id	sid	tid	token	lemma	pos
cana-2910	1	1	communications	communication	NOUN
cana-2910	1	2	on	on	ADP
cana-2910	1	3	applied	apply	VERB
cana-2910	1	4	nonlinear	nonlinear	ADJ
cana-2910	1	5	analysis	analysis	NOUN
cana-2910	1	6	issn	issn	NOUN
cana-2910	1	7	:	:	PUNCT
cana-2910	1	8	1074	1074	NUM
cana-2910	1	9	-	-	PUNCT
cana-2910	1	10	133x	133x	NUM
cana-2910	1	11	vol	vol	NOUN
cana-2910	1	12	32	32	NUM
cana-2910	1	13	no	no	NOUN
cana-2910	1	14	.	.	PUNCT
cana-2910	2	1	4s	4s	NUM
cana-2910	2	2	(	(	PUNCT
cana-2910	2	3	2025	2025	NUM
cana-2910	2	4	)	)	PUNCT
cana-2910	2	5	646	646	NUM
cana-2910	2	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	2	7	comparative	comparative	ADJ
cana-2910	2	8	analysis	analysis	NOUN
cana-2910	2	9	of	of	ADP
cana-2910	2	10	svm	svm	ADJ
cana-2910	2	11	variants	variant	NOUN
cana-2910	2	12	for	for	ADP
cana-2910	2	13	gst	gst	PROPN
cana-2910	2	14	fraud	fraud	NOUN
cana-2910	2	15	detection	detection	PROPN
cana-2910	2	16	vivek	vivek	PROPN
cana-2910	2	17	vyas1	vyas1	PROPN
cana-2910	2	18	,	,	PUNCT
cana-2910	2	19	himanshu	himanshu	PROPN
cana-2910	2	20	thakkar2	thakkar2	PROPN
cana-2910	2	21	,	,	PUNCT
cana-2910	2	22	siddharth	siddharth	PROPN
cana-2910	2	23	dabhade3	dabhade3	PROPN
cana-2910	2	24	,	,	PUNCT
cana-2910	2	25	ramdas	ramdas	PROPN
cana-2910	2	26	gore4	gore4	PROPN
cana-2910	2	27	,	,	PUNCT
cana-2910	2	28	hetal	hetal	ADJ
cana-2910	2	29	thaker5	thaker5	ADJ
cana-2910	2	30	1,2,3,4,5national	1,2,3,4,5national	NUM
cana-2910	2	31	forensic	forensic	ADJ
cana-2910	2	32	sciences	sciences	PROPN
cana-2910	2	33	university	university	PROPN
cana-2910	2	34	,	,	PUNCT
cana-2910	2	35	gandhinagar	gandhinagar	NOUN
cana-2910	2	36	,	,	PUNCT
cana-2910	2	37	gujarat	gujarat	PROPN
cana-2910	2	38	,	,	PUNCT
cana-2910	2	39	india	india	PROPN
cana-2910	2	40	article	article	NOUN
cana-2910	2	41	history	history	NOUN
cana-2910	2	42	:	:	PUNCT
cana-2910	2	43	received	receive	VERB
cana-2910	2	44	:	:	PUNCT
cana-2910	2	45	04	04	NUM
cana-2910	2	46	-	-	SYM
cana-2910	2	47	10	10	NUM
cana-2910	2	48	-	-	PUNCT
cana-2910	2	49	2024	2024	NUM
cana-2910	2	50	revised	revise	VERB
cana-2910	2	51	:	:	PUNCT
cana-2910	2	52	30	30	NUM
cana-2910	2	53	-	-	SYM
cana-2910	2	54	11	11	NUM
cana-2910	2	55	-	-	PUNCT
cana-2910	2	56	2024	2024	NUM
cana-2910	2	57	accepted	accept	VERB
cana-2910	2	58	:	:	PUNCT
cana-2910	2	59	09	09	NUM
cana-2910	2	60	-	-	SYM
cana-2910	2	61	12	12	NUM
cana-2910	2	62	-	-	PUNCT
cana-2910	2	63	2024	2024	NUM
cana-2910	2	64	abstract	abstract	NOUN
cana-2910	2	65	:	:	PUNCT
cana-2910	2	66	this	this	DET
cana-2910	2	67	study	study	NOUN
cana-2910	2	68	explores	explore	VERB
cana-2910	2	69	various	various	ADJ
cana-2910	2	70	support	support	NOUN
cana-2910	2	71	vector	vector	NOUN
cana-2910	2	72	machine	machine	NOUN
cana-2910	2	73	(	(	PUNCT
cana-2910	2	74	svm	svm	PROPN
cana-2910	2	75	)	)	PUNCT
cana-2910	2	76	variants	variant	NOUN
cana-2910	2	77	and	and	CCONJ
cana-2910	2	78	provides	provide	VERB
cana-2910	2	79	an	an	DET
cana-2910	2	80	analytical	analytical	ADJ
cana-2910	2	81	comparison	comparison	NOUN
cana-2910	2	82	to	to	PART
cana-2910	2	83	identify	identify	VERB
cana-2910	2	84	their	their	PRON
cana-2910	2	85	effectiveness	effectiveness	NOUN
cana-2910	2	86	in	in	ADP
cana-2910	2	87	detecting	detect	VERB
cana-2910	2	88	goods	good	NOUN
cana-2910	2	89	and	and	CCONJ
cana-2910	2	90	services	service	NOUN
cana-2910	2	91	tax	tax	NOUN
cana-2910	2	92	(	(	PUNCT
cana-2910	2	93	gst	gst	NOUN
cana-2910	2	94	)	)	PUNCT
cana-2910	2	95	fraud	fraud	NOUN
cana-2910	2	96	.	.	PUNCT
cana-2910	3	1	gst	gst	PROPN
cana-2910	3	2	fraud	fraud	NOUN
cana-2910	3	3	poses	pose	VERB
cana-2910	3	4	significant	significant	ADJ
cana-2910	3	5	challenges	challenge	NOUN
cana-2910	3	6	to	to	ADP
cana-2910	3	7	regulatory	regulatory	ADJ
cana-2910	3	8	authorities	authority	NOUN
cana-2910	3	9	and	and	CCONJ
cana-2910	3	10	businesses	business	NOUN
cana-2910	3	11	,	,	PUNCT
cana-2910	3	12	necessitating	necessitate	VERB
cana-2910	3	13	robust	robust	ADJ
cana-2910	3	14	detection	detection	NOUN
cana-2910	3	15	methods	method	NOUN
cana-2910	3	16	.	.	PUNCT
cana-2910	4	1	svm	svm	PROPN
cana-2910	4	2	,	,	PUNCT
cana-2910	4	3	a	a	DET
cana-2910	4	4	powerful	powerful	ADJ
cana-2910	4	5	machine	machine	NOUN
cana-2910	4	6	learning	learning	NOUN
cana-2910	4	7	algorithm	algorithm	NOUN
cana-2910	4	8	,	,	PUNCT
cana-2910	4	9	offers	offer	VERB
cana-2910	4	10	promise	promise	NOUN
cana-2910	4	11	in	in	ADP
cana-2910	4	12	this	this	DET
cana-2910	4	13	domain	domain	NOUN
cana-2910	4	14	due	due	ADP
cana-2910	4	15	to	to	ADP
cana-2910	4	16	its	its	PRON
cana-2910	4	17	ability	ability	NOUN
cana-2910	4	18	to	to	PART
cana-2910	4	19	handle	handle	VERB
cana-2910	4	20	complex	complex	ADJ
cana-2910	4	21	data	datum	NOUN
cana-2910	4	22	and	and	CCONJ
cana-2910	4	23	nonlinear	nonlinear	ADJ
cana-2910	4	24	relationships	relationship	NOUN
cana-2910	4	25	.	.	PUNCT
cana-2910	5	1	through	through	ADP
cana-2910	5	2	a	a	DET
cana-2910	5	3	comprehensive	comprehensive	ADJ
cana-2910	5	4	examination	examination	NOUN
cana-2910	5	5	of	of	ADP
cana-2910	5	6	svm	svm	ADJ
cana-2910	5	7	variants	variant	NOUN
cana-2910	5	8	,	,	PUNCT
cana-2910	5	9	including	include	VERB
cana-2910	5	10	linear	linear	PROPN
cana-2910	5	11	svm	svm	PROPN
cana-2910	5	12	,	,	PUNCT
cana-2910	5	13	polynomial	polynomial	ADJ
cana-2910	5	14	svm	svm	NOUN
cana-2910	5	15	,	,	PUNCT
cana-2910	5	16	and	and	CCONJ
cana-2910	5	17	radial	radial	ADJ
cana-2910	5	18	basis	basis	NOUN
cana-2910	5	19	function	function	NOUN
cana-2910	5	20	svm	svm	PROPN
cana-2910	5	21	,	,	PUNCT
cana-2910	5	22	this	this	DET
cana-2910	5	23	study	study	NOUN
cana-2910	5	24	assesses	assess	VERB
cana-2910	5	25	their	their	PRON
cana-2910	5	26	performance	performance	NOUN
cana-2910	5	27	in	in	ADP
cana-2910	5	28	gst	gst	PROPN
cana-2910	5	29	fraud	fraud	NOUN
cana-2910	5	30	detection	detection	NOUN
cana-2910	5	31	.	.	PUNCT
cana-2910	6	1	additionally	additionally	ADV
cana-2910	6	2	,	,	PUNCT
cana-2910	6	3	computational	computational	ADJ
cana-2910	6	4	efficiency	efficiency	NOUN
cana-2910	6	5	and	and	CCONJ
cana-2910	6	6	scalability	scalability	NOUN
cana-2910	6	7	are	be	AUX
cana-2910	6	8	investigated	investigate	VERB
cana-2910	6	9	to	to	PART
cana-2910	6	10	gauge	gauge	VERB
cana-2910	6	11	the	the	DET
cana-2910	6	12	practical	practical	ADJ
cana-2910	6	13	viability	viability	NOUN
cana-2910	6	14	of	of	ADP
cana-2910	6	15	each	each	DET
cana-2910	6	16	variant	variant	NOUN
cana-2910	6	17	.	.	PUNCT
cana-2910	7	1	the	the	DET
cana-2910	7	2	findings	finding	NOUN
cana-2910	7	3	contribute	contribute	VERB
cana-2910	7	4	to	to	ADP
cana-2910	7	5	advancing	advance	VERB
cana-2910	7	6	the	the	DET
cana-2910	7	7	understanding	understanding	NOUN
cana-2910	7	8	of	of	ADP
cana-2910	7	9	svm	svm	PROPN
cana-2910	7	10	's	's	PART
cana-2910	7	11	applicability	applicability	NOUN
cana-2910	7	12	in	in	ADP
cana-2910	7	13	fraud	fraud	NOUN
cana-2910	7	14	detection	detection	NOUN
cana-2910	7	15	contexts	context	NOUN
cana-2910	7	16	and	and	CCONJ
cana-2910	7	17	offer	offer	VERB
cana-2910	7	18	insights	insight	NOUN
cana-2910	7	19	into	into	ADP
cana-2910	7	20	selecting	select	VERB
cana-2910	7	21	the	the	DET
cana-2910	7	22	most	most	ADV
cana-2910	7	23	suitable	suitable	ADJ
cana-2910	7	24	variant	variant	NOUN
cana-2910	7	25	for	for	ADP
cana-2910	7	26	gst	gst	NOUN
cana-2910	7	27	fraud	fraud	NOUN
cana-2910	7	28	identification	identification	NOUN
cana-2910	7	29	.	.	PUNCT
cana-2910	8	1	ultimately	ultimately	ADV
cana-2910	8	2	,	,	PUNCT
cana-2910	8	3	this	this	DET
cana-2910	8	4	research	research	NOUN
