-4047	77	25	,	,	PUNCT
iajs-4047	77	26	model	model	NOUN
iajs-4047	77	27	,	,	PUNCT
iajs-4047	77	28	grid	grid	NOUN
iajs-4047	77	29	computing	computing	NOUN
iajs-4047	77	30	,	,	PUNCT
iajs-4047	77	31	or	or	CCONJ
iajs-4047	77	32	density	density	NOUN
iajs-4047	77	33	computing	computing	NOUN
iajs-4047	77	34	.	.	PUNCT
iajs-4047	78	1	as	as	ADP
iajs-4047	78	2	a	a	DET
iajs-4047	78	3	result	result	NOUN
iajs-4047	78	4	,	,	PUNCT
iajs-4047	78	5	hundreds	hundred	NOUN
iajs-4047	78	6	of	of	ADP
iajs-4047	78	7	articles	article	NOUN
iajs-4047	78	8	include	include	VERB
iajs-4047	78	9	numerous	numerous	ADJ
iajs-4047	78	10	clustering	clustering	ADJ
iajs-4047	78	11	techniques	technique	NOUN
iajs-4047	78	12	.	.	PUNCT
iajs-4047	79	1	these	these	DET
iajs-4047	79	2	approaches	approach	NOUN
iajs-4047	79	3	are	be	AUX
iajs-4047	79	4	divided	divide	VERB
iajs-4047	79	5	into	into	ADP
iajs-4047	79	6	five	five	NUM
iajs-4047	79	7	types	type	NOUN
iajs-4047	79	8	:	:	PUNCT
iajs-4047	79	9	partitioning	partition	VERB
iajs-4047	79	10	,	,	PUNCT
iajs-4047	79	11	density	density	NOUN
iajs-4047	79	12	-	-	PUNCT
iajs-4047	79	13	based	base	VERB
iajs-4047	79	14	,	,	PUNCT
iajs-4047	79	15	hierarchical	hierarchical	ADJ
iajs-4047	79	16	,	,	PUNCT
iajs-4047	79	17	and	and	CCONJ
iajs-4047	79	18	grid	grid	NOUN
iajs-4047	79	19	-	-	PUNCT
iajs-4047	79	20	based	base	VERB
iajs-4047	79	21	methods	method	NOUN
iajs-4047	79	22	.	.	PUNCT
iajs-4047	80	1	each	each	DET
iajs-4047	80	2	strategy	strategy	NOUN
iajs-4047	80	3	has	have	VERB
iajs-4047	80	4	advantages	advantage	NOUN
iajs-4047	80	5	and	and	CCONJ
iajs-4047	80	6	disadvantages	disadvantage	NOUN
iajs-4047	80	7	(	(	PUNCT
iajs-4047	80	8	13	13	NUM
iajs-4047	80	9	)	)	PUNCT
iajs-4047	80	10	.	.	PUNCT
iajs-4047	81	1	1	1	X
iajs-4047	81	2	.	.	X
iajs-4047	81	3	hierarchical	hierarchical	ADJ
iajs-4047	81	4	clustering	clustering	NOUN
iajs-4047	81	5	:	:	PUNCT
iajs-4047	81	6	it	it	PRON
iajs-4047	81	7	is	be	AUX
iajs-4047	81	8	a	a	DET
iajs-4047	81	9	cluster	cluster	NOUN
iajs-4047	81	10	analysis	analysis	NOUN
iajs-4047	81	11	technique	technique	NOUN
iajs-4047	81	12	that	that	PRON
iajs-4047	81	13	aims	aim	VERB
iajs-4047	81	14	to	to	PART
iajs-4047	81	15	create	create	VERB
iajs-4047	81	16	a	a	DET
iajs-4047	81	17	hierarchical	hierarchical	ADJ
iajs-4047	81	18	cluster	cluster	NOUN
iajs-4047	81	19	structure	structure	NOUN
iajs-4047	81	20	.	.	PUNCT
iajs-4047	82	1	a	a	DET
iajs-4047	82	2	hierarchical	hierarchical	ADJ
iajs-4047	82	3	clustering	clustering	NOUN
iajs-4047	82	4	technique	technique	NOUN
iajs-4047	82	5	may	may	AUX
iajs-4047	82	6	be	be	AUX
iajs-4047	82	7	defined	define	VERB
iajs-4047	82	8	as	as	ADP
iajs-4047	82	9	a	a	DET
iajs-4047	82	10	collection	collection	NOUN
iajs-4047	82	11	of	of	ADP
iajs-4047	82	12	standard	standard	ADJ
iajs-4047	82	13	(	(	PUNCT
iajs-4047	82	14	flat	flat	ADJ
iajs-4047	82	15	)	)	PUNCT
iajs-4047	82	16	clustering	cluster	VERB
iajs-4047	82	17	algorithms	algorithm	NOUN
iajs-4047	82	18	grouped	group	VERB
iajs-4047	82	19	in	in	ADP
iajs-4047	82	20	a	a	DET
iajs-4047	82	21	tree	tree	NOUN
iajs-4047	82	22	form	form	NOUN
iajs-4047	82	23	as	as	ADP
iajs-4047	82	24	the	the	DET
iajs-4047	82	25	shape	shape	NOUN
iajs-4047	82	26	in	in	ADP
iajs-4047	82	27	figure	figure	NOUN
iajs-4047	82	28	1	1	NUM
iajs-4047	82	29	.	.	NOUN
iajs-4047	82	30	which	which	PRON
iajs-4047	82	31	provides	provide	VERB
iajs-4047	82	32	a	a	DET
iajs-4047	82	33	dendrogram	dendrogram	NOUN
iajs-4047	82	34	for	for	ADP
iajs-4047	82	35	visual	visual	ADJ
iajs-4047	82	36	interpretation	interpretation	NOUN
iajs-4047	82	37	.	.	PUNCT
iajs-4047	83	1	these	these	DET
iajs-4047	83	2	techniques	technique	NOUN
iajs-4047	83	3	create	create	VERB
iajs-4047	83	4	clusters	cluster	NOUN
iajs-4047	83	5	by	by	ADP
iajs-4047	83	6	recursively	recursively	ADV
iajs-4047	83	7	splitting	split	VERB
iajs-4047	83	8	the	the	DET
iajs-4047	83	9	items	item	NOUN
iajs-4047	83	10	in	in	ADP
iajs-4047	83	11	either	either	CCONJ
iajs-4047	83	12	top	top	ADJ
iajs-4047	83	13	-	-	PUNCT
iajs-4047	83	14	down	down	NOUN
iajs-4047	83	15	or	or	CCONJ
iajs-4047	83	16	bottom	bottom	ADJ
iajs-4047	83	17	-	-	PUNCT
iajs-4047	83	18	up	up	ADP
iajs-4047	83	19	mode	mode	NOUN
iajs-4047	83	20	,	,	PUNCT
iajs-4047	83	21	so	so	CCONJ
iajs-4047	83	22	the	the	DET
iajs-4047	83	23	number	number	NOUN
iajs-4047	83	24	of	of	ADP
iajs-4047	83	25	clusters	cluster	NOUN
iajs-4047	83	26	does	do	AUX
iajs-4047	83	27	not	not	PART
iajs-4047	83	28	need	need	VERB
iajs-4047	83	29	to	to	PART
iajs-4047	83	30	be	be	AUX
iajs-4047	83	31	provided	provide	VERB
iajs-4047	83	32	beforehand	beforehand	ADV
iajs-4047	83	33	.	.	PUNCT
iajs-4047	84	1	the	the	DET
iajs-4047	84	2	advantage	advantage	NOUN
iajs-4047	84	3	of	of	ADP
iajs-4047	84	4	this	this	DET
iajs-4047	84	5	type	type	NOUN
iajs-4047	84	6	is	be	AUX
iajs-4047	84	7	capturing	capture	VERB
iajs-4047	84	8	clusters	cluster	NOUN
iajs-4047	84	9	at	at	ADP
iajs-4047	84	10	different	different	ADJ
iajs-4047	84	11	scales	scale	NOUN
iajs-4047	84	12	.	.	PUNCT
iajs-4047	85	1	however	however	ADV
iajs-4047	85	2	,	,	PUNCT
iajs-4047	85	3	large	large	ADJ
iajs-4047	85	4	datasets	dataset	NOUN
iajs-4047	85	5	are	be	AUX
iajs-4047	85	6	computationally	computationally	ADV
iajs-4047	85	7	costly	costly	ADJ
iajs-4047	85	8	,	,	PUNCT
iajs-4047	85	9	making	make	VERB
iajs-4047	85	10	it	it	PRON
iajs-4047	85	11	difficult	difficult	ADJ
iajs-4047	85	12	to	to	PART
iajs-4047	85	13	find	find	VERB
iajs-4047	85	14	the	the	DET
iajs-4047	85	15	right	right	ADJ
iajs-4047	85	16	number	number	NOUN
iajs-4047	85	17	of	of	ADP
iajs-4047	85	18	clusters	cluster	NOUN
iajs-4047	85	19	from	from	ADP
iajs-4047	85	20	the	the	DET
iajs-4047	85	21	dendrogram	dendrogram	NOUN
iajs-4047	85	22	;	;	PUNCT
iajs-4047	85	23	they	they	PRON
iajs-4047	85	24	can	can	AUX
iajs-4047	85	25	not	not	PART
iajs-4047	85	26	provide	provide	VERB
iajs-4047	85	27	the	the	DET
iajs-4047	85	28	(	(	PUNCT
iajs-4047	85	29	k	k	NOUN
iajs-4047	85	30	)	)	PUNCT
iajs-4047	85	31	beforehand	beforehand	ADV
iajs-4047	85	32	and	and	CCONJ
iajs-4047	85	33	are	be	AUX
iajs-4047	85	34	not	not	PART
iajs-4047	85	35	suitable	suitable	ADJ
iajs-4047	85	36	for	for	ADP
iajs-4047	85	37	huge	huge	ADJ
iajs-4047	85	38	datasets	dataset	NOUN
iajs-4047	85	39	(	(	PUNCT
iajs-4047	85	40	14	14	NUM
iajs-4047	85	41	)	)	PUNCT
iajs-4047	85	42	.	.	PUNCT
iajs-4047	86	1	figure	figure	NOUN
iajs-4047	86	2	1	1	NUM
iajs-4047	86	3	.	.	PUNCT
iajs-4047	86	4	hierarchical	hierarchical	ADJ
iajs-4047	86	5	clustering	clustering	NOUN
iajs-4047	86	6	(	(	PUNCT
iajs-4047	86	7	15	15	NUM
iajs-4047	86	8	)	)	PUNCT
iajs-4047	86	9	ihjpas	ihjpa	NOUN
iajs-4047	86	10	.	.	PUNCT
iajs-4047	87	1	2025	2025	NUM
iajs-4047	87	2	,	,	PUNCT
iajs-4047	87	3	38	38	NUM
iajs-4047	87	4	(	(	PUNCT
iajs-4047	87	5	2	2	NUM
iajs-4047	87	6	)	)	PUNCT
iajs-4047	87	7	428	428	NUM
iajs-4047	87	8	2	2	NUM
iajs-4047	87	9	.	.	PUNCT
iajs-4047	87	10	density	density	NOUN
iajs-4047	87	11	-	-	PUNCT
iajs-4047	87	12	based	base	VERB
iajs-4047	87	13	cluster	cluster	NOUN
iajs-4047	87	14	:	:	PUNCT
iajs-4047	87	15	it	it	PRON
iajs-4047	87	16	appears	appear	VERB
iajs-4047	87	17	in	in	ADP
iajs-4047	87	18	geographical	geographical	ADJ
iajs-4047	87	19	applications	application	NOUN
iajs-4047	87	20	,	,	PUNCT
iajs-4047	87	21	such	such	ADJ
iajs-4047	87	22	as	as	ADP
iajs-4047	87	23	clusters	cluster	NOUN
iajs-4047	87	24	of	of	ADP
iajs-4047	87	25	points	point	NOUN
iajs-4047	87	26	related	relate	VERB
iajs-4047	87	27	to	to	ADP
iajs-4047	87	28	rivers	river	NOUN
iajs-4047	87	29	,	,	PUNCT
iajs-4047	87	30	highways	highway	NOUN
iajs-4047	87	31	,	,	PUNCT
iajs-4047	87	32	electricity	electricity	NOUN
iajs-4047	87	33	lines	line	NOUN
iajs-4047	87	34	,	,	PUNCT
iajs-4047	87	35	or	or	CCONJ
iajs-4047	87	36	any	any	DET
iajs-4047	87	37	linked	link	VERB
iajs-4047	87	38	form	form	NOUN
iajs-4047	87	39	in	in	ADP
iajs-4047	87	40	image	image	NOUN
iajs-4047	87	41	segmentation	segmentation	NOUN
iajs-4047	87	42	(	(	PUNCT
iajs-4047	87	43	16	16	NUM
iajs-4047	87	44	)	)	PUNCT
iajs-4047	87	45	.	.	PUNCT
iajs-4047	88	1	the	the	DET
iajs-4047	88	2	main	main	ADJ
iajs-4047	88	3	advantage	advantage	NOUN
iajs-4047	88	4	of	of	ADP
iajs-4047	88	5	density	density	NOUN
iajs-4047	88	6	-	-	PUNCT
iajs-4047	88	7	based	base	VERB
iajs-4047	88	8	clustering	clustering	NOUN
iajs-4047	88	9	is	be	AUX
iajs-4047	88	10	that	that	SCONJ
iajs-4047	88	11	the	the	DET
iajs-4047	88	12	number	number	NOUN
iajs-4047	88	13	of	of	ADP
iajs-4047	88	14	clusters	cluster	NOUN
iajs-4047	88	15	is	be	AUX
iajs-4047	88	16	not	not	PART
iajs-4047	88	17	required	require	VERB
iajs-4047	88	18	,	,	PUNCT
iajs-4047	88	19	and	and	CCONJ
iajs-4047	88	20	clusters	cluster	NOUN
iajs-4047	88	21	of	of	ADP
iajs-4047	88	22	any	any	DET
iajs-4047	88	23	shape	shape	NOUN
iajs-4047	88	24	may	may	AUX
iajs-4047	88	25	be	be	AUX
iajs-4047	88	26	discovered	discover	VERB
iajs-4047	88	27	.	.	PUNCT
iajs-4047	89	1	many	many	ADJ
iajs-4047	89	2	density	density	NOUN
iajs-4047	89	3	-	-	PUNCT
iajs-4047	89	4	based	base	VERB
iajs-4047	89	5	clustering	clustering	ADJ
iajs-4047	89	6	methods	method	NOUN
iajs-4047	89	7	have	have	AUX
iajs-4047	89	8	been	be	AUX
iajs-4047	89	9	developed	develop	VERB
iajs-4047	89	10	.	.	PUNCT
iajs-4047	90	1	the	the	DET
iajs-4047	90	2	most	most	ADV
iajs-4047	90	3	common	common	ADJ
iajs-4047	90	4	is	be	AUX
iajs-4047	90	5	density	density	NOUN
iajs-4047	90	6	-	-	PUNCT
iajs-4047	90	7	based	base	VERB
iajs-4047	90	8	spatial	spatial	ADJ
iajs-4047	90	9	clustering	clustering	NOUN
iajs-4047	90	10	of	of	ADP
iajs-4047	90	11	applications	application	NOUN
iajs-4047	90	12	with	with	ADP
iajs-4047	90	13	noise	noise	NOUN
iajs-4047	90	14	(	(	PUNCT
iajs-4047	90	15	dbscan	dbscan	NOUN
iajs-4047	90	16	)	)	PUNCT
iajs-4047	90	17	(	(	PUNCT
iajs-4047	90	18	17	17	NUM
iajs-4047	90	19	)	)	PUNCT
iajs-4047	90	20	.	.	PUNCT
iajs-4047	91	1	this	this	DET
iajs-4047	91	2	type	type	NOUN
iajs-4047	91	3	is	be	AUX
iajs-4047	91	4	robust	robust	ADJ
iajs-4047	91	5	to	to	PART
iajs-4047	91	6	noise	noise	NOUN
iajs-4047	91	7	and	and	CCONJ
iajs-4047	91	8	outliers	outlier	NOUN
iajs-4047	91	9	;	;	PUNCT
iajs-4047	91	10	it	it	PRON
iajs-4047	91	11	identifies	identify	VERB
iajs-4047	91	12	randomly	randomly	ADV
iajs-4047	91	13	formed	form	VERB
iajs-4047	91	14	clusters	cluster	NOUN
iajs-4047	91	15	,	,	PUNCT
iajs-4047	91	16	and	and	CCONJ
iajs-4047	91	17	there	there	PRON
iajs-4047	91	18	is	be	VERB
iajs-4047	91	19	no	no	DET
iajs-4047	91	20	need	need	NOUN
iajs-4047	91	21	for	for	SCONJ
iajs-4047	91	22	a	a	DET
iajs-4047	91	23	certain	certain	ADJ
iajs-4047	91	24	number	number	NOUN
iajs-4047	91	25	of	of	ADP
iajs-4047	91	26	clusters	cluster	NOUN
iajs-4047	91	27	to	to	PART
iajs-4047	91	28	be	be	AUX
iajs-4047	91	29	specified	specify	VERB
iajs-4047	91	30	.	.	PUNCT
iajs-4047	92	1	however	however	ADV
iajs-4047	92	2	,	,	PUNCT
iajs-4047	92	3	it	it	PRON
iajs-4047	92	4	is	be	AUX
iajs-4047	92	5	sensitive	sensitive	ADJ
iajs-4047	92	6	to	to	ADP
iajs-4047	92	7	the	the	DET
iajs-4047	92	8	density	density	NOUN
iajs-4047	92	9	parameter	parameter	NOUN
iajs-4047	92	10	settings	setting	NOUN
iajs-4047	92	11	and	and	CCONJ
iajs-4047	92	12	unsuitable	unsuitable	ADJ
iajs-4047	92	13	for	for	ADP
iajs-4047	92	14	clusters	cluster	NOUN
iajs-4047	92	15	with	with	ADP
iajs-4047	92	16	varying	vary	VERB
iajs-4047	92	17	densities	density	NOUN
iajs-4047	92	18	.	.	PUNCT
iajs-4047	93	1	an	an	DET
iajs-4047	93	2	example	example	NOUN
iajs-4047	93	3	of	of	ADP
iajs-4047	93	4	densitybased	densitybase	VERB
iajs-4047	93	5	clusters	cluster	NOUN
iajs-4047	93	6	is	be	AUX
iajs-4047	93	7	shown	show	VERB
iajs-4047	93	8	in	in	ADP
iajs-4047	93	9	figure	figure	NOUN
iajs-4047	93	10	2	2	NUM
iajs-4047	93	11	.	.	PUNCT
iajs-4047	93	12	figure	figure	NOUN
iajs-4047	93	13	2	2	NUM
iajs-4047	93	14	.	.	PUNCT
iajs-4047	93	15	density	density	NOUN
iajs-4047	93	16	-	-	PUNCT
iajs-4047	93	17	based	base	VERB
iajs-4047	93	18	clusters	cluster	NOUN
iajs-4047	93	19	(	(	PUNCT
iajs-4047	93	20	source	source	NOUN
iajs-4047	93	21	(	(	PUNCT
iajs-4047	93	22	18	18	NUM
iajs-4047	93	23	)	)	PUNCT
iajs-4047	93	24	)	)	PUNCT
iajs-4047	94	1	3	3	X
iajs-4047	94	2	.	.	X
iajs-4047	94	3	gaussian	gaussian	ADJ
iajs-4047	94	4	mixture	mixture	NOUN
iajs-4047	94	5	models	model	NOUN
iajs-4047	94	6	(	(	PUNCT
iajs-4047	94	7	gmm	gmm	NOUN
iajs-4047	94	8	):	):	PUNCT
iajs-4047	94	9	this	this	DET
iajs-4047	94	10	strong	strong	ADJ
iajs-4047	94	11	nonlinear	nonlinear	ADJ
iajs-4047	94	12	model	model	NOUN
iajs-4047	94	13	accurately	accurately	ADV
iajs-4047	94	14	fits	fit	VERB
iajs-4047	94	15	varied	varied	ADJ
iajs-4047	94	16	data	datum	NOUN
iajs-4047	94	17	distributions	distribution	NOUN
iajs-4047	94	18	and	and	CCONJ
iajs-4047	94	19	may	may	AUX
iajs-4047	94	20	successfully	successfully	ADV
iajs-4047	94	21	develop	develop	VERB
iajs-4047	94	22	solutions	solution	NOUN
iajs-4047	94	23	of	of	ADP
iajs-4047	94	24	higher	high	ADJ
iajs-4047	94	25	quality	quality	NOUN
iajs-4047	94	26	based	base	VERB
iajs-4047	94	27	on	on	ADP
iajs-4047	94	28	the	the	DET
iajs-4047	94	29	distributions	distribution	NOUN
iajs-4047	94	30	.	.	PUNCT
iajs-4047	95	1	figure	figure	VERB
iajs-4047	95	2	3	3	NUM
iajs-4047	95	3	.	.	PUNCT
iajs-4047	95	4	shows	show	VERB
iajs-4047	95	5	the	the	DET
iajs-4047	95	6	expectation	expectation	NOUN
iajs-4047	95	7	-	-	PUNCT
iajs-4047	95	8	maximization	maximization	NOUN
iajs-4047	95	9	(	(	PUNCT
iajs-4047	95	10	em	em	NOUN
iajs-4047	95	11	)	)	PUNCT
iajs-4047	95	12	algorithm	algorithm	NOUN
iajs-4047	95	13	with	with	ADP
iajs-4047	95	14	gaussian	gaussian	ADJ
iajs-4047	95	15	mixture	mixture	NOUN
iajs-4047	95	16	models	model	NOUN
iajs-4047	95	17	(	(	PUNCT
iajs-4047	95	18	19	19	NUM
iajs-4047	95	19	)	)	PUNCT
iajs-4047	95	20	.	.	PUNCT
iajs-4047	96	1	the	the	DET
iajs-4047	96	2	gaussian	gaussian	NOUN
iajs-4047	96	3	can	can	AUX
iajs-4047	96	4	model	model	VERB
iajs-4047	96	5	complex	complex	ADJ
iajs-4047	96	6	cluster	cluster	NOUN
iajs-4047	96	7	shapes	shape	NOUN
iajs-4047	96	8	and	and	CCONJ
iajs-4047	96	9	provide	provide	VERB
iajs-4047	96	10	probabilistic	probabilistic	ADJ
iajs-4047	96	11	cluster	cluster	NOUN
iajs-4047	96	12	assignments	assignment	NOUN
iajs-4047	96	13	.	.	PUNCT
iajs-4047	97	1	however	however	ADV
iajs-4047	97	2	,	,	PUNCT
iajs-4047	97	3	it	it	PRON
iajs-4047	97	4	is	be	AUX
iajs-4047	97	5	sensitive	sensitive	ADJ
iajs-4047	97	6	to	to	ADP
iajs-4047	97	7	initialization	initialization	NOUN
iajs-4047	97	8	values	value	NOUN
iajs-4047	97	9	,	,	PUNCT
iajs-4047	97	10	it	it	PRON
iajs-4047	97	11	is	be	AUX
iajs-4047	97	12	possible	possible	ADJ
iajs-4047	97	13	to	to	PART
iajs-4047	97	14	converge	converge	VERB
iajs-4047	97	15	to	to	ADP
iajs-4047	97	16	local	local	ADJ
iajs-4047	97	17	optimum	optimum	ADJ
iajs-4047	97	18	values	value	NOUN
iajs-4047	97	19	,	,	PUNCT
iajs-4047	97	20	and	and	CCONJ
iajs-4047	97	21	it	it	PRON
iajs-4047	97	22	is	be	AUX
iajs-4047	97	23	more	more	ADV
iajs-4047	97	24	computationally	computationally	ADV
iajs-4047	97	25	expensive	expensive	ADJ
iajs-4047	97	26	than	than	ADP
iajs-4047	97	27	k	k	NOUN
iajs-4047	97	28	-	-	PUNCT
iajs-4047	97	29	means	means	NOUN
iajs-4047	97	30	.	.	PUNCT
iajs-4047	98	1	figure	figure	VERB
iajs-4047	98	2	3	3	NUM
iajs-4047	98	3	.	.	PUNCT
iajs-4047	98	4	gaussian	gaussian	ADJ
iajs-4047	98	5	mixture	mixture	NOUN
iajs-4047	98	6	models	model	NOUN
iajs-4047	98	7	ihjpas	ihjpa	VERB
iajs-4047	98	8	.	.	PUNCT
iajs-4047	99	1	2025	2025	NUM
iajs-4047	99	2	,	,	PUNCT
iajs-4047	99	3	38	38	NUM
iajs-4047	99	4	(	(	PUNCT
iajs-4047	99	5	2	2	NUM
iajs-4047	99	6	)	)	PUNCT
iajs-4047	99	7	429	429	NUM
iajs-4047	99	8	4	4	NUM
iajs-4047	99	9	.	.	PUNCT
iajs-4047	99	10	fuzzy	fuzzy	ADJ
iajs-4047	99	11	clustering	clustering	NOUN
iajs-4047	99	12	:	:	PUNCT
iajs-4047	99	13	it	it	PRON
iajs-4047	99	14	is	be	AUX
iajs-4047	99	15	an	an	DET
iajs-4047	99	16	important	important	ADJ
iajs-4047	99	17	type	type	NOUN
iajs-4047	99	18	of	of	ADP
iajs-4047	99	19	clustering	clustering	NOUN
iajs-4047	99	20	where	where	SCONJ
iajs-4047	99	21	items	item	NOUN
iajs-4047	99	22	or	or	CCONJ
iajs-4047	99	23	objects	object	NOUN
iajs-4047	99	24	can	can	AUX
iajs-4047	99	25	belong	belong	VERB
iajs-4047	99	26	to	to	ADP
iajs-4047	99	27	many	many	ADJ
iajs-4047	99	28	clusters	cluster	NOUN
iajs-4047	99	29	with	with	ADP
iajs-4047	99	30	varying	vary	VERB
iajs-4047	99	31	degrees	degree	NOUN
iajs-4047	99	32	of	of	ADP
iajs-4047	99	33	membership	membership	NOUN
iajs-4047	99	34	.	.	PUNCT
iajs-4047	100	1	instead	instead	ADV
iajs-4047	100	2	of	of	ADP
iajs-4047	100	3	hard	hard	ADJ
iajs-4047	100	4	assignments	assignment	NOUN
iajs-4047	100	5	,	,	PUNCT
iajs-4047	100	6	where	where	SCONJ
iajs-4047	100	7	each	each	DET
iajs-4047	100	8	data	datum	NOUN
iajs-4047	100	9	point	point	NOUN
iajs-4047	100	10	belongs	belong	VERB
iajs-4047	100	11	to	to	ADP
iajs-4047	100	12	only	only	ADV
iajs-4047	100	13	one	one	NUM
iajs-4047	100	14	cluster	cluster	NOUN
iajs-4047	100	15	,	,	PUNCT
iajs-4047	100	16	as	as	SCONJ
iajs-4047	100	17	shown	show	VERB
iajs-4047	100	18	in	in	ADP
iajs-4047	100	19	figure	figure	NOUN
iajs-4047	100	20	4	4	NUM
iajs-4047	100	21	.	.	NOUN
iajs-4047	100	22	fuzzy	fuzzy	ADJ
iajs-4047	100	23	clustering	clustering	NOUN
iajs-4047	100	24	assigns	assign	NOUN
iajs-4047	100	25	membership	membership	NOUN
iajs-4047	100	26	values	value	NOUN
iajs-4047	100	27	to	to	ADP
iajs-4047	100	28	data	datum	NOUN
iajs-4047	100	29	points	point	NOUN
iajs-4047	100	30	indicating	indicate	VERB
iajs-4047	100	31	the	the	DET
iajs-4047	100	32	degree	degree	NOUN
iajs-4047	100	33	to	to	PART
iajs-4047	100	34	which	which	PRON
iajs-4047	100	35	they	they	PRON
iajs-4047	100	36	belong	belong	VERB
iajs-4047	100	37	to	to	ADP
iajs-4047	100	38	each	each	DET
iajs-4047	100	39	cluster	cluster	NOUN
iajs-4047	100	40	.	.	PUNCT
iajs-4047	101	1	the	the	DET
iajs-4047	101	2	fuzzy	fuzzy	ADJ
iajs-4047	101	3	c	c	NOUN
iajs-4047	101	4	-	-	PUNCT
iajs-4047	101	5	means	means	NOUN
iajs-4047	101	6	(	(	PUNCT
iajs-4047	101	7	fcm	fcm	PROPN
iajs-4047	101	8	)	)	PUNCT
iajs-4047	101	9	algorithm	algorithm	NOUN
iajs-4047	101	10	allows	allow	VERB
iajs-4047	101	11	for	for	ADP
iajs-4047	101	12	soft	soft	ADJ
iajs-4047	101	13	clustering	clustering	NOUN
iajs-4047	101	14	where	where	SCONJ
iajs-4047	101	15	data	data	NOUN
iajs-4047	101	16	points	point	NOUN
iajs-4047	101	17	can	can	AUX
iajs-4047	101	18	belong	belong	VERB
iajs-4047	101	19	to	to	ADP
iajs-4047	101	20	multiple	multiple	ADJ
iajs-4047	101	21	clusters	cluster	NOUN
iajs-4047	101	22	.	.	PUNCT
iajs-4047	102	1	it	it	PRON
iajs-4047	102	2	handles	handle	VERB
iajs-4047	102	3	noise	noise	NOUN
iajs-4047	102	4	and	and	CCONJ
iajs-4047	102	5	outliers	outlier	NOUN
iajs-4047	102	6	better	well	ADJ
iajs-4047	102	7	than	than	ADP
iajs-4047	102	8	traditional	traditional	ADJ
iajs-4047	102	9	hard	hard	ADJ
iajs-4047	102	10	clustering	clustering	ADJ
iajs-4047	102	11	methods	method	NOUN
iajs-4047	102	12	and	and	CCONJ
iajs-4047	102	13	provides	provide	VERB
iajs-4047	102	14	more	more	ADJ
iajs-4047	102	15	flexibility	flexibility	NOUN
iajs-4047	102	16	in	in	ADP
iajs-4047	102	17	capturing	capture	VERB
iajs-4047	102	18	the	the	DET
iajs-4047	102	19	uncertainty	uncertainty	NOUN
iajs-4047	102	20	in	in	ADP
iajs-4047	102	21	data	data	PROPN
iajs-4047	102	22	.	.	PUNCT
iajs-4047	103	1	interpretation	interpretation	NOUN
iajs-4047	103	2	of	of	ADP
iajs-4047	103	3	fuzzy	fuzzy	ADJ
iajs-4047	103	4	clusters	cluster	NOUN
iajs-4047	103	5	can	can	AUX
iajs-4047	103	6	be	be	AUX
iajs-4047	103	7	more	more	ADV
iajs-4047	103	8	complex	complex	ADJ
iajs-4047	103	9	than	than	ADP
iajs-4047	103	10	traditional	traditional	ADJ
iajs-4047	103	11	hard	hard	ADJ
iajs-4047	103	12	clusters	cluster	NOUN
iajs-4047	103	13	(	(	PUNCT
iajs-4047	103	14	20	20	NUM
iajs-4047	103	15	)	)	PUNCT
iajs-4047	103	16	.	.	PUNCT
iajs-4047	104	1	figure	figure	VERB
iajs-4047	104	2	4	4	NUM
iajs-4047	104	3	.	.	PUNCT
iajs-4047	104	4	fuzzy	fuzzy	ADJ
iajs-4047	104	5	clustering	cluster	VERB
iajs-4047	104	6	5	5	NUM
iajs-4047	104	7	.	.	PUNCT
iajs-4047	105	1	partition	partition	NOUN
iajs-4047	105	2	clustering	clustering	NOUN
iajs-4047	105	3	:	:	PUNCT
iajs-4047	105	4	as	as	SCONJ
iajs-4047	105	5	shown	show	VERB
iajs-4047	105	6	in	in	ADP
iajs-4047	105	7	figure	figure	NOUN
iajs-4047	105	8	5	5	NUM
iajs-4047	105	9	.	.	PUNCT
iajs-4047	106	1	the	the	DET
iajs-4047	106	2	k	k	NOUN
iajs-4047	106	3	-	-	PUNCT
iajs-4047	106	4	means	means	NOUN
iajs-4047	106	5	algorithm	algorithm	NOUN
iajs-4047	106	6	is	be	AUX
iajs-4047	106	7	easy	easy	ADJ
iajs-4047	106	8	and	and	CCONJ
iajs-4047	106	9	simple	simple	ADJ
iajs-4047	106	10	to	to	PART
iajs-4047	106	11	implement	implement	VERB
iajs-4047	106	12	,	,	PUNCT
iajs-4047	106	13	computationally	computationally	ADV
iajs-4047	106	14	cost	cost	NOUN
iajs-4047	106	15	-	-	PUNCT
iajs-4047	106	16	effective	effective	ADJ
iajs-4047	106	17	,	,	PUNCT
iajs-4047	106	18	works	work	VERB
iajs-4047	106	19	well	well	ADV
iajs-4047	106	20	with	with	ADP
iajs-4047	106	21	spherical	spherical	ADJ
iajs-4047	106	22	clusters	cluster	NOUN
iajs-4047	106	23	,	,	PUNCT
iajs-4047	106	24	and	and	CCONJ
iajs-4047	106	25	is	be	AUX
iajs-4047	106	26	sensitive	sensitive	ADJ
iajs-4047	106	27	to	to	ADP
iajs-4047	106	28	the	the	DET
iajs-4047	106	29	initial	initial	ADJ
iajs-4047	106	30	cluster	cluster	NOUN
iajs-4047	106	31	centers	center	NOUN