cana-2910	8	5	aids	aid	VERB
cana-2910	8	6	stakeholders	stakeholder	NOUN
cana-2910	8	7	,	,	PUNCT
cana-2910	8	8	including	include	VERB
cana-2910	8	9	tax	tax	NOUN
cana-2910	8	10	authorities	authority	NOUN
cana-2910	8	11	and	and	CCONJ
cana-2910	8	12	businesses	business	NOUN
cana-2910	8	13	,	,	PUNCT
cana-2910	8	14	in	in	ADP
cana-2910	8	15	implementing	implement	VERB
cana-2910	8	16	effective	effective	ADJ
cana-2910	8	17	strategies	strategy	NOUN
cana-2910	8	18	to	to	PART
cana-2910	8	19	combat	combat	VERB
cana-2910	8	20	fraudulent	fraudulent	ADJ
cana-2910	8	21	activities	activity	NOUN
cana-2910	8	22	and	and	CCONJ
cana-2910	8	23	uphold	uphold	VERB
cana-2910	8	24	fiscal	fiscal	ADJ
cana-2910	8	25	integrity	integrity	NOUN
cana-2910	8	26	.	.	PUNCT
cana-2910	9	1	keywords	keyword	NOUN
cana-2910	9	2	:	:	PUNCT
cana-2910	9	3	support	support	VERB
cana-2910	9	4	vector	vector	NOUN
cana-2910	9	5	machines	machine	NOUN
cana-2910	9	6	(	(	PUNCT
cana-2910	9	7	svm	svm	PROPN
cana-2910	9	8	)	)	PUNCT
cana-2910	9	9	,	,	PUNCT
cana-2910	9	10	gst	gst	NOUN
cana-2910	9	11	fraud	fraud	NOUN
cana-2910	9	12	,	,	PUNCT
cana-2910	9	13	input	input	NOUN
cana-2910	9	14	tax	tax	NOUN
cana-2910	9	15	credit	credit	NOUN
cana-2910	9	16	.	.	PUNCT
cana-2910	10	1	gst	gst	PROPN
cana-2910	10	2	is	be	AUX
cana-2910	10	3	a	a	DET
cana-2910	10	4	comprehensive	comprehensive	ADJ
cana-2910	10	5	,	,	PUNCT
cana-2910	10	6	multistage	multistage	NOUN
cana-2910	10	7	,	,	PUNCT
cana-2910	10	8	destination	destination	NOUN
cana-2910	10	9	based	base	VERB
cana-2910	10	10	indirect	indirect	ADJ
cana-2910	10	11	tax	tax	NOUN
cana-2910	10	12	implemented	implement	VERB
cana-2910	10	13	in	in	ADP
cana-2910	10	14	india	india	PROPN
cana-2910	10	15	on	on	ADP
cana-2910	10	16	1st	1st	PROPN
cana-2910	10	17	july	july	PROPN
cana-2910	10	18	2017	2017	NUM
cana-2910	10	19	.	.	PUNCT
cana-2910	11	1	in	in	ADP
cana-2910	11	2	recent	recent	ADJ
cana-2910	11	3	years	year	NOUN
cana-2910	11	4	,	,	PUNCT
cana-2910	11	5	the	the	DET
cana-2910	11	6	application	application	NOUN
cana-2910	11	7	of	of	ADP
cana-2910	11	8	goods	good	NOUN
cana-2910	11	9	and	and	CCONJ
cana-2910	11	10	services	service	NOUN
cana-2910	11	11	tax	tax	NOUN
cana-2910	11	12	in	in	ADP
cana-2910	11	13	india	india	PROPN
cana-2910	11	14	has	have	AUX
cana-2910	11	15	brought	bring	VERB
cana-2910	11	16	about	about	ADP
cana-2910	11	17	significant	significant	ADJ
cana-2910	11	18	changes	change	NOUN
cana-2910	11	19	to	to	ADP
cana-2910	11	20	the	the	DET
cana-2910	11	21	country	country	NOUN
cana-2910	11	22	's	's	PART
cana-2910	11	23	tax	tax	NOUN
cana-2910	11	24	system	system	NOUN
cana-2910	11	25	.	.	PUNCT
cana-2910	12	1	goods	good	NOUN
cana-2910	12	2	and	and	CCONJ
cana-2910	12	3	services	service	NOUN
cana-2910	12	4	tax	tax	NOUN
cana-2910	12	5	is	be	AUX
cana-2910	12	6	an	an	DET
cana-2910	12	7	indirect	indirect	ADJ
cana-2910	12	8	tax	tax	NOUN
cana-2910	12	9	levied	levy	VERB
cana-2910	12	10	in	in	ADP
cana-2910	12	11	india	india	PROPN
cana-2910	12	12	since	since	SCONJ
cana-2910	12	13	july	july	PROPN
cana-2910	12	14	1	1	NUM
cana-2910	12	15	,	,	PUNCT
cana-2910	12	16	2017	2017	NUM
cana-2910	12	17	.	.	PUNCT
cana-2910	13	1	the	the	DET
cana-2910	13	2	implementation	implementation	NOUN
cana-2910	13	3	of	of	ADP
cana-2910	13	4	gst	gst	PROPN
cana-2910	13	5	has	have	AUX
cana-2910	13	6	been	be	AUX
cana-2910	13	7	hailed	hail	VERB
cana-2910	13	8	as	as	ADP
cana-2910	13	9	the	the	DET
cana-2910	13	10	biggest	big	ADJ
cana-2910	13	11	tax	tax	NOUN
cana-2910	13	12	reform	reform	NOUN
cana-2910	13	13	in	in	ADP
cana-2910	13	14	india	india	PROPN
cana-2910	13	15	since	since	SCONJ
cana-2910	13	16	1947	1947	NUM
cana-2910	13	17	.	.	PUNCT
cana-2910	14	1	with	with	ADP
cana-2910	14	2	the	the	DET
cana-2910	14	3	introduction	introduction	NOUN
cana-2910	14	4	of	of	ADP
cana-2910	14	5	gst	gst	NOUN
cana-2910	14	6	,	,	PUNCT
cana-2910	14	7	multiple	multiple	ADJ
cana-2910	14	8	indirect	indirect	ADJ
cana-2910	14	9	taxes	taxis	NOUN
cana-2910	14	10	have	have	AUX
cana-2910	14	11	been	be	AUX
cana-2910	14	12	replaced	replace	VERB
cana-2910	14	13	by	by	ADP
cana-2910	14	14	a	a	DET
cana-2910	14	15	single	single	ADJ
cana-2910	14	16	tax	tax	NOUN
cana-2910	14	17	structure	structure	NOUN
cana-2910	14	18	.	.	PUNCT
cana-2910	15	1	this	this	DET
cana-2910	15	2	tax	tax	NOUN
cana-2910	15	3	reform	reform	NOUN
cana-2910	15	4	has	have	AUX
cana-2910	15	5	not	not	PART
cana-2910	15	6	only	only	ADV
cana-2910	15	7	simplified	simplify	VERB
cana-2910	15	8	the	the	DET
cana-2910	15	9	taxation	taxation	NOUN
cana-2910	15	10	process	process	NOUN
cana-2910	15	11	but	but	CCONJ
cana-2910	15	12	also	also	ADV
cana-2910	15	13	aimed	aim	VERB
cana-2910	15	14	to	to	PART
cana-2910	15	15	eliminate	eliminate	VERB
cana-2910	15	16	complications	complication	NOUN
cana-2910	15	17	and	and	CCONJ
cana-2910	15	18	double	double	ADJ
cana-2910	15	19	taxation	taxation	NOUN
cana-2910	15	20	.	.	PUNCT
cana-2910	16	1	however	however	ADV
cana-2910	16	2	,	,	PUNCT
cana-2910	16	3	with	with	ADP
cana-2910	16	4	any	any	DET
cana-2910	16	5	major	major	ADJ
cana-2910	16	6	change	change	NOUN
cana-2910	16	7	comes	come	VERB
cana-2910	16	8	the	the	DET
cana-2910	16	9	potential	potential	NOUN
cana-2910	16	10	for	for	ADP
cana-2910	16	11	misuse	misuse	NOUN
cana-2910	16	12	and	and	CCONJ
cana-2910	16	13	fraud	fraud	NOUN
cana-2910	16	14	.	.	PUNCT
cana-2910	17	1	one	one	NUM
cana-2910	17	2	of	of	ADP
cana-2910	17	3	the	the	DET
cana-2910	17	4	challenges	challenge	NOUN
cana-2910	17	5	faced	face	VERB
cana-2910	17	6	by	by	ADP
cana-2910	17	7	the	the	DET
cana-2910	17	8	indian	indian	ADJ
cana-2910	17	9	government	government	NOUN
cana-2910	17	10	in	in	ADP
cana-2910	17	11	implementing	implement	VERB
cana-2910	17	12	gst	gst	NOUN
cana-2910	17	13	is	be	AUX
cana-2910	17	14	dealing	deal	VERB
cana-2910	17	15	with	with	ADP
cana-2910	17	16	fraudulent	fraudulent	ADJ
cana-2910	17	17	activities	activity	NOUN
cana-2910	17	18	.	.	PUNCT
cana-2910	18	1	after	after	ADP
cana-2910	18	2	implementation	implementation	NOUN
cana-2910	18	3	of	of	ADP
cana-2910	18	4	gst	gst	PROPN
cana-2910	18	5	the	the	DET
cana-2910	18	6	fraud	fraud	NOUN
cana-2910	18	7	in	in	ADP
cana-2910	18	8	gst	gst	PROPN
cana-2910	18	9	is	be	AUX
cana-2910	18	10	increasing	increase	VERB
cana-2910	18	11	rapidly	rapidly	ADV
cana-2910	18	12	.	.	PUNCT
cana-2910	19	1	as	as	ADP
cana-2910	19	2	per	per	ADP
cana-2910	19	3	answer	answer	NOUN
cana-2910	19	4	given	give	VERB
cana-2910	19	5	by	by	ADP
cana-2910	19	6	finance	finance	NOUN
cana-2910	19	7	minister	minister	NOUN
cana-2910	19	8	in	in	ADP
cana-2910	19	9	the	the	DET
cana-2910	19	10	lok	lok	PROPN
cana-2910	19	11	sabha	sabha	NOUN
cana-2910	19	12	,	,	PUNCT
cana-2910	19	13	from	from	ADP
cana-2910	19	14	july	july	PROPN
cana-2910	19	15	2017	2017	NUM
cana-2910	19	16	to	to	ADP
cana-2910	19	17	february	february	PROPN
cana-2910	19	18	2023	2023	NUM
cana-2910	19	19	there	there	PRON
cana-2910	19	20	was	be	VERB
cana-2910	19	21	close	close	ADJ
cana-2910	19	22	to	to	AUX
cana-2910	19	23	rs	rs	NOUN
cana-2910	19	24	.	.	PUNCT
cana-2910	20	1	3.08	3.08	NUM
cana-2910	20	2	lakh	lakh	NOUN
cana-2910	20	3	crore	crore	NUM
cana-2910	20	4	gst	gst	NOUN
cana-2910	20	5	evasion	evasion	NOUN
cana-2910	20	6	was	be	AUX
cana-2910	20	7	reported	report	VERB
cana-2910	20	8	,	,	PUNCT
cana-2910	20	9	and	and	CCONJ
cana-2910	20	10	1402	1402	NUM
cana-2910	20	11	offenders	offender	NOUN
cana-2910	20	12	were	be	AUX
cana-2910	20	13	detained	detain	VERB
cana-2910	20	14	,	,	PUNCT
cana-2910	20	15	1.03	1.03	NUM
cana-2910	20	16	lakh	lakh	NOUN
cana-2910	20	17	crore	crore	NOUN
cana-2910	20	18	was	be	AUX
cana-2910	20	19	recovered	recover	VERB
cana-2910	20	20	by	by	ADP
cana-2910	20	21	the	the	DET
cana-2910	20	22	gst	gst	PROPN
cana-2910	20	23	department	department	PROPN
cana-2910	20	24	.	.	PUNCT
cana-2910	21	1	goods	good	NOUN
cana-2910	21	2	and	and	CCONJ
cana-2910	21	3	services	service	NOUN
cana-2910	21	4	tax	tax	NOUN
cana-2910	21	5	is	be	AUX
cana-2910	21	6	a	a	DET
cana-2910	21	7	successful	successful	ADJ
cana-2910	21	8	method	method	NOUN
cana-2910	21	9	for	for	ADP
cana-2910	21	10	raising	raise	VERB
cana-2910	21	11	government	government	NOUN
cana-2910	21	12	revenue	revenue	NOUN
cana-2910	21	13	,	,	PUNCT
cana-2910	21	14	but	but	CCONJ
cana-2910	21	15	it	it	PRON
cana-2910	21	16	is	be	AUX
cana-2910	21	17	also	also	ADV
cana-2910	21	18	susceptive	susceptive	ADJ
cana-2910	21	19	to	to	PART
cana-2910	21	20	fraud	fraud	VERB
cana-2910	21	21	.	.	PUNCT
cana-2910	22	1	it	it	PRON
cana-2910	22	2	is	be	AUX
cana-2910	22	3	frequently	frequently	ADV
cana-2910	22	4	exploited	exploit	VERB
cana-2910	22	5	by	by	ADP
cana-2910	22	6	taxpayers	taxpayer	NOUN
cana-2910	22	7	depleting	deplete	VERB
cana-2910	22	8	the	the	DET
cana-2910	22	9	government	government	NOUN
cana-2910	22	10	tax	tax	NOUN
cana-2910	22	11	revenue	revenue	NOUN
cana-2910	22	12	.	.	PUNCT
cana-2910	23	1	the	the	DET
cana-2910	23	2	volume	volume	NOUN
cana-2910	23	3	of	of	ADP
cana-2910	23	4	gst	gst	PROPN
cana-2910	23	5	fraud	fraud	NOUN
cana-2910	23	6	is	be	AUX
cana-2910	23	7	increasing	increase	VERB
cana-2910	23	8	day	day	NOUN
cana-2910	23	9	by	by	ADP
cana-2910	23	10	day	day	NOUN
cana-2910	23	11	so	so	SCONJ
cana-2910	23	12	that	that	SCONJ
cana-2910	23	13	demand	demand	NOUN
cana-2910	23	14	for	for	ADP
cana-2910	23	15	forensic	forensic	ADJ
cana-2910	23	16	accountants	accountant	NOUN
cana-2910	23	17	is	be	AUX
cana-2910	23	18	increasing	increase	VERB
cana-2910	23	19	rapidly	rapidly	ADV
cana-2910	23	20	.	.	PUNCT
cana-2910	24	1	1	1	X
cana-2910	24	2	.	.	X
cana-2910	24	3	introduction	introduction	NOUN
cana-2910	24	4	vivek.vyas@nfsu.ac.in1	vivek.vyas@nfsu.ac.in1	NOUN
cana-2910	24	5	,	,	PUNCT
cana-2910	24	6	himanshu.thakkar@nfsu.ac.in2	himanshu.thakkar@nfsu.ac.in2	INTJ
cana-2910	24	7	,	,	PUNCT
cana-2910	24	8	siddharth.dabhade@nfsu.ac.in3	siddharth.dabhade@nfsu.ac.in3	NOUN
cana-2910	24	9	,	,	PUNCT
cana-2910	24	10	ramdas.gore@nfsu.ac.in4	ramdas.gore@nfsu.ac.in4	NOUN
cana-2910	24	11	,	,	PUNCT
cana-2910	24	12	hetal.thaker@nfsu.ac.in5	hetal.thaker@nfsu.ac.in5	NOUN
cana-2910	24	13	mailto:vivek.vyas@nfsu.ac.in	mailto:vivek.vyas@nfsu.ac.in	NOUN
cana-2910	24	14	mailto:himanshu.thakkar@nfsu.ac.in	mailto:himanshu.thakkar@nfsu.ac.in	NUM
cana-2910	24	15	mailto:siddharth.dabhade@nfsu.ac.in	mailto:siddharth.dabhade@nfsu.ac.in	PROPN
cana-2910	24	16	mailto:ramdas.gore@nfsu.ac.in	mailto:ramdas.gore@nfsu.ac.in	NUM
cana-2910	24	17	mailto:hetal.thaker@nfsu.ac.in	mailto:hetal.thaker@nfsu.ac.in	PROPN
cana-2910	24	18	mailto:hetal.thaker@nfsu.ac.in	mailto:hetal.thaker@nfsu.ac.in	PROPN
cana-2910	24	19	communications	communication	NOUN
cana-2910	24	20	on	on	ADP
cana-2910	24	21	applied	apply	VERB
cana-2910	24	22	nonlinear	nonlinear	ADJ
cana-2910	24	23	analysis	analysis	NOUN
cana-2910	24	24	issn	issn	NOUN
cana-2910	24	25	:	:	PUNCT
cana-2910	24	26	1074	1074	NUM
cana-2910	24	27	-	-	PUNCT
cana-2910	24	28	133x	133x	NUM
cana-2910	24	29	vol	vol	NOUN
cana-2910	24	30	32	32	NUM
cana-2910	24	31	no	no	NOUN
cana-2910	24	32	.	.	PUNCT
cana-2910	25	1	4s	4s	NUM
cana-2910	25	2	(	(	PUNCT
cana-2910	25	3	2025	2025	NUM
cana-2910	25	4	)	)	PUNCT
cana-2910	25	5	647	647	NUM
cana-2910	25	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	25	7	according	accord	VERB
cana-2910	25	8	to	to	ADP
cana-2910	25	9	gst	gst	NOUN
cana-2910	25	10	enforcement	enforcement	NOUN
cana-2910	25	11	probe	probe	NOUN
cana-2910	25	12	(	(	PUNCT
cana-2910	25	13	case	case	NOUN
cana-2910	25	14	under	under	ADP
cana-2910	25	15	investigation	investigation	NOUN
cana-2910	25	16	)	)	PUNCT
cana-2910	25	17	in	in	ADP
cana-2910	25	18	5000	5000	NUM
cana-2910	25	19	crore	crore	NOUN
cana-2910	25	20	gst	gst	NOUN
cana-2910	25	21	scam	scam	NOUN
cana-2910	25	22	in	in	ADP
cana-2910	25	23	bhavnagar	bhavnagar	PROPN
cana-2910	25	24	the	the	DET
cana-2910	25	25	fraudster	fraudster	NOUN
cana-2910	25	26	made	make	VERB
cana-2910	25	27	a	a	DET
cana-2910	25	28	gang	gang	NOUN
cana-2910	25	29	in	in	ADP
cana-2910	25	30	which	which	PRON
cana-2910	25	31	they	they	PRON
cana-2910	25	32	offered	offer	VERB
cana-2910	25	33	providing	provide	VERB
cana-2910	25	34	government	government	NOUN
cana-2910	25	35	support	support	NOUN
cana-2910	25	36	and	and	CCONJ
cana-2910	25	37	change	change	VERB
cana-2910	25	38	phone	phone	NOUN
cana-2910	25	39	number	number	NOUN
cana-2910	25	40	in	in	ADP
cana-2910	25	41	aadhaar	aadhaar	NOUN
cana-2910	25	42	card	card	NOUN
cana-2910	25	43	.	.	PUNCT
cana-2910	26	1	then	then	ADV
cana-2910	26	2	based	base	VERB
cana-2910	26	3	on	on	ADP
cana-2910	26	4	aadhaar	aadhaar	NOUN
cana-2910	26	5	card	card	NOUN
cana-2910	26	6	fraudster	fraudster	NOUN
cana-2910	26	7	used	use	VERB
cana-2910	26	8	to	to	PART
cana-2910	26	9	get	get	VERB
cana-2910	26	10	pan	pan	NOUN
cana-2910	26	11	numbers	number	NOUN
cana-2910	26	12	and	and	CCONJ
cana-2910	26	13	then	then	ADV
cana-2910	26	14	get	get	VERB
cana-2910	26	15	gst	gst	NOUN
cana-2910	26	16	registrations	registration	NOUN
cana-2910	26	17	for	for	ADP
cana-2910	26	18	the	the	DET
cana-2910	26	19	creation	creation	NOUN
cana-2910	26	20	of	of	ADP
cana-2910	26	21	shell	shell	ADJ
cana-2910	26	22	companies	company	NOUN
cana-2910	26	23	.	.	PUNCT
cana-2910	27	1	according	accord	VERB
cana-2910	27	2	to	to	ADP
cana-2910	27	3	special	special	ADJ
cana-2910	27	4	investigation	investigation	NOUN
cana-2910	27	5	team	team	NOUN
cana-2910	27	6	fraudster	fraudster	NOUN
cana-2910	27	7	have	have	AUX
cana-2910	27	8	created	create	VERB
cana-2910	27	9	approx	approx	PROPN
cana-2910	27	10	1500	1500	NUM
cana-2910	27	11	shell	shell	NOUN
cana-2910	27	12	companies	company	NOUN
cana-2910	27	13	,	,	PUNCT
cana-2910	27	14	transactions	transaction	NOUN
cana-2910	27	15	worth	worth	ADJ
cana-2910	27	16	rs	rs	NOUN
cana-2910	27	17	.	.	PROPN
cana-2910	27	18	40,000	40,000	NUM
cana-2910	27	19	crore	crore	NUM
cana-2910	27	20	.	.	PUNCT
cana-2910	28	1	it	it	PRON
cana-2910	28	2	is	be	AUX
cana-2910	28	3	the	the	DET
cana-2910	28	4	largest	large	ADJ
cana-2910	28	5	gst	gst	NOUN
cana-2910	28	6	fraud	fraud	NOUN
cana-2910	28	7	in	in	ADP
cana-2910	28	8	the	the	DET
cana-2910	28	9	history	history	NOUN
cana-2910	28	10	of	of	ADP
cana-2910	28	11	gujarat	gujarat	PROPN
cana-2910	28	12	.	.	PUNCT
cana-2910	29	1	gst	gst	PROPN
cana-2910	29	2	fraud	fraud	NOUN
cana-2910	29	3	is	be	AUX
cana-2910	29	4	serious	serious	ADJ
cana-2910	29	5	concern	concern	NOUN
cana-2910	29	6	and	and	CCONJ
cana-2910	29	7	it	it	PRON
cana-2910	29	8	undermine	undermine	VERB
cana-2910	29	9	the	the	DET
cana-2910	29	10	financial	financial	ADJ
cana-2910	29	11	stability	stability	NOUN
cana-2910	29	12	of	of	ADP
cana-2910	29	13	the	the	DET
cana-2910	29	14	nation	nation	NOUN
cana-2910	29	15	.	.	PUNCT
cana-2910	30	1	for	for	ADP
cana-2910	30	2	gst	gst	PROPN
cana-2910	30	3	fraud	fraud	NOUN
cana-2910	30	4	various	various	ADJ
cana-2910	30	5	modes	mode	NOUN
cana-2910	30	6	operandi	operandi	NOUN
cana-2910	30	7	has	have	AUX
cana-2910	30	8	been	be	AUX
cana-2910	30	9	observed	observe	VERB
cana-2910	30	10	in	in	ADP
cana-2910	30	11	the	the	DET
cana-2910	30	12	gst	gst	NOUN
cana-2910	30	13	fraud	fraud	NOUN
cana-2910	30	14	.	.	PUNCT