iajs-4047	106	32	.	.	PUNCT
iajs-4047	107	1	however	however	ADV
iajs-4047	107	2	,	,	PUNCT
iajs-4047	107	3	the	the	DET
iajs-4047	107	4	number	number	NOUN
iajs-4047	107	5	of	of	ADP
iajs-4047	107	6	clusters	cluster	NOUN
iajs-4047	107	7	(	(	PUNCT
iajs-4047	107	8	k	k	NOUN
iajs-4047	107	9	)	)	PUNCT
iajs-4047	107	10	must	must	AUX
iajs-4047	107	11	be	be	AUX
iajs-4047	107	12	set	set	VERB
iajs-4047	107	13	in	in	ADP
iajs-4047	107	14	advance	advance	NOUN
iajs-4047	107	15	,	,	PUNCT
iajs-4047	107	16	and	and	CCONJ
iajs-4047	107	17	it	it	PRON
iajs-4047	107	18	is	be	AUX
iajs-4047	107	19	not	not	PART
iajs-4047	107	20	suitable	suitable	ADJ
iajs-4047	107	21	for	for	ADP
iajs-4047	107	22	clusters	cluster	NOUN
iajs-4047	107	23	with	with	ADP
iajs-4047	107	24	different	different	ADJ
iajs-4047	107	25	sizes	size	NOUN
iajs-4047	107	26	and	and	CCONJ
iajs-4047	107	27	densities	density	NOUN
iajs-4047	107	28	.	.	PUNCT
iajs-4047	108	1	figure	figure	NOUN
iajs-4047	108	2	5	5	NUM
iajs-4047	108	3	.	.	PUNCT
iajs-4047	109	1	partition	partition	NOUN
iajs-4047	109	2	clustering	cluster	VERB
iajs-4047	109	3	2.2	2.2	NUM
iajs-4047	109	4	.	.	PUNCT
iajs-4047	110	1	clustering	cluster	VERB
iajs-4047	110	2	algorithms	algorithm	NOUN
iajs-4047	110	3	there	there	PRON
iajs-4047	110	4	are	be	VERB
iajs-4047	110	5	many	many	ADJ
iajs-4047	110	6	clustering	clustering	ADJ
iajs-4047	110	7	algorithms	algorithm	NOUN
iajs-4047	110	8	used	use	VERB
iajs-4047	110	9	to	to	PART
iajs-4047	110	10	divide	divide	VERB
iajs-4047	110	11	a	a	DET
iajs-4047	110	12	specific	specific	ADJ
iajs-4047	110	13	dataset	dataset	NOUN
iajs-4047	110	14	into	into	ADP
iajs-4047	110	15	a	a	DET
iajs-4047	110	16	set	set	NOUN
iajs-4047	110	17	of	of	ADP
iajs-4047	110	18	clusters	cluster	NOUN
iajs-4047	110	19	,	,	PUNCT
iajs-4047	110	20	but	but	CCONJ
iajs-4047	110	21	the	the	DET
iajs-4047	110	22	most	most	ADV
iajs-4047	110	23	important	important	ADJ
iajs-4047	110	24	of	of	ADP
iajs-4047	110	25	them	they	PRON
iajs-4047	110	26	is	be	AUX
iajs-4047	110	27	the	the	DET
iajs-4047	110	28	k	k	NOUN
iajs-4047	110	29	-	-	PUNCT
iajs-4047	110	30	means	means	NOUN
iajs-4047	110	31	algorithm	algorithm	NOUN
iajs-4047	110	32	(	(	PUNCT
iajs-4047	110	33	21	21	NUM
iajs-4047	110	34	)	)	PUNCT
iajs-4047	110	35	.	.	PUNCT
iajs-4047	111	1	ihjpas	ihjpas	PROPN
iajs-4047	111	2	.	.	PUNCT
iajs-4047	112	1	2025	2025	NUM
iajs-4047	112	2	,	,	PUNCT
iajs-4047	112	3	38	38	NUM
iajs-4047	112	4	(	(	PUNCT
iajs-4047	112	5	2	2	NUM
iajs-4047	112	6	)	)	PUNCT
iajs-4047	112	7	430	430	NUM
iajs-4047	112	8	2.2.1	2.2.1	NUM
iajs-4047	112	9	.	.	PUNCT
iajs-4047	113	1	k	k	X
iajs-4047	113	2	-	-	PUNCT
iajs-4047	113	3	means	means	NOUN
iajs-4047	113	4	algorithm	algorithm	NOUN
iajs-4047	113	5	the	the	DET
iajs-4047	113	6	k	k	NOUN
iajs-4047	113	7	-	-	PUNCT
iajs-4047	113	8	means	means	NOUN
iajs-4047	113	9	algorithm	algorithm	NOUN
iajs-4047	113	10	is	be	AUX
iajs-4047	113	11	a	a	DET
iajs-4047	113	12	technique	technique	NOUN
iajs-4047	113	13	of	of	ADP
iajs-4047	113	14	dividing	divide	VERB
iajs-4047	113	15	n	n	PRON
iajs-4047	113	16	items	item	NOUN
iajs-4047	113	17	into	into	ADP
iajs-4047	113	18	k	k	PROPN
iajs-4047	113	19	clusters	cluster	NOUN
iajs-4047	113	20	based	base	VERB
iajs-4047	113	21	on	on	ADP
iajs-4047	113	22	the	the	DET
iajs-4047	113	23	least	least	ADJ
iajs-4047	113	24	distance	distance	NOUN
iajs-4047	113	25	between	between	ADP
iajs-4047	113	26	the	the	DET
iajs-4047	113	27	center	center	NOUN
iajs-4047	113	28	of	of	ADP
iajs-4047	113	29	the	the	DET
iajs-4047	113	30	cluster	cluster	NOUN
iajs-4047	113	31	and	and	CCONJ
iajs-4047	113	32	the	the	DET
iajs-4047	113	33	other	other	ADJ
iajs-4047	113	34	points	point	NOUN
iajs-4047	113	35	.	.	PUNCT
iajs-4047	114	1	k	k	X
iajs-4047	114	2	-	-	PUNCT
iajs-4047	114	3	means	means	NOUN
iajs-4047	114	4	uses	use	VERB
iajs-4047	114	5	various	various	ADJ
iajs-4047	114	6	distance	distance	NOUN
iajs-4047	114	7	functions	function	NOUN
iajs-4047	114	8	to	to	PART
iajs-4047	114	9	measure	measure	VERB
iajs-4047	114	10	the	the	DET
iajs-4047	114	11	similarity	similarity	NOUN
iajs-4047	114	12	among	among	ADP
iajs-4047	114	13	the	the	DET
iajs-4047	114	14	objects	object	NOUN
iajs-4047	114	15	.	.	PUNCT
iajs-4047	115	1	the	the	DET
iajs-4047	115	2	most	most	ADV
iajs-4047	115	3	used	use	VERB
iajs-4047	115	4	functions	function	NOUN
iajs-4047	115	5	are	be	AUX
iajs-4047	115	6	euclidean	euclidean	ADJ
iajs-4047	115	7	distance	distance	NOUN
iajs-4047	115	8	and	and	CCONJ
iajs-4047	115	9	manhattan	manhattan	PROPN
iajs-4047	115	10	distance	distance	NOUN
iajs-4047	115	11	(	(	PUNCT
iajs-4047	115	12	city	city	NOUN
iajs-4047	115	13	block	block	NOUN
iajs-4047	115	14	distance	distance	NOUN
iajs-4047	115	15	)	)	PUNCT
iajs-4047	115	16	.	.	PUNCT
iajs-4047	116	1	figure	figure	NOUN
iajs-4047	116	2	6	6	NUM
iajs-4047	116	3	.	.	PUNCT
iajs-4047	117	1	shows	show	VERB
iajs-4047	117	2	the	the	DET
iajs-4047	117	3	steps	step	NOUN
iajs-4047	117	4	of	of	ADP
iajs-4047	117	5	the	the	DET
iajs-4047	117	6	k	k	NOUN
iajs-4047	117	7	-	-	PUNCT
iajs-4047	117	8	means	means	NOUN
iajs-4047	117	9	algorithm	algorithm	NOUN
iajs-4047	117	10	.	.	PUNCT
iajs-4047	118	1	figure	figure	NOUN
iajs-4047	118	2	6	6	NUM
iajs-4047	118	3	.	.	PUNCT
iajs-4047	119	1	flowchart	flowchart	NOUN
iajs-4047	119	2	of	of	ADP
iajs-4047	119	3	k	k	PROPN
iajs-4047	119	4	-	-	PUNCT
iajs-4047	119	5	means	means	PROPN
iajs-4047	119	6	(	(	PUNCT
iajs-4047	119	7	22	22	NUM
iajs-4047	119	8	)	)	PUNCT
iajs-4047	119	9	2.2.2	2.2.2	NUM
iajs-4047	119	10	.	.	PUNCT
iajs-4047	120	1	genetic	genetic	ADJ
iajs-4047	120	2	algorithm	algorithm	NOUN
iajs-4047	120	3	genetic	genetic	ADJ
iajs-4047	120	4	algorithms	algorithm	NOUN
iajs-4047	120	5	are	be	AUX
iajs-4047	120	6	random	random	ADJ
iajs-4047	120	7	search	search	NOUN
iajs-4047	120	8	and	and	CCONJ
iajs-4047	120	9	optimization	optimization	NOUN
iajs-4047	120	10	strategies	strategy	NOUN
iajs-4047	120	11	driven	drive	VERB
iajs-4047	120	12	by	by	ADP
iajs-4047	120	13	ideas	idea	NOUN
iajs-4047	120	14	of	of	ADP
iajs-4047	120	15	evolution	evolution	NOUN
iajs-4047	120	16	and	and	CCONJ
iajs-4047	120	17	natural	natural	ADJ
iajs-4047	120	18	genetics	genetic	NOUN
iajs-4047	120	19	.	.	PUNCT
iajs-4047	121	1	they	they	PRON
iajs-4047	121	2	are	be	AUX
iajs-4047	121	3	typically	typically	ADV
iajs-4047	121	4	used	use	VERB
iajs-4047	121	5	to	to	PART
iajs-4047	121	6	find	find	VERB
iajs-4047	121	7	solutions	solution	NOUN
iajs-4047	121	8	to	to	ADP
iajs-4047	121	9	optimization	optimization	NOUN
iajs-4047	121	10	and	and	CCONJ
iajs-4047	121	11	search	search	NOUN
iajs-4047	121	12	problems	problem	NOUN
iajs-4047	121	13	by	by	ADP
iajs-4047	121	14	mimicking	mimic	VERB
iajs-4047	121	15	the	the	DET
iajs-4047	121	16	process	process	NOUN
iajs-4047	121	17	of	of	ADP
iajs-4047	121	18	natural	natural	ADJ
iajs-4047	121	19	selection	selection	NOUN
iajs-4047	121	20	to	to	PART
iajs-4047	121	21	evolve	evolve	VERB
iajs-4047	121	22	toward	toward	ADP
iajs-4047	121	23	better	well	ADJ
iajs-4047	121	24	solutions	solution	NOUN
iajs-4047	121	25	.	.	PUNCT
iajs-4047	122	1	because	because	SCONJ
iajs-4047	122	2	this	this	DET
iajs-4047	122	3	algorithm	algorithm	NOUN
iajs-4047	122	4	is	be	AUX
iajs-4047	122	5	used	use	VERB
iajs-4047	122	6	for	for	ADP
iajs-4047	122	7	optimization	optimization	NOUN
iajs-4047	122	8	,	,	PUNCT
iajs-4047	122	9	it	it	PRON
iajs-4047	122	10	will	will	AUX
iajs-4047	122	11	use	use	VERB
iajs-4047	122	12	it	it	PRON
iajs-4047	122	13	to	to	PART
iajs-4047	122	14	find	find	VERB
iajs-4047	122	15	the	the	DET
iajs-4047	122	16	optimal	optimal	ADJ
iajs-4047	122	17	number	number	NOUN
iajs-4047	122	18	of	of	ADP
iajs-4047	122	19	clusters	cluster	NOUN
iajs-4047	122	20	.	.	PUNCT
iajs-4047	123	1	figures	figure	NOUN
iajs-4047	123	2	7	7	NUM
iajs-4047	123	3	and	and	CCONJ
iajs-4047	123	4	8	8	NUM
iajs-4047	123	5	.	.	PUNCT
iajs-4047	124	1	show	show	VERB
iajs-4047	124	2	the	the	DET
iajs-4047	124	3	steps	step	NOUN
iajs-4047	124	4	of	of	ADP
iajs-4047	124	5	this	this	DET
iajs-4047	124	6	algorithm	algorithm	NOUN
iajs-4047	124	7	.	.	PUNCT
iajs-4047	125	1	ihjpas	ihjpas	PROPN
iajs-4047	125	2	.	.	PUNCT
iajs-4047	126	1	2025	2025	NUM
iajs-4047	126	2	,	,	PUNCT
iajs-4047	126	3	38	38	NUM
iajs-4047	126	4	(	(	PUNCT
iajs-4047	126	5	2	2	NUM
iajs-4047	126	6	)	)	PUNCT
iajs-4047	126	7	431	431	NUM
iajs-4047	126	8	figure	figure	NOUN
iajs-4047	126	9	7	7	NUM
iajs-4047	126	10	.	.	PUNCT
iajs-4047	127	1	genetic	genetic	ADJ
iajs-4047	127	2	algorithm	algorithm	NOUN
iajs-4047	127	3	(	(	PUNCT
iajs-4047	127	4	23	23	NUM
iajs-4047	127	5	)	)	PUNCT
iajs-4047	127	6	figure	figure	NOUN
iajs-4047	127	7	8	8	NUM
iajs-4047	127	8	.	.	PUNCT
iajs-4047	127	9	flowchart	flowchart	NOUN
iajs-4047	127	10	of	of	ADP
iajs-4047	127	11	genetic	genetic	ADJ
iajs-4047	127	12	(	(	PUNCT
iajs-4047	127	13	24	24	NUM
iajs-4047	127	14	)	)	PUNCT
iajs-4047	127	15	2.3	2.3	NUM
iajs-4047	127	16	.	.	PUNCT
iajs-4047	128	1	how	how	SCONJ
iajs-4047	128	2	to	to	PART
iajs-4047	128	3	find	find	VERB
iajs-4047	128	4	the	the	DET
iajs-4047	128	5	optimal	optimal	ADJ
iajs-4047	128	6	number	number	NOUN
iajs-4047	128	7	of	of	ADP
iajs-4047	128	8	clusters	cluster	NOUN
iajs-4047	128	9	finding	find	VERB
iajs-4047	128	10	the	the	DET
iajs-4047	128	11	optimal	optimal	ADJ
iajs-4047	128	12	number	number	NOUN
iajs-4047	128	13	of	of	ADP
iajs-4047	128	14	clusters	cluster	NOUN
iajs-4047	128	15	in	in	ADP
iajs-4047	128	16	a	a	DET
iajs-4047	128	17	dataset	dataset	NOUN
iajs-4047	128	18	is	be	AUX
iajs-4047	128	19	a	a	DET
iajs-4047	128	20	crucial	crucial	ADJ
iajs-4047	128	21	step	step	NOUN
iajs-4047	128	22	in	in	ADP
iajs-4047	128	23	clustering	clustering	ADJ
iajs-4047	128	24	analysis	analysis	NOUN
iajs-4047	128	25	.	.	PUNCT
iajs-4047	129	1	several	several	ADJ
iajs-4047	129	2	methods	method	NOUN
iajs-4047	129	3	can	can	AUX
iajs-4047	129	4	help	help	VERB
iajs-4047	129	5	predict	predict	VERB
iajs-4047	129	6	the	the	DET
iajs-4047	129	7	optimal	optimal	ADJ
iajs-4047	129	8	number	number	NOUN
iajs-4047	129	9	of	of	ADP
iajs-4047	129	10	clusters	cluster	NOUN
iajs-4047	129	11	without	without	ADP
iajs-4047	129	12	relying	rely	VERB
iajs-4047	129	13	solely	solely	ADV
iajs-4047	129	14	on	on	ADP
iajs-4047	129	15	subjective	subjective	ADJ
iajs-4047	129	16	judgment	judgment	NOUN
iajs-4047	129	17	.	.	PUNCT
iajs-4047	130	1	here	here	ADV
iajs-4047	130	2	are	be	AUX
iajs-4047	130	3	some	some	DET
iajs-4047	130	4	common	common	ADJ
iajs-4047	130	5	techniques	technique	NOUN
iajs-4047	130	6	used	use	VERB
iajs-4047	130	7	to	to	PART
iajs-4047	130	8	find	find	VERB
iajs-4047	130	9	the	the	DET
iajs-4047	130	10	correct	correct	ADJ
iajs-4047	130	11	number	number	NOUN
iajs-4047	130	12	of	of	ADP
iajs-4047	130	13	clusters	cluster	NOUN
iajs-4047	130	14	:	:	PUNCT
iajs-4047	130	15	1	1	X
iajs-4047	130	16	.	.	X
iajs-4047	130	17	elbow	elbow	NOUN
iajs-4047	130	18	method	method	NOUN
iajs-4047	130	19	:	:	PUNCT
iajs-4047	130	20	it	it	PRON
iajs-4047	130	21	provides	provide	VERB
iajs-4047	130	22	a	a	DET
iajs-4047	130	23	visual	visual	ADJ
iajs-4047	130	24	cue	cue	NOUN
iajs-4047	130	25	to	to	PART
iajs-4047	130	26	determine	determine	VERB
iajs-4047	130	27	a	a	DET
iajs-4047	130	28	reasonable	reasonable	ADJ
iajs-4047	130	29	number	number	NOUN
iajs-4047	130	30	of	of	ADP
iajs-4047	130	31	clusters	cluster	NOUN
iajs-4047	130	32	(	(	PUNCT
iajs-4047	130	33	25	25	NUM
iajs-4047	130	34	)	)	PUNCT
iajs-4047	130	35	.	.	PUNCT
iajs-4047	131	1	it	it	PRON
iajs-4047	131	2	is	be	AUX
iajs-4047	131	3	simple	simple	ADJ
iajs-4047	131	4	and	and	CCONJ
iajs-4047	131	5	easy	easy	ADJ
iajs-4047	131	6	to	to	PART
iajs-4047	131	7	implement	implement	VERB
iajs-4047	131	8	and	and	CCONJ
iajs-4047	131	9	can	can	AUX
iajs-4047	131	10	calculate	calculate	VERB
iajs-4047	131	11	the	the	DET
iajs-4047	131	12	within	within	ADP
iajs-4047	131	13	-	-	PUNCT
iajs-4047	131	14	cluster	cluster	NOUN
iajs-4047	131	15	sum	sum	NOUN
iajs-4047	131	16	of	of	ADP
iajs-4047	131	17	squares	square	NOUN
iajs-4047	131	18	(	(	PUNCT
iajs-4047	131	19	wcss	wcss	ADJ
iajs-4047	131	20	)	)	PUNCT
iajs-4047	131	21	for	for	ADP
iajs-4047	131	22	a	a	DET
iajs-4047	131	23	range	range	NOUN
iajs-4047	131	24	of	of	ADP
iajs-4047	131	25	different	different	ADJ
iajs-4047	131	26	numbers	number	NOUN
iajs-4047	131	27	of	of	ADP
iajs-4047	131	28	clusters	cluster	NOUN
iajs-4047	131	29	and	and	CCONJ
iajs-4047	131	30	look	look	VERB
iajs-4047	131	31	for	for	ADP
iajs-4047	131	32	the	the	DET
iajs-4047	131	33	"	"	PUNCT
iajs-4047	131	34	elbow	elbow	NOUN
iajs-4047	131	35	point	point	NOUN
iajs-4047	131	36	"	"	PUNCT
iajs-4047	131	37	where	where	SCONJ
iajs-4047	131	38	the	the	DET
iajs-4047	131	39	rate	rate	NOUN
iajs-4047	131	40	of	of	ADP
iajs-4047	131	41	decrease	decrease	NOUN
iajs-4047	131	42	in	in	ADP
iajs-4047	131	43	wcss	wcss	PROPN
iajs-4047	131	44	slows	slow	VERB
iajs-4047	131	45	down	down	ADP
iajs-4047	131	46	.	.	PUNCT
iajs-4047	132	1	however	however	ADV
iajs-4047	132	2	,	,	PUNCT
iajs-4047	132	3	it	it	PRON
iajs-4047	132	4	may	may	AUX
iajs-4047	132	5	not	not	PART
iajs-4047	132	6	always	always	ADV
iajs-4047	132	7	produce	produce	VERB
iajs-4047	132	8	a	a	DET
iajs-4047	132	9	clear	clear	ADJ
iajs-4047	132	10	elbow	elbow	NOUN
iajs-4047	132	11	(	(	PUNCT
iajs-4047	132	12	smooth	smooth	ADJ
iajs-4047	132	13	elbow	elbow	NOUN
iajs-4047	132	14	)	)	PUNCT
iajs-4047	132	15	.	.	PUNCT
iajs-4047	133	1	2	2	X
iajs-4047	133	2	.	.	X
iajs-4047	133	3	silhouette	silhouette	NOUN
iajs-4047	133	4	coefficient	coefficient	NOUN
iajs-4047	133	5	:	:	PUNCT
iajs-4047	133	6	the	the	DET
iajs-4047	133	7	silhouette	silhouette	NOUN
iajs-4047	133	8	coefficient	coefficient	NOUN
iajs-4047	133	9	(	(	PUNCT
iajs-4047	133	10	sc	sc	PROPN
iajs-4047	133	11	)	)	PUNCT
iajs-4047	133	12	was	be	AUX
iajs-4047	133	13	established	establish	VERB
iajs-4047	133	14	to	to	PART
iajs-4047	133	15	quantify	quantify	VERB
iajs-4047	133	16	cluster	cluster	NOUN
iajs-4047	133	17	density	density	NOUN
iajs-4047	133	18	and	and	CCONJ
iajs-4047	133	19	separation	separation	NOUN
iajs-4047	133	20	(	(	PUNCT
iajs-4047	133	21	26	26	NUM
iajs-4047	133	22	)	)	PUNCT
iajs-4047	133	23	.	.	PUNCT
iajs-4047	134	1	it	it	PRON
iajs-4047	134	2	is	be	AUX
iajs-4047	134	3	limited	limit	VERB
iajs-4047	134	4	to	to	ADP
iajs-4047	134	5	the	the	DET
iajs-4047	134	6	interval	interval	NOUN
iajs-4047	134	7	[	[	X
iajs-4047	134	8	-1	-1	X
iajs-4047	134	9	,	,	PUNCT
iajs-4047	134	10	1	1	NUM
iajs-4047	134	11	]	]	PUNCT
iajs-4047	134	12	.	.	PUNCT
iajs-4047	135	1	it	it	PRON
iajs-4047	135	2	calculates	calculate	VERB
iajs-4047	135	3	the	the	DET
iajs-4047	135	4	average	average	ADJ
iajs-4047	135	5	silhouette	silhouette	NOUN
iajs-4047	135	6	score	score	NOUN
iajs-4047	135	7	for	for	ADP
iajs-4047	135	8	a	a	DET
iajs-4047	135	9	range	range	NOUN
iajs-4047	135	10	of	of	ADP
iajs-4047	135	11	different	different	ADJ
iajs-4047	135	12	numbers	number	NOUN
iajs-4047	135	13	of	of	ADP
iajs-4047	135	14	clusters	cluster	NOUN
iajs-4047	135	15	.	.	PUNCT
iajs-4047	136	1	the	the	DET
iajs-4047	136	2	silhouette	silhouette	NOUN
iajs-4047	136	3	score	score	NOUN
iajs-4047	136	4	indicates	indicate	VERB
iajs-4047	136	5	how	how	SCONJ
iajs-4047	136	6	similar	similar	ADJ
iajs-4047	136	7	an	an	DET
iajs-4047	136	8	object	object	NOUN
iajs-4047	136	9	is	be	AUX
iajs-4047	136	10	to	to	ADP
iajs-4047	136	11	its	its	PRON
iajs-4047	136	12	own	own	ADJ
iajs-4047	136	13	cluster	cluster	NOUN
iajs-4047	136	14	compared	compare	VERB
iajs-4047	136	15	to	to	ADP
iajs-4047	136	16	other	other	ADJ
iajs-4047	136	17	clusters	cluster	NOUN
iajs-4047	136	18	:	:	PUNCT
iajs-4047	136	19	𝑠𝑖	𝑠𝑖	PROPN
iajs-4047	136	20	=	=	SYM
iajs-4047	136	21	𝑏𝑖−𝑎𝑖	𝑏𝑖−𝑎𝑖	ADJ
iajs-4047	136	22	max⁡(𝑎𝑖,𝑏𝑖	max⁡(𝑎𝑖,𝑏𝑖	NOUN
iajs-4047	136	23	)	)	PUNCT
iajs-4047	136	24	⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡(1	⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡(1	NOUN
iajs-4047	136	25	)	)	PUNCT
iajs-4047	136	26	negative	negative	ADJ
iajs-4047	136	27	values	value	NOUN
iajs-4047	136	28	for	for	ADP
iajs-4047	136	29	a	a	DET
iajs-4047	136	30	point	point	NOUN
iajs-4047	136	31	indicate	indicate	VERB
iajs-4047	136	32	that	that	SCONJ
iajs-4047	136	33	the	the	DET
iajs-4047	136	34	instance	instance	NOUN
iajs-4047	136	35	is	be	AUX
iajs-4047	136	36	in	in	ADP
iajs-4047	136	37	the	the	DET
iajs-4047	136	38	wrong	wrong	ADJ
iajs-4047	136	39	cluster	cluster	NOUN
iajs-4047	136	40	.	.	PUNCT
iajs-4047	137	1	positive	positive	ADJ
iajs-4047	137	2	numbers	number	NOUN
iajs-4047	137	3	imply	imply	VERB
iajs-4047	137	4	accurate	accurate	ADJ
iajs-4047	137	5	and	and	CCONJ
iajs-4047	137	6	dense	dense	ADJ
iajs-4047	137	7	clustering	clustering	NOUN
iajs-4047	137	8	,	,	PUNCT
iajs-4047	137	9	with	with	ADP
iajs-4047	137	10	larger	large	ADJ
iajs-4047	137	11	values	value	NOUN
iajs-4047	137	12	suggesting	suggest	VERB
iajs-4047	137	13	a	a	DET
iajs-4047	137	14	bigger	big	ADJ
iajs-4047	137	15	ratio	ratio	NOUN
iajs-4047	137	16	of	of	ADP
iajs-4047	137	17	bi	bi	ADJ
iajs-4047	137	18	values	value	NOUN
iajs-4047	137	19	to	to	PART
iajs-4047	137	20	(	(	PUNCT
iajs-4047	137	21	ai	ai	VERB
iajs-4047	137	22	)	)	PUNCT
iajs-4047	137	23	values	value	NOUN
iajs-4047	137	24	.	.	PUNCT
iajs-4047	138	1	this	this	PRON
iajs-4047	138	2	means	mean	VERB
iajs-4047	138	3	that	that	SCONJ
iajs-4047	138	4	instance	instance	NOUN
iajs-4047	138	5	i	i	PRON
iajs-4047	138	6	is	be	AUX
iajs-4047	138	7	more	more	ADV
iajs-4047	138	8	similar	similar	ADJ
iajs-4047	138	9	to	to	ADP
iajs-4047	138	10	other	other	ADJ
iajs-4047	138	11	instances	instance	NOUN
iajs-4047	138	12	in	in	ADP
iajs-4047	138	13	its	its	PRON
iajs-4047	138	14	own	own	ADJ
iajs-4047	138	15	cluster	cluster	NOUN
iajs-4047	138	16	than	than	ADP
iajs-4047	138	17	to	to	ADP
iajs-4047	138	18	instances	instance	NOUN
iajs-4047	138	19	in	in	ADP
iajs-4047	138	20	the	the	DET
iajs-4047	138	21	next	next	ADJ
iajs-4047	138	22	closest	close	ADJ
iajs-4047	138	23	cluster	cluster	NOUN
iajs-4047	138	24	.	.	PUNCT
iajs-4047	139	1	values	value	NOUN
iajs-4047	139	2	around	around	ADP
iajs-4047	139	3	zero	zero	NUM
iajs-4047	139	4	suggest	suggest	VERB
iajs-4047	139	5	that	that	SCONJ
iajs-4047	139	6	the	the	DET
iajs-4047	139	7	clusters	cluster	NOUN
iajs-4047	139	8	are	be	AUX
iajs-4047	139	9	overlapping	overlap	VERB
iajs-4047	139	10	(	(	PUNCT
iajs-4047	139	11	27	27	NUM
iajs-4047	139	12	)	)	PUNCT
iajs-4047	139	13	.	.	PUNCT
iajs-4047	140	1	it	it	PRON
iajs-4047	140	2	is	be	AUX
iajs-4047	140	3	,	,	PUNCT
iajs-4047	140	4	computationally	computationally	ADV
iajs-4047	140	5	,	,	PUNCT
iajs-4047	140	6	more	more	ADV
iajs-4047	140	7	expensive	expensive	ADJ
iajs-4047	140	8	than	than	ADP
iajs-4047	140	9	the	the	DET
iajs-4047	140	10	elbow	elbow	NOUN
iajs-4047	140	11	method	method	NOUN
iajs-4047	140	12	.	.	PUNCT
iajs-4047	141	1	3	3	X
iajs-4047	141	2	.	.	X
iajs-4047	141	3	gap	gap	NOUN
iajs-4047	141	4	statistic	statistic	NOUN
iajs-4047	141	5	:	:	PUNCT
iajs-4047	141	6	it	it	PRON
iajs-4047	141	7	compares	compare	VERB
iajs-4047	141	8	the	the	DET
iajs-4047	141	9	within	within	ADP
iajs-4047	141	10	-	-	PUNCT
iajs-4047	141	11	cluster	cluster	NOUN
iajs-4047	141	12	dispersion	dispersion	NOUN
iajs-4047	141	13	for	for	ADP
iajs-4047	141	14	different	different	ADJ
iajs-4047	141	15	numbers	number	NOUN
iajs-4047	141	16	of	of	ADP
iajs-4047	141	17	clusters	cluster	NOUN
iajs-4047	141	18	with	with	ADP
iajs-4047	141	19	what	what	PRON
iajs-4047	141	20	would	would	AUX
iajs-4047	141	21	be	be	AUX
iajs-4047	141	22	expected	expect	VERB
iajs-4047	141	23	by	by	ADP
iajs-4047	141	24	random	random	ADJ
iajs-4047	141	25	chance	chance	NOUN
iajs-4047	141	26	(	(	PUNCT
iajs-4047	141	27	28	28	NUM
iajs-4047	141	28	)	)	PUNCT
iajs-4047	141	29	.	.	PUNCT
iajs-4047	142	1	the	the	DET
iajs-4047	142	2	right	right	ADJ
iajs-4047	142	3	number	number	NOUN
iajs-4047	142	4	of	of	ADP
iajs-4047	142	5	clusters	cluster	NOUN
iajs-4047	142	6	is	be	AUX
iajs-4047	142	7	where	where	SCONJ
iajs-4047	142	8	the	the	DET
iajs-4047	142	9	gap	gap	NOUN
iajs-4047	142	10	statistic	statistic	NOUN
iajs-4047	142	11	is	be	AUX
iajs-4047	142	12	maximized	maximize	VERB
iajs-4047	142	13	:	:	PUNCT
iajs-4047	142	14	ihjpas	ihjpas	PROPN
iajs-4047	142	15	.	.	PUNCT
iajs-4047	143	1	2025	2025	NUM
iajs-4047	143	2	,	,	PUNCT
iajs-4047	143	3	38	38	NUM
iajs-4047	143	4	(	(	PUNCT
iajs-4047	143	5	2	2	NUM
iajs-4047	143	6	)	)	PUNCT
iajs-4047	143	7	432	432	NUM
iajs-4047	143	8	⁡⁡⁡𝐺𝑎𝑝⁡(𝑘	⁡⁡⁡𝐺𝑎𝑝⁡(𝑘	NOUN
iajs-4047	143	9	)	)	PUNCT
iajs-4047	143	10	=	=	PUNCT
iajs-4047	143	11	log	log	VERB
iajs-4047	143	12	⁡(wk	⁡(wk	NOUN
iajs-4047	143	13	∗	∗	NOUN
iajs-4047	143	14	)	)	PUNCT
iajs-4047	144	1	−	−	ADP
iajs-4047	144	2	log(𝑊𝑘)⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡(2	log(𝑊𝑘)⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡(2	PROPN
iajs-4047	144	3	)	)	PUNCT
iajs-4047	145	1			NOUN
iajs-4047	145	2	advantages	advantage	NOUN
iajs-4047	145	3	:	:	PUNCT
iajs-4047	145	4	i.	i.	NOUN
iajs-4047	145	5	accounts	account	VERB
iajs-4047	145	6	for	for	ADP
iajs-4047	145	7	the	the	DET
iajs-4047	145	8	randomness	randomness	NOUN
iajs-4047	145	9	in	in	ADP
iajs-4047	145	10	the	the	DET
iajs-4047	145	11	data	datum	NOUN
iajs-4047	145	12	.	.	PUNCT
iajs-4047	146	1	ii	ii	PROPN
iajs-4047	146	2	.	.	PROPN
iajs-4047	146	3	helps	help	VERB
iajs-4047	146	4	avoid	avoid	VERB
iajs-4047	146	5	overfitting	overfitte	VERB