cana-2910	31	1	the	the	DET
cana-2910	31	2	objective	objective	NOUN
cana-2910	31	3	of	of	ADP
cana-2910	31	4	this	this	DET
cana-2910	31	5	paper	paper	NOUN
cana-2910	31	6	is	be	AUX
cana-2910	31	7	to	to	PART
cana-2910	31	8	explore	explore	VERB
cana-2910	31	9	the	the	DET
cana-2910	31	10	various	various	ADJ
cana-2910	31	11	types	type	NOUN
cana-2910	31	12	of	of	ADP
cana-2910	31	13	gst	gst	PROPN
cana-2910	31	14	fraud	fraud	PROPN
cana-2910	31	15	prevalent	prevalent	PROPN
cana-2910	31	16	in	in	ADP
cana-2910	31	17	india	india	PROPN
cana-2910	31	18	.	.	PUNCT
cana-2910	32	1	the	the	DET
cana-2910	32	2	crucial	crucial	ADJ
cana-2910	32	3	role	role	NOUN
cana-2910	32	4	of	of	ADP
cana-2910	32	5	forensic	forensic	ADJ
cana-2910	32	6	accountants	accountant	NOUN
cana-2910	32	7	in	in	ADP
cana-2910	32	8	detecting	detect	VERB
cana-2910	32	9	,	,	PUNCT
cana-2910	32	10	investigating	investigate	VERB
cana-2910	32	11	,	,	PUNCT
cana-2910	32	12	and	and	CCONJ
cana-2910	32	13	preventing	prevent	VERB
cana-2910	32	14	the	the	DET
cana-2910	32	15	gst	gst	NOUN
cana-2910	32	16	fraud	fraud	NOUN
cana-2910	32	17	in	in	ADP
cana-2910	32	18	india	india	PROPN
cana-2910	32	19	.	.	PUNCT
cana-2910	33	1	this	this	DET
cana-2910	33	2	paper	paper	NOUN
cana-2910	33	3	aims	aim	VERB
cana-2910	33	4	to	to	PART
cana-2910	33	5	contribute	contribute	VERB
cana-2910	33	6	towards	towards	ADP
cana-2910	33	7	discussing	discuss	VERB
cana-2910	33	8	comprehensive	comprehensive	ADJ
cana-2910	33	9	strategies	strategy	NOUN
cana-2910	33	10	to	to	PART
cana-2910	33	11	tackle	tackle	VERB
cana-2910	33	12	gst	gst	PROPN
cana-2910	33	13	fraud	fraud	NOUN
cana-2910	33	14	.	.	PUNCT
cana-2910	34	1	fig	fig	NOUN
cana-2910	34	2	.	.	PUNCT
cana-2910	35	1	1	1	X
cana-2910	35	2	.	.	X
cana-2910	35	3	tax	tax	NOUN
cana-2910	35	4	flow	flow	NOUN
cana-2910	35	5	diagram	diagram	NOUN
cana-2910	35	6	of	of	ADP
cana-2910	35	7	gst	gst	PROPN
cana-2910	35	8	this	this	DET
cana-2910	35	9	paper	paper	NOUN
cana-2910	35	10	introduces	introduce	VERB
cana-2910	35	11	various	various	ADJ
cana-2910	35	12	machine	machine	NOUN
cana-2910	35	13	learning	learning	NOUN
cana-2910	35	14	methods	method	NOUN
cana-2910	35	15	for	for	ADP
cana-2910	35	16	effectively	effectively	ADV
cana-2910	35	17	forecasting	forecast	VERB
cana-2910	35	18	gst	gst	PROPN
cana-2910	35	19	fraud	fraud	NOUN
cana-2910	35	20	,	,	PUNCT
cana-2910	35	21	including	include	VERB
cana-2910	35	22	svm	svm	ADJ
cana-2910	35	23	quadratic	quadratic	ADJ
cana-2910	35	24	,	,	PUNCT
cana-2910	35	25	svm	svm	ADJ
cana-2910	35	26	-	-	PUNCT
cana-2910	35	27	coarse	coarse	ADJ
cana-2910	35	28	gaussian	gaussian	NOUN
cana-2910	35	29	,	,	PUNCT
cana-2910	35	30	svm	svm	ADJ
cana-2910	35	31	-	-	ADJ
cana-2910	35	32	cubic	cubic	ADJ
cana-2910	35	33	,	,	PUNCT
cana-2910	35	34	svm	svm	ADJ
cana-2910	35	35	-	-	ADJ
cana-2910	35	36	fine	fine	ADJ
cana-2910	35	37	gaussian	gaussian	NOUN
cana-2910	35	38	,	,	PUNCT
cana-2910	35	39	svm	svm	ADJ
cana-2910	35	40	-	-	NOUN
cana-2910	35	41	linear	linear	ADJ
cana-2910	35	42	,	,	PUNCT
cana-2910	35	43	and	and	CCONJ
cana-2910	35	44	svm	svm	ADJ
cana-2910	35	45	-	-	PUNCT
cana-2910	35	46	medium	medium	ADJ
cana-2910	35	47	gaussian	gaussian	NOUN
cana-2910	35	48	.	.	PUNCT
cana-2910	36	1	consequently	consequently	ADV
cana-2910	36	2	,	,	PUNCT
cana-2910	36	3	this	this	DET
cana-2910	36	4	research	research	NOUN
cana-2910	36	5	aims	aim	VERB
cana-2910	36	6	to	to	PART
cana-2910	36	7	address	address	VERB
cana-2910	36	8	the	the	DET
cana-2910	36	9	question	question	NOUN
cana-2910	36	10	of	of	ADP
cana-2910	36	11	accurately	accurately	ADV
cana-2910	36	12	predicting	predict	VERB
cana-2910	36	13	gst	gst	NOUN
cana-2910	36	14	fraud	fraud	NOUN
cana-2910	36	15	by	by	ADP
cana-2910	36	16	utilizing	utilize	VERB
cana-2910	36	17	these	these	DET
cana-2910	36	18	models	model	NOUN
cana-2910	36	19	and	and	CCONJ
cana-2910	36	20	determining	determine	VERB
cana-2910	36	21	which	which	DET
cana-2910	36	22	one	one	PRON
cana-2910	36	23	performs	perform	VERB
cana-2910	36	24	better	well	ADV
cana-2910	36	25	.	.	PUNCT
cana-2910	37	1	furthermore	furthermore	ADV
cana-2910	37	2	,	,	PUNCT
cana-2910	37	3	these	these	DET
cana-2910	37	4	models	model	NOUN
cana-2910	37	5	will	will	AUX
cana-2910	37	6	serve	serve	VERB
cana-2910	37	7	as	as	ADP
cana-2910	37	8	initial	initial	ADJ
cana-2910	37	9	models	model	NOUN
cana-2910	37	10	for	for	ADP
cana-2910	37	11	predicting	predict	VERB
cana-2910	37	12	gst	gst	NOUN
cana-2910	37	13	fraud	fraud	NOUN
cana-2910	37	14	.	.	PUNCT
cana-2910	38	1	in	in	ADP
cana-2910	38	2	this	this	DET
cana-2910	38	3	paper	paper	NOUN
cana-2910	38	4	[	[	X
cana-2910	38	5	1	1	X
cana-2910	38	6	]	]	PUNCT
cana-2910	38	7	found	find	VERB
cana-2910	38	8	that	that	SCONJ
cana-2910	38	9	with	with	ADP
cana-2910	38	10	the	the	DET
cana-2910	38	11	help	help	NOUN
cana-2910	38	12	of	of	ADP
cana-2910	38	13	transaction	transaction	NOUN
cana-2910	38	14	level	level	NOUN
cana-2910	38	15	data	datum	NOUN
cana-2910	38	16	analysis	analysis	NOUN
cana-2910	38	17	800	800	NUM
cana-2910	38	18	ghost	ghost	NOUN
cana-2910	38	19	firms	firm	NOUN
cana-2910	38	20	has	have	AUX
cana-2910	38	21	been	be	AUX
cana-2910	38	22	identified	identify	VERB
cana-2910	38	23	by	by	ADP
cana-2910	38	24	the	the	DET
cana-2910	38	25	tax	tax	NOUN
cana-2910	38	26	authority	authority	NOUN
cana-2910	38	27	of	of	ADP
cana-2910	38	28	ecuador	ecuador	PROPN
cana-2910	38	29	.	.	PUNCT
cana-2910	39	1	these	these	DET
cana-2910	39	2	ghost	ghost	NOUN
cana-2910	39	3	firms	firm	NOUN
cana-2910	39	4	were	be	AUX
cana-2910	39	5	not	not	PART
cana-2910	39	6	only	only	ADV
cana-2910	39	7	involved	involve	VERB
cana-2910	39	8	in	in	ADP
cana-2910	39	9	evasion	evasion	NOUN
cana-2910	39	10	of	of	ADP
cana-2910	39	11	value	value	NOUN
cana-2910	39	12	added	add	VERB
cana-2910	39	13	tax	tax	NOUN
cana-2910	39	14	but	but	CCONJ
cana-2910	39	15	also	also	ADV
cana-2910	39	16	in	in	ADP
cana-2910	39	17	corporate	corporate	ADJ
cana-2910	39	18	income	income	NOUN
cana-2910	39	19	taxes	taxis	NOUN
cana-2910	39	20	.	.	PUNCT
cana-2910	40	1	author	author	NOUN
cana-2910	40	2	studied	study	VERB
cana-2910	40	3	[	[	PUNCT
cana-2910	40	4	2	2	X
cana-2910	40	5	]	]	PUNCT
cana-2910	40	6	some	some	DET
cana-2910	40	7	tax	tax	NOUN
cana-2910	40	8	evasion	evasion	NOUN
cana-2910	40	9	techniques	technique	NOUN
cana-2910	40	10	widespread	widespread	ADJ
cana-2910	40	11	in	in	ADP
cana-2910	40	12	goods	good	NOUN
cana-2910	40	13	and	and	CCONJ
cana-2910	40	14	services	service	NOUN
cana-2910	40	15	tax	tax	NOUN
cana-2910	40	16	in	in	ADP
cana-2910	40	17	telangana	telangana	PROPN
cana-2910	40	18	state	state	PROPN
cana-2910	40	19	.	.	PUNCT
cana-2910	41	1	various	various	ADJ
cana-2910	41	2	modus	modus	X
cana-2910	41	3	operandi	operandi	NOUN
cana-2910	41	4	of	of	ADP
cana-2910	41	5	gst	gst	PROPN
cana-2910	41	6	input	input	NOUN
cana-2910	41	7	tax	tax	NOUN
cana-2910	41	8	credit	credit	NOUN
cana-2910	41	9	evasion	evasion	NOUN
cana-2910	41	10	scam	scam	NOUN
cana-2910	41	11	has	have	AUX
cana-2910	41	12	been	be	AUX
cana-2910	41	13	identified	identify	VERB
cana-2910	41	14	with	with	ADP
cana-2910	41	15	the	the	DET
cana-2910	41	16	help	help	NOUN
cana-2910	41	17	of	of	ADP
cana-2910	41	18	sensitive	sensitive	ADJ
cana-2910	41	19	parameters	parameter	NOUN
cana-2910	41	20	.	.	PUNCT
cana-2910	42	1	it	it	PRON
cana-2910	42	2	is	be	AUX
cana-2910	42	3	observed	observe	VERB
cana-2910	42	4	that	that	SCONJ
cana-2910	42	5	shell	shell	ADJ
cana-2910	42	6	companies	company	NOUN
cana-2910	42	7	were	be	AUX
cana-2910	42	8	opened	open	VERB
cana-2910	42	9	in	in	ADP
cana-2910	42	10	different	different	ADJ
cana-2910	42	11	states	state	NOUN
cana-2910	42	12	.	.	PUNCT
cana-2910	43	1	for	for	ADP
cana-2910	43	2	tax	tax	NOUN
cana-2910	43	3	evasion	evasion	NOUN
cana-2910	43	4	fraudster	fraudster	NOUN
cana-2910	43	5	shows	show	NOUN
cana-2910	43	6	purchase	purchase	VERB
cana-2910	43	7	from	from	ADP
cana-2910	43	8	other	other	ADJ
cana-2910	43	9	state	state	NOUN
cana-2910	43	10	and	and	CCONJ
cana-2910	43	11	investigating	investigate	VERB
cana-2910	43	12	such	such	ADJ
cana-2910	43	13	malicious	malicious	ADJ
cana-2910	43	14	dealers	dealer	NOUN
cana-2910	43	15	is	be	AUX
cana-2910	43	16	difficult	difficult	ADJ
cana-2910	43	17	.	.	PUNCT
cana-2910	44	1	input	input	NOUN
cana-2910	44	2	tax	tax	NOUN
cana-2910	44	3	credit	credit	NOUN
cana-2910	44	4	has	have	AUX
cana-2910	44	5	been	be	AUX
cana-2910	44	6	availed	avail	VERB
cana-2910	44	7	with	with	ADP
cana-2910	44	8	the	the	DET
cana-2910	44	9	help	help	NOUN
cana-2910	44	10	of	of	ADP
cana-2910	44	11	fake	fake	ADJ
cana-2910	44	12	billing	billing	NOUN
cana-2910	44	13	.	.	PUNCT
cana-2910	45	1	tax	tax	NOUN
cana-2910	45	2	system	system	NOUN
cana-2910	45	3	should	should	AUX
cana-2910	45	4	be	be	AUX
cana-2910	45	5	simple	simple	ADJ
cana-2910	45	6	,	,	PUNCT
cana-2910	45	7	and	and	CCONJ
cana-2910	45	8	it	it	PRON
cana-2910	45	9	should	should	AUX
cana-2910	45	10	be	be	AUX
cana-2910	45	11	levied	levy	VERB
cana-2910	45	12	and	and	CCONJ
cana-2910	45	13	collect	collect	VERB
cana-2910	45	14	the	the	DET
cana-2910	45	15	tax	tax	NOUN
cana-2910	45	16	at	at	ADP
cana-2910	45	17	a	a	DET
cana-2910	45	18	single	single	ADJ
cana-2910	45	19	point	point	NOUN
cana-2910	45	20	based	base	VERB
cana-2910	45	21	on	on	ADP
cana-2910	45	22	algorithms	algorithm	NOUN
cana-2910	45	23	illegitimate	illegitimate	ADJ
cana-2910	45	24	transactions	transaction	NOUN
cana-2910	45	25	have	have	AUX
cana-2910	45	26	been	be	AUX
cana-2910	45	27	identified	identify	VERB
cana-2910	45	28	.	.	PUNCT
cana-2910	46	1	the	the	DET
cana-2910	46	2	result	result	NOUN
cana-2910	46	3	suggests	suggest	VERB
cana-2910	46	4	that	that	SCONJ
cana-2910	46	5	circular	circular	ADJ
cana-2910	46	6	trading	trading	NOUN
cana-2910	46	7	evasion	evasion	NOUN
cana-2910	46	8	technique	technique	NOUN
cana-2910	46	9	have	have	AUX
cana-2910	46	10	been	be	AUX
cana-2910	46	11	used	use	VERB
cana-2910	46	12	by	by	ADP
cana-2910	46	13	the	the	DET
cana-2910	46	14	perpetrators	perpetrator	NOUN
cana-2910	46	15	where	where	SCONJ
cana-2910	46	16	malicious	malicious	ADJ
cana-2910	46	17	dealers	dealer	NOUN
cana-2910	46	18	do	do	VERB
cana-2910	46	19	heavy	heavy	ADJ
cana-2910	46	20	fake	fake	ADJ
cana-2910	46	21	sales	sale	NOUN
cana-2910	46	22	and	and	CCONJ
cana-2910	46	23	purchase	purchase	NOUN
cana-2910	46	24	transactions	transaction	NOUN
cana-2910	46	25	among	among	ADP
cana-2910	46	26	themselves	themselves	PRON
cana-2910	46	27	only	only	ADV
cana-2910	46	28	that	that	PRON
cana-2910	46	29	go	go	VERB
cana-2910	46	30	around	around	ADV
cana-2910	46	31	in	in	ADP
cana-2910	46	32	a	a	DET
cana-2910	46	33	circular	circular	ADJ
cana-2910	46	34	manner	manner	NOUN
cana-2910	46	35	in	in	ADP
cana-2910	46	36	short	short	ADJ
cana-2910	46	37	period	period	NOUN
cana-2910	46	38	2	2	NUM
cana-2910	46	39	.	.	PUNCT
cana-2910	46	40	literature	literature	NOUN
cana-2910	46	41	review	review	NOUN
cana-2910	46	42	communications	communication	NOUN
cana-2910	46	43	on	on	ADP
cana-2910	46	44	applied	apply	VERB
cana-2910	46	45	nonlinear	nonlinear	ADJ
cana-2910	46	46	analysis	analysis	NOUN
cana-2910	46	47	issn	issn	NOUN
cana-2910	46	48	:	:	PUNCT
cana-2910	46	49	1074	1074	NUM
cana-2910	46	50	-	-	PUNCT
cana-2910	46	51	133x	133x	NUM
cana-2910	46	52	vol	vol	NOUN
cana-2910	46	53	32	32	NUM
cana-2910	46	54	no	no	NOUN
cana-2910	46	55	.	.	PUNCT
cana-2910	47	1	4s	4s	NUM
cana-2910	47	2	(	(	PUNCT
cana-2910	47	3	2025	2025	NUM
cana-2910	47	4	)	)	PUNCT
cana-2910	47	5	648	648	NUM
cana-2910	47	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	47	7	of	of	ADP
cana-2910	47	8	time	time	NOUN
cana-2910	47	9	.	.	PUNCT
cana-2910	48	1	it	it	PRON
cana-2910	48	2	generates	generate	VERB
cana-2910	48	3	vouchers	voucher	NOUN
cana-2910	48	4	and	and	CCONJ
cana-2910	48	5	avail	avail	VERB
cana-2910	48	6	fake	fake	ADJ
cana-2910	48	7	input	input	NOUN
cana-2910	48	8	tax	tax	NOUN
cana-2910	48	9	credit	credit	NOUN
cana-2910	48	10	without	without	ADP
cana-2910	48	11	any	any	DET
cana-2910	48	12	meaningful	meaningful	ADJ
cana-2910	48	13	value	value	NOUN
cana-2910	48	14	addition	addition	NOUN
cana-2910	48	15	[	[	X
cana-2910	48	16	3	3	NUM
cana-2910	48	17	]	]	PUNCT
cana-2910	48	18	.	.	PUNCT
cana-2910	49	1	it	it	PRON
cana-2910	49	2	provides	provide	VERB
cana-2910	49	3	a	a	DET
cana-2910	49	4	detailed	detailed	ADJ
cana-2910	49	5	exploration	exploration	NOUN
cana-2910	49	6	of	of	ADP
cana-2910	49	7	preventative	preventative	ADJ
cana-2910	49	8	strategies	strategy	NOUN
cana-2910	49	9	to	to	PART
cana-2910	49	10	minimize	minimize	VERB
cana-2910	49	11	goods	good	NOUN
cana-2910	49	12	and	and	CCONJ
cana-2910	49	13	services	service	NOUN
cana-2910	49	14	tax	tax	NOUN
cana-2910	49	15	(	(	PUNCT
cana-2910	49	16	gst	gst	NOUN
cana-2910	49	17	)	)	PUNCT
cana-2910	49	18	fraud	fraud	NOUN
cana-2910	49	19	,	,	PUNCT
cana-2910	49	20	which	which	PRON
cana-2910	49	21	is	be	AUX
cana-2910	49	22	essential	essential	ADJ
cana-2910	49	23	for	for	ADP
cana-2910	49	24	preserving	preserve	VERB
cana-2910	49	25	government	government	NOUN
cana-2910	49	26	revenue	revenue	NOUN
cana-2910	49	27	.	.	PUNCT
cana-2910	50	1	to	to	PART
cana-2910	50	2	prevent	prevent	VERB
cana-2910	50	3	gst	gst	PROPN
cana-2910	50	4	fraud	fraud	NOUN
cana-2910	50	5	researcher	researcher	PROPN
cana-2910	50	6	has	have	AUX
cana-2910	50	7	suggested	suggest	VERB
cana-2910	50	8	that	that	SCONJ
cana-2910	50	9	further	further	ADJ
cana-2910	50	10	research	research	NOUN
cana-2910	50	11	should	should	AUX
cana-2910	50	12	be	be	AUX
cana-2910	50	13	carried	carry	VERB
cana-2910	50	14	out	out	ADP
cana-2910	50	15	on	on	ADP
cana-2910	50	16	identification	identification	NOUN
cana-2910	50	17	of	of	ADP
cana-2910	50	18	the	the	DET
cana-2910	50	19	conduct	conduct	NOUN
cana-2910	50	20	and	and	CCONJ
cana-2910	50	21	profiling	profiling	NOUN
cana-2910	50	22	of	of	ADP
cana-2910	50	23	impostors	impostor	NOUN
cana-2910	50	24	so	so	SCONJ
cana-2910	50	25	that	that	SCONJ
cana-2910	50	26	such	such	ADJ
cana-2910	50	27	gst	gst	NOUN
cana-2910	50	28	fraud	fraud	NOUN
cana-2910	50	29	can	can	AUX
cana-2910	50	30	be	be	AUX
cana-2910	50	31	detect	detect	NOUN
cana-2910	50	32	at	at	ADP
cana-2910	50	33	the	the	DET
cana-2910	50	34	early	early	ADJ
cana-2910	50	35	stages	stage	NOUN
cana-2910	50	36	.	.	PUNCT
cana-2910	51	1	through	through	ADP
cana-2910	51	2	the	the	DET
cana-2910	51	3	use	use	NOUN
cana-2910	51	4	of	of	ADP
cana-2910	51	5	qualitative	qualitative	ADJ
cana-2910	51	6	research	research	NOUN
cana-2910	51	7	methods	method	NOUN
cana-2910	51	8	,	,	PUNCT
cana-2910	51	9	[	[	X
cana-2910	51	10	4	4	X
cana-2910	51	11	]	]	PUNCT
cana-2910	51	12	looked	look	VERB
cana-2910	51	13	at	at	ADP
cana-2910	51	14	cases	case	NOUN
cana-2910	51	15	of	of	ADP
cana-2910	51	16	gst	gst	NOUN
cana-2910	51	17	fraud	fraud	NOUN
cana-2910	51	18	that	that	PRON
cana-2910	51	19	occurred	occur	VERB
cana-2910	51	20	in	in	ADP
cana-2910	51	21	malaysia	malaysia	PROPN
cana-2910	51	22	.	.	PUNCT
cana-2910	52	1	their	their	PRON
cana-2910	52	2	research	research	NOUN
cana-2910	52	3	turned	turn	VERB
cana-2910	52	4	up	up	ADP
cana-2910	52	5	a	a	DET
cana-2910	52	6	number	number	NOUN