iajs-4047	146	6	.	.	PUNCT
iajs-4047	147	1			X
iajs-4047	147	2	disadvantages	disadvantage	VERB
iajs-4047	147	3	:	:	PUNCT
iajs-4047	147	4	i.	i.	NOUN
iajs-4047	147	5	computationally	computationally	ADV
iajs-4047	147	6	intensive	intensive	ADJ
iajs-4047	147	7	.	.	PUNCT
iajs-4047	148	1	ii	ii	PROPN
iajs-4047	148	2	.	.	PROPN
iajs-4047	148	3	requires	require	VERB
iajs-4047	148	4	generating	generate	VERB
iajs-4047	148	5	random	random	ADJ
iajs-4047	148	6	data	datum	NOUN
iajs-4047	148	7	for	for	ADP
iajs-4047	148	8	comparison	comparison	NOUN
iajs-4047	148	9	.	.	PUNCT
iajs-4047	149	1	4	4	X
iajs-4047	149	2	.	.	X
iajs-4047	149	3	davies	davy	NOUN
iajs-4047	149	4	–	–	PUNCT
iajs-4047	149	5	bouldin	bouldin	NOUN
iajs-4047	149	6	index	index	NOUN
iajs-4047	149	7	method	method	NOUN
iajs-4047	149	8	:	:	PUNCT
iajs-4047	149	9	computes	compute	VERB
iajs-4047	149	10	the	the	DET
iajs-4047	149	11	average	average	ADJ
iajs-4047	149	12	similarity	similarity	NOUN
iajs-4047	149	13	measure	measure	NOUN
iajs-4047	149	14	between	between	ADP
iajs-4047	149	15	each	each	DET
iajs-4047	149	16	cluster	cluster	NOUN
iajs-4047	149	17	and	and	CCONJ
iajs-4047	149	18	its	its	PRON
iajs-4047	149	19	most	most	ADV
iajs-4047	149	20	similar	similar	ADJ
iajs-4047	149	21	one	one	NUM
iajs-4047	149	22	.	.	PUNCT
iajs-4047	150	1	the	the	DET
iajs-4047	150	2	right	right	ADJ
iajs-4047	150	3	number	number	NOUN
iajs-4047	150	4	of	of	ADP
iajs-4047	150	5	clusters	cluster	NOUN
iajs-4047	150	6	minimizes	minimize	VERB
iajs-4047	150	7	this	this	DET
iajs-4047	150	8	index	index	NOUN
iajs-4047	150	9	.	.	PUNCT
iajs-4047	151	1	it	it	PRON
iajs-4047	151	2	is	be	AUX
iajs-4047	151	3	a	a	DET
iajs-4047	151	4	measure	measure	NOUN
iajs-4047	151	5	of	of	ADP
iajs-4047	151	6	the	the	DET
iajs-4047	151	7	clustering	clustering	ADJ
iajs-4047	151	8	quality	quality	NOUN
iajs-4047	151	9	and	and	CCONJ
iajs-4047	151	10	can	can	AUX
iajs-4047	151	11	be	be	AUX
iajs-4047	151	12	used	use	VERB
iajs-4047	151	13	to	to	PART
iajs-4047	151	14	evaluate	evaluate	VERB
iajs-4047	151	15	the	the	DET
iajs-4047	151	16	clustering	clustering	ADJ
iajs-4047	151	17	results	result	NOUN
iajs-4047	151	18	.	.	PUNCT
iajs-4047	152	1	it	it	PRON
iajs-4047	152	2	is	be	AUX
iajs-4047	152	3	based	base	VERB
iajs-4047	152	4	on	on	ADP
iajs-4047	152	5	the	the	DET
iajs-4047	152	6	average	average	ADJ
iajs-4047	152	7	similarity	similarity	NOUN
iajs-4047	152	8	between	between	ADP
iajs-4047	152	9	each	each	DET
iajs-4047	152	10	cluster	cluster	NOUN
iajs-4047	152	11	and	and	CCONJ
iajs-4047	152	12	its	its	PRON
iajs-4047	152	13	most	most	ADV
iajs-4047	152	14	similar	similar	ADJ
iajs-4047	152	15	one	one	NOUN
iajs-4047	152	16	,	,	PUNCT
iajs-4047	152	17	and	and	CCONJ
iajs-4047	152	18	the	the	DET
iajs-4047	152	19	average	average	ADJ
iajs-4047	152	20	dissimilarity	dissimilarity	NOUN
iajs-4047	152	21	between	between	ADP
iajs-4047	152	22	cluster	cluster	NOUN
iajs-4047	152	23	centers	center	NOUN
iajs-4047	152	24	(	(	PUNCT
iajs-4047	152	25	29	29	NUM
iajs-4047	152	26	)	)	PUNCT
iajs-4047	152	27	.	.	PUNCT
iajs-4047	153	1	the	the	DET
iajs-4047	153	2	davis	davis	PROPN
iajs-4047	153	3	-	-	PUNCT
iajs-4047	153	4	bouldin	bouldin	NOUN
iajs-4047	153	5	index	index	NOUN
iajs-4047	153	6	is	be	AUX
iajs-4047	153	7	calculated	calculate	VERB
iajs-4047	153	8	using	use	VERB
iajs-4047	153	9	the	the	DET
iajs-4047	153	10	following	follow	VERB
iajs-4047	153	11	formula	formula	NOUN
iajs-4047	153	12	:	:	PUNCT
iajs-4047	153	13	⁡𝐷𝐵	⁡𝐷𝐵	NOUN
iajs-4047	153	14	=	=	SYM
iajs-4047	153	15	1	1	NUM
iajs-4047	153	16	k	k	NOUN
iajs-4047	153	17	⁡∑	⁡∑	NUM
iajs-4047	153	18	⁡𝑚𝑎𝑥	⁡𝑚𝑎𝑥	NOUN
iajs-4047	153	19	(	(	PUNCT
iajs-4047	153	20	𝜎𝑖+𝜎𝑗	𝜎𝑖+𝜎𝑗	X
iajs-4047	153	21	𝑑(𝑐𝑖,𝑐𝑗	𝑑(𝑐𝑖,𝑐𝑗	NOUN
iajs-4047	153	22	)	)	PUNCT
iajs-4047	153	23	)	)	PUNCT
iajs-4047	154	1	𝑘	𝑘	PRON
iajs-4047	154	2	𝑖=1	𝑖=1	PROPN
iajs-4047	154	3	⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡(3	⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡⁡(3	PROPN
iajs-4047	154	4	)	)	PUNCT
iajs-4047	154	5	where	where	SCONJ
iajs-4047	154	6	:	:	PUNCT
iajs-4047	154	7	k	k	X
iajs-4047	154	8	is	be	AUX
iajs-4047	154	9	the	the	DET
iajs-4047	154	10	number	number	NOUN
iajs-4047	154	11	of	of	ADP
iajs-4047	154	12	clusters	cluster	NOUN
iajs-4047	154	13	.	.	PUNCT
iajs-4047	155	1	𝛔i	𝛔i	PROPN
iajs-4047	155	2	is	be	AUX
iajs-4047	155	3	the	the	DET
iajs-4047	155	4	average	average	ADJ
iajs-4047	155	5	distance	distance	NOUN
iajs-4047	155	6	between	between	ADP
iajs-4047	155	7	pointsin	pointsin	NOUN
iajs-4047	155	8	cluster	cluster	NOUN
iajs-4047	155	9	i	i	PRON
iajs-4047	155	10	and	and	CCONJ
iajs-4047	155	11	the	the	DET
iajs-4047	155	12	centroid	centroid	NOUN
iajs-4047	155	13	of	of	ADP
iajs-4047	155	14	cluster	cluster	NOUN
iajs-4047	155	15	i.	i.	PROPN
iajs-4047	155	16	𝛔j	𝛔j	PROPN
iajs-4047	155	17	is	be	AUX
iajs-4047	155	18	the	the	DET
iajs-4047	155	19	average	average	ADJ
iajs-4047	155	20	dustance	dustance	NOUN
iajs-4047	155	21	between	between	ADP
iajs-4047	155	22	points	point	NOUN
iajs-4047	155	23	cluster	cluster	NOUN
iajs-4047	155	24	j	j	PROPN
iajs-4047	155	25	and	and	CCONJ
iajs-4047	155	26	the	the	DET
iajs-4047	155	27	centriod	centriod	NOUN
iajs-4047	155	28	of	of	ADP
iajs-4047	155	29	cluster	cluster	NOUN
iajs-4047	155	30	j.	j.	PROPN
iajs-4047	155	31	d(ci	d(ci	PROPN
iajs-4047	155	32	,	,	PUNCT
iajs-4047	155	33	cj	cj	NOUN
iajs-4047	155	34	)	)	PUNCT
iajs-4047	155	35	is	be	AUX
iajs-4047	155	36	the	the	DET
iajs-4047	155	37	distance	distance	NOUN
iajs-4047	155	38	between	between	ADP
iajs-4047	155	39	the	the	DET
iajs-4047	155	40	centroids	centroid	NOUN
iajs-4047	155	41	of	of	ADP
iajs-4047	155	42	clusters	cluster	NOUN
iajs-4047	155	43	i	i	PRON
iajs-4047	155	44	and	and	CCONJ
iajs-4047	155	45	j.	j.	PROPN
iajs-4047	155	46			NOUN
iajs-4047	155	47	advantages	advantage	NOUN
iajs-4047	155	48	:	:	PUNCT
iajs-4047	155	49	i.	i.	NOUN
iajs-4047	155	50	provides	provide	VERB
iajs-4047	155	51	a	a	DET
iajs-4047	155	52	measure	measure	NOUN
iajs-4047	155	53	of	of	ADP
iajs-4047	155	54	the	the	DET
iajs-4047	155	55	clustering	clustering	ADJ
iajs-4047	155	56	quality	quality	NOUN
iajs-4047	155	57	.	.	PUNCT
iajs-4047	156	1	ii	ii	PROPN
iajs-4047	156	2	.	.	PROPN
iajs-4047	156	3	encourages	encourage	VERB
iajs-4047	156	4	clusters	cluster	NOUN
iajs-4047	156	5	to	to	PART
iajs-4047	156	6	be	be	AUX
iajs-4047	156	7	well	well	ADV
iajs-4047	156	8	separated	separate	VERB
iajs-4047	156	9	.	.	PUNCT
iajs-4047	157	1			X
iajs-4047	157	2	disadvantages	disadvantage	VERB
iajs-4047	157	3	:	:	PUNCT
iajs-4047	157	4	i.	i.	NOUN
iajs-4047	157	5	requires	require	VERB
iajs-4047	157	6	distance	distance	NOUN
iajs-4047	157	7	/	/	SYM
iajs-4047	157	8	similarity	similarity	NOUN
iajs-4047	157	9	measure	measure	NOUN
iajs-4047	157	10	between	between	ADP
iajs-4047	157	11	clusters	cluster	NOUN
iajs-4047	157	12	.	.	PUNCT
iajs-4047	158	1	ii	ii	PROPN
iajs-4047	158	2	.	.	PUNCT
iajs-4047	158	3	not	not	PART
iajs-4047	158	4	as	as	ADV
iajs-4047	158	5	widely	widely	ADV
iajs-4047	158	6	used	use	VERB
iajs-4047	158	7	as	as	ADP
iajs-4047	158	8	some	some	DET
iajs-4047	158	9	other	other	ADJ
iajs-4047	158	10	methods	method	NOUN
iajs-4047	158	11	.	.	PUNCT
iajs-4047	159	1	2.4	2.4	NUM
iajs-4047	159	2	.	.	PUNCT
iajs-4047	160	1	our	our	PRON
iajs-4047	160	2	proposal	proposal	NOUN
iajs-4047	160	3	this	this	DET
iajs-4047	160	4	section	section	NOUN
iajs-4047	160	5	describes	describe	VERB
iajs-4047	160	6	the	the	DET
iajs-4047	160	7	steps	step	NOUN
iajs-4047	160	8	to	to	PART
iajs-4047	160	9	discover	discover	VERB
iajs-4047	160	10	the	the	DET
iajs-4047	160	11	appropriate	appropriate	ADJ
iajs-4047	160	12	number	number	NOUN
iajs-4047	160	13	of	of	ADP
iajs-4047	160	14	clusters	cluster	NOUN
iajs-4047	160	15	.	.	PUNCT
iajs-4047	161	1	genetic	genetic	ADJ
iajs-4047	161	2	algorithm	algorithm	NOUN
iajs-4047	161	3	(	(	PUNCT
iajs-4047	161	4	ga	ga	NOUN
iajs-4047	161	5	)	)	PUNCT
iajs-4047	161	6	implementation	implementation	NOUN
iajs-4047	161	7	for	for	ADP
iajs-4047	161	8	finding	find	VERB
iajs-4047	161	9	the	the	DET
iajs-4047	161	10	ideal	ideal	ADJ
iajs-4047	161	11	number	number	NOUN
iajs-4047	161	12	of	of	ADP
iajs-4047	161	13	clusters	cluster	NOUN
iajs-4047	161	14	(	(	PUNCT
iajs-4047	161	15	k	k	NOUN
iajs-4047	161	16	)	)	PUNCT
iajs-4047	161	17	,	,	PUNCT
iajs-4047	161	18	the	the	DET
iajs-4047	161	19	individual	individual	ADJ
iajs-4047	161	20	representation	representation	NOUN
iajs-4047	161	21	is	be	AUX
iajs-4047	161	22	based	base	VERB
iajs-4047	161	23	on	on	ADP
iajs-4047	161	24	the	the	DET
iajs-4047	161	25	choice	choice	NOUN
iajs-4047	161	26	of	of	ADP
iajs-4047	161	27	the	the	DET
iajs-4047	161	28	number	number	NOUN
iajs-4047	161	29	of	of	ADP
iajs-4047	161	30	clusters	cluster	NOUN
iajs-4047	161	31	(	(	PUNCT
iajs-4047	161	32	k	k	NOUN
iajs-4047	161	33	)	)	PUNCT
iajs-4047	161	34	for	for	ADP
iajs-4047	161	35	each	each	DET
iajs-4047	161	36	member	member	NOUN
iajs-4047	161	37	of	of	ADP
iajs-4047	161	38	the	the	DET
iajs-4047	161	39	population	population	NOUN
iajs-4047	161	40	.	.	PUNCT
iajs-4047	162	1	each	each	DET
iajs-4047	162	2	individual	individual	ADJ
iajs-4047	162	3	(	(	PUNCT
iajs-4047	162	4	solution	solution	NOUN
iajs-4047	162	5	)	)	PUNCT
iajs-4047	162	6	in	in	ADP
iajs-4047	162	7	the	the	DET
iajs-4047	162	8	population	population	NOUN
iajs-4047	162	9	represents	represent	VERB
iajs-4047	162	10	a	a	DET
iajs-4047	162	11	potential	potential	ADJ
iajs-4047	162	12	solution	solution	NOUN
iajs-4047	162	13	,	,	PUNCT
iajs-4047	162	14	which	which	PRON
iajs-4047	162	15	is	be	AUX
iajs-4047	162	16	a	a	DET
iajs-4047	162	17	possible	possible	ADJ
iajs-4047	162	18	value	value	NOUN
iajs-4047	162	19	for	for	ADP
iajs-4047	162	20	the	the	DET
iajs-4047	162	21	number	number	NOUN
iajs-4047	162	22	of	of	ADP
iajs-4047	162	23	clusters	cluster	NOUN
iajs-4047	162	24	.	.	PUNCT
iajs-4047	163	1	the	the	DET
iajs-4047	163	2	genetic	genetic	ADJ
iajs-4047	163	3	algorithm	algorithm	NOUN
iajs-4047	163	4	uses	use	VERB
iajs-4047	163	5	an	an	DET
iajs-4047	163	6	integer	integer	NOUN
iajs-4047	163	7	encoding	encoding	NOUN
iajs-4047	163	8	for	for	ADP
iajs-4047	163	9	the	the	DET
iajs-4047	163	10	representation	representation	NOUN
iajs-4047	163	11	of	of	ADP
iajs-4047	163	12	individuals	individual	NOUN
iajs-4047	163	13	.	.	PUNCT
iajs-4047	164	1	each	each	DET
iajs-4047	164	2	gene	gene	NOUN
iajs-4047	164	3	in	in	ADP
iajs-4047	164	4	the	the	DET
iajs-4047	164	5	chromosome	chromosome	NOUN
iajs-4047	164	6	represents	represent	VERB
iajs-4047	164	7	a	a	DET
iajs-4047	164	8	potential	potential	ADJ
iajs-4047	164	9	value	value	NOUN
iajs-4047	164	10	for	for	ADP
iajs-4047	164	11	the	the	DET
iajs-4047	164	12	number	number	NOUN
iajs-4047	164	13	of	of	ADP
iajs-4047	164	14	clusters	cluster	NOUN
iajs-4047	164	15	(	(	PUNCT
iajs-4047	164	16	k	k	NOUN
iajs-4047	164	17	)	)	PUNCT
iajs-4047	164	18	within	within	ADP
iajs-4047	164	19	the	the	DET
iajs-4047	164	20	specified	specified	ADJ
iajs-4047	164	21	range	range	NOUN
iajs-4047	164	22	(	(	PUNCT
iajs-4047	164	23	k_min	k_min	NOUN
iajs-4047	164	24	to	to	PART
iajs-4047	164	25	k_max	k_max	PROPN
iajs-4047	164	26	)	)	PUNCT
iajs-4047	164	27	.	.	PUNCT
iajs-4047	165	1	the	the	DET
iajs-4047	165	2	chromosome	chromosome	NOUN
iajs-4047	165	3	represents	represent	VERB
iajs-4047	165	4	an	an	DET
iajs-4047	165	5	individual	individual	NOUN
iajs-4047	165	6	in	in	ADP
iajs-4047	165	7	the	the	DET
iajs-4047	165	8	population	population	NOUN
iajs-4047	165	9	.	.	PUNCT
iajs-4047	166	1	each	each	DET
iajs-4047	166	2	gene	gene	NOUN
iajs-4047	166	3	in	in	ADP
iajs-4047	166	4	the	the	DET
iajs-4047	166	5	chromosome	chromosome	NOUN
iajs-4047	166	6	represents	represent	VERB
iajs-4047	166	7	a	a	DET
iajs-4047	166	8	potential	potential	ADJ
iajs-4047	166	9	value	value	NOUN
iajs-4047	166	10	for	for	ADP
iajs-4047	166	11	the	the	DET
iajs-4047	166	12	number	number	NOUN
iajs-4047	166	13	of	of	ADP
iajs-4047	166	14	clusters	cluster	NOUN
iajs-4047	166	15	(	(	PUNCT
iajs-4047	166	16	k	k	NOUN
iajs-4047	166	17	)	)	PUNCT
iajs-4047	166	18	.	.	PUNCT
iajs-4047	167	1	the	the	DET
iajs-4047	167	2	range	range	NOUN
iajs-4047	167	3	of	of	ADP
iajs-4047	167	4	possible	possible	ADJ
iajs-4047	167	5	values	value	NOUN
iajs-4047	167	6	for	for	ADP
iajs-4047	167	7	each	each	DET
iajs-4047	167	8	gene	gene	NOUN
iajs-4047	167	9	is	be	AUX
iajs-4047	167	10	between	between	ADP
iajs-4047	167	11	k_min	k_min	PROPN
iajs-4047	167	12	and	and	CCONJ
iajs-4047	167	13	k_max	k_max	PROPN
iajs-4047	167	14	.	.	PUNCT
iajs-4047	168	1	the	the	DET
iajs-4047	168	2	encoding	encoding	NOUN
iajs-4047	168	3	is	be	AUX
iajs-4047	168	4	based	base	VERB
iajs-4047	168	5	on	on	ADP
iajs-4047	168	6	an	an	DET
iajs-4047	168	7	integer	integer	NOUN
iajs-4047	168	8	representation	representation	NOUN
iajs-4047	168	9	where	where	SCONJ
iajs-4047	168	10	each	each	DET
iajs-4047	168	11	gene	gene	NOUN
iajs-4047	168	12	corresponds	correspond	VERB
iajs-4047	168	13	to	to	ADP
iajs-4047	168	14	a	a	DET
iajs-4047	168	15	specific	specific	ADJ
iajs-4047	168	16	value	value	NOUN
iajs-4047	168	17	for	for	ADP
iajs-4047	168	18	k.	k.	PROPN
iajs-4047	168	19	the	the	DET
iajs-4047	168	20	population	population	NOUN
iajs-4047	168	21	is	be	AUX
iajs-4047	168	22	initialized	initialize	VERB
iajs-4047	168	23	with	with	ADP
iajs-4047	168	24	random	random	ADJ
iajs-4047	168	25	integers	integer	NOUN
iajs-4047	168	26	within	within	ADP
iajs-4047	168	27	the	the	DET
iajs-4047	168	28	range	range	NOUN
iajs-4047	168	29	1	1	NUM
iajs-4047	168	30	to	to	PART
iajs-4047	168	31	len	len	PROPN
iajs-4047	168	32	(	(	PUNCT
iajs-4047	168	33	gaps	gap	NOUN
iajs-4047	168	34	)	)	PUNCT
iajs-4047	168	35	,	,	PUNCT
iajs-4047	168	36	representing	represent	VERB
iajs-4047	168	37	potential	potential	ADJ
iajs-4047	168	38	values	value	NOUN
iajs-4047	168	39	for	for	ADP
iajs-4047	168	40	k.	k.	PROPN
iajs-4047	168	41	each	each	DET
iajs-4047	168	42	individual	individual	NOUN
iajs-4047	168	43	's	's	PART
iajs-4047	168	44	fitness	fitness	NOUN
iajs-4047	168	45	is	be	AUX
iajs-4047	168	46	evaluated	evaluate	VERB
iajs-4047	168	47	based	base	VERB
iajs-4047	168	48	on	on	ADP
iajs-4047	168	49	the	the	DET
iajs-4047	168	50	gap	gap	NOUN
iajs-4047	168	51	statistic	statistic	NOUN
iajs-4047	168	52	values	value	NOUN
iajs-4047	168	53	.	.	PUNCT
iajs-4047	169	1	individuals	individual	NOUN
iajs-4047	169	2	with	with	ADP
iajs-4047	169	3	better	well	ADJ
iajs-4047	169	4	fitness	fitness	NOUN
iajs-4047	169	5	values	value	NOUN
iajs-4047	169	6	are	be	AUX
iajs-4047	169	7	selected	select	VERB
iajs-4047	169	8	for	for	ADP
iajs-4047	169	9	the	the	DET
iajs-4047	169	10	next	next	ADJ
iajs-4047	169	11	generation	generation	NOUN
iajs-4047	169	12	.	.	PUNCT
iajs-4047	170	1	during	during	ADP
iajs-4047	170	2	the	the	DET
iajs-4047	170	3	crossover	crossover	NOUN
iajs-4047	170	4	stage	stage	NOUN
iajs-4047	170	5	,	,	PUNCT
iajs-4047	170	6	selected	select	VERB
iajs-4047	170	7	individuals	individual	NOUN
iajs-4047	170	8	are	be	AUX
iajs-4047	170	9	combined	combine	VERB
iajs-4047	170	10	to	to	PART
iajs-4047	170	11	produce	produce	VERB
iajs-4047	170	12	offspring	offspring	NOUN
iajs-4047	170	13	with	with	ADP
iajs-4047	170	14	a	a	DET
iajs-4047	170	15	mix	mix	NOUN
iajs-4047	170	16	of	of	ADP
iajs-4047	170	17	genes	gene	NOUN
iajs-4047	170	18	from	from	ADP
iajs-4047	170	19	the	the	DET
iajs-4047	170	20	selected	select	VERB
iajs-4047	170	21	parents	parent	NOUN
iajs-4047	170	22	.	.	PUNCT
iajs-4047	171	1	then	then	ADV
iajs-4047	171	2	,	,	PUNCT
iajs-4047	171	3	the	the	DET
iajs-4047	171	4	mutation	mutation	NOUN
iajs-4047	171	5	randomly	randomly	ADV
iajs-4047	171	6	changes	change	VERB
iajs-4047	171	7	some	some	DET
iajs-4047	171	8	genes	gene	NOUN
iajs-4047	171	9	in	in	ADP
iajs-4047	171	10	the	the	DET
iajs-4047	171	11	offspring	offspring	NOUN
iajs-4047	171	12	to	to	PART
iajs-4047	171	13	introduce	introduce	VERB
iajs-4047	171	14	diversity	diversity	NOUN
iajs-4047	171	15	in	in	ADP
iajs-4047	171	16	the	the	DET
iajs-4047	171	17	population	population	NOUN
iajs-4047	171	18	.	.	PUNCT
iajs-4047	172	1	in	in	ADP
iajs-4047	172	2	the	the	DET
iajs-4047	172	3	gap	gap	NOUN
iajs-4047	172	4	statistic	statistic	NOUN
iajs-4047	172	5	strategy	strategy	NOUN
iajs-4047	172	6	for	for	ADP
iajs-4047	172	7	determining	determine	VERB
iajs-4047	172	8	the	the	DET
iajs-4047	172	9	optimal	optimal	ADJ
iajs-4047	172	10	number	number	NOUN
iajs-4047	172	11	of	of	ADP
iajs-4047	172	12	clusters	cluster	NOUN
iajs-4047	172	13	in	in	ADP
iajs-4047	172	14	a	a	DET
iajs-4047	172	15	ihjpas	ihjpa	NOUN
iajs-4047	172	16	.	.	PUNCT
iajs-4047	173	1	2025	2025	NUM
iajs-4047	173	2	,	,	PUNCT
iajs-4047	173	3	38	38	NUM
iajs-4047	173	4	(	(	PUNCT
iajs-4047	173	5	2	2	NUM
iajs-4047	173	6	)	)	PUNCT
iajs-4047	173	7	433	433	NUM
iajs-4047	173	8	dataset	dataset	NOUN
iajs-4047	173	9	,	,	PUNCT
iajs-4047	173	10	generating	generate	VERB
iajs-4047	173	11	appropriate	appropriate	ADJ
iajs-4047	173	12	reference	reference	NOUN
iajs-4047	173	13	data	datum	NOUN
iajs-4047	173	14	is	be	AUX
iajs-4047	173	15	crucial	crucial	ADJ
iajs-4047	173	16	for	for	ADP
iajs-4047	173	17	comparing	compare	VERB
iajs-4047	173	18	the	the	DET
iajs-4047	173	19	within	within	ADJ
iajs-4047	173	20	-	-	PUNCT
iajs-4047	173	21	cluster	cluster	NOUN
iajs-4047	173	22	dispersion	dispersion	NOUN
iajs-4047	173	23	of	of	ADP
iajs-4047	173	24	the	the	DET
iajs-4047	173	25	original	original	ADJ
iajs-4047	173	26	data	datum	NOUN
iajs-4047	173	27	by	by	ADP
iajs-4047	173	28	using	use	VERB
iajs-4047	173	29	uniform	uniform	ADJ
iajs-4047	173	30	distribution	distribution	NOUN
iajs-4047	173	31	,	,	PUNCT
iajs-4047	173	32	which	which	PRON
iajs-4047	173	33	is	be	AUX
iajs-4047	173	34	the	the	DET
iajs-4047	173	35	points	point	NOUN
iajs-4047	173	36	that	that	PRON
iajs-4047	173	37	are	be	AUX
iajs-4047	173	38	randomly	randomly	ADV
iajs-4047	173	39	distributed	distribute	VERB
iajs-4047	173	40	within	within	ADP
iajs-4047	173	41	the	the	DET
iajs-4047	173	42	same	same	ADJ
iajs-4047	173	43	range	range	NOUN
iajs-4047	173	44	as	as	ADP
iajs-4047	173	45	the	the	DET
iajs-4047	173	46	original	original	ADJ
iajs-4047	173	47	data	datum	NOUN
iajs-4047	173	48	,	,	PUNCT
iajs-4047	173	49	ensuring	ensure	VERB
iajs-4047	173	50	that	that	SCONJ
iajs-4047	173	51	reference	reference	NOUN
iajs-4047	173	52	data	datum	NOUN
iajs-4047	173	53	.	.	PUNCT
iajs-4047	174	1	the	the	DET
iajs-4047	174	2	gap	gap	NOUN
iajs-4047	174	3	statistic	statistic	NOUN
iajs-4047	174	4	is	be	AUX
iajs-4047	174	5	calculated	calculate	VERB
iajs-4047	174	6	as	as	ADP
iajs-4047	174	7	the	the	DET
iajs-4047	174	8	difference	difference	NOUN
iajs-4047	174	9	between	between	ADP
iajs-4047	174	10	the	the	DET
iajs-4047	174	11	log	log	NOUN
iajs-4047	174	12	of	of	ADP
iajs-4047	174	13	the	the	DET
iajs-4047	174	14	within	within	ADJ
iajs-4047	174	15	-	-	PUNCT
iajs-4047	174	16	cluster	cluster	NOUN
iajs-4047	174	17	dispersion	dispersion	NOUN
iajs-4047	174	18	for	for	ADP
iajs-4047	174	19	the	the	DET
iajs-4047	174	20	original	original	ADJ
iajs-4047	174	21	data	datum	NOUN
iajs-4047	174	22	and	and	CCONJ
iajs-4047	174	23	the	the	DET
iajs-4047	174	24	expected	expect	VERB
iajs-4047	174	25	log	log	NOUN
iajs-4047	174	26	dispersion	dispersion	NOUN
iajs-4047	174	27	for	for	ADP
iajs-4047	174	28	the	the	DET
iajs-4047	174	29	reference	reference	NOUN
iajs-4047	174	30	data	datum	NOUN
iajs-4047	174	31	.	.	PUNCT
iajs-4047	175	1	let	let	VERB
iajs-4047	175	2	's	us	PRON
iajs-4047	175	3	denote	denote	VERB
iajs-4047	175	4	the	the	DET
iajs-4047	175	5	within	within	ADP
iajs-4047	175	6	-	-	PUNCT
iajs-4047	175	7	cluster	cluster	NOUN
iajs-4047	175	8	dispersion	dispersion	NOUN
iajs-4047	175	9	for	for	ADP
iajs-4047	175	10	k	k	PROPN
iajs-4047	175	11	clusters	cluster	NOUN
iajs-4047	175	12	in	in	ADP
iajs-4047	175	13	the	the	DET
iajs-4047	175	14	original	original	ADJ
iajs-4047	175	15	data	datum	NOUN
iajs-4047	175	16	as	as	ADP
iajs-4047	175	17	(	(	PUNCT
iajs-4047	175	18	wk	wk	NOUN
iajs-4047	175	19	)	)	PUNCT
iajs-4047	175	20	,	,	PUNCT
iajs-4047	175	21	and	and	CCONJ
iajs-4047	175	22	the	the	DET
iajs-4047	175	23	expected	expect	VERB
iajs-4047	175	24	within	within	ADP
iajs-4047	175	25	-	-	PUNCT
iajs-4047	175	26	cluster	cluster	NOUN
iajs-4047	175	27	dispersion	dispersion	NOUN
iajs-4047	175	28	for	for	ADP
iajs-4047	175	29	k	k	PROPN
iajs-4047	175	30	clusters	cluster	NOUN
iajs-4047	175	31	in	in	ADP
iajs-4047	175	32	the	the	DET
iajs-4047	175	33	reference	reference	NOUN
iajs-4047	175	34	data	datum	NOUN
iajs-4047	175	35	as	as	ADP
iajs-4047	175	36	(	(	PUNCT
iajs-4047	175	37	wk∗	wk∗	NOUN
iajs-4047	175	38	)	)	PUNCT
iajs-4047	175	39	.	.	PUNCT
iajs-4047	176	1	the	the	DET
iajs-4047	176	2	fitness	fitness	NOUN
iajs-4047	176	3	function	function	NOUN
iajs-4047	176	4	is	be	AUX
iajs-4047	176	5	:	:	PUNCT
iajs-4047	176	6	max	max	PROPN
iajs-4047	176	7	(	(	PUNCT
iajs-4047	176	8	gap	gap	NOUN
iajs-4047	176	9	(	(	PUNCT
iajs-4047	176	10	k)=	k)=	X
iajs-4047	176	11	(	(	PUNCT
iajs-4047	176	12	log(wk*)-log(wk	log(wk*)-log(wk	NOUN
iajs-4047	176	13	)	)	PUNCT
iajs-4047	176	14	)	)	PUNCT
iajs-4047	176	15	)	)	PUNCT
iajs-4047	177	1	the	the	DET
iajs-4047	177	2	gap	gap	NOUN
iajs-4047	177	3	statistic	statistic	NOUN
iajs-4047	177	4	is	be	AUX
iajs-4047	177	5	a	a	DET
iajs-4047	177	6	measure	measure	NOUN
iajs-4047	177	7	used	use	VERB
iajs-4047	177	8	to	to	PART
iajs-4047	177	9	compare	compare	VERB
iajs-4047	177	10	the	the	DET
iajs-4047	177	11	within	within	ADP
iajs-4047	177	12	-	-	PUNCT
iajs-4047	177	13	cluster	cluster	NOUN
iajs-4047	177	14	dispersion	dispersion	NOUN
iajs-4047	177	15	of	of	ADP
iajs-4047	177	16	a	a	DET
iajs-4047	177	17	given	give	VERB
iajs-4047	177	18	dataset	dataset	NOUN
iajs-4047	177	19	with	with	ADP
iajs-4047	177	20	that	that	PRON
iajs-4047	177	21	of	of	ADP
iajs-4047	177	22	reference	reference	NOUN
iajs-4047	177	23	datasets	dataset	NOUN
iajs-4047	177	24	.	.	PUNCT
iajs-4047	178	1	the	the	DET
iajs-4047	178	2	gap	gap	NOUN
iajs-4047	178	3	statistic	statistic	NOUN
iajs-4047	178	4	formula	formula	NOUN
iajs-4047	178	5	takes	take	VERB
iajs-4047	178	6	the	the	DET
iajs-4047	178	7	difference	difference	NOUN
iajs-4047	178	8	between	between	ADP
iajs-4047	178	9	the	the	DET
iajs-4047	178	10	logarithm	logarithm	NOUN
iajs-4047	178	11	of	of	ADP
iajs-4047	178	12	the	the	DET
iajs-4047	178	13	within	within	ADJ
iajs-4047	178	14	-	-	PUNCT
iajs-4047	178	15	cluster	cluster	NOUN
iajs-4047	178	16	dispersion	dispersion	NOUN
iajs-4047	178	17	of	of	ADP
iajs-4047	178	18	the	the	DET
iajs-4047	178	19	reference	reference	NOUN
iajs-4047	178	20	datasets	dataset	NOUN
iajs-4047	178	21	and	and	CCONJ
iajs-4047	178	22	the	the	DET
iajs-4047	178	23	logarithm	logarithm	NOUN
iajs-4047	178	24	of	of	ADP
iajs-4047	178	25	the	the	DET
iajs-4047	178	26	withincluster	withincluster	ADJ
iajs-4047	178	27	dispersion	dispersion	NOUN
iajs-4047	178	28	of	of	ADP
iajs-4047	178	29	the	the	DET
iajs-4047	178	30	original	original	ADJ
iajs-4047	178	31	dataset	dataset	NOUN
iajs-4047	178	32	.	.	PUNCT
iajs-4047	179	1	if	if	SCONJ
iajs-4047	179	2	the	the	DET
iajs-4047	179	3	average	average	ADJ
iajs-4047	179	4	within	within	ADJ
iajs-4047	179	5	-	-	PUNCT
iajs-4047	179	6	cluster	cluster	NOUN
iajs-4047	179	7	dispersion	dispersion	NOUN
iajs-4047	179	8	of	of	ADP
iajs-4047	179	9	the	the	DET
iajs-4047	179	10	reference	reference	NOUN
iajs-4047	179	11	datasets	dataset	NOUN
iajs-4047	179	12	is	be	AUX
iajs-4047	179	13	greater	great	ADJ
iajs-4047	179	14	than	than	ADP
iajs-4047	179	15	the	the	DET
iajs-4047	179	16	within	within	ADP
iajs-4047	179	17	-	-	PUNCT
iajs-4047	179	18	cluster	cluster	NOUN
iajs-4047	179	19	dispersion	dispersion	NOUN
iajs-4047	179	20	of	of	ADP
iajs-4047	179	21	the	the	DET
iajs-4047	179	22	original	original	ADJ
iajs-4047	179	23	dataset	dataset	NOUN
iajs-4047	179	24	,	,	PUNCT
iajs-4047	179	25	the	the	DET
iajs-4047	179	26	gap	gap	NOUN
iajs-4047	179	27	statistic	statistic	NOUN
iajs-4047	179	28	will	will	AUX
iajs-4047	179	29	be	be	AUX
iajs-4047	179	30	negative	negative	ADJ
iajs-4047	179	31	.	.	PUNCT
iajs-4047	180	1	so	so	ADV
iajs-4047	180	2	,	,	PUNCT
iajs-4047	180	3	by	by	ADP
iajs-4047	180	4	using	use	VERB
iajs-4047	180	5	the	the	DET
iajs-4047	180	6	gap	gap	NOUN
iajs-4047	180	7	statistic	statistic	NOUN
iajs-4047	180	8	equation	equation	NOUN
iajs-4047	180	9	in	in	ADP
iajs-4047	180	10	the	the	DET
iajs-4047	180	11	genetic	genetic	ADJ
iajs-4047	180	12	algorithm	algorithm	NOUN
iajs-4047	180	13	's	's	PART
iajs-4047	180	14	objective	objective	ADJ
iajs-4047	180	15	function	function	NOUN
iajs-4047	180	16	,	,	PUNCT
iajs-4047	180	17	we	we	PRON
iajs-4047	180	18	can	can	AUX
iajs-4047	180	19	find	find	VERB
iajs-4047	180	20	the	the	DET
iajs-4047	180	21	optimal	optimal	ADJ
iajs-4047	180	22	number	number	NOUN
iajs-4047	180	23	of	of	ADP
iajs-4047	180	24	clusters	cluster	NOUN
iajs-4047	180	25	for	for	ADP
iajs-4047	180	26	standard	standard	ADJ
iajs-4047	180	27	and	and	CCONJ
iajs-4047	180	28	synthetic	synthetic	ADJ
iajs-4047	180	29	datasets	dataset	NOUN
iajs-4047	180	30	.	.	PUNCT
iajs-4047	181	1	the	the	DET
iajs-4047	181	2	steps	step	NOUN
iajs-4047	181	3	of	of	ADP
iajs-4047	181	4	the	the	DET
iajs-4047	181	5	genetic	genetic	ADJ
iajs-4047	181	6	algorithm	algorithm	NOUN
iajs-4047	181	7	are	be	AUX
iajs-4047	181	8	executed	execute	VERB
iajs-4047	181	9	,	,	PUNCT
iajs-4047	181	10	and	and	CCONJ
iajs-4047	181	11	upon	upon	SCONJ
iajs-4047	181	12	reaching	reach	VERB
iajs-4047	181	13	the	the	DET
iajs-4047	181	14	objective	objective	ADJ
iajs-4047	181	15	function	function	NOUN
iajs-4047	181	16	,	,	PUNCT
iajs-4047	181	17	algorithm	algorithm	PROPN
iajs-4047	181	18	1	1	NUM
iajs-4047	181	19	is	be	AUX
iajs-4047	181	20	executed	execute	VERB
iajs-4047	181	21	to	to	PART
iajs-4047	181	22	find	find	VERB
iajs-4047	181	23	the	the	DET
iajs-4047	181	24	max	max	PROPN
iajs-4047	181	25	value	value	NOUN
iajs-4047	181	26	of	of	ADP
iajs-4047	181	27	the	the	DET
iajs-4047	181	28	objective	objective	ADJ
iajs-4047	181	29	function	function	NOUN
iajs-4047	181	30	,	,	PUNCT
iajs-4047	181	31	which	which	PRON
iajs-4047	181	32	is	be	AUX
iajs-4047	181	33	considered	consider	VERB
iajs-4047	181	34	the	the	DET
iajs-4047	181	35	optimal	optimal	ADJ
iajs-4047	181	36	number	number	NOUN
iajs-4047	181	37	of	of	ADP
iajs-4047	181	38	clusters	cluster	NOUN
iajs-4047	181	39	.	.	PUNCT
iajs-4047	182	1	algorithm1	algorithm1	NOUN
iajs-4047	182	2	:	:	PUNCT
iajs-4047	182	3	steps	step	NOUN
iajs-4047	182	4	to	to	PART
iajs-4047	182	5	find	find	VERB
iajs-4047	182	6	the	the	DET
iajs-4047	182	7	result	result	NOUN
iajs-4047	182	8	of	of	ADP
iajs-4047	182	9	objective	objective	ADJ
iajs-4047	182	10	function	function	NOUN
iajs-4047	182	11	input	input	NOUN
iajs-4047	182	12	:	:	PUNCT
iajs-4047	182	13	original	original	ADJ
iajs-4047	182	14	data	datum	NOUN
iajs-4047	182	15	output	output	NOUN
iajs-4047	182	16	:	:	PUNCT
iajs-4047	182	17	best	good	ADJ
iajs-4047	182	18	number	number	NOUN
iajs-4047	182	19	of	of	ADP
iajs-4047	182	20	cluster	cluster	NOUN
iajs-4047	182	21	set	set	VERB
iajs-4047	182	22	initial	initial	ADJ
iajs-4047	182	23	parameters	parameter	NOUN
iajs-4047	182	24	:	:	PUNCT
iajs-4047	182	25	define	define	VERB
iajs-4047	182	26	the	the	DET
iajs-4047	182	27	maximum	maximum	ADJ
iajs-4047	182	28	number	number	NOUN
iajs-4047	182	29	of	of	ADP
iajs-4047	182	30	clusters	cluster	NOUN
iajs-4047	182	31	(	(	PUNCT
iajs-4047	182	32	k_max	k_max	NOUN
iajs-4047	182	33	)	)	PUNCT
iajs-4047	182	34	choose	choose	VERB
iajs-4047	182	35	the	the	DET
iajs-4047	182	36	range	range	NOUN
iajs-4047	182	37	of	of	ADP
iajs-4047	182	38	k	k	PROPN
iajs-4047	182	39	values	value	NOUN
iajs-4047	182	40	to	to	PART
iajs-4047	182	41	evaluate	evaluate	VERB
iajs-4047	182	42	(	(	PUNCT
iajs-4047	182	43	from	from	ADP
iajs-4047	182	44	2	2	NUM
iajs-4047	182	45	to	to	ADP
iajs-4047	182	46	k_max	k_max	PROPN
iajs-4047	182	47	)	)	PUNCT
iajs-4047	182	48	initialize	initialize	NOUN
iajs-4047	182	49	k	k	NOUN
iajs-4047	182	50	=	=	SYM
iajs-4047	182	51	2	2	NUM
iajs-4047	182	52	k_max	k_max	NOUN
iajs-4047	182	53	=	=	SYM
iajs-4047	182	54	10	10	NUM
iajs-4047	182	55	loop	loop	NOUN
iajs-4047	182	56	:	:	PUNCT
iajs-4047	182	57	fit	fit	ADJ
iajs-4047	182	58	k	k	NOUN
iajs-4047	182	59	-	-	PUNCT
iajs-4047	182	60	means	mean	NOUN
iajs-4047	182	61	:	:	PUNCT
iajs-4047	182	62	apply	apply	VERB
iajs-4047	182	63	k	k	NOUN
iajs-4047	182	64	-	-	PUNCT
iajs-4047	182	65	means	means	NOUN
iajs-4047	182	66	clustering	cluster	VERB
iajs-4047	182	67	to	to	ADP
iajs-4047	182	68	the	the	DET
iajs-4047	182	69	data	datum	NOUN
iajs-4047	182	70	for	for	ADP
iajs-4047	182	71	k	k	PROPN
iajs-4047	182	72	clusters	cluster	NOUN
iajs-4047	182	73	calculate	calculate	VERB
iajs-4047	182	74	within	within	ADP
iajs-4047	182	75	-	-	PUNCT
iajs-4047	182	76	cluster	cluster	NOUN
iajs-4047	182	77	dispersion	dispersion	NOUN
iajs-4047	182	78	(	(	PUNCT
iajs-4047	182	79	wk	wk	INTJ
iajs-4047	182	80	):	):	PUNCT
iajs-4047	182	81	compute	compute	VERB
iajs-4047	182	82	the	the	DET
iajs-4047	182	83	within	within	ADP
iajs-4047	182	84	-	-	PUNCT
iajs-4047	182	85	cluster	cluster	NOUN
iajs-4047	182	86	dispersion	dispersion	NOUN
iajs-4047	182	87	for	for	ADP
iajs-4047	182	88	k	k	PROPN
iajs-4047	182	89	cluster	cluster	NOUN
iajs-4047	182	90	generate	generate	NOUN
iajs-4047	182	91	reference	reference	NOUN
iajs-4047	182	92	data	datum	NOUN
iajs-4047	182	93	:	:	PUNCT
iajs-4047	182	94	create	create	VERB
iajs-4047	182	95	reference	reference	NOUN
iajs-4047	182	96	data	datum	NOUN
iajs-4047	182	97	using	use	VERB
iajs-4047	182	98	a	a	DET
iajs-4047	182	99	uniform	uniform	ADJ
iajs-4047	182	100	distribution	distribution	NOUN
iajs-4047	182	101	fit	fit	ADJ
iajs-4047	182	102	k	k	NOUN
iajs-4047	182	103	-	-	PUNCT
iajs-4047	182	104	means	means	NOUN
iajs-4047	182	105	on	on	ADP
iajs-4047	182	106	the	the	DET
iajs-4047	182	107	reference	reference	NOUN
iajs-4047	182	108	data	datum	NOUN
iajs-4047	182	109	for	for	ADP
iajs-4047	182	110	k	k	PROPN
iajs-4047	182	111	cluster	cluster	NOUN
iajs-4047	182	112	calculate	calculate	NOUN
iajs-4047	182	113	expected	expect	VERB
iajs-4047	182	114	within	within	ADP
iajs-4047	182	115	-	-	PUNCT
iajs-4047	182	116	cluster	cluster	NOUN
iajs-4047	182	117	dispersion	dispersion	NOUN
iajs-4047	182	118	(	(	PUNCT
iajs-4047	182	119	wk	wk	ADP
iajs-4047	182	120	*	*	NOUN
iajs-4047	182	121	)	)	PUNCT
iajs-4047	182	122	compute	compute	NOUN
iajs-4047	182	123	gap	gap	NOUN
iajs-4047	182	124	statistic	statistic	NOUN
iajs-4047	182	125	:	:	PUNCT
iajs-4047	182	126	calculate	calculate	NOUN
iajs-4047	182	127	gap	gap	NOUN
iajs-4047	182	128	statistic	statistic	NOUN
iajs-4047	182	129	:	:	PUNCT
iajs-4047	182	130	gap(k	gap(k	PROPN
iajs-4047	182	131	)	)	PUNCT
iajs-4047	182	132	=	=	PUNCT
iajs-4047	182	133	log(wk	log(wk	NOUN
iajs-4047	182	134	*	*	NOUN
iajs-4047	182	135	)	)	PUNCT
iajs-4047	182	136	log(wk	log(wk	NUM
iajs-4047	182	137	)	)	PUNCT
iajs-4047	182	138	increment	increment	NOUN
iajs-4047	182	139	k	k	PROPN
iajs-4047	182	140	check	check	NOUN
iajs-4047	182	141	termination	termination	NOUN
iajs-4047	182	142	criteria	criterion	NOUN
iajs-4047	182	143	:	:	PUNCT
iajs-4047	182	144	if	if	SCONJ
iajs-4047	182	145	k	k	PROPN
iajs-4047	182	146	reaches	reach	VERB
iajs-4047	182	147	k_max	k_max	PROPN
iajs-4047	182	148	,	,	PUNCT
iajs-4047	182	149	exit	exit	NOUN
iajs-4047	182	150	loop	loop	NOUN
iajs-4047	182	151	end	end	NOUN
iajs-4047	182	152	of	of	ADP
iajs-4047	182	153	loop	loop	NOUN
iajs-4047	182	154	select	select	ADJ
iajs-4047	182	155	optimal	optimal	ADJ
iajs-4047	182	156	k	k	NOUN
iajs-4047	182	157	:	:	PUNCT
iajs-4047	182	158	analyze	analyze	VERB
iajs-4047	182	159	gap	gap	NOUN
iajs-4047	182	160	statistic	statistic	NOUN
iajs-4047	182	161	values	value	NOUN
iajs-4047	182	162	then	then	ADV
iajs-4047	182	163	multiply	multiply	VERB
iajs-4047	182	164	the	the	DET
iajs-4047	182	165	result	result	NOUN
iajs-4047	182	166	with	with	ADP
iajs-4047	182	167	negative	negative	ADJ
iajs-4047	182	168	1	1	NUM
iajs-4047	182	169	to	to	PART
iajs-4047	182	170	determine	determine	VERB
iajs-4047	182	171	the	the	DET
iajs-4047	182	172	optimal	optimal	ADJ
iajs-4047	182	173	number	number	NOUN
iajs-4047	182	174	of	of	ADP
iajs-4047	182	175	clusters	cluster	NOUN
iajs-4047	182	176	calculate	calculate	VERB
iajs-4047	182	177	the	the	DET
iajs-4047	182	178	standard	standard	ADJ
iajs-4047	182	179	error	error	NOUN
iajs-4047	182	180	end	end	VERB
iajs-4047	182	181	3	3	NUM
iajs-4047	182	182	.	.	NOUN
iajs-4047	182	183	results	result	NOUN
iajs-4047	182	184	and	and	CCONJ
iajs-4047	182	185	discussion	discussion	NOUN
iajs-4047	182	186	in	in	ADP
iajs-4047	182	187	the	the	DET
iajs-4047	182	188	beginning	beginning	NOUN
iajs-4047	182	189	,	,	PUNCT
iajs-4047	182	190	we	we	PRON
iajs-4047	182	191	show	show	VERB
iajs-4047	182	192	the	the	DET
iajs-4047	182	193	results	result	NOUN
iajs-4047	182	194	of	of	ADP
iajs-4047	182	195	four	four	NUM
iajs-4047	182	196	standard	standard	ADJ
iajs-4047	182	197	datasets	dataset	NOUN
iajs-4047	182	198	(	(	PUNCT
iajs-4047	182	199	the	the	DET
iajs-4047	182	200	iris	iris	NOUN
iajs-4047	182	201	dataset	dataset	VERB
iajs-4047	182	202	,	,	PUNCT
iajs-4047	182	203	the	the	DET
iajs-4047	182	204	wine	wine	NOUN
iajs-4047	182	205	dataset	dataset	VERB
iajs-4047	182	206	,	,	PUNCT
iajs-4047	182	207	the	the	DET
iajs-4047	182	208	digits	digit	NOUN
iajs-4047	182	209	dataset	dataset	VERB
iajs-4047	182	210	,	,	PUNCT
iajs-4047	182	211	and	and	CCONJ
iajs-4047	182	212	the	the	DET
iajs-4047	182	213	breast	breast	NOUN
iajs-4047	182	214	cancer	cancer	NOUN
iajs-4047	182	215	dataset	dataset	NOUN
iajs-4047	182	216	)	)	PUNCT
iajs-4047	182	217	by	by	ADP
iajs-4047	182	218	applying	apply	VERB
iajs-4047	182	219	the	the	DET
iajs-4047	182	220	genetic	genetic	ADJ
iajs-4047	182	221	algorithm	algorithm	NOUN
iajs-4047	182	222	on	on	ADP
iajs-4047	182	223	ihjpas	ihjpas	PROPN
iajs-4047	182	224	.	.	PUNCT
iajs-4047	183	1	2025	2025	NUM
iajs-4047	183	2	,	,	PUNCT
iajs-4047	183	3	38	38	NUM
iajs-4047	183	4	(	(	PUNCT
iajs-4047	183	5	2	2	NUM
iajs-4047	183	6	)	)	PUNCT
iajs-4047	183	7	434	434	NUM
iajs-4047	183	8	them	they	PRON
iajs-4047	183	9	and	and	CCONJ
iajs-4047	183	10	finding	find	VERB
iajs-4047	183	11	the	the	DET
iajs-4047	183	12	optimal	optimal	ADJ
iajs-4047	183	13	number	number	NOUN
iajs-4047	183	14	of	of	ADP
iajs-4047	183	15	each	each	DET
iajs-4047	183	16	dataset	dataset	VERB
iajs-4047	183	17	by	by	ADP
iajs-4047	183	18	utilizing	utilize	VERB
iajs-4047	183	19	the	the	DET
iajs-4047	183	20	gap	gap	NOUN
iajs-4047	183	21	statistic	statistic	NOUN
iajs-4047	183	22	using	use	VERB
iajs-4047	183	23	python	python	PROPN
iajs-4047	183	24	code	code	NOUN
iajs-4047	183	25	on	on	ADP
iajs-4047	183	26	colab	colab	PROPN
iajs-4047	183	27	google	google	PROPN
iajs-4047	183	28	.	.	PUNCT
iajs-4047	184	1	3.1	3.1	NUM
iajs-4047	184	2	.	.	PUNCT
iajs-4047	185	1	experimental	experimental	ADJ
iajs-4047	185	2	results	result	NOUN
iajs-4047	185	3	a	a	DET
iajs-4047	185	4	genetic	genetic	ADJ
iajs-4047	185	5	algorithm	algorithm	NOUN
iajs-4047	185	6	was	be	AUX
iajs-4047	185	7	implemented	implement	VERB
iajs-4047	185	8	on	on	ADP
iajs-4047	185	9	standard	standard	ADJ
iajs-4047	185	10	and	and	CCONJ
iajs-4047	185	11	synthetic	synthetic	ADJ
iajs-4047	185	12	datasets	dataset	NOUN
iajs-4047	185	13	to	to	PART
iajs-4047	185	14	find	find	VERB
iajs-4047	185	15	the	the	DET
iajs-4047	185	16	optimal	optimal	ADJ
iajs-4047	185	17	number	number	NOUN
iajs-4047	185	18	of	of	ADP
iajs-4047	185	19	clusters	cluster	NOUN
iajs-4047	185	20	and	and	CCONJ
iajs-4047	185	21	show	show	VERB
iajs-4047	185	22	the	the	DET
iajs-4047	185	23	results	result	NOUN
iajs-4047	185	24	of	of	ADP
iajs-4047	185	25	four	four	NUM
iajs-4047	185	26	examples	example	NOUN
iajs-4047	185	27	of	of	ADP
iajs-4047	185	28	standard	standard	ADJ
iajs-4047	185	29	datasets	dataset	NOUN
iajs-4047	185	30	below	below	ADV
iajs-4047	185	31	.	.	PUNCT
iajs-4047	186	1	example	example	NOUN
iajs-4047	187	1	1	1	NUM
iajs-4047	187	2	.	.	PUNCT
iajs-4047	187	3	this	this	DET
iajs-4047	187	4	method	method	NOUN
iajs-4047	187	5	is	be	AUX
iajs-4047	187	6	applied	apply	VERB
iajs-4047	187	7	to	to	ADP
iajs-4047	187	8	the	the	DET
iajs-4047	187	9	iris	iris	NOUN
iajs-4047	187	10	dataset	dataset	VERB
iajs-4047	187	11	.	.	PUNCT
iajs-4047	188	1	the	the	DET
iajs-4047	188	2	dataset	dataset	NOUN
iajs-4047	188	3	is	be	AUX
iajs-4047	188	4	commonly	commonly	ADV
iajs-4047	188	5	used	use	VERB
iajs-4047	188	6	for	for	ADP
iajs-4047	188	7	classification	classification	NOUN
iajs-4047	188	8	tasks	task	NOUN
iajs-4047	188	9	,	,	PUNCT
iajs-4047	188	10	clustering	clustering	ADJ
iajs-4047	188	11	algorithms	algorithm	NOUN
iajs-4047	188	12	,	,	PUNCT
iajs-4047	188	13	and	and	CCONJ
iajs-4047	188	14	data	datum	NOUN
iajs-4047	188	15	visualization	visualization	NOUN
iajs-4047	188	16	techniques	technique	NOUN
iajs-4047	188	17	.	.	PUNCT
iajs-4047	189	1	it	it	PRON
iajs-4047	189	2	contains	contain	VERB
iajs-4047	189	3	150	150	NUM
iajs-4047	189	4	instances	instance	NOUN
iajs-4047	189	5	,	,	PUNCT
iajs-4047	189	6	with	with	ADP
iajs-4047	189	7	50	50	NUM
iajs-4047	189	8	instances	instance	NOUN
iajs-4047	189	9	for	for	ADP
iajs-4047	189	10	each	each	DET
iajs-4047	189	11	class	class	NOUN
iajs-4047	189	12	.	.	PUNCT
iajs-4047	190	1	the	the	DET
iajs-4047	190	2	dataset	dataset	NOUN
iajs-4047	190	3	contains	contain	VERB
iajs-4047	190	4	measurements	measurement	NOUN
iajs-4047	190	5	of	of	ADP
iajs-4047	190	6	four	four	NUM
iajs-4047	190	7	features	feature	NOUN
iajs-4047	190	8	of	of	ADP
iajs-4047	190	9	three	three	NUM
iajs-4047	190	10	species	specie	NOUN
iajs-4047	190	11	of	of	ADP
iajs-4047	190	12	iris	iris	NOUN
iajs-4047	190	13	flowers	flower	NOUN
iajs-4047	190	14	(	(	PUNCT
iajs-4047	190	15	30	30	NUM
iajs-4047	190	16	)	)	PUNCT
iajs-4047	190	17	.	.	PUNCT
iajs-4047	191	1	figure	figure	NOUN
iajs-4047	191	2	9	9	NUM
iajs-4047	191	3	.	.	PUNCT
iajs-4047	192	1	shows	show	VERB
iajs-4047	192	2	the	the	DET
iajs-4047	192	3	plot	plot	NOUN
iajs-4047	192	4	of	of	ADP
iajs-4047	192	5	sepal	sepal	ADJ
iajs-4047	192	6	width	width	NOUN
iajs-4047	192	7	and	and	CCONJ
iajs-4047	192	8	length	length	NOUN
iajs-4047	192	9	in	in	ADP
iajs-4047	192	10	the	the	DET
iajs-4047	192	11	iris	iris	NOUN
iajs-4047	192	12	dataset	dataset	VERB
iajs-4047	192	13	.	.	PUNCT
iajs-4047	193	1	figure	figure	NOUN
iajs-4047	193	2	9	9	NUM
iajs-4047	193	3	.	.	PUNCT
iajs-4047	194	1	plot	plot	NOUN
iajs-4047	194	2	of	of	ADP
iajs-4047	194	3	sepal	sepal	ADJ
iajs-4047	194	4	width	width	NOUN
iajs-4047	194	5	and	and	CCONJ
iajs-4047	194	6	length	length	NOUN
iajs-4047	194	7	of	of	ADP
iajs-4047	194	8	iris	iris	NOUN
iajs-4047	194	9	dataset	dataset	ADJ
iajs-4047	194	10	figure	figure	NOUN
iajs-4047	194	11	10	10	NUM
iajs-4047	194	12	.	.	PUNCT
iajs-4047	195	1	distribution	distribution	NOUN
iajs-4047	195	2	of	of	ADP
iajs-4047	195	3	iris	iris	NOUN
iajs-4047	195	4	dataset	dataset	NOUN
iajs-4047	195	5	ihjpas	ihjpa	NOUN
iajs-4047	195	6	.	.	PUNCT
iajs-4047	196	1	2025	2025	NUM
iajs-4047	196	2	,	,	PUNCT
iajs-4047	196	3	38	38	NUM
iajs-4047	196	4	(	(	PUNCT
iajs-4047	196	5	2	2	NUM
iajs-4047	196	6	)	)	PUNCT
iajs-4047	196	7	435	435	NUM
iajs-4047	196	8	figure	figure	NOUN
iajs-4047	196	9	11	11	NUM
iajs-4047	196	10	.	.	PUNCT
iajs-4047	197	1	gap	gap	NOUN
iajs-4047	197	2	statistic	statistic	NOUN
iajs-4047	197	3	of	of	ADP
iajs-4047	197	4	iris	iris	NOUN
iajs-4047	197	5	dataset	dataset	ADJ
iajs-4047	197	6	figure	figure	NOUN
iajs-4047	197	7	10	10	NUM
iajs-4047	197	8	.	.	PUNCT
iajs-4047	198	1	shows	show	VERB
iajs-4047	198	2	the	the	DET
iajs-4047	198	3	distribution	distribution	NOUN
iajs-4047	198	4	of	of	ADP
iajs-4047	198	5	the	the	DET
iajs-4047	198	6	iris	iris	NOUN
iajs-4047	198	7	dataset	dataset	NOUN
iajs-4047	198	8	,	,	PUNCT
iajs-4047	198	9	and	and	CCONJ
iajs-4047	198	10	figure	figure	VERB
iajs-4047	198	11	11	11	NUM
iajs-4047	198	12	.	.	PUNCT
iajs-4047	199	1	shows	show	VERB
iajs-4047	199	2	the	the	DET
iajs-4047	199	3	plot	plot	NOUN
iajs-4047	199	4	of	of	ADP
iajs-4047	199	5	the	the	DET
iajs-4047	199	6	gap	gap	NOUN
iajs-4047	199	7	statistic	statistic	NOUN
iajs-4047	199	8	of	of	ADP
iajs-4047	199	9	the	the	DET
iajs-4047	199	10	iris	iris	NOUN
iajs-4047	199	11	dataset	dataset	VERB
iajs-4047	199	12	.	.	PUNCT
iajs-4047	200	1	the	the	DET
iajs-4047	200	2	ideal	ideal	ADJ
iajs-4047	200	3	number	number	NOUN
iajs-4047	200	4	of	of	ADP
iajs-4047	200	5	clusters	cluster	NOUN
iajs-4047	200	6	is	be	AUX
iajs-4047	200	7	3	3	NUM
iajs-4047	200	8	,	,	PUNCT
iajs-4047	200	9	which	which	PRON
iajs-4047	200	10	is	be	AUX
iajs-4047	200	11	determined	determine	VERB
iajs-4047	200	12	by	by	ADP
iajs-4047	200	13	using	use	VERB
iajs-4047	200	14	the	the	DET
iajs-4047	200	15	genetic	genetic	ADJ
iajs-4047	200	16	algorithm	algorithm	NOUN
iajs-4047	200	17	,	,	PUNCT
iajs-4047	200	18	as	as	SCONJ
iajs-4047	200	19	shown	show	VERB
iajs-4047	200	20	in	in	ADP
iajs-4047	200	21	tables	table	NOUN
iajs-4047	200	22	1	1	NUM
iajs-4047	200	23	and	and	CCONJ
iajs-4047	200	24	2	2	NUM
iajs-4047	200	25	.	.	NOUN
iajs-4047	200	26	example	example	NOUN
iajs-4047	201	1	2	2	NUM
iajs-4047	201	2	.	.	PUNCT
iajs-4047	202	1	the	the	DET
iajs-4047	202	2	wine	wine	NOUN
iajs-4047	202	3	quality	quality	NOUN
iajs-4047	202	4	dataset	dataset	NOUN
iajs-4047	202	5	is	be	AUX
iajs-4047	202	6	a	a	DET
iajs-4047	202	7	classic	classic	ADJ
iajs-4047	202	8	dataset	dataset	NOUN
iajs-4047	202	9	used	use	VERB
iajs-4047	202	10	for	for	ADP
iajs-4047	202	11	classification	classification	NOUN
iajs-4047	202	12	tasks	task	NOUN
iajs-4047	202	13	.	.	PUNCT
iajs-4047	203	1	while	while	SCONJ
iajs-4047	203	2	it	it	PRON
iajs-4047	203	3	is	be	AUX
iajs-4047	203	4	primarily	primarily	ADV
iajs-4047	203	5	designed	design	VERB
iajs-4047	203	6	for	for	ADP
iajs-4047	203	7	classification	classification	NOUN
iajs-4047	203	8	rather	rather	ADV
iajs-4047	203	9	than	than	ADP
iajs-4047	203	10	clustering	cluster	VERB
iajs-4047	203	11	,	,	PUNCT
iajs-4047	203	12	it	it	PRON
iajs-4047	203	13	is	be	AUX
iajs-4047	203	14	available	available	ADJ
iajs-4047	203	15	from	from	ADP
iajs-4047	203	16	the	the	DET
iajs-4047	203	17	uci	uci	PROPN
iajs-4047	203	18	machine	machine	NOUN
iajs-4047	203	19	learning	learn	VERB
iajs-4047	203	20	repository	repository	NOUN
iajs-4047	203	21	and	and	CCONJ
iajs-4047	203	22	includes	include	VERB
iajs-4047	203	23	data	datum	NOUN
iajs-4047	203	24	for	for	ADP
iajs-4047	203	25	both	both	CCONJ
iajs-4047	203	26	red	red	ADJ
iajs-4047	203	27	and	and	CCONJ
iajs-4047	203	28	white	white	ADJ
iajs-4047	203	29	wines	wine	NOUN
iajs-4047	203	30	.	.	PUNCT
iajs-4047	204	1	the	the	DET
iajs-4047	204	2	goal	goal	NOUN
iajs-4047	204	3	of	of	ADP
iajs-4047	204	4	the	the	DET