cana-2910	52	7	of	of	ADP
cana-2910	52	8	different	different	ADJ
cana-2910	52	9	types	type	NOUN
cana-2910	52	10	of	of	ADP
cana-2910	52	11	gst	gst	PROPN
cana-2910	52	12	fraud	fraud	NOUN
cana-2910	52	13	,	,	PUNCT
cana-2910	52	14	including	include	VERB
cana-2910	52	15	phony	phony	ADJ
cana-2910	52	16	claims	claim	NOUN
cana-2910	52	17	,	,	PUNCT
cana-2910	52	18	manipulated	manipulate	VERB
cana-2910	52	19	sales	sale	NOUN
cana-2910	52	20	data	datum	NOUN
cana-2910	52	21	,	,	PUNCT
cana-2910	52	22	neglected	neglect	VERB
cana-2910	52	23	registration	registration	NOUN
cana-2910	52	24	requirements	requirement	NOUN
cana-2910	52	25	,	,	PUNCT
cana-2910	52	26	filing	file	VERB
cana-2910	52	27	incomplete	incomplete	ADJ
cana-2910	52	28	gst	gst	NOUN
cana-2910	52	29	reports	report	NOUN
cana-2910	52	30	,	,	PUNCT
cana-2910	52	31	using	use	VERB
cana-2910	52	32	gst	gst	NOUN
cana-2910	52	33	avoidance	avoidance	NOUN
cana-2910	52	34	strategies	strategy	NOUN
cana-2910	52	35	,	,	PUNCT
cana-2910	52	36	and	and	CCONJ
cana-2910	52	37	taking	take	VERB
cana-2910	52	38	part	part	NOUN
cana-2910	52	39	in	in	ADP
cana-2910	52	40	carousel	carousel	NOUN
cana-2910	52	41	fraud	fraud	NOUN
cana-2910	52	42	schemes	scheme	NOUN
cana-2910	52	43	.	.	PUNCT
cana-2910	53	1	the	the	DET
cana-2910	53	2	researchers	researcher	NOUN
cana-2910	53	3	also	also	ADV
cana-2910	53	4	observed	observe	VERB
cana-2910	53	5	that	that	SCONJ
cana-2910	53	6	those	those	PRON
cana-2910	53	7	with	with	ADP
cana-2910	53	8	average	average	ADJ
cana-2910	53	9	educational	educational	ADJ
cana-2910	53	10	backgrounds	background	NOUN
cana-2910	53	11	and	and	CCONJ
cana-2910	53	12	medium	medium	ADJ
cana-2910	53	13	-	-	PUNCT
cana-2910	53	14	sized	sized	ADJ
cana-2910	53	15	firms	firm	NOUN
cana-2910	53	16	appear	appear	VERB
cana-2910	53	17	to	to	PART
cana-2910	53	18	be	be	AUX
cana-2910	53	19	more	more	ADV
cana-2910	53	20	likely	likely	ADJ
cana-2910	53	21	to	to	PART
cana-2910	53	22	commit	commit	VERB
cana-2910	53	23	gst	gst	PROPN
cana-2910	53	24	fraud	fraud	NOUN
cana-2910	53	25	.	.	PUNCT
cana-2910	54	1	[	[	X
cana-2910	54	2	5	5	NUM
cana-2910	54	3	]	]	PUNCT
cana-2910	54	4	;	;	PUNCT
cana-2910	54	5	these	these	DET
cana-2910	54	6	studies	study	NOUN
cana-2910	54	7	concluded	conclude	VERB
cana-2910	54	8	that	that	SCONJ
cana-2910	54	9	fraud	fraud	NOUN
cana-2910	54	10	could	could	AUX
cana-2910	54	11	potentially	potentially	ADV
cana-2910	54	12	be	be	AUX
cana-2910	54	13	curbed	curb	VERB
cana-2910	54	14	through	through	ADP
cana-2910	54	15	preventive	preventive	ADJ
cana-2910	54	16	measures	measure	NOUN
cana-2910	54	17	.	.	PUNCT
cana-2910	55	1	organizations	organization	NOUN
cana-2910	55	2	need	need	VERB
cana-2910	55	3	to	to	PART
cana-2910	55	4	implement	implement	VERB
cana-2910	55	5	strong	strong	ADJ
cana-2910	55	6	internal	internal	ADJ
cana-2910	55	7	controls	control	NOUN
cana-2910	55	8	and	and	CCONJ
cana-2910	55	9	systems	system	NOUN
cana-2910	55	10	,	,	PUNCT
cana-2910	55	11	as	as	ADV
cana-2910	55	12	well	well	ADV
cana-2910	55	13	as	as	ADP
cana-2910	55	14	educate	educate	VERB
cana-2910	55	15	their	their	PRON
cana-2910	55	16	employees	employee	NOUN
cana-2910	55	17	on	on	ADP
cana-2910	55	18	ethical	ethical	ADJ
cana-2910	55	19	practices	practice	NOUN
cana-2910	55	20	.	.	PUNCT
cana-2910	56	1	this	this	PRON
cana-2910	56	2	will	will	AUX
cana-2910	56	3	help	help	VERB
cana-2910	56	4	in	in	ADP
cana-2910	56	5	creating	create	VERB
cana-2910	56	6	a	a	DET
cana-2910	56	7	culture	culture	NOUN
cana-2910	56	8	of	of	ADP
cana-2910	56	9	integrity	integrity	NOUN
cana-2910	56	10	and	and	CCONJ
cana-2910	56	11	compliance	compliance	NOUN
cana-2910	56	12	,	,	PUNCT
cana-2910	56	13	making	make	VERB
cana-2910	56	14	it	it	PRON
cana-2910	56	15	less	less	ADV
cana-2910	56	16	likely	likely	ADJ
cana-2910	56	17	for	for	SCONJ
cana-2910	56	18	individuals	individual	NOUN
cana-2910	56	19	to	to	PART
cana-2910	56	20	engage	engage	VERB
cana-2910	56	21	in	in	ADP
cana-2910	56	22	gst	gst	NOUN
cana-2910	56	23	fraud	fraud	NOUN
cana-2910	56	24	.	.	PUNCT
cana-2910	57	1	in	in	ADP
cana-2910	57	2	this	this	DET
cana-2910	57	3	study	study	NOUN
cana-2910	57	4	,	,	PUNCT
cana-2910	57	5	various	various	ADJ
cana-2910	57	6	types	type	NOUN
cana-2910	57	7	of	of	ADP
cana-2910	57	8	support	support	NOUN
cana-2910	57	9	vector	vector	NOUN
cana-2910	57	10	machines	machine	NOUN
cana-2910	57	11	(	(	PUNCT
cana-2910	57	12	svm	svm	PROPN
cana-2910	57	13	)	)	PUNCT
cana-2910	57	14	are	be	AUX
cana-2910	57	15	utilized	utilize	VERB
cana-2910	57	16	,	,	PUNCT
cana-2910	57	17	employing	employ	VERB
cana-2910	57	18	a	a	DET
cana-2910	57	19	range	range	NOUN
cana-2910	57	20	of	of	ADP
cana-2910	57	21	kernel	kernel	NOUN
cana-2910	57	22	functions	function	NOUN
cana-2910	57	23	.	.	PUNCT
cana-2910	58	1	svm	svm	PROPN
cana-2910	58	2	serves	serve	VERB
cana-2910	58	3	as	as	ADP
cana-2910	58	4	a	a	DET
cana-2910	58	5	supervised	supervised	ADJ
cana-2910	58	6	machine	machine	NOUN
cana-2910	58	7	learning	learning	NOUN
cana-2910	58	8	technique	technique	NOUN
cana-2910	58	9	applied	apply	VERB
cana-2910	58	10	in	in	ADP
cana-2910	58	11	tasks	task	NOUN
cana-2910	58	12	involving	involve	VERB
cana-2910	58	13	classification	classification	NOUN
cana-2910	58	14	and	and	CCONJ
cana-2910	58	15	regression	regression	NOUN
cana-2910	58	16	[	[	X
cana-2910	58	17	6	6	NUM
cana-2910	58	18	]	]	PUNCT
cana-2910	58	19	.	.	PUNCT
cana-2910	59	1	the	the	DET
cana-2910	59	2	kernel	kernel	PROPN
cana-2910	59	3	function	function	NOUN
cana-2910	59	4	within	within	ADP
cana-2910	59	5	svm	svm	PROPN
cana-2910	59	6	plays	play	VERB
cana-2910	59	7	a	a	DET
cana-2910	59	8	crucial	crucial	ADJ
cana-2910	59	9	role	role	NOUN
cana-2910	59	10	in	in	ADP
cana-2910	59	11	defining	define	VERB
cana-2910	59	12	the	the	DET
cana-2910	59	13	decision	decision	NOUN
cana-2910	59	14	boundary	boundary	NOUN
cana-2910	59	15	that	that	PRON
cana-2910	59	16	segregates	segregate	VERB
cana-2910	59	17	distinct	distinct	ADJ
cana-2910	59	18	classes	class	NOUN
cana-2910	59	19	.	.	PUNCT
cana-2910	60	1	the	the	DET
cana-2910	60	2	support	support	NOUN
cana-2910	60	3	vector	vector	NOUN
cana-2910	60	4	machine	machine	NOUN
cana-2910	60	5	(	(	PUNCT
cana-2910	60	6	svm	svm	ADJ
cana-2910	60	7	)	)	PUNCT
cana-2910	60	8	algorithm	algorithm	NOUN
cana-2910	60	9	utilized	utilize	VERB
cana-2910	60	10	here	here	ADV
cana-2910	60	11	is	be	AUX
cana-2910	60	12	the	the	DET
cana-2910	60	13	standard	standard	ADJ
cana-2910	60	14	one	one	NUM
cana-2910	60	15	with	with	ADP
cana-2910	60	16	a	a	DET
cana-2910	60	17	quadratic	quadratic	ADJ
cana-2910	60	18	kernel	kernel	NOUN
cana-2910	60	19	function	function	NOUN
cana-2910	60	20	.	.	PUNCT
cana-2910	61	1	by	by	ADP
cana-2910	61	2	mapping	map	VERB
cana-2910	61	3	data	datum	NOUN
cana-2910	61	4	points	point	NOUN
cana-2910	61	5	to	to	ADP
cana-2910	61	6	a	a	DET
cana-2910	61	7	higher	high	ADJ
cana-2910	61	8	dimensional	dimensional	ADJ
cana-2910	61	9	space	space	NOUN
cana-2910	61	10	,	,	PUNCT
cana-2910	61	11	it	it	PRON
cana-2910	61	12	becomes	become	VERB
cana-2910	61	13	capable	capable	ADJ
cana-2910	61	14	of	of	ADP
cana-2910	61	15	handling	handle	VERB
cana-2910	61	16	non	non	ADJ
cana-2910	61	17	-	-	ADJ
cana-2910	61	18	linearly	linearly	ADV
cana-2910	61	19	separable	separable	ADJ
cana-2910	61	20	data	datum	NOUN
cana-2910	61	21	[	[	X
cana-2910	61	22	7	7	NUM
cana-2910	61	23	]	]	PUNCT
cana-2910	61	24	.	.	PUNCT
cana-2910	62	1	although	although	SCONJ
cana-2910	62	2	training	train	VERB
cana-2910	62	3	the	the	DET
cana-2910	62	4	quadratic	quadratic	ADJ
cana-2910	62	5	kernel	kernel	NOUN
cana-2910	62	6	can	can	AUX
cana-2910	62	7	be	be	AUX
cana-2910	62	8	computationally	computationally	ADV
cana-2910	62	9	expensive	expensive	ADJ
cana-2910	62	10	,	,	PUNCT
cana-2910	62	11	it	it	PRON
cana-2910	62	12	proves	prove	VERB
cana-2910	62	13	to	to	PART
cana-2910	62	14	be	be	AUX
cana-2910	62	15	effective	effective	ADJ
cana-2910	62	16	for	for	ADP
cana-2910	62	17	intricate	intricate	ADJ
cana-2910	62	18	datasets	dataset	NOUN
cana-2910	62	19	.	.	PUNCT
cana-2910	63	1	in	in	ADP
cana-2910	63	2	this	this	DET
cana-2910	63	3	case	case	NOUN
cana-2910	63	4	,	,	PUNCT
cana-2910	63	5	the	the	DET
cana-2910	63	6	svm	svm	NOUN
cana-2910	63	7	with	with	ADP
cana-2910	63	8	a	a	DET
cana-2910	63	9	quadratic	quadratic	ADJ
cana-2910	63	10	kernel	kernel	NOUN
cana-2910	63	11	employs	employ	VERB
cana-2910	63	12	a	a	DET
cana-2910	63	13	quadratic	quadratic	ADJ
cana-2910	63	14	polynomial	polynomial	NOUN
cana-2910	63	15	as	as	ADP
cana-2910	63	16	the	the	DET
cana-2910	63	17	kernel	kernel	PROPN
cana-2910	63	18	function	function	PROPN
cana-2910	63	19	,	,	PUNCT
cana-2910	63	20	resulting	result	VERB
cana-2910	63	21	in	in	ADP
cana-2910	63	22	a	a	DET
cana-2910	63	23	decision	decision	NOUN
cana-2910	63	24	boundary	boundary	NOUN
cana-2910	63	25	that	that	PRON
cana-2910	63	26	takes	take	VERB
cana-2910	63	27	the	the	DET
cana-2910	63	28	form	form	NOUN
cana-2910	63	29	of	of	ADP
cana-2910	63	30	a	a	DET
cana-2910	63	31	quadratic	quadratic	ADJ
cana-2910	63	32	curve	curve	NOUN
cana-2910	63	33	in	in	ADP
cana-2910	63	34	the	the	DET
cana-2910	63	35	input	input	NOUN
cana-2910	63	36	space	space	NOUN
cana-2910	63	37	.	.	PUNCT
cana-2910	64	1	this	this	DET
cana-2910	64	2	particular	particular	ADJ
cana-2910	64	3	type	type	NOUN
cana-2910	64	4	of	of	ADP
cana-2910	64	5	svm	svm	PROPN
cana-2910	64	6	is	be	AUX
cana-2910	64	7	well	well	ADV
cana-2910	64	8	-	-	PUNCT
cana-2910	64	9	suited	suited	ADJ
cana-2910	64	10	for	for	ADP
cana-2910	64	11	capturing	capture	VERB
cana-2910	64	12	more	more	ADJ
cana-2910	64	13	intricate	intricate	ADJ
cana-2910	64	14	relationships	relationship	NOUN
cana-2910	64	15	between	between	ADP
cana-2910	64	16	features	feature	NOUN
cana-2910	64	17	.	.	PUNCT
cana-2910	65	1	this	this	DET
cana-2910	65	2	version	version	NOUN
cana-2910	65	3	employs	employ	VERB
cana-2910	65	4	a	a	DET
cana-2910	65	5	gaussian	gaussian	ADJ
cana-2910	65	6	kernel	kernel	NOUN
cana-2910	65	7	function	function	VERB
cana-2910	65	8	with	with	ADP
cana-2910	65	9	a	a	DET
cana-2910	65	10	wide	wide	ADJ
cana-2910	65	11	width	width	NOUN
cana-2910	65	12	.	.	PUNCT
cana-2910	66	1	the	the	DET
cana-2910	66	2	kernel	kernel	PROPN
cana-2910	66	3	exhibits	exhibit	VERB
cana-2910	66	4	a	a	DET
cana-2910	66	5	smooth	smooth	ADJ
cana-2910	66	6	decision	decision	NOUN
cana-2910	66	7	boundary	boundary	NOUN
cana-2910	66	8	and	and	CCONJ
cana-2910	66	9	is	be	AUX
cana-2910	66	10	effective	effective	ADJ
cana-2910	66	11	for	for	ADP
cana-2910	66	12	data	datum	NOUN
cana-2910	66	13	with	with	ADP
cana-2910	66	14	smooth	smooth	ADJ
cana-2910	66	15	,	,	PUNCT
cana-2910	66	16	continuous	continuous	ADJ
cana-2910	66	17	relationships	relationship	NOUN
cana-2910	66	18	between	between	ADP
cana-2910	66	19	features	feature	NOUN
cana-2910	66	20	[	[	X
cana-2910	66	21	8	8	NUM
cana-2910	66	22	]	]	PUNCT
cana-2910	66	23	.	.	PUNCT
cana-2910	67	1	nevertheless	nevertheless	ADV
cana-2910	67	2	,	,	PUNCT
cana-2910	67	3	it	it	PRON
cana-2910	67	4	may	may	AUX
cana-2910	67	5	not	not	PART
cana-2910	67	6	be	be	AUX
cana-2910	67	7	appropriate	appropriate	ADJ
cana-2910	67	8	for	for	ADP
cana-2910	67	9	capturing	capture	VERB
cana-2910	67	10	intricate	intricate	ADJ
cana-2910	67	11	,	,	PUNCT
cana-2910	67	12	localized	localized	ADJ
cana-2910	67	13	patterns	pattern	NOUN
cana-2910	67	14	.	.	PUNCT
cana-2910	68	1	in	in	ADP
cana-2910	68	2	the	the	DET
cana-2910	68	3	context	context	NOUN
cana-2910	68	4	of	of	ADP
cana-2910	68	5	svm	svm	PROPN
cana-2910	68	6	,	,	PUNCT
cana-2910	68	7	the	the	DET
cana-2910	68	8	gaussian	gaussian	ADJ
cana-2910	68	9	kernel	kernel	NOUN
cana-2910	68	10	(	(	PUNCT
cana-2910	68	11	also	also	ADV
cana-2910	68	12	referred	refer	VERB
cana-2910	68	13	to	to	ADP
cana-2910	68	14	as	as	ADP
cana-2910	68	15	radial	radial	ADJ
cana-2910	68	16	basis	basis	NOUN
cana-2910	68	17	function	function	NOUN
cana-2910	68	18	or	or	CCONJ
cana-2910	68	19	rbf	rbf	PROPN
cana-2910	68	20	)	)	PUNCT
cana-2910	68	21	is	be	AUX
cana-2910	68	22	a	a	DET
cana-2910	68	23	commonly	commonly	ADV
cana-2910	68	24	favored	favor	VERB
cana-2910	68	25	option	option	NOUN
cana-2910	68	26	.	.	PUNCT
cana-2910	69	1	the	the	DET
cana-2910	69	2	term	term	NOUN
cana-2910	69	3	"	"	PUNCT
cana-2910	69	4	coarse	coarse	NOUN
cana-2910	69	5	"	"	PUNCT
cana-2910	69	6	typically	typically	ADV
cana-2910	69	7	denotes	denote	VERB
cana-2910	69	8	a	a	DET
cana-2910	69	9	larger	large	ADJ
cana-2910	69	10	bandwidth	bandwidth	NOUN
cana-2910	69	11	or	or	CCONJ
cana-2910	69	12	spread	spread	VERB
cana-2910	69	13	parameter	parameter	NOUN
cana-2910	69	14	in	in	ADP
cana-2910	69	15	the	the	DET
cana-2910	69	16	gaussian	gaussian	ADJ
cana-2910	69	17	kernel	kernel	NOUN
cana-2910	69	18	.	.	PUNCT
cana-2910	70	1	a	a	DET
cana-2910	70	2	wider	wide	ADJ
cana-2910	70	3	bandwidth	bandwidth	ADJ
cana-2910	70	4	results	result	NOUN
cana-2910	70	5	in	in	ADP
cana-2910	70	6	a	a	DET
cana-2910	70	7	smoother	smooth	ADJ
cana-2910	70	8	decision	decision	NOUN
cana-2910	70	9	boundary	boundary	ADV
cana-2910	70	10	and	and	CCONJ
cana-2910	70	11	encompasses	encompass	VERB
cana-2910	70	12	broader	broad	ADJ
cana-2910	70	13	patterns	pattern	NOUN
cana-2910	70	14	in	in	ADP
cana-2910	70	15	the	the	DET
cana-2910	70	16	data	datum	NOUN
cana-2910	70	17	.	.	PUNCT
cana-2910	71	1	this	this	DET
cana-2910	71	2	version	version	NOUN
cana-2910	71	3	utilizes	utilize	VERB
cana-2910	71	4	a	a	DET
cana-2910	71	5	cubic	cubic	ADJ
cana-2910	71	6	kernel	kernel	NOUN
cana-2910	71	7	function	function	NOUN
cana-2910	71	8	,	,	PUNCT
cana-2910	71	9	which	which	PRON
cana-2910	71	10	exhibits	exhibit	VERB
cana-2910	71	11	a	a	DET
cana-2910	71	12	more	more	ADV
cana-2910	71	13	distinct	distinct	ADJ
cana-2910	71	14	decision	decision	NOUN
cana-2910	71	15	boundary	boundary	ADJ
cana-2910	71	16	in	in	ADP
cana-2910	71	17	contrast	contrast	NOUN
cana-2910	71	18	to	to	ADP
cana-2910	71	19	the	the	DET
cana-2910	71	20	gaussian	gaussian	ADJ
cana-2910	71	21	kernel	kernel	NOUN
cana-2910	72	1	[	[	X
cana-2910	72	2	9	9	NUM
cana-2910	72	3	]	]	PUNCT
cana-2910	72	4	.	.	PUNCT
cana-2910	73	1	it	it	PRON
cana-2910	73	2	proves	prove	VERB
cana-2910	73	3	to	to	PART
cana-2910	73	4	be	be	AUX
cana-2910	73	5	advantageous	advantageous	ADJ
cana-2910	73	6	for	for	ADP
cana-2910	73	7	datasets	dataset	NOUN
cana-2910	73	8	with	with	ADP
cana-2910	73	9	well	well	ADV
cana-2910	73	10	-	-	PUNCT
cana-2910	73	11	defined	define	VERB
cana-2910	73	12	class	class	NOUN
cana-2910	73	13	boundaries	boundary	NOUN
cana-2910	73	14	,	,	PUNCT
cana-2910	73	15	but	but	CCONJ
cana-2910	73	16	it	it	PRON
cana-2910	73	17	may	may	AUX
cana-2910	73	18	not	not	PART
cana-2910	73	19	yield	yield	VERB
cana-2910	73	20	satisfactory	satisfactory	ADJ
cana-2910	73	21	results	result	NOUN
cana-2910	73	22	for	for	ADP
cana-2910	73	23	datasets	dataset	NOUN
cana-2910	73	24	with	with	ADP
cana-2910	73	25	overlapping	overlap	VERB
cana-2910	73	26	classes	class	NOUN
cana-2910	73	27	or	or	CCONJ
cana-2910	73	28	noise	noise	NOUN
cana-2910	73	29	.	.	PUNCT
cana-2910	74	1	similar	similar	ADJ
cana-2910	74	2	to	to	ADP
cana-2910	74	3	the	the	DET