iajs-4047	204	5	dataset	dataset	NOUN
iajs-4047	204	6	is	be	AUX
iajs-4047	204	7	to	to	PART
iajs-4047	204	8	model	model	VERB
iajs-4047	204	9	wine	wine	NOUN
iajs-4047	204	10	quality	quality	NOUN
iajs-4047	204	11	based	base	VERB
iajs-4047	204	12	on	on	ADP
iajs-4047	204	13	physicochemical	physicochemical	ADJ
iajs-4047	204	14	tests	test	NOUN
iajs-4047	204	15	.	.	PUNCT
iajs-4047	205	1	it	it	PRON
iajs-4047	205	2	contains	contain	VERB
iajs-4047	205	3	4,898	4,898	NUM
iajs-4047	205	4	instances	instance	NOUN
iajs-4047	205	5	and	and	CCONJ
iajs-4047	205	6	11	11	NUM
iajs-4047	205	7	features	feature	NOUN
iajs-4047	205	8	:	:	PUNCT
iajs-4047	205	9	(	(	PUNCT
iajs-4047	205	10	1	1	NUM
iajs-4047	205	11	-	-	PUNCT
iajs-4047	205	12	fixed	fix	VERB
iajs-4047	205	13	acidity	acidity	NOUN
iajs-4047	205	14	,	,	PUNCT
iajs-4047	205	15	2	2	NUM
iajs-4047	205	16	volatile	volatile	ADJ
iajs-4047	205	17	acidity	acidity	NOUN
iajs-4047	205	18	,	,	PUNCT
iajs-4047	205	19	3	3	NUM
iajs-4047	205	20	citric	citric	NOUN
iajs-4047	205	21	acid	acid	NOUN
iajs-4047	205	22	,	,	PUNCT
iajs-4047	205	23	4	4	NUM
iajs-4047	205	24	residual	residual	ADJ
iajs-4047	205	25	sugar	sugar	NOUN
iajs-4047	205	26	,	,	PUNCT
iajs-4047	205	27	5	5	NUM
iajs-4047	205	28	–	–	PUNCT
iajs-4047	205	29	chlorides	chloride	NOUN
iajs-4047	205	30	,	,	PUNCT
iajs-4047	205	31	6	6	NUM
iajs-4047	205	32	free	free	ADJ
iajs-4047	205	33	sulfur	sulfur	NOUN
iajs-4047	205	34	dioxide	dioxide	NOUN
iajs-4047	205	35	,	,	PUNCT
iajs-4047	205	36	7	7	NUM
iajs-4047	205	37	total	total	ADJ
iajs-4047	205	38	sulfur	sulfur	NOUN
iajs-4047	205	39	dioxide	dioxide	NOUN
iajs-4047	205	40	8	8	NUM
iajs-4047	205	41	density	density	NOUN
iajs-4047	205	42	9	9	NUM
iajs-4047	205	43	ph	ph	NOUN
iajs-4047	205	44	10	10	NUM
iajs-4047	205	45	sulphates	sulphate	NOUN
iajs-4047	205	46	11	11	NUM
iajs-4047	205	47	–	–	PUNCT
iajs-4047	205	48	alcohol	alcohol	NOUN
iajs-4047	205	49	)	)	PUNCT
iajs-4047	205	50	.	.	PUNCT
iajs-4047	206	1	figure	figure	NOUN
iajs-4047	206	2	12	12	NUM
iajs-4047	206	3	shows	show	VERB
iajs-4047	206	4	the	the	DET
iajs-4047	206	5	distribution	distribution	NOUN
iajs-4047	206	6	of	of	ADP
iajs-4047	206	7	the	the	DET
iajs-4047	206	8	wine	wine	NOUN
iajs-4047	206	9	dataset	dataset	VERB
iajs-4047	206	10	before	before	ADP
iajs-4047	206	11	finding	find	VERB
iajs-4047	206	12	the	the	DET
iajs-4047	206	13	optimal	optimal	ADJ
iajs-4047	206	14	number	number	NOUN
iajs-4047	206	15	of	of	ADP
iajs-4047	206	16	clusters	cluster	NOUN
iajs-4047	206	17	.	.	PUNCT
iajs-4047	207	1	figure	figure	NOUN
iajs-4047	207	2	12	12	NUM
iajs-4047	207	3	.	.	PUNCT
iajs-4047	208	1	distribution	distribution	NOUN
iajs-4047	208	2	of	of	ADP
iajs-4047	208	3	wine	wine	NOUN
iajs-4047	208	4	dataset	dataset	VERB
iajs-4047	208	5	before	before	ADP
iajs-4047	208	6	finding	find	VERB
iajs-4047	208	7	the	the	DET
iajs-4047	208	8	optimal	optimal	ADJ
iajs-4047	208	9	number	number	NOUN
iajs-4047	208	10	of	of	ADP
iajs-4047	208	11	clusters	cluster	NOUN
iajs-4047	208	12	ihjpas	ihjpa	VERB
iajs-4047	208	13	.	.	PUNCT
iajs-4047	209	1	2025	2025	NUM
iajs-4047	209	2	,	,	PUNCT
iajs-4047	209	3	38	38	NUM
iajs-4047	209	4	(	(	PUNCT
iajs-4047	209	5	2	2	NUM
iajs-4047	209	6	)	)	PUNCT
iajs-4047	209	7	436	436	NUM
iajs-4047	209	8	figure	figure	NOUN
iajs-4047	209	9	13	13	NUM
iajs-4047	209	10	.	.	PUNCT
iajs-4047	210	1	distribution	distribution	NOUN
iajs-4047	210	2	of	of	ADP
iajs-4047	210	3	wine	wine	NOUN
iajs-4047	210	4	dataset	dataset	VERB
iajs-4047	210	5	after	after	ADP
iajs-4047	210	6	finding	find	VERB
iajs-4047	210	7	the	the	DET
iajs-4047	210	8	optimal	optimal	ADJ
iajs-4047	210	9	number	number	NOUN
iajs-4047	210	10	of	of	ADP
iajs-4047	210	11	clusters	cluster	NOUN
iajs-4047	210	12	figure	figure	VERB
iajs-4047	210	13	13	13	NUM
iajs-4047	210	14	.	.	PUNCT
iajs-4047	211	1	shows	show	VERB
iajs-4047	211	2	the	the	DET
iajs-4047	211	3	distribution	distribution	NOUN
iajs-4047	211	4	of	of	ADP
iajs-4047	211	5	the	the	DET
iajs-4047	211	6	wine	wine	NOUN
iajs-4047	211	7	dataset	dataset	VERB
iajs-4047	211	8	after	after	ADP
iajs-4047	211	9	finding	find	VERB
iajs-4047	211	10	the	the	DET
iajs-4047	211	11	optimal	optimal	ADJ
iajs-4047	211	12	number	number	NOUN
iajs-4047	211	13	of	of	ADP
iajs-4047	211	14	clusters	cluster	NOUN
iajs-4047	211	15	,	,	PUNCT
iajs-4047	211	16	and	and	CCONJ
iajs-4047	211	17	figure	figure	VERB
iajs-4047	211	18	14	14	NUM
iajs-4047	211	19	.	.	PUNCT
iajs-4047	212	1	shows	show	VERB
iajs-4047	212	2	the	the	DET
iajs-4047	212	3	plot	plot	NOUN
iajs-4047	212	4	of	of	ADP
iajs-4047	212	5	the	the	DET
iajs-4047	212	6	gap	gap	NOUN
iajs-4047	212	7	statistic	statistic	NOUN
iajs-4047	212	8	of	of	ADP
iajs-4047	212	9	the	the	DET
iajs-4047	212	10	wine	wine	NOUN
iajs-4047	212	11	dataset	dataset	NOUN
iajs-4047	212	12	.	.	PUNCT
iajs-4047	213	1	the	the	DET
iajs-4047	213	2	optimal	optimal	ADJ
iajs-4047	213	3	number	number	NOUN
iajs-4047	213	4	of	of	ADP
iajs-4047	213	5	clusters	cluster	NOUN
iajs-4047	213	6	of	of	ADP
iajs-4047	213	7	the	the	DET
iajs-4047	213	8	wine	wine	NOUN
iajs-4047	213	9	dataset	dataset	NOUN
iajs-4047	213	10	is	be	AUX
iajs-4047	213	11	2	2	NUM
iajs-4047	213	12	,	,	PUNCT
iajs-4047	213	13	as	as	SCONJ
iajs-4047	213	14	shown	show	VERB
iajs-4047	213	15	in	in	ADP
iajs-4047	213	16	tables	table	NOUN
iajs-4047	213	17	1	1	NUM
iajs-4047	213	18	and	and	CCONJ
iajs-4047	213	19	5	5	NUM
iajs-4047	213	20	.	.	X
iajs-4047	213	21	figure	figure	NOUN
iajs-4047	213	22	14	14	NUM
iajs-4047	213	23	.	.	PUNCT
iajs-4047	214	1	gap	gap	NOUN
iajs-4047	214	2	statistic	statistic	NOUN
iajs-4047	214	3	of	of	ADP
iajs-4047	214	4	wine	wine	NOUN
iajs-4047	214	5	dataset	dataset	VERB
iajs-4047	214	6	example	example	NOUN
iajs-4047	214	7	3	3	X
iajs-4047	214	8	.	.	PUNCT
iajs-4047	215	1	the	the	DET
iajs-4047	215	2	digits	digit	NOUN
iajs-4047	215	3	dataset	dataset	VERB
iajs-4047	215	4	is	be	AUX
iajs-4047	215	5	a	a	DET
iajs-4047	215	6	commonly	commonly	ADV
iajs-4047	215	7	used	use	VERB
iajs-4047	215	8	dataset	dataset	NOUN
iajs-4047	215	9	in	in	ADP
iajs-4047	215	10	machine	machine	NOUN
iajs-4047	215	11	learning	learn	VERB
iajs-4047	215	12	for	for	ADP
iajs-4047	215	13	practicing	practice	VERB
iajs-4047	215	14	classification	classification	NOUN
iajs-4047	215	15	algorithms	algorithm	NOUN
iajs-4047	215	16	.	.	PUNCT
iajs-4047	216	1	it	it	PRON
iajs-4047	216	2	consists	consist	VERB
iajs-4047	216	3	of	of	ADP
iajs-4047	216	4	8x8	8x8	NUM
iajs-4047	216	5	pixel	pixel	NOUN
iajs-4047	216	6	images	image	NOUN
iajs-4047	216	7	of	of	ADP
iajs-4047	216	8	handwritten	handwritten	ADJ
iajs-4047	216	9	digits	digit	NOUN
iajs-4047	216	10	(	(	PUNCT
iajs-4047	216	11	0	0	NUM
iajs-4047	216	12	-	-	SYM
iajs-4047	216	13	9	9	NUM
iajs-4047	216	14	)	)	PUNCT
iajs-4047	216	15	.	.	PUNCT
iajs-4047	217	1	each	each	DET
iajs-4047	217	2	sample	sample	NOUN
iajs-4047	217	3	in	in	ADP
iajs-4047	217	4	the	the	DET
iajs-4047	217	5	dataset	dataset	NOUN
iajs-4047	217	6	represents	represent	VERB
iajs-4047	217	7	an	an	DET
iajs-4047	217	8	image	image	NOUN
iajs-4047	217	9	of	of	ADP
iajs-4047	217	10	a	a	DET
iajs-4047	217	11	handwritten	handwritten	ADJ
iajs-4047	217	12	digit	digit	NOUN
iajs-4047	217	13	.	.	PUNCT
iajs-4047	218	1	each	each	DET
iajs-4047	218	2	pixel	pixel	PROPN
iajs-4047	218	3	value	value	NOUN
iajs-4047	218	4	is	be	AUX
iajs-4047	218	5	an	an	DET
iajs-4047	218	6	integer	integer	NOUN
iajs-4047	218	7	ranging	range	VERB
iajs-4047	218	8	from	from	ADP
iajs-4047	218	9	0	0	NUM
iajs-4047	218	10	to	to	ADP
iajs-4047	218	11	16	16	NUM
iajs-4047	218	12	,	,	PUNCT
iajs-4047	218	13	representing	represent	VERB
iajs-4047	218	14	grayscale	grayscale	NOUN
iajs-4047	218	15	values	value	NOUN
iajs-4047	218	16	.	.	PUNCT
iajs-4047	219	1	the	the	DET
iajs-4047	219	2	dataset	dataset	NOUN
iajs-4047	219	3	has	have	VERB
iajs-4047	219	4	a	a	DET
iajs-4047	219	5	total	total	NOUN
iajs-4047	219	6	of	of	ADP
iajs-4047	219	7	1797	1797	NUM
iajs-4047	219	8	samples	sample	NOUN
iajs-4047	219	9	(	(	PUNCT
iajs-4047	219	10	31	31	NUM
iajs-4047	219	11	)	)	PUNCT
iajs-4047	219	12	.	.	PUNCT
iajs-4047	220	1	figure	figure	NOUN
iajs-4047	220	2	15	15	NUM
iajs-4047	220	3	.	.	PUNCT
iajs-4047	221	1	shows	show	VERB
iajs-4047	221	2	the	the	DET
iajs-4047	221	3	plot	plot	NOUN
iajs-4047	221	4	of	of	ADP
iajs-4047	221	5	the	the	DET
iajs-4047	221	6	gap	gap	NOUN
iajs-4047	221	7	statistic	statistic	NOUN
iajs-4047	221	8	of	of	ADP
iajs-4047	221	9	the	the	DET
iajs-4047	221	10	digits	digit	NOUN
iajs-4047	221	11	dataset	dataset	VERB
iajs-4047	221	12	.	.	PUNCT
iajs-4047	222	1	ihjpas	ihjpas	PROPN
iajs-4047	222	2	.	.	PUNCT
iajs-4047	223	1	2025	2025	NUM
iajs-4047	223	2	,	,	PUNCT
iajs-4047	223	3	38	38	NUM
iajs-4047	223	4	(	(	PUNCT
iajs-4047	223	5	2	2	NUM
iajs-4047	223	6	)	)	PUNCT
iajs-4047	223	7	437	437	NUM
iajs-4047	223	8	figure	figure	NOUN
iajs-4047	223	9	15	15	NUM
iajs-4047	223	10	.	.	PUNCT
iajs-4047	224	1	gap	gap	NOUN
iajs-4047	224	2	statistic	statistic	NOUN
iajs-4047	224	3	of	of	ADP
iajs-4047	224	4	digits	digit	NOUN
iajs-4047	224	5	dataset	dataset	VERB
iajs-4047	224	6	the	the	DET
iajs-4047	224	7	optimal	optimal	ADJ
iajs-4047	224	8	number	number	NOUN
iajs-4047	224	9	of	of	ADP
iajs-4047	224	10	clusters	cluster	NOUN
iajs-4047	224	11	of	of	ADP
iajs-4047	224	12	the	the	DET
iajs-4047	224	13	digits	digit	NOUN
iajs-4047	224	14	dataset	dataset	VERB
iajs-4047	224	15	is	be	AUX
iajs-4047	224	16	10	10	NUM
iajs-4047	224	17	,	,	PUNCT
iajs-4047	224	18	as	as	SCONJ
iajs-4047	224	19	shown	show	VERB
iajs-4047	224	20	in	in	ADP
iajs-4047	224	21	table	table	NOUN
iajs-4047	224	22	1	1	NUM
iajs-4047	224	23	.	.	PUNCT
iajs-4047	224	24	example	example	NOUN
iajs-4047	225	1	4	4	NUM
iajs-4047	225	2	.	.	PUNCT
iajs-4047	226	1	the	the	DET
iajs-4047	226	2	breast	breast	NOUN
iajs-4047	226	3	cancer	cancer	NOUN
iajs-4047	226	4	dataset	dataset	NOUN
iajs-4047	226	5	is	be	AUX
iajs-4047	226	6	a	a	DET
iajs-4047	226	7	common	common	ADJ
iajs-4047	226	8	dataset	dataset	NOUN
iajs-4047	226	9	used	use	VERB
iajs-4047	226	10	in	in	ADP
iajs-4047	226	11	machine	machine	NOUN
iajs-4047	226	12	learning	learn	VERB
iajs-4047	226	13	for	for	ADP
iajs-4047	226	14	classification	classification	NOUN
iajs-4047	226	15	tasks	task	NOUN
iajs-4047	226	16	,	,	PUNCT
iajs-4047	226	17	particularly	particularly	ADV
iajs-4047	226	18	in	in	ADP
iajs-4047	226	19	the	the	DET
iajs-4047	226	20	context	context	NOUN
iajs-4047	226	21	of	of	ADP
iajs-4047	226	22	predicting	predict	VERB
iajs-4047	226	23	whether	whether	SCONJ
iajs-4047	226	24	a	a	DET
iajs-4047	226	25	tumor	tumor	NOUN
iajs-4047	226	26	is	be	AUX
iajs-4047	226	27	benign	benign	ADJ
iajs-4047	226	28	or	or	CCONJ
iajs-4047	226	29	malignant	malignant	ADJ
iajs-4047	226	30	based	base	VERB
iajs-4047	226	31	on	on	ADP
iajs-4047	226	32	features	feature	NOUN
iajs-4047	226	33	derived	derive	VERB
iajs-4047	226	34	from	from	ADP
iajs-4047	226	35	images	image	NOUN
iajs-4047	226	36	of	of	ADP
iajs-4047	226	37	cell	cell	NOUN
iajs-4047	226	38	nuclei	nucleus	NOUN
iajs-4047	226	39	.	.	PUNCT
iajs-4047	227	1	the	the	DET
iajs-4047	227	2	dataset	dataset	NOUN
iajs-4047	227	3	has	have	VERB
iajs-4047	227	4	features	feature	NOUN
iajs-4047	227	5	extracted	extract	VERB
iajs-4047	227	6	from	from	ADP
iajs-4047	227	7	digital	digital	ADJ
iajs-4047	227	8	images	image	NOUN
iajs-4047	227	9	of	of	ADP
iajs-4047	227	10	breast	breast	NOUN
iajs-4047	227	11	masses	masse	NOUN
iajs-4047	227	12	that	that	PRON
iajs-4047	227	13	describe	describe	VERB
iajs-4047	227	14	the	the	DET
iajs-4047	227	15	properties	property	NOUN
iajs-4047	227	16	of	of	ADP
iajs-4047	227	17	cell	cell	NOUN
iajs-4047	227	18	nuclei	nucleus	NOUN
iajs-4047	227	19	found	find	VERB
iajs-4047	227	20	in	in	ADP
iajs-4047	227	21	the	the	DET
iajs-4047	227	22	image	image	NOUN
iajs-4047	227	23	.	.	PUNCT
iajs-4047	228	1	each	each	DET
iajs-4047	228	2	sample	sample	NOUN
iajs-4047	228	3	in	in	ADP
iajs-4047	228	4	the	the	DET
iajs-4047	228	5	dataset	dataset	NOUN
iajs-4047	228	6	represents	represent	VERB
iajs-4047	228	7	information	information	NOUN
iajs-4047	228	8	related	relate	VERB
iajs-4047	228	9	to	to	ADP
iajs-4047	228	10	a	a	DET
iajs-4047	228	11	specific	specific	ADJ
iajs-4047	228	12	breast	breast	NOUN
iajs-4047	228	13	mass	mass	NOUN
iajs-4047	228	14	.	.	PUNCT
iajs-4047	229	1	it	it	PRON
iajs-4047	229	2	contains	contain	VERB
iajs-4047	229	3	7,909	7,909	NUM
iajs-4047	229	4	breast	breast	NOUN
iajs-4047	229	5	cancer	cancer	NOUN
iajs-4047	229	6	images	image	NOUN
iajs-4047	229	7	.	.	PUNCT
iajs-4047	230	1	the	the	DET
iajs-4047	230	2	main	main	ADJ
iajs-4047	230	3	job	job	NOUN
iajs-4047	230	4	for	for	ADP
iajs-4047	230	5	this	this	DET
iajs-4047	230	6	dataset	dataset	NOUN
iajs-4047	230	7	is	be	AUX
iajs-4047	230	8	binary	binary	ADJ
iajs-4047	230	9	classification	classification	NOUN
iajs-4047	230	10	,	,	PUNCT
iajs-4047	230	11	where	where	SCONJ
iajs-4047	230	12	the	the	DET
iajs-4047	230	13	objective	objective	NOUN
iajs-4047	230	14	is	be	AUX
iajs-4047	230	15	to	to	PART
iajs-4047	230	16	guess	guess	VERB
iajs-4047	230	17	from	from	ADP
iajs-4047	230	18	the	the	DET
iajs-4047	230	19	given	give	VERB
iajs-4047	230	20	information	information	NOUN
iajs-4047	230	21	whether	whether	SCONJ
iajs-4047	230	22	a	a	DET
iajs-4047	230	23	tumor	tumor	NOUN
iajs-4047	230	24	is	be	AUX
iajs-4047	230	25	harmless	harmless	ADJ
iajs-4047	230	26	or	or	CCONJ
iajs-4047	230	27	harmful	harmful	ADJ
iajs-4047	230	28	(	(	PUNCT
iajs-4047	230	29	32	32	NUM
iajs-4047	230	30	)	)	PUNCT
iajs-4047	230	31	.	.	PUNCT
iajs-4047	231	1	figure	figure	NOUN
iajs-4047	231	2	16	16	NUM
iajs-4047	231	3	.	.	PUNCT
iajs-4047	232	1	shows	show	VERB
iajs-4047	232	2	the	the	DET
iajs-4047	232	3	distribution	distribution	NOUN
iajs-4047	232	4	of	of	ADP
iajs-4047	232	5	the	the	DET
iajs-4047	232	6	breast	breast	NOUN
iajs-4047	232	7	cancer	cancer	NOUN
iajs-4047	232	8	dataset	dataset	VERB
iajs-4047	232	9	after	after	ADP
iajs-4047	232	10	clustering	cluster	VERB
iajs-4047	232	11	into	into	ADP
iajs-4047	232	12	two	two	NUM
iajs-4047	232	13	sets	set	NOUN
iajs-4047	232	14	,	,	PUNCT
iajs-4047	232	15	as	as	ADP
iajs-4047	232	16	in	in	ADP
iajs-4047	232	17	figure	figure	NOUN
iajs-4047	232	18	17	17	NUM
iajs-4047	232	19	.	.	PUNCT
iajs-4047	233	1	that	that	PRON
iajs-4047	233	2	means	mean	VERB
iajs-4047	233	3	the	the	DET
iajs-4047	233	4	optimal	optimal	ADJ
iajs-4047	233	5	number	number	NOUN
iajs-4047	233	6	of	of	ADP
iajs-4047	233	7	clusters	cluster	NOUN
iajs-4047	233	8	is	be	AUX
iajs-4047	233	9	2	2	NUM
iajs-4047	233	10	,	,	PUNCT
iajs-4047	233	11	as	as	SCONJ
iajs-4047	233	12	shown	show	VERB
iajs-4047	233	13	in	in	ADP
iajs-4047	233	14	table	table	NOUN
iajs-4047	233	15	1	1	NUM
iajs-4047	233	16	.	.	PUNCT
iajs-4047	233	17	figure	figure	NOUN
iajs-4047	233	18	16	16	NUM
iajs-4047	233	19	.	.	PUNCT
iajs-4047	234	1	distribution	distribution	NOUN
iajs-4047	234	2	of	of	ADP
iajs-4047	234	3	breast	breast	NOUN
iajs-4047	234	4	cancer	cancer	NOUN
iajs-4047	234	5	dataset	dataset	NOUN
iajs-4047	234	6	ihjpas	ihjpas	PROPN
iajs-4047	234	7	.	.	PUNCT
iajs-4047	235	1	2025	2025	NUM
iajs-4047	235	2	,	,	PUNCT
iajs-4047	235	3	38	38	NUM
iajs-4047	235	4	(	(	PUNCT
iajs-4047	235	5	2	2	NUM
iajs-4047	235	6	)	)	PUNCT
iajs-4047	235	7	438	438	NUM
iajs-4047	235	8	figure	figure	NOUN
iajs-4047	235	9	17	17	NUM
iajs-4047	235	10	.	.	PUNCT
iajs-4047	236	1	gap	gap	NOUN
iajs-4047	236	2	statistic	statistic	NOUN
iajs-4047	236	3	of	of	ADP
iajs-4047	236	4	breast	breast	NOUN
iajs-4047	236	5	cancer	cancer	NOUN
iajs-4047	236	6	dataset	dataset	NOUN
iajs-4047	236	7	table	table	NOUN
iajs-4047	236	8	1	1	NUM
iajs-4047	236	9	.	.	PUNCT
iajs-4047	236	10	will	will	AUX
iajs-4047	236	11	present	present	VERB
iajs-4047	236	12	the	the	DET
iajs-4047	236	13	results	result	NOUN
iajs-4047	236	14	.	.	PUNCT
iajs-4047	237	1	determine	determine	VERB
iajs-4047	237	2	the	the	DET
iajs-4047	237	3	optimal	optimal	ADJ
iajs-4047	237	4	number	number	NOUN
iajs-4047	237	5	of	of	ADP
iajs-4047	237	6	clusters	cluster	NOUN
iajs-4047	237	7	for	for	ADP
iajs-4047	237	8	four	four	NUM
iajs-4047	237	9	datasets	dataset	NOUN
iajs-4047	237	10	within	within	ADP
iajs-4047	237	11	a	a	DET
iajs-4047	237	12	specified	specified	ADJ
iajs-4047	237	13	cluster	cluster	NOUN
iajs-4047	237	14	range	range	NOUN
iajs-4047	237	15	.	.	PUNCT
iajs-4047	238	1	other	other	ADJ
iajs-4047	238	2	methods	method	NOUN
iajs-4047	238	3	show	show	VERB
iajs-4047	238	4	the	the	DET
iajs-4047	238	5	optimal	optimal	ADJ
iajs-4047	238	6	number	number	NOUN
iajs-4047	238	7	of	of	ADP
iajs-4047	238	8	clusters	cluster	NOUN
iajs-4047	238	9	in	in	ADP
iajs-4047	238	10	tables	table	NOUN
iajs-4047	238	11	2	2	NUM
iajs-4047	238	12	,	,	PUNCT
iajs-4047	238	13	3	3	NUM
iajs-4047	238	14	,	,	PUNCT
iajs-4047	238	15	4	4	NUM
iajs-4047	238	16	,	,	PUNCT
iajs-4047	238	17	and	and	CCONJ
iajs-4047	238	18	5	5	NUM
iajs-4047	238	19	.	.	PUNCT
iajs-4047	239	1	so	so	ADV
iajs-4047	239	2	the	the	DET
iajs-4047	239	3	comparison	comparison	NOUN
iajs-4047	239	4	is	be	AUX
iajs-4047	239	5	clear	clear	ADJ
iajs-4047	239	6	.	.	PUNCT
iajs-4047	240	1	table	table	NOUN
iajs-4047	240	2	6	6	NUM
iajs-4047	240	3	.	.	PUNCT
iajs-4047	240	4	illustrates	illustrate	VERB
iajs-4047	240	5	the	the	DET
iajs-4047	240	6	comparison	comparison	NOUN
iajs-4047	240	7	clearly	clearly	ADV
iajs-4047	240	8	.	.	PUNCT
iajs-4047	241	1	table	table	NOUN
iajs-4047	241	2	1	1	NUM
iajs-4047	241	3	.	.	PUNCT
iajs-4047	241	4	results	result	NOUN
iajs-4047	241	5	of	of	ADP
iajs-4047	241	6	(	(	PUNCT
iajs-4047	241	7	2	2	NUM
iajs-4047	241	8	to	to	PART
iajs-4047	241	9	10	10	NUM
iajs-4047	241	10	)	)	PUNCT
iajs-4047	241	11	range	range	VERB
iajs-4047	241	12	to	to	PART
iajs-4047	241	13	find	find	VERB
iajs-4047	241	14	the	the	DET
iajs-4047	241	15	optimal	optimal	ADJ
iajs-4047	241	16	number	number	NOUN
iajs-4047	241	17	of	of	ADP
iajs-4047	241	18	clusters	cluster	NOUN
iajs-4047	241	19	for	for	ADP
iajs-4047	241	20	the	the	DET
iajs-4047	241	21	four	four	NUM
iajs-4047	241	22	datasets	dataset	NOUN
iajs-4047	241	23	2	2	NUM
iajs-4047	241	24	3	3	NUM
iajs-4047	241	25	4	4	NUM
iajs-4047	241	26	5	5	NUM
iajs-4047	241	27	6	6	NUM
iajs-4047	241	28	7	7	NUM
iajs-4047	241	29	8	8	NUM
iajs-4047	241	30	9	9	NUM
iajs-4047	241	31	10	10	NUM
iajs-4047	241	32	iris	iris	NOUN
iajs-4047	241	33	dataset	dataset	VERB
iajs-4047	241	34	1.727	1.727	NUM
iajs-4047	241	35	1.773	1.773	NUM
iajs-4047	241	36	1.424	1.424	NUM
iajs-4047	241	37	1.276	1.276	NUM
iajs-4047	241	38	1.292	1.292	NUM
iajs-4047	241	39	1.422	1.422	NUM
iajs-4047	241	40	1.275	1.275	NUM
iajs-4047	241	41	1.121	1.121	NUM
iajs-4047	241	42	1.230	1.230	NUM
iajs-4047	241	43	wine	wine	NOUN
iajs-4047	241	44	dataset	dataset	VERB
iajs-4047	241	45	2.255	2.255	NUM
iajs-4047	241	46	2.029	2.029	NUM
iajs-4047	241	47	2.027	2.027	NUM
iajs-4047	241	48	1.999	1.999	NUM
iajs-4047	241	49	2.000	2.000	NUM
iajs-4047	241	50	1.989	1.989	NUM
iajs-4047	241	51	1.969	1.969	NUM
iajs-4047	241	52	1.933	1.933	NUM
iajs-4047	241	53	1.917	1.917	NUM
iajs-4047	241	54	digits	digit	NOUN
iajs-4047	241	55	dataset	dataset	VERB
iajs-4047	241	56	-2.405	-2.405	NUM
iajs-4047	241	57	-2.327	-2.327	NOUN
iajs-4047	241	58	-2.268	-2.268	PUNCT
iajs-4047	241	59	-2.224	-2.224	X
iajs-4047	242	1	-2.193	-2.193	PUNCT
iajs-4047	242	2	-2.150	-2.150	NOUN
iajs-4047	242	3	-2.119	-2.119	PUNCT
iajs-4047	242	4	-2.093	-2.093	NUM
iajs-4047	242	5	-2.059	-2.059	PROPN
iajs-4047	242	6	breast	breast	NOUN
iajs-4047	242	7	cancer	cancer	NOUN
iajs-4047	242	8	dataset	dataset	VERB
iajs-4047	242	9	2.119	2.119	NUM
iajs-4047	242	10	2.014	2.014	NUM
iajs-4047	242	11	1.943	1.943	NUM
iajs-4047	242	12	1.970	1.970	NUM
iajs-4047	242	13	1.907	1.907	NUM
iajs-4047	242	14	1.838	1.838	NUM
iajs-4047	242	15	1.759	1.759	NUM
iajs-4047	242	16	1.738	1.738	NUM
iajs-4047	242	17	1.702	1.702	NUM
iajs-4047	242	18	table	table	NOUN
iajs-4047	242	19	2	2	NUM
iajs-4047	242	20	.	.	PUNCT
iajs-4047	242	21	finding	find	VERB
iajs-4047	242	22	the	the	DET
iajs-4047	242	23	optimal	optimal	ADJ
iajs-4047	242	24	number	number	NOUN
iajs-4047	242	25	of	of	ADP
iajs-4047	242	26	clusters	cluster	NOUN
iajs-4047	242	27	by	by	ADP
iajs-4047	242	28	using	use	VERB
iajs-4047	242	29	silhouette	silhouette	NOUN
iajs-4047	242	30	and	and	CCONJ
iajs-4047	242	31	davies	davy	NOUN
iajs-4047	242	32	-	-	PUNCT
iajs-4047	242	33	bouldin	bouldin	NOUN
iajs-4047	242	34	on	on	ADP
iajs-4047	242	35	the	the	DET
iajs-4047	242	36	iris	iris	NOUN
iajs-4047	242	37	dataset	dataset	VERB
iajs-4047	242	38	2	2	NUM
iajs-4047	242	39	3	3	NUM
iajs-4047	242	40	4	4	NUM
iajs-4047	242	41	5	5	NUM
iajs-4047	242	42	6	6	NUM
iajs-4047	242	43	7	7	NUM
iajs-4047	242	44	8	8	NUM
iajs-4047	242	45	9	9	NUM
iajs-4047	242	46	10	10	NUM
iajs-4047	242	47	silhouette	silhouette	NOUN
iajs-4047	242	48	score	score	NOUN
iajs-4047	242	49	0.581	0.581	NUM
iajs-4047	242	50	0.479	0.479	NUM
iajs-4047	242	51	0.385	0.385	NUM
iajs-4047	242	52	0.345	0.345	NUM
iajs-4047	242	53	0.333	0.333	NUM
iajs-4047	242	54	0.266	0.266	NUM
iajs-4047	242	55	0.341	0.341	NUM
iajs-4047	242	56	0.324	0.324	NUM
iajs-4047	242	57	0.335	0.335	NUM
iajs-4047	242	58	davies	davy	NOUN
iajs-4047	242	59	–	–	PUNCT
iajs-4047	242	60	bouldin	bouldin	NOUN
iajs-4047	242	61	0.593	0.593	NUM
iajs-4047	242	62	0.789	0.789	NUM
iajs-4047	242	63	0.869	0.869	NUM
iajs-4047	242	64	0.943	0.943	NUM
iajs-4047	242	65	0.993	0.993	NUM
iajs-4047	242	66	1.124	1.124	NUM
iajs-4047	242	67	0.990	0.990	NUM
iajs-4047	242	68	0.977	0.977	NUM
iajs-4047	242	69	0.975	0.975	NUM
iajs-4047	242	70	table	table	NOUN
iajs-4047	242	71	3	3	NUM
iajs-4047	242	72	.	.	PUNCT
iajs-4047	242	73	finding	find	VERB
iajs-4047	242	74	the	the	DET
iajs-4047	242	75	optimal	optimal	ADJ
iajs-4047	242	76	number	number	NOUN
iajs-4047	242	77	of	of	ADP
iajs-4047	242	78	clusters	cluster	NOUN
iajs-4047	242	79	by	by	ADP
iajs-4047	242	80	using	use	VERB
iajs-4047	242	81	silhouette	silhouette	NOUN
iajs-4047	242	82	and	and	CCONJ
iajs-4047	242	83	davies	davy	NOUN
iajs-4047	242	84	-	-	PUNCT
iajs-4047	242	85	bouldin	bouldin	NOUN
iajs-4047	242	86	on	on	ADP
iajs-4047	242	87	the	the	DET
iajs-4047	242	88	breast	breast	NOUN
iajs-4047	242	89	cancer	cancer	NOUN
iajs-4047	242	90	dataset	dataset	VERB
iajs-4047	242	91	2	2	NUM
iajs-4047	242	92	3	3	NUM
iajs-4047	242	93	4	4	NUM
iajs-4047	242	94	5	5	NUM
iajs-4047	242	95	6	6	NUM
iajs-4047	242	96	7	7	NUM
iajs-4047	242	97	8	8	NUM
iajs-4047	242	98	9	9	NUM
iajs-4047	242	99	10	10	NUM
iajs-4047	242	100	silhouette	silhouette	NOUN
iajs-4047	242	101	score	score	NOUN
iajs-4047	242	102	0.344	0.344	NUM
iajs-4047	242	103	0.315	0.315	NUM
iajs-4047	242	104	0.274	0.274	NUM
iajs-4047	242	105	0.164	0.164	NUM
iajs-4047	242	106	0.145	0.145	NUM
iajs-4047	242	107	0.146	0.146	NUM
iajs-4047	242	108	0.161	0.161	NUM
iajs-4047	242	109	0.143	0.143	NUM
iajs-4047	242	110	0.147	0.147	NUM
iajs-4047	242	111	davies	davy	NOUN
iajs-4047	242	112	bouldin	bouldin	PROPN
iajs-4047	242	113	1.309	1.309	NUM
iajs-4047	242	114	1.539	1.539	NUM
iajs-4047	242	115	1.492	1.492	NUM
iajs-4047	242	116	1.429	1.429	NUM
iajs-4047	242	117	1.503	1.503	NUM
iajs-4047	242	118	1.499	1.499	NUM
iajs-4047	242	119	1.555	1.555	NUM
iajs-4047	242	120	1.502	1.502	NUM
iajs-4047	242	121	1.511	1.511	NUM
iajs-4047	242	122	table	table	NOUN
iajs-4047	242	123	4	4	NUM
iajs-4047	242	124	.	.	PUNCT
iajs-4047	242	125	finding	find	VERB
iajs-4047	242	126	the	the	DET
iajs-4047	242	127	optimal	optimal	ADJ
iajs-4047	242	128	number	number	NOUN
iajs-4047	242	129	of	of	ADP
iajs-4047	242	130	clusters	cluster	NOUN
iajs-4047	242	131	by	by	ADP
iajs-4047	242	132	using	use	VERB
iajs-4047	242	133	silhouette	silhouette	NOUN
iajs-4047	242	134	and	and	CCONJ
iajs-4047	242	135	davies	davy	NOUN
iajs-4047	242	136	-	-	PUNCT
iajs-4047	242	137	bouldin	bouldin	NOUN
iajs-4047	242	138	on	on	ADP
iajs-4047	242	139	the	the	DET
iajs-4047	242	140	digits	digit	NOUN
iajs-4047	242	141	dataset	dataset	VERB
iajs-4047	242	142	2	2	NUM
iajs-4047	242	143	3	3	NUM
iajs-4047	242	144	4	4	NUM
iajs-4047	242	145	5	5	NUM
iajs-4047	242	146	6	6	NUM
iajs-4047	242	147	7	7	NUM
iajs-4047	242	148	8	8	NUM
iajs-4047	242	149	9	9	NUM
iajs-4047	242	150	10	10	NUM
iajs-4047	242	151	silhouette	silhouette	NOUN
iajs-4047	242	152	score	score	NOUN
iajs-4047	242	153	0.386	0.386	NUM
iajs-4047	242	154	0.104	0.104	NUM
iajs-4047	242	155	0.106	0.106	NUM
iajs-4047	242	156	0.102	0.102	NUM
iajs-4047	242	157	0.104	0.104	NUM
iajs-4047	242	158	0.111	0.111	NUM
iajs-4047	242	159	0.127	0.127	NUM
iajs-4047	242	160	0.130	0.130	NUM
iajs-4047	242	161	0.135	0.135	NUM
iajs-4047	242	162	davies	davy	NOUN
iajs-4047	242	163	bouldin	bouldin	VERB
iajs-4047	242	164	1.562	1.562	NUM
iajs-4047	242	165	2.292	2.292	NUM
iajs-4047	242	166	2.406	2.406	NUM
iajs-4047	242	167	2.252	2.252	NUM
iajs-4047	242	168	2.232	2.232	NUM
iajs-4047	242	169	2.117	2.117	NUM
iajs-4047	242	170	2.055	2.055	NUM
iajs-4047	242	171	1.893	1.893	NUM
iajs-4047	242	172	1.806	1.806	NUM
iajs-4047	242	173	table	table	NOUN
iajs-4047	242	174	5	5	NUM
iajs-4047	242	175	.	.	PUNCT
iajs-4047	242	176	finding	find	VERB
iajs-4047	242	177	the	the	DET
iajs-4047	242	178	optimal	optimal	ADJ
iajs-4047	242	179	number	number	NOUN
iajs-4047	242	180	of	of	ADP
iajs-4047	242	181	clusters	cluster	NOUN
iajs-4047	242	182	by	by	ADP
iajs-4047	242	183	using	use	VERB
iajs-4047	242	184	silhouette	silhouette	NOUN
iajs-4047	242	185	and	and	CCONJ
iajs-4047	242	186	davies	davy	NOUN
iajs-4047	242	187	-	-	PUNCT
iajs-4047	242	188	bouldin	bouldin	NOUN
iajs-4047	242	189	on	on	ADP
iajs-4047	242	190	the	the	DET
iajs-4047	242	191	wine	wine	NOUN
iajs-4047	242	192	dataset	dataset	NOUN
iajs-4047	242	193	results	result	NOUN
iajs-4047	242	194	2	2	NUM
iajs-4047	242	195	3	3	NUM
iajs-4047	242	196	4	4	NUM
iajs-4047	242	197	5	5	NUM
iajs-4047	242	198	6	6	NUM
iajs-4047	242	199	7	7	NUM
iajs-4047	242	200	8	8	NUM
iajs-4047	242	201	9	9	NUM
iajs-4047	242	202	10	10	NUM
iajs-4047	242	203	silhouette	silhouette	NOUN
iajs-4047	242	204	score	score	NOUN
iajs-4047	242	205	0.265	0.265	NUM
iajs-4047	242	206	0.284	0.284	NUM
iajs-4047	242	207	0.254	0.254	NUM
iajs-4047	242	208	0.183	0.183	NUM
iajs-4047	242	209	0.168	0.168	NUM
iajs-4047	242	210	0.172	0.172	NUM
iajs-4047	242	211	0.162	0.162	NUM
iajs-4047	242	212	0.173	0.173	NUM
iajs-4047	242	213	0.139	0.139	NUM
iajs-4047	242	214	davies	davy	NOUN
iajs-4047	242	215	bouldin	bouldin	VERB
iajs-4047	242	216	1.494	1.494	NUM
iajs-4047	242	217	1.389	1.389	NUM
iajs-4047	242	218	1.695	1.695	NUM
iajs-4047	242	219	1.912	1.912	NUM
iajs-4047	242	220	1.930	1.930	NUM
iajs-4047	242	221	1.701	1.701	NUM
iajs-4047	242	222	1.843	1.843	NUM
iajs-4047	242	223	1.643	1.643	NUM
iajs-4047	242	224	1.719	1.719	NUM
iajs-4047	242	225	ihjpas	ihjpa	NOUN
iajs-4047	242	226	.	.	PUNCT
iajs-4047	243	1	2025	2025	NUM
iajs-4047	243	2	,	,	PUNCT
iajs-4047	243	3	38	38	NUM
iajs-4047	243	4	(	(	PUNCT
iajs-4047	243	5	2	2	NUM
iajs-4047	243	6	)	)	PUNCT
iajs-4047	243	7	439	439	NUM
iajs-4047	243	8	table	table	NOUN
iajs-4047	243	9	6	6	NUM
iajs-4047	243	10	.	.	PUNCT
iajs-4047	244	1	the	the	DET
iajs-4047	244	2	optimal	optimal	ADJ
iajs-4047	244	3	number	number	NOUN
iajs-4047	244	4	of	of	ADP
iajs-4047	244	5	clusters	cluster	NOUN
iajs-4047	244	6	for	for	ADP
iajs-4047	244	7	four	four	NUM
iajs-4047	244	8	datasets	dataset	NOUN
iajs-4047	244	9	by	by	ADP
iajs-4047	244	10	using	use	VERB
iajs-4047	244	11	the	the	DET
iajs-4047	244	12	three	three	NUM
iajs-4047	244	13	ways	way	NOUN
iajs-4047	244	14	genetic	genetic	ADJ
iajs-4047	244	15	algorithm	algorithm	NOUN
iajs-4047	244	16	silhouette	silhouette	NOUN
iajs-4047	244	17	score	score	NOUN
iajs-4047	244	18	davies	davy	NOUN
iajs-4047	244	19	-	-	PUNCT
iajs-4047	244	20	bouldin	bouldin	NOUN
iajs-4047	244	21	iris	iris	NOUN
iajs-4047	244	22	dataset	dataset	VERB
iajs-4047	244	23	3	3	NUM
iajs-4047	244	24	2	2	NUM
iajs-4047	244	25	2	2	NUM
iajs-4047	244	26	wine	wine	NOUN
iajs-4047	244	27	dataset	dataset	VERB
iajs-4047	244	28	2	2	NUM
iajs-4047	244	29	3	3	NUM
iajs-4047	244	30	3	3	NUM
iajs-4047	244	31	breast	breast	NOUN
iajs-4047	244	32	cancer	cancer	NOUN
iajs-4047	244	33	dataset	dataset	VERB
iajs-4047	244	34	2	2	NUM
iajs-4047	244	35	2	2	NUM
iajs-4047	244	36	2	2	NUM
iajs-4047	244	37	digits	digit	NOUN
iajs-4047	244	38	dataset	dataset	VERB
iajs-4047	244	39	10	10	NUM
iajs-4047	244	40	2	2	NUM
iajs-4047	244	41	2	2	NUM
iajs-4047	244	42	table	table	NOUN
iajs-4047	244	43	7	7	NUM
iajs-4047	244	44	.	.	NOUN
iajs-4047	244	45	four	four	NUM
iajs-4047	244	46	datasets	dataset	NOUN
iajs-4047	244	47	and	and	CCONJ
iajs-4047	244	48	the	the	DET
iajs-4047	244	49	values	value	NOUN
iajs-4047	244	50	of	of	ADP
iajs-4047	244	51	the	the	DET
iajs-4047	244	52	standard	standard	ADJ
iajs-4047	244	53	error	error	NOUN
iajs-4047	244	54	for	for	SCONJ
iajs-4047	244	55	each	each	DET
iajs-4047	244	56	optimal	optimal	ADJ
iajs-4047	244	57	number	number	NOUN
iajs-4047	244	58	of	of	ADP
iajs-4047	244	59	clusters	cluster	NOUN
iajs-4047	244	60	optimal	optimal	ADJ
iajs-4047	244	61	number	number	NOUN
iajs-4047	244	62	standard	standard	ADJ
iajs-4047	244	63	error	error	NOUN
iajs-4047	244	64	iris	iris	NOUN
iajs-4047	244	65	dataset	dataset	VERB
iajs-4047	244	66	3	3	NUM
iajs-4047	244	67	0.711	0.711	NUM
iajs-4047	244	68	wine	wine	NOUN
iajs-4047	244	69	dataset	dataset	VERB
iajs-4047	244	70	2	2	NUM
iajs-4047	244	71	0.234	0.234	NUM
iajs-4047	244	72	breast	breast	NOUN
iajs-4047	244	73	cancer	cancer	NOUN
iajs-4047	244	74	dataset	dataset	VERB
iajs-4047	244	75	2	2	NUM
iajs-4047	244	76	0.224	0.224	NUM
iajs-4047	244	77	digits	digit	NOUN
iajs-4047	244	78	dataset	dataset	VERB
iajs-4047	244	79	10	10	NUM
iajs-4047	244	80	0.0362	0.0362	NUM
iajs-4047	244	81	table	table	NOUN
iajs-4047	244	82	7	7	NUM
iajs-4047	244	83	.	.	PUNCT
iajs-4047	244	84	shows	show	VERB
iajs-4047	244	85	the	the	DET
iajs-4047	244	86	results	result	NOUN
iajs-4047	244	87	of	of	ADP
iajs-4047	244	88	the	the	DET
iajs-4047	244	89	optimal	optimal	ADJ
iajs-4047	244	90	number	number	NOUN
iajs-4047	244	91	of	of	ADP
iajs-4047	244	92	clusters	cluster	NOUN
iajs-4047	244	93	for	for	ADP
iajs-4047	244	94	the	the	DET
iajs-4047	244	95	four	four	NUM
iajs-4047	244	96	datasets	dataset	NOUN
iajs-4047	244	97	and	and	CCONJ
iajs-4047	244	98	the	the	DET
iajs-4047	244	99	standard	standard	ADJ
iajs-4047	244	100	error	error	NOUN
iajs-4047	244	101	of	of	ADP
iajs-4047	244	102	each	each	DET
iajs-4047	244	103	one	one	NUM
iajs-4047	244	104	of	of	ADP
iajs-4047	244	105	them	they	PRON
iajs-4047	244	106	.	.	PUNCT
iajs-4047	245	1	3.2	3.2	NUM
iajs-4047	245	2	.	.	PUNCT
iajs-4047	245	3	discussion	discussion	NOUN
iajs-4047	245	4	when	when	SCONJ
iajs-4047	245	5	using	use	VERB
iajs-4047	245	6	the	the	DET
iajs-4047	245	7	silhouette	silhouette	NOUN
iajs-4047	245	8	score	score	NOUN
iajs-4047	245	9	to	to	PART
iajs-4047	245	10	find	find	VERB
iajs-4047	245	11	the	the	DET
iajs-4047	245	12	optimal	optimal	ADJ
iajs-4047	245	13	number	number	NOUN
iajs-4047	245	14	of	of	ADP
iajs-4047	245	15	clusters	cluster	NOUN
iajs-4047	245	16	,	,	PUNCT
iajs-4047	245	17	first	first	ADV
iajs-4047	245	18	apply	apply	VERB
iajs-4047	245	19	the	the	DET
iajs-4047	245	20	k	k	NOUN
iajs-4047	245	21	-	-	PUNCT
iajs-4047	245	22	means	means	NOUN
iajs-4047	245	23	algorithm	algorithm	NOUN
iajs-4047	245	24	to	to	PART
iajs-4047	245	25	divide	divide	VERB
iajs-4047	245	26	the	the	DET
iajs-4047	245	27	dataset	dataset	NOUN
iajs-4047	245	28	into	into	ADP
iajs-4047	245	29	the	the	DET
iajs-4047	245	30	range	range	NOUN
iajs-4047	245	31	of	of	ADP
iajs-4047	245	32	clusters	cluster	NOUN
iajs-4047	245	33	.	.	PUNCT
iajs-4047	246	1	for	for	ADP
iajs-4047	246	2	example	example	NOUN
iajs-4047	246	3	,	,	PUNCT
iajs-4047	246	4	when	when	SCONJ
iajs-4047	246	5	using	use	VERB
iajs-4047	246	6	the	the	DET
iajs-4047	246	7	silhouette	silhouette	NOUN
iajs-4047	246	8	score	score	NOUN
iajs-4047	246	9	to	to	PART
iajs-4047	246	10	find	find	VERB
iajs-4047	246	11	the	the	DET
iajs-4047	246	12	optimal	optimal	ADJ
iajs-4047	246	13	number	number	NOUN
iajs-4047	246	14	of	of	ADP
iajs-4047	246	15	clusters	cluster	NOUN
iajs-4047	246	16	on	on	ADP
iajs-4047	246	17	a	a	DET
iajs-4047	246	18	specific	specific	ADJ
iajs-4047	246	19	dataset	dataset	NOUN
iajs-4047	246	20	,	,	PUNCT
iajs-4047	246	21	after	after	SCONJ
iajs-4047	246	22	the	the	DET
iajs-4047	246	23	data	datum	NOUN
iajs-4047	246	24	was	be	AUX
iajs-4047	246	25	divided	divide	VERB
iajs-4047	246	26	into	into	ADP
iajs-4047	246	27	2	2	NUM
iajs-4047	246	28	to	to	PART
iajs-4047	246	29	10	10	NUM
iajs-4047	246	30	clusters	cluster	NOUN
iajs-4047	246	31	,	,	PUNCT
iajs-4047	246	32	the	the	DET
iajs-4047	246	33	biggest	big	ADJ
iajs-4047	246	34	result	result	NOUN
iajs-4047	246	35	(	(	PUNCT
iajs-4047	246	36	close	close	ADV
iajs-4047	246	37	to	to	PART
iajs-4047	246	38	1	1	NUM
iajs-4047	246	39	)	)	PUNCT
iajs-4047	246	40	represents	represent	VERB
iajs-4047	246	41	the	the	DET
iajs-4047	246	42	optimal	optimal	ADJ
iajs-4047	246	43	number	number	NOUN
iajs-4047	246	44	of	of	ADP
iajs-4047	246	45	clusters	cluster	NOUN
iajs-4047	246	46	.	.	PUNCT
iajs-4047	247	1	when	when	SCONJ
iajs-4047	247	2	applied	apply	VERB
iajs-4047	247	3	to	to	ADP
iajs-4047	247	4	multiple	multiple	ADJ
iajs-4047	247	5	datasets	dataset	NOUN
iajs-4047	247	6	,	,	PUNCT
iajs-4047	247	7	the	the	DET
iajs-4047	247	8	results	result	NOUN
iajs-4047	247	9	were	be	AUX
iajs-4047	247	10	correct	correct	ADJ
iajs-4047	247	11	,	,	PUNCT
iajs-4047	247	12	as	as	ADP
iajs-4047	247	13	with	with	ADP
iajs-4047	247	14	the	the	DET
iajs-4047	247	15	breast	breast	NOUN
iajs-4047	247	16	cancer	cancer	NOUN
iajs-4047	247	17	dataset	dataset	NOUN
iajs-4047	247	18	.	.	PUNCT
iajs-4047	248	1	table	table	NOUN
iajs-4047	248	2	3	3	NUM
iajs-4047	248	3	displays	display	VERB
iajs-4047	248	4	the	the	DET
iajs-4047	248	5	results	result	NOUN
iajs-4047	248	6	.	.	PUNCT
iajs-4047	249	1	similarly	similarly	ADV
iajs-4047	249	2	,	,	PUNCT
iajs-4047	249	3	for	for	ADP
iajs-4047	249	4	the	the	DET
iajs-4047	249	5	davies	davies	PROPN
iajs-4047	249	6	bouldin	bouldin	PROPN
iajs-4047	249	7	index	index	PROPN
iajs-4047	249	8	,	,	PUNCT
iajs-4047	249	9	a	a	DET
iajs-4047	249	10	smaller	small	ADJ
iajs-4047	249	11	value	value	NOUN
iajs-4047	249	12	indicates	indicate	VERB
iajs-4047	249	13	a	a	DET
iajs-4047	249	14	more	more	ADV
iajs-4047	249	15	optimal	optimal	ADJ
iajs-4047	249	16	clustering	clustering	NOUN
iajs-4047	249	17	solution	solution	NOUN
iajs-4047	249	18	(	(	PUNCT
iajs-4047	249	19	approaching	approach	VERB
iajs-4047	249	20	0	0	NUM
iajs-4047	249	21	)	)	PUNCT
iajs-4047	249	22	.	.	PUNCT
iajs-4047	250	1	this	this	DET
iajs-4047	250	2	index	index	NOUN
iajs-4047	250	3	is	be	AUX
iajs-4047	250	4	used	use	VERB
iajs-4047	250	5	to	to	PART
iajs-4047	250	6	find	find	VERB
iajs-4047	250	7	the	the	DET
iajs-4047	250	8	optimal	optimal	ADJ
iajs-4047	250	9	number	number	NOUN
iajs-4047	250	10	of	of	ADP
iajs-4047	250	11	clusters	cluster	NOUN
iajs-4047	250	12	but	but	CCONJ
iajs-4047	250	13	does	do	AUX
iajs-4047	250	14	not	not	PART
iajs-4047	250	15	give	give	VERB
iajs-4047	250	16	the	the	DET
iajs-4047	250	17	right	right	ADJ
iajs-4047	250	18	results	result	NOUN
iajs-4047	250	19	in	in	ADP
iajs-4047	250	20	all	all	DET
iajs-4047	250	21	tested	test	VERB
iajs-4047	250	22	datasets	dataset	NOUN
iajs-4047	250	23	,	,	PUNCT
iajs-4047	250	24	as	as	SCONJ
iajs-4047	250	25	applied	apply	VERB
iajs-4047	250	26	to	to	ADP
iajs-4047	250	27	the	the	DET
iajs-4047	250	28	iris	iris	NOUN
iajs-4047	250	29	dataset	dataset	VERB
iajs-4047	250	30	as	as	SCONJ
iajs-4047	250	31	shown	show	VERB
iajs-4047	250	32	in	in	ADP
iajs-4047	250	33	table	table	NOUN
iajs-4047	250	34	2	2	NUM
iajs-4047	250	35	.	.	PUNCT
iajs-4047	251	1	the	the	DET
iajs-4047	251	2	minimum	minimum	ADJ
iajs-4047	251	3	number	number	NOUN
iajs-4047	251	4	is	be	AUX
iajs-4047	251	5	2	2	NUM
iajs-4047	251	6	clusters	cluster	NOUN
iajs-4047	251	7	,	,	PUNCT
iajs-4047	251	8	but	but	CCONJ
iajs-4047	251	9	the	the	DET
iajs-4047	251	10	right	right	ADJ
iajs-4047	251	11	number	number	NOUN
iajs-4047	251	12	is	be	AUX
iajs-4047	251	13	3	3	NUM
iajs-4047	251	14	clusters	cluster	NOUN
iajs-4047	251	15	.	.	PUNCT
iajs-4047	252	1	so	so	ADV
iajs-4047	252	2	,	,	PUNCT
iajs-4047	252	3	a	a	DET
iajs-4047	252	4	genetic	genetic	ADJ
iajs-4047	252	5	algorithm	algorithm	NOUN
iajs-4047	252	6	was	be	AUX
iajs-4047	252	7	needed	need	VERB
iajs-4047	252	8	to	to	PART
iajs-4047	252	9	find	find	VERB
iajs-4047	252	10	the	the	DET
iajs-4047	252	11	best	good	ADJ
iajs-4047	252	12	number	number	NOUN
iajs-4047	252	13	of	of	ADP
iajs-4047	252	14	clusters	cluster	NOUN
iajs-4047	252	15	across	across	ADP
iajs-4047	252	16	all	all	DET
iajs-4047	252	17	datasets	dataset	NOUN
iajs-4047	252	18	that	that	PRON
iajs-4047	252	19	were	be	AUX
iajs-4047	252	20	tested	test	VERB
iajs-4047	252	21	,	,	PUNCT
iajs-4047	252	22	compare	compare	VERB
iajs-4047	252	23	these	these	DET
iajs-4047	252	24	approaches	approach	NOUN
iajs-4047	252	25	,	,	PUNCT
iajs-4047	252	26	and	and	CCONJ
iajs-4047	252	27	find	find	VERB
iajs-4047	252	28	the	the	DET
iajs-4047	252	29	right	right	ADJ
iajs-4047	252	30	answers	answer	NOUN
iajs-4047	252	31	,	,	PUNCT
iajs-4047	252	32	as	as	SCONJ
iajs-4047	252	33	shown	show	VERB
iajs-4047	252	34	in	in	ADP
iajs-4047	252	35	table	table	NOUN
iajs-4047	252	36	6	6	NUM
iajs-4047	252	37	.	.	PUNCT
iajs-4047	253	1	the	the	DET
iajs-4047	253	2	right	right	ADJ
iajs-4047	253	3	number	number	NOUN
iajs-4047	253	4	of	of	ADP
iajs-4047	253	5	clusters	cluster	NOUN
iajs-4047	253	6	of	of	ADP
iajs-4047	253	7	the	the	DET
iajs-4047	253	8	iris	iris	NOUN
iajs-4047	253	9	dataset	dataset	NOUN
iajs-4047	253	10	is	be	AUX
iajs-4047	253	11	3	3	NUM
iajs-4047	253	12	,	,	PUNCT
iajs-4047	253	13	the	the	DET
iajs-4047	253	14	best	good	ADJ
iajs-4047	253	15	number	number	NOUN
iajs-4047	253	16	of	of	ADP
iajs-4047	253	17	the	the	DET
iajs-4047	253	18	wine	wine	NOUN
iajs-4047	253	19	quality	quality	NOUN
iajs-4047	253	20	dataset	dataset	NOUN
iajs-4047	253	21	is	be	AUX
iajs-4047	253	22	2	2	NUM
iajs-4047	253	23	,	,	PUNCT
iajs-4047	253	24	and	and	CCONJ
iajs-4047	253	25	the	the	DET
iajs-4047	253	26	breast	breast	NOUN
iajs-4047	253	27	cancer	cancer	NOUN
iajs-4047	253	28	dataset	dataset	NOUN
iajs-4047	253	29	has	have	VERB
iajs-4047	253	30	10	10	NUM
iajs-4047	253	31	clusters	cluster	NOUN
iajs-4047	253	32	of	of	ADP
iajs-4047	253	33	digits	digit	NOUN
iajs-4047	253	34	.	.	PUNCT
iajs-4047	254	1	4	4	X
iajs-4047	254	2	.	.	X
iajs-4047	254	3	conclusion	conclusion	NOUN
iajs-4047	254	4	in	in	ADP
iajs-4047	254	5	clustering	cluster	VERB
iajs-4047	254	6	analysis	analysis	NOUN
iajs-4047	254	7	,	,	PUNCT
iajs-4047	254	8	many	many	ADJ
iajs-4047	254	9	procedures	procedure	NOUN
iajs-4047	254	10	necessitate	necessitate	ADJ
iajs-4047	254	11	the	the	DET
iajs-4047	254	12	designer	designer	NOUN
iajs-4047	254	13	to	to	PART
iajs-4047	254	14	supply	supply	VERB
iajs-4047	254	15	the	the	DET
iajs-4047	254	16	number	number	NOUN
iajs-4047	254	17	of	of	ADP
iajs-4047	254	18	clusters	cluster	NOUN
iajs-4047	254	19	.	.	PUNCT
iajs-4047	255	1	the	the	DET
iajs-4047	255	2	cluster	cluster	NOUN
iajs-4047	255	3	algorithms	algorithm	NOUN
iajs-4047	255	4	may	may	AUX
iajs-4047	255	5	not	not	PART
iajs-4047	255	6	have	have	VERB
iajs-4047	255	7	the	the	DET
iajs-4047	255	8	ability	ability	NOUN
iajs-4047	255	9	to	to	PART
iajs-4047	255	10	locate	locate	VERB
iajs-4047	255	11	the	the	DET
iajs-4047	255	12	appropriate	appropriate	ADJ
iajs-4047	255	13	number	number	NOUN
iajs-4047	255	14	of	of	ADP
iajs-4047	255	15	clusters	cluster	NOUN
iajs-4047	255	16	in	in	ADP
iajs-4047	255	17	advance	advance	NOUN
iajs-4047	255	18	.	.	PUNCT
iajs-4047	256	1	this	this	DET
iajs-4047	256	2	paper	paper	NOUN
iajs-4047	256	3	suggests	suggest	VERB
iajs-4047	256	4	a	a	DET
iajs-4047	256	5	new	new	ADJ
iajs-4047	256	6	goal	goal	NOUN
iajs-4047	256	7	function	function	NOUN
iajs-4047	256	8	for	for	ADP
iajs-4047	256	9	the	the	DET
iajs-4047	256	10	genetic	genetic	ADJ
iajs-4047	256	11	algorithm	algorithm	NOUN
iajs-4047	256	12	(	(	PUNCT
iajs-4047	256	13	ga)based	ga)based	ADJ
iajs-4047	256	14	gap	gap	NOUN
iajs-4047	256	15	statistic	statistic	NOUN
iajs-4047	256	16	clustering	clustering	NOUN
iajs-4047	256	17	method	method	NOUN
iajs-4047	256	18	based	base	VERB
iajs-4047	256	19	on	on	ADP
iajs-4047	256	20	the	the	DET
iajs-4047	256	21	clustering	clustering	ADJ
iajs-4047	256	22	partition	partition	NOUN
iajs-4047	256	23	.	.	PUNCT
iajs-4047	257	1	the	the	DET
iajs-4047	257	2	genetic	genetic	ADJ
iajs-4047	257	3	algorithm	algorithm	NOUN
iajs-4047	257	4	(	(	PUNCT
iajs-4047	257	5	ga	ga	NOUN
iajs-4047	257	6	)	)	PUNCT
iajs-4047	257	7	is	be	AUX
iajs-4047	257	8	an	an	DET
iajs-4047	257	9	optimization	optimization	NOUN
iajs-4047	257	10	technique	technique	NOUN
iajs-4047	257	11	that	that	PRON
iajs-4047	257	12	can	can	AUX
iajs-4047	257	13	present	present	VERB
iajs-4047	257	14	the	the	DET
iajs-4047	257	15	optimal	optimal	ADJ
iajs-4047	257	16	number	number	NOUN
iajs-4047	257	17	of	of	ADP
iajs-4047	257	18	clusters	cluster	NOUN
iajs-4047	257	19	for	for	ADP
iajs-4047	257	20	four	four	NUM
iajs-4047	257	21	different	different	ADJ
iajs-4047	257	22	datasets	dataset	NOUN
iajs-4047	257	23	:	:	PUNCT
iajs-4047	257	24	the	the	DET
iajs-4047	257	25	iris	iris	NOUN
iajs-4047	257	26	dataset	dataset	VERB
iajs-4047	257	27	,	,	PUNCT
iajs-4047	257	28	the	the	DET
iajs-4047	257	29	wine	wine	NOUN
iajs-4047	257	30	dataset	dataset	VERB
iajs-4047	257	31	,	,	PUNCT
iajs-4047	257	32	the	the	DET
iajs-4047	257	33	digits	digit	NOUN
iajs-4047	257	34	dataset	dataset	VERB
iajs-4047	257	35	,	,	PUNCT
iajs-4047	257	36	and	and	CCONJ
iajs-4047	257	37	the	the	DET
iajs-4047	257	38	breast	breast	NOUN
iajs-4047	257	39	cancer	cancer	NOUN
iajs-4047	257	40	dataset	dataset	NOUN
iajs-4047	257	41	)	)	PUNCT
iajs-4047	257	42	.	.	PUNCT
iajs-4047	258	1	the	the	DET
iajs-4047	258	2	genetic	genetic	ADJ
iajs-4047	258	3	algorithm	algorithm	NOUN
iajs-4047	258	4	(	(	PUNCT
iajs-4047	258	5	ga	ga	PROPN
iajs-4047	258	6	)	)	PUNCT
iajs-4047	258	7	with	with	ADP
iajs-4047	258	8	a	a	DET
iajs-4047	258	9	new	new	ADJ
iajs-4047	258	10	objective	objective	ADJ
iajs-4047	258	11	function	function	NOUN
iajs-4047	258	12	found	find	VERB
iajs-4047	258	13	the	the	DET
iajs-4047	258	14	right	right	ADJ
iajs-4047	258	15	number	number	NOUN
iajs-4047	258	16	of	of	ADP
iajs-4047	258	17	clusters	cluster	NOUN
iajs-4047	258	18	in	in	ADP
iajs-4047	258	19	four	four	NUM
iajs-4047	258	20	datasets	dataset	NOUN
iajs-4047	258	21	.	.	PUNCT
iajs-4047	259	1	acknowledgment	acknowledgment	NOUN
iajs-4047	259	2	thanks	thank	NOUN
iajs-4047	259	3	to	to	ADP
iajs-4047	259	4	the	the	DET
iajs-4047	259	5	department	department	PROPN
iajs-4047	259	6	of	of	ADP
iajs-4047	259	7	computer	computer	NOUN
iajs-4047	259	8	sciences	sciences	PROPN
iajs-4047	259	9	,	,	PUNCT
iajs-4047	259	10	college	college	NOUN
iajs-4047	259	11	of	of	ADP
iajs-4047	259	12	sciences	science	NOUN
iajs-4047	259	13	,	,	PUNCT
iajs-4047	259	14	university	university	NOUN
iajs-4047	259	15	of	of	ADP
iajs-4047	259	16	baghdad	baghdad	PROPN
iajs-4047	259	17	,	,	PUNCT
iajs-4047	259	18	for	for	ADP
iajs-4047	259	19	their	their	PRON
iajs-4047	259	20	support	support	NOUN
iajs-4047	259	21	and	and	CCONJ
iajs-4047	259	22	encouragement	encouragement	NOUN
iajs-4047	259	23	.	.	PUNCT
iajs-4047	260	1	conflict	conflict	NOUN
iajs-4047	260	2	of	of	ADP
iajs-4047	260	3	interest	interest	NOUN
iajs-4047	260	4	the	the	DET
iajs-4047	260	5	authors	author	NOUN
iajs-4047	260	6	declare	declare	VERB
iajs-4047	260	7	that	that	SCONJ
iajs-4047	260	8	they	they	PRON
iajs-4047	260	9	have	have	VERB
iajs-4047	260	10	no	no	DET
iajs-4047	260	11	conflicts	conflict	NOUN
iajs-4047	260	12	of	of	ADP
iajs-4047	260	13	interest	interest	NOUN
iajs-4047	260	14	.	.	PUNCT
iajs-4047	261	1	ihjpas	ihjpas	PROPN
iajs-4047	261	2	.	.	PUNCT
iajs-4047	262	1	2025	2025	NUM
iajs-4047	262	2	,	,	PUNCT
iajs-4047	262	3	38	38	NUM
iajs-4047	262	4	(	(	PUNCT
iajs-4047	262	5	2	2	NUM
iajs-4047	262	6	)	)	PUNCT
iajs-4047	262	7	440	440	NUM
iajs-4047	262	8	funding	funding	NOUN
iajs-4047	262	9	there	there	PRON
iajs-4047	262	10	is	be	VERB
iajs-4047	262	11	no	no	DET
iajs-4047	262	12	funding	funding	NOUN
iajs-4047	262	13	for	for	ADP
iajs-4047	262	14	this	this	DET
iajs-4047	262	15	research	research	NOUN
iajs-4047	262	16	.	.	PUNCT
iajs-4047	263	1	references	reference	NOUN
iajs-4047	263	2	1	1	NUM
iajs-4047	263	3	.	.	PUNCT
iajs-4047	264	1	zhu	zhu	PROPN
iajs-4047	264	2	e	e	PROPN
iajs-4047	264	3	,	,	PUNCT
iajs-4047	264	4	zhang	zhang	PROPN
iajs-4047	264	5	y	y	PROPN
iajs-4047	264	6	,	,	PUNCT
iajs-4047	264	7	wen	wen	PROPN
iajs-4047	264	8	p	p	PROPN
iajs-4047	264	9	,	,	PUNCT
iajs-4047	264	10	liu	liu	PROPN
iajs-4047	264	11	f.	f.	PROPN
iajs-4047	264	12	fast	fast	PROPN
iajs-4047	264	13	and	and	CCONJ
iajs-4047	264	14	stable	stable	ADJ
iajs-4047	264	15	clustering	clustering	ADJ
iajs-4047	264	16	analysis	analysis	NOUN
iajs-4047	264	17	based	base	VERB
iajs-4047	264	18	on	on	ADP
iajs-4047	264	19	grid	grid	NOUN
iajs-4047	264	20	-	-	PUNCT
iajs-4047	264	21	mapping	mapping	NOUN
iajs-4047	264	22	k	k	ADJ
iajs-4047	264	23	-	-	PUNCT
iajs-4047	264	24	means	means	NOUN
iajs-4047	264	25	algorithm	algorithm	NOUN
iajs-4047	264	26	and	and	CCONJ
iajs-4047	264	27	new	new	ADJ
iajs-4047	264	28	clustering	clustering	ADJ
iajs-4047	264	29	validity	validity	NOUN
iajs-4047	264	30	index	index	NOUN
iajs-4047	264	31	.	.	PUNCT
iajs-4047	265	1	neurocomputing	neurocompute	VERB
iajs-4047	265	2	.	.	PUNCT
iajs-4047	266	1	2019;363:149	2019;363:149	NUM
iajs-4047	266	2	-	-	SYM
iajs-4047	266	3	70	70	NUM
iajs-4047	266	4	.	.	PUNCT
iajs-4047	267	1	https://doi.org/10.1016/j.neucom.2019.07.048	https://doi.org/10.1016/j.neucom.2019.07.048	ADJ
iajs-4047	267	2	2	2	NUM
iajs-4047	267	3	.	.	PUNCT
iajs-4047	268	1	abdullah	abdullah	PROPN
iajs-4047	268	2	d.	d.	PROPN
iajs-4047	268	3	determining	determine	VERB
iajs-4047	268	4	a	a	DET
iajs-4047	268	5	cluster	cluster	NOUN
iajs-4047	268	6	centroid	centroid	NOUN
iajs-4047	268	7	of	of	ADP
iajs-4047	268	8	kmeans	kmean	NOUN
iajs-4047	268	9	clustering	cluster	VERB
iajs-4047	268	10	using	use	VERB
iajs-4047	268	11	genetic	genetic	ADJ
iajs-4047	268	12	algorithm	algorithm	NOUN
iajs-4047	268	13	.	.	PUNCT
iajs-4047	269	1	international	international	ADJ
iajs-4047	269	2	journal	journal	PROPN
iajs-4047	269	3	of	of	ADP
iajs-4047	269	4	computer	computer	NOUN
iajs-4047	269	5	science	science	NOUN
iajs-4047	269	6	and	and	CCONJ
iajs-4047	269	7	software	software	NOUN
iajs-4047	269	8	engineering	engineering	NOUN
iajs-4047	269	9	(	(	PUNCT
iajs-4047	269	10	ijcsse	ijcsse	NOUN
iajs-4047	269	11	)	)	PUNCT
iajs-4047	269	12	.	.	PUNCT
iajs-4047	270	1	2015;4(6):160	2015;4(6):160	NUM
iajs-4047	270	2	-	-	SYM
iajs-4047	270	3	4	4	NUM
iajs-4047	270	4	.	.	NOUN
iajs-4047	271	1	3	3	NUM
iajs-4047	271	2	.	.	X
iajs-4047	271	3	punhani	punhani	PROPN
iajs-4047	271	4	a	a	PRON
iajs-4047	271	5	,	,	PUNCT
iajs-4047	271	6	faujdar	faujdar	NOUN
iajs-4047	271	7	n	n	NOUN
iajs-4047	271	8	,	,	PUNCT
iajs-4047	271	9	mishra	mishra	PROPN
iajs-4047	271	10	kk	kk	PROPN
iajs-4047	271	11	,	,	PUNCT
iajs-4047	271	12	subramanian	subramanian	ADJ
iajs-4047	271	13	m.	m.	NOUN
iajs-4047	271	14	binning	binning	NOUN
iajs-4047	271	15	-	-	PUNCT
iajs-4047	271	16	based	base	VERB
iajs-4047	271	17	silhouette	silhouette	NOUN
iajs-4047	271	18	approach	approach	NOUN
iajs-4047	271	19	to	to	PART
iajs-4047	271	20	find	find	VERB
iajs-4047	271	21	the	the	DET
iajs-4047	271	22	optimal	optimal	ADJ
iajs-4047	271	23	cluster	cluster	NOUN
iajs-4047	271	24	using	use	VERB
iajs-4047	271	25	k	k	NOUN
iajs-4047	271	26	-	-	PUNCT
iajs-4047	271	27	means	mean	NOUN
iajs-4047	271	28	.	.	PUNCT
iajs-4047	272	1	ieee	ieee	NOUN
iajs-4047	272	2	access	access	NOUN
iajs-4047	272	3	.	.	PUNCT
iajs-4047	273	1	2022;10:115025	2022;10:115025	NUM
iajs-4047	273	2	-	-	SYM
iajs-4047	273	3	32	32	NUM
iajs-4047	273	4	.	.	PUNCT
iajs-4047	274	1	https://doi.org	https://doi.org	VERB
iajs-4047	274	2	/10.1109	/10.1109	ADJ
iajs-4047	274	3	/	/	SYM
iajs-4047	274	4	access.2022.3215568	access.2022.3215568	NOUN
iajs-4047	274	5	4	4	NUM
iajs-4047	274	6	.	.	X
iajs-4047	275	1	sultan	sultan	PROPN
iajs-4047	275	2	alalawi	alalawi	PROPN
iajs-4047	275	3	sj	sj	PROPN
iajs-4047	275	4	,	,	PUNCT
iajs-4047	275	5	mohd	mohd	PROPN
iajs-4047	275	6	shaharanee	shaharanee	NOUN
iajs-4047	275	7	in	in	ADV
iajs-4047	275	8	,	,	PUNCT
iajs-4047	275	9	mohd	mohd	PROPN
iajs-4047	275	10	jamil	jamil	PROPN
iajs-4047	275	11	j.	j.	PROPN
iajs-4047	275	12	clustering	cluster	VERB
iajs-4047	275	13	student	student	NOUN
iajs-4047	275	14	performance	performance	NOUN
iajs-4047	275	15	data	datum	NOUN
iajs-4047	275	16	using	use	VERB
iajs-4047	275	17	kmeans	kmean	NOUN
iajs-4047	275	18	algorithms	algorithm	NOUN
iajs-4047	275	19	.	.	PUNCT
iajs-4047	276	1	journal	journal	NOUN
iajs-4047	276	2	of	of	ADP
iajs-4047	276	3	computational	computational	ADJ
iajs-4047	276	4	innovation	innovation	NOUN
iajs-4047	276	5	and	and	CCONJ
iajs-4047	276	6	analytics	analytic	NOUN
iajs-4047	276	7	(	(	PUNCT
iajs-4047	276	8	jcia	jcia	PROPN
iajs-4047	276	9	)	)	PUNCT
iajs-4047	276	10	.	.	PUNCT
iajs-4047	277	1	2023;2(1):41	2023;2(1):41	NUM
iajs-4047	277	2	-	-	SYM
iajs-4047	277	3	55	55	NUM
iajs-4047	277	4	.	.	PUNCT
iajs-4047	278	1	https://doi.org/10.32890/jcia2023.2.1.3	https://doi.org/10.32890/jcia2023.2.1.3	PROPN
iajs-4047	278	2	5	5	NUM
iajs-4047	278	3	.	.	PUNCT
iajs-4047	278	4	yang	yang	PROPN
iajs-4047	278	5	j	j	PROPN
iajs-4047	278	6	,	,	PUNCT
iajs-4047	278	7	lee	lee	PROPN
iajs-4047	278	8	j	j	PROPN
iajs-4047	278	9	-	-	PROPN
iajs-4047	278	10	y	y	PROPN
iajs-4047	278	11	,	,	PUNCT
iajs-4047	278	12	choi	choi	NOUN
iajs-4047	278	13	m	m	PROPN
iajs-4047	278	14	,	,	PUNCT
iajs-4047	278	15	joo	joo	PROPN
iajs-4047	278	16	y	y	PROPN
iajs-4047	278	17	,	,	PUNCT
iajs-4047	278	18	editors	editor	NOUN
iajs-4047	278	19	.	.	PUNCT
iajs-4047	279	1	a	a	DET
iajs-4047	279	2	new	new	ADJ
iajs-4047	279	3	approach	approach	NOUN
iajs-4047	279	4	to	to	PART
iajs-4047	279	5	determine	determine	VERB
iajs-4047	279	6	the	the	DET
iajs-4047	279	7	optimal	optimal	ADJ
iajs-4047	279	8	number	number	NOUN
iajs-4047	279	9	of	of	ADP
iajs-4047	279	10	clusters	cluster	NOUN
iajs-4047	279	11	based	base	VERB
iajs-4047	279	12	on	on	ADP
iajs-4047	279	13	the	the	DET
iajs-4047	279	14	gap	gap	NOUN
iajs-4047	279	15	statistic	statistic	NOUN
iajs-4047	279	16	.	.	PUNCT
iajs-4047	280	1	international	international	ADJ
iajs-4047	280	2	conference	conference	NOUN
iajs-4047	280	3	on	on	ADP
iajs-4047	280	4	machine	machine	NOUN
iajs-4047	280	5	learning	learn	VERB
iajs-4047	280	6	for	for	ADP
iajs-4047	280	7	networking	networking	NOUN
iajs-4047	280	8	;	;	PUNCT
iajs-4047	280	9	2019	2019	NUM
iajs-4047	280	10	;	;	PUNCT
iajs-4047	280	11	lecture	lecture	NOUN
iajs-4047	280	12	notes	note	NOUN
iajs-4047	280	13	in	in	ADP
iajs-4047	280	14	computer	computer	NOUN
iajs-4047	280	15	science	science	NOUN
iajs-4047	280	16	,	,	PUNCT
iajs-4047	280	17	vol	vol	NOUN
iajs-4047	280	18	12081	12081	NUM
iajs-4047	280	19	:	:	PUNCT
iajs-4047	280	20	springer	springer	NOUN
iajs-4047	280	21	,	,	PUNCT
iajs-4047	280	22	cham	cham	PROPN
iajs-4047	280	23	.	.	PUNCT
iajs-4047	281	1	https://doi.org/	https://doi.org/	VERB
iajs-4047	281	2	10.1007/978	10.1007/978	NUM
iajs-4047	281	3	-	-	SYM
iajs-4047	281	4	3	3	NUM
iajs-4047	281	5	-	-	PUNCT
iajs-4047	281	6	030	030	NUM
iajs-4047	281	7	-	-	PUNCT
iajs-4047	281	8	45778	45778	NUM
iajs-4047	281	9	-	-	PUNCT
iajs-4047	281	10	5_15	5_15	NUM
iajs-4047	281	11	6	6	NUM
iajs-4047	281	12	.	.	PUNCT
iajs-4047	282	1	mor	mor	PROPN
iajs-4047	282	2	m	m	PROPN
iajs-4047	282	3	,	,	PUNCT
iajs-4047	282	4	gupta	gupta	PROPN
iajs-4047	282	5	p	p	NOUN
iajs-4047	282	6	,	,	PUNCT
iajs-4047	282	7	sharma	sharma	PROPN
iajs-4047	282	8	p.	p.	NOUN
iajs-4047	282	9	a	a	DET
iajs-4047	282	10	genetic	genetic	ADJ
iajs-4047	282	11	algorithm	algorithm	NOUN
iajs-4047	282	12	approach	approach	NOUN
iajs-4047	282	13	for	for	ADP
iajs-4047	282	14	clustering	clustering	NOUN
iajs-4047	282	15	.	.	PUNCT
iajs-4047	283	1	int	int	NOUN
iajs-4047	284	1	j	j	PROPN
iajs-4047	284	2	eng	eng	PROPN
iajs-4047	284	3	comput	comput	PROPN
iajs-4047	284	4	sci	sci	PROPN
iajs-4047	284	5	.	.	PUNCT
iajs-4047	285	1	2014;3(6):6442	2014;3(6):6442	NUM
iajs-4047	285	2	-	-	SYM
iajs-4047	285	3	7	7	NUM
iajs-4047	285	4	.	.	NOUN
iajs-4047	285	5	7	7	NUM
iajs-4047	285	6	.	.	X
iajs-4047	285	7	el	el	PROPN
iajs-4047	285	8	-	-	PUNCT
iajs-4047	285	9	shorbagy	shorbagy	PROPN
iajs-4047	285	10	ma	ma	PROPN
iajs-4047	285	11	,	,	PUNCT
iajs-4047	285	12	ayoub	ayoub	PROPN
iajs-4047	285	13	a	a	PROPN
iajs-4047	285	14	,	,	PUNCT
iajs-4047	285	15	mousa	mousa	NOUN
iajs-4047	285	16	a	a	PRON
iajs-4047	285	17	,	,	PUNCT
iajs-4047	285	18	el	el	PROPN
iajs-4047	285	19	-	-	PROPN
iajs-4047	285	20	desoky	desoky	PROPN
iajs-4047	285	21	i.	i.	NOUN
iajs-4047	285	22	an	an	DET
iajs-4047	285	23	enhanced	enhance	VERB
iajs-4047	285	24	genetic	genetic	ADJ
iajs-4047	285	25	algorithm	algorithm	NOUN
iajs-4047	285	26	with	with	ADP
iajs-4047	285	27	new	new	ADJ
iajs-4047	285	28	mutation	mutation	NOUN
iajs-4047	285	29	for	for	ADP
iajs-4047	285	30	cluster	cluster	NOUN
iajs-4047	285	31	analysis	analysis	NOUN
iajs-4047	285	32	.	.	PUNCT
iajs-4047	286	1	computational	computational	ADJ
iajs-4047	286	2	statistics	statistic	NOUN
iajs-4047	286	3	.	.	PUNCT
iajs-4047	287	1	2019;34:1355	2019;34:1355	NUM
iajs-4047	287	2	-	-	SYM
iajs-4047	287	3	92	92	NUM
iajs-4047	287	4	.	.	PUNCT
iajs-4047	288	1	https://doi.org/10.1007/s00180-019-00871-5	https://doi.org/10.1007/s00180-019-00871-5	NOUN
iajs-4047	288	2	8	8	NUM
iajs-4047	288	3	.	.	PUNCT
iajs-4047	289	1	hruschka	hruschka	PROPN
iajs-4047	289	2	er	er	INTJ
iajs-4047	289	3	,	,	PUNCT
iajs-4047	289	4	ebecken	ebecken	VERB
iajs-4047	289	5	nf	nf	NOUN
iajs-4047	289	6	.	.	PUNCT
iajs-4047	290	1	a	a	DET
iajs-4047	290	2	genetic	genetic	ADJ
iajs-4047	290	3	algorithm	algorithm	NOUN
iajs-4047	290	4	for	for	ADP
iajs-4047	290	5	cluster	cluster	NOUN
iajs-4047	290	6	analysis	analysis	NOUN
iajs-4047	290	7	.	.	PUNCT
iajs-4047	291	1	intelligent	intelligent	ADJ
iajs-4047	291	2	data	datum	NOUN
iajs-4047	291	3	analysis	analysis	NOUN
iajs-4047	291	4	.	.	PUNCT
iajs-4047	292	1	2003;7(1):15	2003;7(1):15	NUM
iajs-4047	292	2	-	-	SYM
iajs-4047	292	3	25	25	NUM
iajs-4047	292	4	.	.	PUNCT
iajs-4047	292	5	https://doi.org/10.3233/ida-2003-7103	https://doi.org/10.3233/ida-2003-7103	NOUN
iajs-4047	292	6	9	9	NUM
iajs-4047	292	7	.	.	PUNCT
iajs-4047	293	1	liu	liu	PROPN
iajs-4047	293	2	,	,	PUNCT
iajs-4047	293	3	y.	y.	PROPN
iajs-4047	293	4	;	;	PUNCT
iajs-4047	293	5	ye	ye	NUM
iajs-4047	293	6	,	,	PUNCT
iajs-4047	293	7	m.	m.	NOUN
iajs-4047	293	8	;	;	PUNCT
iajs-4047	293	9	peng	peng	PROPN
iajs-4047	293	10	,	,	PUNCT
iajs-4047	293	11	j.	j.	PROPN
iajs-4047	293	12	;	;	PUNCT
iajs-4047	293	13	wu	wu	PROPN
iajs-4047	293	14	,	,	PUNCT
iajs-4047	293	15	h.	h.	PROPN
iajs-4047	293	16	finding	find	VERB
iajs-4047	293	17	the	the	DET
iajs-4047	293	18	optimal	optimal	ADJ
iajs-4047	293	19	number	number	NOUN
iajs-4047	293	20	of	of	ADP
iajs-4047	293	21	clusters	cluster	NOUN
iajs-4047	293	22	using	use	VERB
iajs-4047	293	23	genetic	genetic	ADJ
iajs-4047	293	24	algorithms	algorithm	NOUN
iajs-4047	293	25	.	.	PUNCT
iajs-4047	294	1	in	in	ADP
iajs-4047	294	2	proceedings	proceeding	NOUN
iajs-4047	294	3	of	of	ADP
iajs-4047	294	4	the	the	DET
iajs-4047	294	5	2008	2008	NUM
iajs-4047	294	6	ieee	ieee	NOUN
iajs-4047	294	7	conference	conference	NOUN
iajs-4047	294	8	on	on	ADP
iajs-4047	294	9	cybernetics	cybernetic	NOUN
iajs-4047	294	10	and	and	CCONJ
iajs-4047	294	11	intelligent	intelligent	ADJ
iajs-4047	294	12	systems	system	NOUN
iajs-4047	294	13	;	;	PUNCT
iajs-4047	294	14	2008	2008	NUM
iajs-4047	294	15	;	;	PUNCT
iajs-4047	294	16	pp	pp	PROPN
iajs-4047	294	17	.	.	PUNCT
iajs-4047	294	18	1325	1325	NUM
iajs-4047	294	19	–	–	PUNCT
iajs-4047	294	20	1330	1330	NUM
iajs-4047	294	21	.	.	PUNCT
iajs-4047	295	1	https://doi.org/10.1109/iccis.2008.4670864	https://doi.org/10.1109/iccis.2008.4670864	PROPN
iajs-4047	295	2	10	10	NUM
iajs-4047	295	3	.	.	PUNCT
iajs-4047	296	1	rahman	rahman	PROPN
iajs-4047	296	2	ma	ma	PROPN
iajs-4047	296	3	,	,	PUNCT
iajs-4047	296	4	islam	islam	PROPN
iajs-4047	296	5	mz	mz	PROPN
iajs-4047	296	6	.	.	PROPN
iajs-4047	297	1	a	a	DET
iajs-4047	297	2	hybrid	hybrid	ADJ
iajs-4047	297	3	clustering	clustering	NOUN
iajs-4047	297	4	technique	technique	NOUN
iajs-4047	297	5	combining	combine	VERB
iajs-4047	297	6	a	a	DET
iajs-4047	297	7	novel	novel	ADJ
iajs-4047	297	8	genetic	genetic	ADJ
iajs-4047	297	9	algorithm	algorithm	NOUN
iajs-4047	297	10	with	with	ADP
iajs-4047	297	11	kmeans	kmean	NOUN
iajs-4047	297	12	.	.	PUNCT
iajs-4047	298	1	knowledge	knowledge	NOUN
iajs-4047	298	2	-	-	PUNCT
iajs-4047	298	3	based	base	VERB
iajs-4047	298	4	systems	system	NOUN
iajs-4047	298	5	.	.	PUNCT
iajs-4047	299	1	2014;71:345	2014;71:345	NUM
iajs-4047	299	2	-	-	SYM
iajs-4047	299	3	65	65	NUM
iajs-4047	299	4	.	.	PUNCT
iajs-4047	300	1	https://doi.org/10.1016/j.knosys.2014.08.011	https://doi.org/10.1016/j.knosys.2014.08.011	NUM
iajs-4047	300	2	11	11	NUM
iajs-4047	300	3	.	.	PUNCT
iajs-4047	301	1	roy	roy	PROPN
iajs-4047	301	2	dk	dk	PROPN
iajs-4047	301	3	,	,	PUNCT
iajs-4047	301	4	sharma	sharma	PROPN
iajs-4047	301	5	lk	lk	PROPN
iajs-4047	301	6	.	.	PROPN
iajs-4047	301	7	genetic	genetic	PROPN
iajs-4047	301	8	k	k	ADJ
iajs-4047	301	9	-	-	PUNCT
iajs-4047	301	10	means	mean	VERB
iajs-4047	301	11	clustering	cluster	VERB
iajs-4047	301	12	algorithm	algorithm	NOUN
iajs-4047	301	13	for	for	ADP
iajs-4047	301	14	mixed	mixed	ADJ
iajs-4047	301	15	numeric	numeric	ADJ
iajs-4047	301	16	and	and	CCONJ
iajs-4047	301	17	categorical	categorical	ADJ
iajs-4047	301	18	data	data	NOUN
iajs-4047	301	19	sets	set	NOUN
iajs-4047	301	20	.	.	PUNCT
iajs-4047	302	1	international	international	ADJ
iajs-4047	302	2	journal	journal	NOUN
iajs-4047	302	3	of	of	ADP
iajs-4047	302	4	artificial	artificial	ADJ
iajs-4047	302	5	intelligence	intelligence	NOUN
iajs-4047	302	6	&	&	CCONJ
iajs-4047	302	7	applications	application	NOUN
iajs-4047	302	8	.	.	PUNCT
iajs-4047	303	1	2010;1(2):23	2010;1(2):23	NUM
iajs-4047	303	2	-	-	SYM
iajs-4047	303	3	8	8	NUM
iajs-4047	303	4	.	.	PUNCT
iajs-4047	303	5	https://doi.org/	https://doi.org/	PROPN
iajs-4047	303	6	10.5121	10.5121	NUM
iajs-4047	303	7	/	/	SYM
iajs-4047	303	8	ijaia.2010.1203	ijaia.2010.1203	NUM
iajs-4047	303	9	12	12	NUM
iajs-4047	303	10	.	.	PUNCT
iajs-4047	304	1	han	han	PROPN
iajs-4047	304	2	s	s	PROPN
iajs-4047	304	3	,	,	PUNCT
iajs-4047	304	4	xiao	xiao	PROPN
iajs-4047	304	5	l	l	PROPN
iajs-4047	304	6	,	,	PUNCT
iajs-4047	304	7	editors	editor	NOUN
iajs-4047	304	8	.	.	PUNCT
iajs-4047	305	1	an	an	DET
iajs-4047	305	2	improved	improve	VERB
iajs-4047	305	3	adaptive	adaptive	ADJ
iajs-4047	305	4	genetic	genetic	ADJ
iajs-4047	305	5	algorithm	algorithm	NOUN
iajs-4047	305	6	.	.	PUNCT
iajs-4047	306	1	shs	shs	NOUN
iajs-4047	306	2	web	web	NOUN
iajs-4047	306	3	of	of	ADP
iajs-4047	306	4	conferences	conference	NOUN
iajs-4047	306	5	;	;	PUNCT
iajs-4047	306	6	2022	2022	NUM
iajs-4047	306	7	:	:	PUNCT
iajs-4047	306	8	edp	edp	PROPN
iajs-4047	306	9	sciences	science	NOUN
iajs-4047	306	10	.	.	PUNCT
iajs-4047	307	1	https://doi.org/10.1051/shsconf/202214001044	https://doi.org/10.1051/shsconf/202214001044	PROPN
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iajs-4047	307	3	.	.	PUNCT
iajs-4047	308	1	fahim	fahim	PROPN
iajs-4047	308	2	a.	a.	PROPN
iajs-4047	308	3	k	k	PROPN
iajs-4047	309	1	and	and	CCONJ
iajs-4047	309	2	starting	start	VERB
iajs-4047	309	3	means	mean	NOUN
iajs-4047	309	4	for	for	ADP
iajs-4047	309	5	k	k	NOUN
iajs-4047	309	6	-	-	PUNCT
iajs-4047	309	7	means	means	NOUN
iajs-4047	309	8	algorithm	algorithm	NOUN
iajs-4047	309	9	.	.	PUNCT
iajs-4047	310	1	journal	journal	NOUN
iajs-4047	310	2	of	of	ADP
iajs-4047	310	3	computational	computational	ADJ
iajs-4047	310	4	science	science	NOUN
iajs-4047	310	5	.	.	PUNCT
iajs-4047	311	1	2021;55:101445	2021;55:101445	NUM
iajs-4047	311	2	.	.	PUNCT
iajs-4047	312	1	https://doi.org/	https://doi.org/	VERB
iajs-4047	312	2	10.1016	10.1016	NUM
iajs-4047	312	3	/	/	SYM
iajs-4047	312	4	j.jocs.2021.101445	j.jocs.2021.101445	NOUN
iajs-4047	312	5	14	14	NUM
iajs-4047	312	6	.	.	PUNCT
iajs-4047	313	1	nazari	nazari	PROPN
iajs-4047	314	1	z	z	PROPN
iajs-4047	314	2	,	,	PUNCT
iajs-4047	314	3	kang	kang	PROPN
iajs-4047	314	4	d	d	PROPN
iajs-4047	314	5	,	,	PUNCT
iajs-4047	314	6	asharif	asharif	PROPN
iajs-4047	314	7	mr	mr	PROPN
iajs-4047	314	8	,	,	PUNCT
iajs-4047	314	9	sung	sung	PROPN
iajs-4047	314	10	y	y	PROPN
iajs-4047	314	11	,	,	PUNCT
iajs-4047	314	12	ogawa	ogawa	PROPN
iajs-4047	314	13	s	s	PROPN
iajs-4047	314	14	,	,	PUNCT
iajs-4047	314	15	editors	editor	NOUN
iajs-4047	314	16	.	.	PUNCT
iajs-4047	315	1	a	a	DET
iajs-4047	315	2	new	new	ADJ
iajs-4047	315	3	hierarchical	hierarchical	ADJ
iajs-4047	315	4	clustering	clustering	ADJ
iajs-4047	315	5	algorithm	algorithm	NOUN
iajs-4047	315	6	.	.	PUNCT
iajs-4047	316	1	2015	2015	NUM
iajs-4047	316	2	international	international	ADJ
iajs-4047	316	3	conference	conference	NOUN
iajs-4047	316	4	on	on	ADP
iajs-4047	316	5	intelligent	intelligent	ADJ
iajs-4047	316	6	informatics	informatic	NOUN
iajs-4047	316	7	and	and	CCONJ
iajs-4047	316	8	biomedical	biomedical	ADJ
iajs-4047	316	9	sciences	science	NOUN
iajs-4047	316	10	(	(	PUNCT
iajs-4047	316	11	iciibms	iciibms	NOUN
iajs-4047	316	12	)	)	PUNCT
iajs-4047	316	13	;	;	PUNCT
iajs-4047	316	14	2015	2015	NUM
iajs-4047	316	15	:	:	PUNCT
iajs-4047	316	16	ieee	ieee	NOUN
iajs-4047	316	17	.	.	PUNCT
iajs-4047	317	1	https://doi.org/10.1109/iciibms.2015.7439517	https://doi.org/10.1109/iciibms.2015.7439517	PROPN
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iajs-4047	317	3	.	.	PUNCT
iajs-4047	318	1	fluck	fluck	VERB
iajs-4047	318	2	e.	e.	PROPN
iajs-4047	318	3	tangles	tangles	PROPN
iajs-4047	318	4	and	and	CCONJ
iajs-4047	318	5	hierarchical	hierarchical	ADJ
iajs-4047	318	6	clustering	clustering	NOUN
iajs-4047	318	7	.	.	PUNCT
iajs-4047	319	1	siam	siam	PROPN
iajs-4047	319	2	journal	journal	PROPN
iajs-4047	319	3	on	on	ADP
iajs-4047	319	4	discrete	discrete	ADJ
iajs-4047	319	5	mathematics	mathematic	NOUN
iajs-4047	319	6	.	.	PUNCT
iajs-4047	320	1	2024;38(1):7592	2024;38(1):7592	NUM
iajs-4047	320	2	.	.	PUNCT
iajs-4047	321	1	https://doi.org/10.1137/22m1484936	https://doi.org/10.1137/22m1484936	PROPN
iajs-4047	321	2	16	16	NUM
iajs-4047	321	3	.	.	PUNCT
iajs-4047	322	1	moulavi	moulavi	PROPN
iajs-4047	322	2	d	d	PROPN
iajs-4047	322	3	,	,	PUNCT
iajs-4047	322	4	jaskowiak	jaskowiak	PROPN
iajs-4047	322	5	pa	pa	PROPN
iajs-4047	322	6	,	,	PUNCT
iajs-4047	322	7	campello	campello	PROPN
iajs-4047	322	8	rj	rj	PROPN
iajs-4047	322	9	,	,	PUNCT
iajs-4047	322	10	zimek	zimek	PROPN
iajs-4047	322	11	a	a	X
iajs-4047	322	12	,	,	PUNCT
iajs-4047	322	13	sander	sander	PROPN
iajs-4047	322	14	j	j	PROPN
iajs-4047	322	15	,	,	PUNCT
iajs-4047	322	16	editors	editor	NOUN
iajs-4047	322	17	.	.	PUNCT
iajs-4047	323	1	density	density	NOUN
iajs-4047	323	2	-	-	PUNCT
iajs-4047	323	3	based	base	VERB
iajs-4047	323	4	clustering	clustering	ADJ
iajs-4047	323	5	validation	validation	NOUN
iajs-4047	323	6	.	.	PUNCT
iajs-4047	324	1	proceedings	proceeding	NOUN
iajs-4047	324	2	of	of	ADP
iajs-4047	324	3	the	the	DET
iajs-4047	324	4	2014	2014	NUM
iajs-4047	324	5	siam	siam	ADJ
iajs-4047	324	6	international	international	ADJ
iajs-4047	324	7	conference	conference	NOUN
iajs-4047	324	8	on	on	ADP
iajs-4047	324	9	data	datum	NOUN
iajs-4047	324	10	mining	mining	NOUN
iajs-4047	324	11	;	;	PUNCT
iajs-4047	324	12	2014	2014	NUM
iajs-4047	324	13	:	:	PUNCT
iajs-4047	324	14	siam	siam	PROPN
iajs-4047	324	15	.	.	PUNCT
iajs-4047	325	1	https://doi.org/10.1137/1.9781611973440.96	https://doi.org/10.1137/1.9781611973440.96	PROPN
iajs-4047	325	2	17	17	NUM
iajs-4047	325	3	.	.	PUNCT
iajs-4047	326	1	behadil	behadil	PROPN
iajs-4047	326	2	sf	sf	PROPN
iajs-4047	326	3	,	,	PUNCT
iajs-4047	326	4	mhalhal	mhalhal	PROPN
iajs-4047	326	5	nk	nk	PROPN
iajs-4047	326	6	.	.	PUNCT
iajs-4047	326	7	mobility	mobility	PROPN
iajs-4047	326	8	prediction	prediction	NOUN
iajs-4047	326	9	based	base	VERB
iajs-4047	326	10	on	on	ADP
iajs-4047	326	11	deep	deep	ADJ
iajs-4047	326	12	learning	learning	NOUN
iajs-4047	326	13	approach	approach	NOUN
iajs-4047	326	14	using	use	VERB
iajs-4047	326	15	gps	gps	PROPN
iajs-4047	326	16	phone	phone	NOUN
iajs-4047	326	17	data	datum	NOUN
iajs-4047	326	18	.	.	PUNCT
iajs-4047	327	1	ibn	ibn	PROPN
iajs-4047	327	2	al	al	PROPN
iajs-4047	327	3	-	-	PUNCT
iajs-4047	327	4	haitham	haitham	PROPN
iajs-4047	327	5	journal	journal	PROPN
iajs-4047	327	6	for	for	ADP
iajs-4047	327	7	pure	pure	ADJ
iajs-4047	327	8	and	and	CCONJ
iajs-4047	327	9	applied	applied	ADJ
iajs-4047	327	10	sciences	science	NOUN
iajs-4047	327	11	.	.	PUNCT
iajs-4047	328	1	2024;37(4):423	2024;37(4):423	NUM
iajs-4047	328	2	-	-	SYM
iajs-4047	328	3	38	38	NUM
iajs-4047	328	4	.	.	PUNCT
iajs-4047	329	1	https://doi.org/10.30526/37.4.3916	https://doi.org/10.30526/37.4.3916	PROPN
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iajs-4047	329	4	blank	blank	ADJ
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iajs-4047	329	6	:	:	PUNCT
iajs-4047	329	7	blank	blank	ADJ
iajs-4047	329	8	about	about	ADP
iajs-4047	329	9	:	:	PUNCT
iajs-4047	329	10	blank	blank	ADJ
iajs-4047	329	11	about	about	ADP
iajs-4047	329	12	:	:	PUNCT
iajs-4047	329	13	blank	blank	ADJ
iajs-4047	329	14	about	about	ADP
iajs-4047	329	15	:	:	PUNCT
iajs-4047	329	16	blank	blank	ADJ
iajs-4047	329	17	about	about	ADP
iajs-4047	329	18	:	:	PUNCT
iajs-4047	329	19	blank	blank	ADJ
iajs-4047	329	20	about	about	ADP
iajs-4047	329	21	:	:	PUNCT
iajs-4047	329	22	blank	blank	ADJ
iajs-4047	329	23	about	about	ADP
iajs-4047	329	24	:	:	PUNCT
iajs-4047	329	25	blank	blank	ADJ
iajs-4047	329	26	about	about	ADP
iajs-4047	329	27	:	:	PUNCT
iajs-4047	329	28	blank	blank	VERB
iajs-4047	329	29	https://doi.org/10.1109/iciibms.2015.7439517	https://doi.org/10.1109/iciibms.2015.7439517	PROPN
iajs-4047	329	30	about	about	ADP
iajs-4047	329	31	:	:	PUNCT
iajs-4047	329	32	blank	blank	ADJ
iajs-4047	329	33	about	about	ADP
iajs-4047	329	34	:	:	PUNCT
iajs-4047	329	35	blank	blank	ADJ
iajs-4047	329	36	about	about	ADP
iajs-4047	329	37	:	:	PUNCT
iajs-4047	329	38	blank	blank	ADJ
iajs-4047	329	39	ihjpas	ihjpas	PROPN
iajs-4047	329	40	.	.	PUNCT
iajs-4047	330	1	2025	2025	NUM
iajs-4047	330	2	,	,	PUNCT
iajs-4047	330	3	38	38	NUM
iajs-4047	330	4	(	(	PUNCT
iajs-4047	330	5	2	2	NUM
iajs-4047	330	6	)	)	PUNCT
iajs-4047	330	7	441	441	NUM
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iajs-4047	330	9	.	.	PUNCT
iajs-4047	331	1	ren	ren	PROPN
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iajs-4047	331	3	,	,	PUNCT
iajs-4047	331	4	wang	wang	PROPN
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iajs-4047	331	6	,	,	PUNCT
iajs-4047	331	7	li	li	PROPN
iajs-4047	331	8	m	m	PROPN
iajs-4047	331	9	,	,	PUNCT
iajs-4047	331	10	xu	xu	PROPN
iajs-4047	331	11	z.	z.	PROPN
iajs-4047	332	1	deep	deep	ADJ
iajs-4047	332	2	density	density	NOUN
iajs-4047	332	3	-	-	PUNCT
iajs-4047	332	4	based	base	VERB
iajs-4047	332	5	image	image	NOUN
iajs-4047	332	6	clustering	clustering	NOUN
iajs-4047	332	7	.	.	PUNCT
iajs-4047	333	1	knowledge	knowledge	NOUN
iajs-4047	333	2	-	-	PUNCT
iajs-4047	333	3	based	base	VERB
iajs-4047	333	4	systems	system	NOUN
iajs-4047	333	5	.	.	PUNCT
iajs-4047	334	1	2020;197:105841	2020;197:105841	NUM
iajs-4047	334	2	.	.	PUNCT
iajs-4047	335	1	https://doi.org/10.1016/j.knosys.2020.105841	https://doi.org/10.1016/j.knosys.2020.105841	PROPN
iajs-4047	335	2	19	19	NUM
iajs-4047	335	3	.	.	PUNCT
iajs-4047	336	1	wang	wang	PROPN
iajs-4047	336	2	f	f	PROPN
iajs-4047	336	3	,	,	PUNCT
iajs-4047	336	4	liao	liao	PROPN
iajs-4047	336	5	f	f	PROPN
iajs-4047	336	6	,	,	PUNCT
iajs-4047	336	7	li	li	PROPN
iajs-4047	336	8	y	y	PROPN
iajs-4047	336	9	,	,	PUNCT
iajs-4047	336	10	wang	wang	PROPN
iajs-4047	336	11	h.	h.	PROPN
iajs-4047	337	1	a	a	DET
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iajs-4047	337	4	strategy	strategy	NOUN
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iajs-4047	337	6	dynamic	dynamic	ADJ
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iajs-4047	337	8	-	-	ADJ
iajs-4047	337	9	objective	objective	ADJ
iajs-4047	337	10	optimization	optimization	NOUN
iajs-4047	337	11	using	use	VERB
iajs-4047	337	12	gaussian	gaussian	ADJ
iajs-4047	337	13	mixture	mixture	NOUN
iajs-4047	337	14	model	model	NOUN
iajs-4047	337	15	.	.	PUNCT
iajs-4047	338	1	information	information	NOUN
iajs-4047	338	2	sciences	sciences	PROPN
iajs-4047	338	3	.	.	PUNCT
iajs-4047	339	1	2021;580:331	2021;580:331	NUM
iajs-4047	339	2	-	-	SYM
iajs-4047	339	3	51	51	NUM
iajs-4047	339	4	.	.	PUNCT
iajs-4047	340	1	https://doi.org/10.1016/j.ins.2021.08.065	https://doi.org/10.1016/j.ins.2021.08.065	NOUN
iajs-4047	340	2	20	20	NUM
iajs-4047	340	3	.	.	PUNCT
iajs-4047	341	1	mahmoudi	mahmoudi	PROPN
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iajs-4047	341	3	,	,	PUNCT
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iajs-4047	341	9	,	,	PUNCT
iajs-4047	341	10	tuan	tuan	PROPN
iajs-4047	341	11	ba	ba	PROPN
iajs-4047	341	12	,	,	PUNCT
iajs-4047	341	13	pho	pho	X
iajs-4047	341	14	k	k	PROPN
iajs-4047	341	15	-	-	PROPN
iajs-4047	341	16	h.	h.	ADJ
iajs-4047	341	17	fuzzy	fuzzy	ADJ
iajs-4047	341	18	clustering	clustering	NOUN
iajs-4047	341	19	method	method	NOUN
iajs-4047	341	20	to	to	PART
iajs-4047	341	21	compare	compare	VERB
iajs-4047	341	22	the	the	DET
iajs-4047	341	23	spread	spread	ADJ
iajs-4047	341	24	rate	rate	NOUN
iajs-4047	341	25	of	of	ADP
iajs-4047	341	26	covid-19	covid-19	PROPN
iajs-4047	341	27	in	in	ADP
iajs-4047	341	28	the	the	DET
iajs-4047	341	29	high	high	ADJ
iajs-4047	341	30	risks	risk	NOUN
iajs-4047	341	31	countries	country	NOUN
iajs-4047	341	32	.	.	PUNCT
iajs-4047	342	1	chaos	chaos	NOUN
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iajs-4047	342	6	.	.	PUNCT
iajs-4047	343	1	2020;140:110230	2020;140:110230	X
iajs-4047	343	2	.	.	PUNCT
iajs-4047	344	1	https://doi.org/10.1016/j.chaos.2020.110230	https://doi.org/10.1016/j.chaos.2020.110230	PROPN
iajs-4047	344	2	21	21	NUM
iajs-4047	344	3	.	.	PUNCT
iajs-4047	345	1	amma	amma	PROPN
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iajs-4047	345	4	,	,	PUNCT
iajs-4047	345	5	amma	amma	PROPN
iajs-4047	345	6	ng	ng	PROPN
iajs-4047	345	7	b.	b.	PROPN
iajs-4047	345	8	pclusba	pclusba	PROPN
iajs-4047	345	9	:	:	PUNCT
iajs-4047	345	10	a	a	DET
iajs-4047	345	11	novel	novel	ADJ
iajs-4047	345	12	partition	partition	NOUN
iajs-4047	345	13	clustering	clustering	NOUN
iajs-4047	345	14	-	-	PUNCT
iajs-4047	345	15	based	base	VERB
iajs-4047	345	16	biometric	biometric	ADJ
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iajs-4047	345	18	mechanism	mechanism	NOUN
iajs-4047	345	19	.	.	PUNCT
iajs-4047	346	1	iete	iete	ADJ
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iajs-4047	346	3	of	of	ADP
iajs-4047	346	4	research	research	NOUN
iajs-4047	346	5	.	.	PUNCT
iajs-4047	347	1	2024;70(1):467	2024;70(1):467	NUM
iajs-4047	347	2	-	-	SYM
iajs-4047	347	3	72	72	NUM
iajs-4047	347	4	.	.	PUNCT
iajs-4047	348	1	https://doi.org/10.1080/03772063.2022.2108917	https://doi.org/10.1080/03772063.2022.2108917	NOUN
iajs-4047	348	2	22	22	NUM
iajs-4047	348	3	.	.	PUNCT
iajs-4047	349	1	kapil	kapil	PROPN
iajs-4047	349	2	s	s	PROPN
iajs-4047	349	3	,	,	PUNCT
iajs-4047	349	4	chawla	chawla	PROPN
iajs-4047	349	5	m	m	PROPN
iajs-4047	349	6	,	,	PUNCT
iajs-4047	349	7	ansari	ansari	PROPN
iajs-4047	349	8	md	md	PROPN
iajs-4047	349	9	,	,	PUNCT
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iajs-4047	350	1	on	on	ADP
iajs-4047	350	2	k	k	ADJ
iajs-4047	350	3	-	-	PUNCT
iajs-4047	350	4	means	mean	VERB
iajs-4047	350	5	data	datum	NOUN
iajs-4047	350	6	clustering	cluster	VERB
iajs-4047	350	7	algorithm	algorithm	NOUN
iajs-4047	350	8	with	with	ADP
iajs-4047	350	9	genetic	genetic	ADJ
iajs-4047	350	10	algorithm	algorithm	NOUN
iajs-4047	350	11	.	.	PUNCT
iajs-4047	351	1	2016	2016	NUM
iajs-4047	351	2	fourth	fourth	ADJ
iajs-4047	351	3	international	international	ADJ
iajs-4047	351	4	conference	conference	NOUN
iajs-4047	351	5	on	on	ADP
iajs-4047	351	6	parallel	parallel	NOUN
iajs-4047	351	7	,	,	PUNCT
iajs-4047	351	8	distributed	distribute	VERB
iajs-4047	351	9	and	and	CCONJ
iajs-4047	351	10	grid	grid	NOUN
iajs-4047	351	11	computing	computing	NOUN
iajs-4047	351	12	(	(	PUNCT
iajs-4047	351	13	pdgc	pdgc	NOUN
iajs-4047	351	14	)	)	PUNCT
iajs-4047	351	15	;	;	PUNCT
iajs-4047	351	16	2016	2016	NUM
iajs-4047	351	17	:	:	PUNCT
iajs-4047	351	18	ieee	ieee	NOUN
iajs-4047	351	19	.	.	PUNCT
iajs-4047	352	1	https://doi.org/10.1109/pdgc.2016.7913145	https://doi.org/10.1109/pdgc.2016.7913145	PROPN
iajs-4047	352	2	23	23	NUM
iajs-4047	352	3	.	.	PUNCT
iajs-4047	353	1	haldurai	haldurai	PROPN
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iajs-4047	353	3	,	,	PUNCT
iajs-4047	353	4	madhubala	madhubala	PROPN
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iajs-4047	353	8	r.	r.	VERB
iajs-4047	353	9	a	a	DET
iajs-4047	353	10	study	study	NOUN
iajs-4047	353	11	on	on	ADP
iajs-4047	353	12	genetic	genetic	ADJ
iajs-4047	353	13	algorithm	algorithm	NOUN
iajs-4047	353	14	and	and	CCONJ
iajs-4047	353	15	its	its	PRON
iajs-4047	353	16	applications	application	NOUN
iajs-4047	353	17	.	.	PUNCT
iajs-4047	354	1	int	int	NOUN
iajs-4047	354	2	j	j	PROPN
iajs-4047	354	3	comput	comput	VERB
iajs-4047	354	4	sci	sci	PROPN
iajs-4047	354	5	eng	eng	PROPN
iajs-4047	354	6	.	.	PUNCT
iajs-4047	355	1	2016;4(10):139	2016;4(10):139	PROPN
iajs-4047	355	2	-	-	SYM
iajs-4047	355	3	43	43	NUM
iajs-4047	355	4	.	.	PUNCT
iajs-4047	356	1	24	24	NUM
iajs-4047	356	2	.	.	PUNCT
iajs-4047	356	3	zeebaree	zeebaree	PROPN
iajs-4047	356	4	dq	dq	PROPN
iajs-4047	356	5	,	,	PUNCT
iajs-4047	356	6	haron	haron	PROPN
iajs-4047	356	7	h	h	PROPN
iajs-4047	356	8	,	,	PUNCT
iajs-4047	356	9	abdulazeez	abdulazeez	PROPN
iajs-4047	356	10	am	be	AUX
iajs-4047	356	11	,	,	PUNCT
iajs-4047	356	12	zeebaree	zeebaree	PROPN
iajs-4047	356	13	s.	s.	PROPN
iajs-4047	356	14	combination	combination	NOUN
iajs-4047	356	15	of	of	ADP
iajs-4047	356	16	k	k	NOUN
iajs-4047	356	17	-	-	PUNCT
iajs-4047	356	18	means	means	NOUN
iajs-4047	356	19	clustering	cluster	VERB
iajs-4047	356	20	with	with	ADP
iajs-4047	356	21	genetic	genetic	ADJ
iajs-4047	356	22	algorithm	algorithm	NOUN
iajs-4047	356	23	:	:	PUNCT
iajs-4047	356	24	a	a	DET
iajs-4047	356	25	review	review	NOUN
iajs-4047	356	26	.	.	PUNCT
iajs-4047	357	1	international	international	ADJ
iajs-4047	357	2	journal	journal	PROPN
iajs-4047	357	3	of	of	ADP
iajs-4047	357	4	applied	apply	VERB
iajs-4047	357	5	engineering	engineering	NOUN
iajs-4047	357	6	research	research	NOUN
iajs-4047	357	7	.	.	PUNCT
iajs-4047	358	1	2017;12(24):14238	2017;12(24):14238	NUM
iajs-4047	358	2	-	-	SYM
iajs-4047	358	3	45	45	NUM
iajs-4047	358	4	.	.	PUNCT
iajs-4047	359	1	25	25	NUM
iajs-4047	359	2	.	.	PUNCT
iajs-4047	360	1	maulana	maulana	PROPN
iajs-4047	360	2	i	i	PROPN
iajs-4047	360	3	,	,	PUNCT
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iajs-4047	360	5	r.	r.	PROPN
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iajs-4047	360	7	knn	knn	PROPN
iajs-4047	360	8	algorithm	algorithm	PROPN
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iajs-4047	360	10	elbow	elbow	NOUN
iajs-4047	360	11	method	method	NOUN
iajs-4047	360	12	for	for	ADP
iajs-4047	360	13	predicting	predict	VERB
iajs-4047	360	14	voter	voter	NOUN
iajs-4047	360	15	participation	participation	NOUN
iajs-4047	360	16	using	use	VERB
iajs-4047	360	17	fixed	fix	VERB
iajs-4047	360	18	voter	voter	NOUN
iajs-4047	360	19	list	list	NOUN
iajs-4047	360	20	data	datum	NOUN
iajs-4047	360	21	(	(	PUNCT
iajs-4047	360	22	dpt	dpt	PROPN
iajs-4047	360	23	)	)	PUNCT
iajs-4047	360	24	.	.	PUNCT
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iajs-4047	361	4	.	.	PUNCT
iajs-4047	362	1	2024;4(7):441	2024;4(7):441	NUM
iajs-4047	362	2	-	-	PUNCT
iajs-4047	362	3	51	51	NUM
iajs-4047	362	4	.	.	PUNCT
iajs-4047	363	1	https://doi.org/10.59188/jurnalsostech.v4i7.1308	https://doi.org/10.59188/jurnalsostech.v4i7.1308	PROPN
iajs-4047	363	2	26	26	NUM
iajs-4047	363	3	.	.	PUNCT
iajs-4047	364	1	vardakas	vardakas	PROPN
iajs-4047	364	2	g	g	PROPN
iajs-4047	364	3	,	,	PUNCT
iajs-4047	364	4	papakostas	papakosta	NOUN
iajs-4047	364	5	i	i	PRON
iajs-4047	364	6	,	,	PUNCT
iajs-4047	364	7	likas	likas	PROPN
iajs-4047	364	8	a.	a.	NOUN
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iajs-4047	364	10	clustering	clustering	NOUN
iajs-4047	364	11	using	use	VERB
iajs-4047	364	12	the	the	DET
iajs-4047	364	13	soft	soft	ADJ
iajs-4047	364	14	silhouette	silhouette	NOUN
iajs-4047	364	15	score	score	NOUN
iajs-4047	364	16	:	:	PUNCT
iajs-4047	364	17	towards	towards	ADP
iajs-4047	364	18	compact	compact	ADJ
iajs-4047	364	19	and	and	CCONJ
iajs-4047	364	20	well	well	ADV
iajs-4047	364	21	-	-	PUNCT
iajs-4047	364	22	separated	separate	VERB
iajs-4047	364	23	clusters	cluster	NOUN
iajs-4047	364	24	.	.	PUNCT
iajs-4047	365	1	arxiv	arxiv	PROPN
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iajs-4047	365	4	.	.	PUNCT
iajs-4047	366	1	2024	2024	NUM
iajs-4047	366	2	.	.	PUNCT
iajs-4047	367	1	https://doi.org/10.48550/arxiv.2402.00608	https://doi.org/10.48550/arxiv.2402.00608	PROPN
iajs-4047	367	2	27	27	NUM
iajs-4047	367	3	.	.	PUNCT
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iajs-4047	368	3	,	,	PUNCT
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iajs-4047	368	5	p	p	X
iajs-4047	368	6	,	,	PUNCT
iajs-4047	368	7	dazeley	dazeley	PROPN
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iajs-4047	368	10	authorship	authorship	NOUN
iajs-4047	368	11	distance	distance	NOUN
iajs-4047	368	12	methods	method	NOUN
iajs-4047	368	13	using	use	VERB
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iajs-4047	368	15	positive	positive	ADJ
iajs-4047	368	16	silhouette	silhouette	NOUN
iajs-4047	368	17	coefficient	coefficient	NOUN
iajs-4047	368	18	.	.	PUNCT
iajs-4047	368	19	natural	natural	ADJ
iajs-4047	368	20	language	language	NOUN
iajs-4047	368	21	engineering	engineering	NOUN
iajs-4047	368	22	.	.	PUNCT
iajs-4047	369	1	2013;19(4):517	2013;19(4):517	NUM
iajs-4047	369	2	-	-	SYM
iajs-4047	369	3	35	35	NUM
iajs-4047	369	4	.	.	PUNCT
iajs-4047	370	1	https://doi.org/	https://doi.org/	NOUN
iajs-4047	370	2	10.1017	10.1017	NUM
iajs-4047	370	3	/	/	SYM
iajs-4047	370	4	s1351324912000241	s1351324912000241	NOUN
iajs-4047	370	5	28	28	NUM
iajs-4047	370	6	.	.	PUNCT
iajs-4047	371	1	sagala	sagala	PROPN
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iajs-4047	371	3	,	,	PUNCT
iajs-4047	371	4	gunawan	gunawan	PROPN
iajs-4047	371	5	aas	aas	PROPN
iajs-4047	371	6	.	.	PUNCT
iajs-4047	372	1	discovering	discover	VERB
iajs-4047	372	2	the	the	DET
iajs-4047	372	3	optimal	optimal	ADJ
iajs-4047	372	4	number	number	NOUN
iajs-4047	372	5	of	of	ADP
iajs-4047	372	6	crime	crime	NOUN
iajs-4047	372	7	cluster	cluster	NOUN
iajs-4047	372	8	using	use	VERB
iajs-4047	372	9	elbow	elbow	NOUN
iajs-4047	372	10	,	,	PUNCT
iajs-4047	372	11	silhouette	silhouette	NOUN
iajs-4047	372	12	,	,	PUNCT
iajs-4047	372	13	gap	gap	NOUN
iajs-4047	372	14	statistics	statistic	NOUN
iajs-4047	372	15	,	,	PUNCT
iajs-4047	372	16	and	and	CCONJ
iajs-4047	372	17	nbclust	nbclust	PROPN
iajs-4047	372	18	methods	method	NOUN
iajs-4047	372	19	.	.	PUNCT
iajs-4047	373	1	comtech	comtech	PROPN
iajs-4047	373	2	:	:	PUNCT
iajs-4047	373	3	computer	computer	NOUN
iajs-4047	373	4	,	,	PUNCT
iajs-4047	373	5	mathematics	mathematics	PROPN
iajs-4047	373	6	and	and	CCONJ
iajs-4047	373	7	engineering	engineering	NOUN
iajs-4047	373	8	applications	application	NOUN
iajs-4047	373	9	.	.	PUNCT
iajs-4047	374	1	2022;13(1):1	2022;13(1):1	NUM
iajs-4047	374	2	-	-	SYM
iajs-4047	374	3	10	10	NUM
iajs-4047	374	4	.	.	PUNCT
iajs-4047	375	1	https://doi.org/	https://doi.org/	NOUN
iajs-4047	375	2	10.21512	10.21512	NUM
iajs-4047	375	3	/	/	SYM
iajs-4047	375	4	comtech.v13i1.7270	comtech.v13i1.7270	NOUN
iajs-4047	375	5	29	29	NUM
iajs-4047	375	6	.	.	PUNCT
iajs-4047	376	1	xiao	xiao	PROPN
iajs-4047	376	2	j	j	PROPN
iajs-4047	376	3	,	,	PUNCT
iajs-4047	376	4	lu	lu	PROPN
iajs-4047	376	5	j	j	PROPN
iajs-4047	376	6	,	,	PUNCT
iajs-4047	376	7	li	li	PROPN
iajs-4047	376	8	x.	x.	PROPN
iajs-4047	376	9	davies	davies	PROPN
iajs-4047	376	10	bouldin	bouldin	PROPN
iajs-4047	376	11	index	index	NOUN
iajs-4047	376	12	based	base	VERB
iajs-4047	376	13	hierarchical	hierarchical	ADJ
iajs-4047	376	14	initialization	initialization	NOUN
iajs-4047	376	15	k	k	NOUN
iajs-4047	376	16	-	-	PUNCT
iajs-4047	376	17	means	mean	NOUN
iajs-4047	376	18	.	.	PUNCT
iajs-4047	377	1	intelligent	intelligent	ADJ
iajs-4047	377	2	data	datum	NOUN
iajs-4047	377	3	analysis	analysis	NOUN
iajs-4047	377	4	.	.	PUNCT
iajs-4047	378	1	2017;21(6):1327	2017;21(6):1327	NUM
iajs-4047	378	2	-	-	SYM
iajs-4047	378	3	38	38	NUM
iajs-4047	378	4	.	.	PUNCT
iajs-4047	379	1	https://doi.org/10.3233/ida-163129	https://doi.org/10.3233/ida-163129	PROPN
iajs-4047	379	2	30	30	NUM
iajs-4047	379	3	.	.	PUNCT
iajs-4047	380	1	gupta	gupta	PROPN
iajs-4047	380	2	t	t	PROPN
iajs-4047	380	3	,	,	PUNCT
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iajs-4047	380	5	sp	sp	PROPN
iajs-4047	380	6	.	.	PUNCT
iajs-4047	381	1	a	a	DET
iajs-4047	381	2	comparison	comparison	NOUN
iajs-4047	381	3	of	of	ADP
iajs-4047	381	4	k	k	NOUN
iajs-4047	381	5	-	-	PUNCT
iajs-4047	381	6	means	mean	VERB
iajs-4047	381	7	clustering	cluster	VERB
iajs-4047	381	8	algorithm	algorithm	NOUN
iajs-4047	381	9	and	and	CCONJ
iajs-4047	381	10	clara	clara	PROPN
iajs-4047	381	11	clustering	cluster	VERB
iajs-4047	381	12	algorithm	algorithm	NOUN
iajs-4047	381	13	on	on	ADP
iajs-4047	381	14	iris	iris	NOUN
iajs-4047	381	15	dataset	dataset	VERB
iajs-4047	381	16	.	.	PUNCT
iajs-4047	382	1	international	international	ADJ
iajs-4047	382	2	journal	journal	PROPN
iajs-4047	382	3	of	of	ADP
iajs-4047	382	4	engineering	engineering	PROPN
iajs-4047	382	5	&	&	CCONJ
iajs-4047	382	6	technology	technology	NOUN
iajs-4047	382	7	.	.	PUNCT
iajs-4047	383	1	2018;7(4):4766	2018;7(4):4766	X
iajs-4047	383	2	-	-	PUNCT
iajs-4047	383	3	8	8	NUM
iajs-4047	383	4	.	.	PUNCT
iajs-4047	384	1	https://doi.org/10.14419/ijet.v7i4.21472	https://doi.org/10.14419/ijet.v7i4.21472	NOUN
iajs-4047	384	2	31	31	NUM
iajs-4047	384	3	.	.	PUNCT
iajs-4047	385	1	seewald	seewald	PROPN
iajs-4047	385	2	ak	ak	PROPN
iajs-4047	385	3	.	.	PROPN
iajs-4047	385	4	digits	digits	PROPN
iajs-4047	385	5	-	-	PUNCT
iajs-4047	385	6	a	a	DET
iajs-4047	385	7	dataset	dataset	NOUN
iajs-4047	385	8	for	for	ADP
iajs-4047	385	9	handwritten	handwritten	ADJ
iajs-4047	385	10	digit	digit	NOUN
iajs-4047	385	11	recognition	recognition	NOUN
iajs-4047	385	12	.	.	PUNCT
iajs-4047	386	1	austrian	austrian	ADJ
iajs-4047	386	2	research	research	NOUN
iajs-4047	386	3	institut	institut	PROPN
iajs-4047	386	4	for	for	ADP
iajs-4047	386	5	artificial	artificial	ADJ
iajs-4047	386	6	intelligence	intelligence	NOUN
iajs-4047	386	7	technical	technical	ADJ
iajs-4047	386	8	report	report	PROPN
iajs-4047	386	9	,	,	PUNCT
iajs-4047	386	10	vienna	vienna	PROPN
iajs-4047	386	11	(	(	PUNCT
iajs-4047	386	12	austria	austria	PROPN
iajs-4047	386	13	)	)	PUNCT
iajs-4047	386	14	.	.	PUNCT
iajs-4047	387	1	2005;7	2005;7	NUM
iajs-4047	387	2	.	.	PUNCT
iajs-4047	388	1	32	32	NUM
iajs-4047	388	2	.	.	PUNCT
iajs-4047	389	1	spanhol	spanhol	PROPN
iajs-4047	389	2	fa	fa	PROPN
iajs-4047	389	3	,	,	PUNCT
iajs-4047	389	4	oliveira	oliveira	PROPN
iajs-4047	389	5	ls	ls	PROPN
iajs-4047	389	6	,	,	PUNCT
iajs-4047	389	7	petitjean	petitjean	ADJ
iajs-4047	389	8	c	c	NOUN
iajs-4047	389	9	,	,	PUNCT
iajs-4047	389	10	heutte	heutte	PROPN
iajs-4047	389	11	l.	l.	PROPN
iajs-4047	389	12	a	a	DET
iajs-4047	389	13	dataset	dataset	NOUN
iajs-4047	389	14	for	for	ADP
iajs-4047	389	15	breast	breast	NOUN
iajs-4047	389	16	cancer	cancer	NOUN
iajs-4047	389	17	histopathological	histopathological	ADJ
iajs-4047	389	18	image	image	NOUN
iajs-4047	389	19	classification	classification	NOUN
iajs-4047	389	20	.	.	PUNCT
iajs-4047	390	1	ieee	ieee	NOUN
iajs-4047	390	2	transactions	transaction	NOUN
iajs-4047	390	3	on	on	ADP
iajs-4047	390	4	biomedical	biomedical	ADJ
iajs-4047	390	5	engineering	engineering	NOUN
iajs-4047	390	6	.	.	PUNCT
iajs-4047	391	1	2015;63(7):1455	2015;63(7):1455	NUM
iajs-4047	391	2	-	-	SYM
iajs-4047	391	3	62	62	NUM
iajs-4047	391	4	.	.	PUNCT
iajs-4047	392	1	https://doi.org/10.1109/tbme.2015.2496264	https://doi.org/10.1109/tbme.2015.2496264	PROPN
iajs-4047	392	2	https://doi.org/10.1016/j.knosys.2020.105841	https://doi.org/10.1016/j.knosys.2020.105841	NOUN
iajs-4047	392	3	about	about	ADP
iajs-4047	392	4	:	:	PUNCT
iajs-4047	392	5	blank	blank	ADJ
iajs-4047	392	6	about	about	ADP
iajs-4047	392	7	:	:	PUNCT
iajs-4047	392	8	blank	blank	ADJ
iajs-4047	392	9	about	about	ADP
iajs-4047	392	10	:	:	PUNCT
iajs-4047	392	11	blank	blank	ADJ
iajs-4047	392	12	about	about	ADP
iajs-4047	392	13	:	:	PUNCT
iajs-4047	392	14	blank	blank	ADJ
iajs-4047	392	15	about	about	ADP
iajs-4047	392	16	:	:	PUNCT
iajs-4047	392	17	blank	blank	ADJ
iajs-4047	392	18	about	about	ADP
iajs-4047	392	19	:	:	PUNCT
iajs-4047	392	20	blank	blank	ADJ
iajs-4047	392	21	about	about	ADP
iajs-4047	392	22	:	:	PUNCT
iajs-4047	392	23	blank	blank	ADJ
iajs-4047	392	24	about	about	ADP
iajs-4047	392	25	:	:	PUNCT
iajs-4047	392	26	blank	blank	ADJ
iajs-4047	392	27	about	about	ADP
iajs-4047	392	28	:	:	PUNCT
iajs-4047	392	29	blank	blank	ADJ