cana-2910	74	4	svm	svm	ADJ
cana-2910	74	5	-	-	ADJ
cana-2910	74	6	quadratic	quadratic	ADJ
cana-2910	74	7	,	,	PUNCT
cana-2910	74	8	the	the	DET
cana-2910	74	9	svm	svm	ADJ
cana-2910	74	10	-	-	ADJ
cana-2910	74	11	cubic	cubic	ADJ
cana-2910	74	12	employs	employ	VERB
cana-2910	74	13	a	a	DET
cana-2910	74	14	cubic	cubic	ADJ
cana-2910	74	15	polynomial	polynomial	NOUN
cana-2910	74	16	as	as	ADP
cana-2910	74	17	its	its	PRON
cana-2910	74	18	kernel	kernel	NOUN
cana-2910	74	19	function	function	NOUN
cana-2910	74	20	.	.	PUNCT
cana-2910	75	1	2.1	2.1	NUM
cana-2910	75	2	.	.	PUNCT
cana-2910	76	1	svm	svm	VERB
cana-2910	76	2	quadratic	quadratic	ADJ
cana-2910	76	3	2.2	2.2	NUM
cana-2910	76	4	.	.	PUNCT
cana-2910	77	1	svm	svm	ADJ
cana-2910	77	2	-	-	PUNCT
cana-2910	77	3	coarse	coarse	ADJ
cana-2910	77	4	gaussian	gaussian	NOUN
cana-2910	77	5	2.3	2.3	NUM
cana-2910	77	6	.	.	PUNCT
cana-2910	78	1	svm	svm	ADJ
cana-2910	78	2	-	-	ADJ
cana-2910	78	3	cubic	cubic	ADJ
cana-2910	78	4	communications	communication	NOUN
cana-2910	78	5	on	on	ADP
cana-2910	78	6	applied	apply	VERB
cana-2910	78	7	nonlinear	nonlinear	ADJ
cana-2910	78	8	analysis	analysis	NOUN
cana-2910	78	9	issn	issn	NOUN
cana-2910	78	10	:	:	PUNCT
cana-2910	78	11	1074	1074	NUM
cana-2910	78	12	-	-	PUNCT
cana-2910	78	13	133x	133x	NUM
cana-2910	78	14	vol	vol	NOUN
cana-2910	78	15	32	32	NUM
cana-2910	78	16	no	no	NOUN
cana-2910	78	17	.	.	PUNCT
cana-2910	79	1	4s	4s	NUM
cana-2910	79	2	(	(	PUNCT
cana-2910	79	3	2025	2025	NUM
cana-2910	79	4	)	)	PUNCT
cana-2910	79	5	649	649	NUM
cana-2910	79	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	79	7	consequently	consequently	ADV
cana-2910	79	8	,	,	PUNCT
cana-2910	79	9	the	the	DET
cana-2910	79	10	decision	decision	NOUN
cana-2910	79	11	boundary	boundary	NOUN
cana-2910	79	12	takes	take	VERB
cana-2910	79	13	the	the	DET
cana-2910	79	14	form	form	NOUN
cana-2910	79	15	of	of	ADP
cana-2910	79	16	a	a	DET
cana-2910	79	17	cubic	cubic	ADJ
cana-2910	79	18	surface	surface	NOUN
cana-2910	79	19	within	within	ADP
cana-2910	79	20	the	the	DET
cana-2910	79	21	input	input	NOUN
cana-2910	79	22	space	space	NOUN
cana-2910	79	23	.	.	PUNCT
cana-2910	80	1	this	this	PRON
cana-2910	80	2	enables	enable	VERB
cana-2910	80	3	the	the	DET
cana-2910	80	4	algorithm	algorithm	NOUN
cana-2910	80	5	to	to	PART
cana-2910	80	6	capture	capture	VERB
cana-2910	80	7	even	even	ADV
cana-2910	80	8	more	more	ADV
cana-2910	80	9	intricate	intricate	ADJ
cana-2910	80	10	relationships	relationship	NOUN
cana-2910	80	11	between	between	ADP
cana-2910	80	12	features	feature	NOUN
cana-2910	80	13	when	when	SCONJ
cana-2910	80	14	compared	compare	VERB
cana-2910	80	15	to	to	ADP
cana-2910	80	16	linear	linear	ADJ
cana-2910	80	17	or	or	CCONJ
cana-2910	80	18	quadratic	quadratic	ADJ
cana-2910	80	19	kernels	kernel	NOUN
cana-2910	80	20	.	.	PUNCT
cana-2910	81	1	this	this	DET
cana-2910	81	2	version	version	NOUN
cana-2910	81	3	utilizes	utilize	VERB
cana-2910	81	4	a	a	DET
cana-2910	81	5	gaussian	gaussian	ADJ
cana-2910	81	6	kernel	kernel	NOUN
cana-2910	81	7	function	function	VERB
cana-2910	81	8	with	with	ADP
cana-2910	81	9	a	a	DET
cana-2910	81	10	narrow	narrow	ADJ
cana-2910	81	11	width	width	NOUN
cana-2910	81	12	.	.	PUNCT
cana-2910	82	1	this	this	DET
cana-2910	82	2	kernel	kernel	NOUN
cana-2910	82	3	is	be	AUX
cana-2910	82	4	highly	highly	ADV
cana-2910	82	5	responsive	responsive	ADJ
cana-2910	82	6	to	to	ADP
cana-2910	82	7	small	small	ADJ
cana-2910	82	8	-	-	PUNCT
cana-2910	82	9	scale	scale	NOUN
cana-2910	82	10	fluctuations	fluctuation	NOUN
cana-2910	82	11	in	in	ADP
cana-2910	82	12	the	the	DET
cana-2910	82	13	data	datum	NOUN
cana-2910	82	14	and	and	CCONJ
cana-2910	82	15	can	can	AUX
cana-2910	82	16	effectively	effectively	ADV
cana-2910	82	17	detect	detect	VERB
cana-2910	82	18	intricate	intricate	ADJ
cana-2910	82	19	patterns	pattern	NOUN
cana-2910	82	20	[	[	X
cana-2910	82	21	10	10	NUM
cana-2910	82	22	]	]	PUNCT
cana-2910	82	23	.	.	PUNCT
cana-2910	83	1	nevertheless	nevertheless	ADV
cana-2910	83	2	,	,	PUNCT
cana-2910	83	3	it	it	PRON
cana-2910	83	4	is	be	AUX
cana-2910	83	5	prone	prone	ADJ
cana-2910	83	6	to	to	ADP
cana-2910	83	7	overfitting	overfitte	VERB
cana-2910	83	8	and	and	CCONJ
cana-2910	83	9	noise	noise	NOUN
cana-2910	83	10	sensitivity	sensitivity	NOUN
cana-2910	83	11	.	.	PUNCT
cana-2910	84	1	in	in	ADP
cana-2910	84	2	contrast	contrast	NOUN
cana-2910	84	3	to	to	ADP
cana-2910	84	4	the	the	DET
cana-2910	84	5	"	"	PUNCT
cana-2910	84	6	coarse	coarse	ADJ
cana-2910	84	7	gaussian	gaussian	NOUN
cana-2910	84	8	,	,	PUNCT
cana-2910	84	9	"	"	PUNCT
cana-2910	84	10	the	the	DET
cana-2910	84	11	term	term	NOUN
cana-2910	84	12	"	"	PUNCT
cana-2910	84	13	fine	fine	ADJ
cana-2910	84	14	gaussian	gaussian	NOUN
cana-2910	84	15	"	"	PUNCT
cana-2910	84	16	probably	probably	ADV
cana-2910	84	17	denotes	denote	VERB
cana-2910	84	18	a	a	DET
cana-2910	84	19	reduced	reduced	ADJ
cana-2910	84	20	bandwidth	bandwidth	NOUN
cana-2910	84	21	or	or	CCONJ
cana-2910	84	22	spread	spread	VERB
cana-2910	84	23	parameter	parameter	NOUN
cana-2910	84	24	in	in	ADP
cana-2910	84	25	the	the	DET
cana-2910	84	26	gaussian	gaussian	ADJ
cana-2910	84	27	kernel	kernel	NOUN
cana-2910	84	28	.	.	PUNCT
cana-2910	85	1	a	a	DET
cana-2910	85	2	smaller	small	ADJ
cana-2910	85	3	bandwidth	bandwidth	NOUN
cana-2910	85	4	leads	lead	VERB
cana-2910	85	5	to	to	ADP
cana-2910	85	6	a	a	DET
cana-2910	85	7	more	more	ADV
cana-2910	85	8	intricate	intricate	ADJ
cana-2910	85	9	decision	decision	NOUN
cana-2910	85	10	boundary	boundary	NOUN
cana-2910	85	11	,	,	PUNCT
cana-2910	85	12	thereby	thereby	ADV
cana-2910	85	13	increasing	increase	VERB
cana-2910	85	14	the	the	DET
cana-2910	85	15	svm	svm	PROPN
cana-2910	85	16	's	's	PART
cana-2910	85	17	sensitivity	sensitivity	NOUN
cana-2910	85	18	to	to	ADP
cana-2910	85	19	local	local	ADJ
cana-2910	85	20	patterns	pattern	NOUN
cana-2910	85	21	in	in	ADP
cana-2910	85	22	the	the	DET
cana-2910	85	23	data	datum	NOUN
cana-2910	85	24	.	.	PUNCT
cana-2910	86	1	the	the	DET
cana-2910	86	2	svm	svm	ADJ
cana-2910	86	3	-	-	PUNCT
cana-2910	86	4	linear	linear	NOUN
cana-2910	86	5	employs	employ	VERB
cana-2910	86	6	a	a	DET
cana-2910	86	7	linear	linear	ADJ
cana-2910	86	8	kernel	kernel	NOUN
cana-2910	86	9	function	function	NOUN
cana-2910	86	10	,	,	PUNCT
cana-2910	86	11	allowing	allow	VERB
cana-2910	86	12	for	for	ADP
cana-2910	86	13	a	a	DET
cana-2910	86	14	hyperplane	hyperplane	NOUN
cana-2910	86	15	decision	decision	NOUN
cana-2910	86	16	boundary	boundary	ADJ
cana-2910	86	17	in	in	ADP
cana-2910	86	18	the	the	DET
cana-2910	86	19	input	input	NOUN
cana-2910	86	20	space	space	NOUN
cana-2910	86	21	[	[	X
cana-2910	86	22	11	11	NUM
cana-2910	86	23	]	]	PUNCT
cana-2910	86	24	.	.	PUNCT
cana-2910	87	1	this	this	PRON
cana-2910	87	2	is	be	AUX
cana-2910	87	3	ideal	ideal	ADJ
cana-2910	87	4	for	for	ADP
cana-2910	87	5	scenarios	scenario	NOUN
cana-2910	87	6	where	where	SCONJ
cana-2910	87	7	the	the	DET
cana-2910	87	8	features	feature	NOUN
cana-2910	87	9	exhibit	exhibit	VERB
cana-2910	87	10	a	a	DET
cana-2910	87	11	linear	linear	ADJ
cana-2910	87	12	relationship	relationship	NOUN
cana-2910	87	13	.	.	PUNCT
cana-2910	88	1	this	this	DET
cana-2910	88	2	approach	approach	NOUN
cana-2910	88	3	directly	directly	ADV
cana-2910	88	4	maps	map	VERB
cana-2910	88	5	data	datum	NOUN
cana-2910	88	6	points	point	NOUN
cana-2910	88	7	to	to	ADP
cana-2910	88	8	the	the	DET
cana-2910	88	9	feature	feature	NOUN
cana-2910	88	10	space	space	NOUN
cana-2910	88	11	without	without	ADP
cana-2910	88	12	any	any	DET
cana-2910	88	13	alteration	alteration	NOUN
cana-2910	88	14	,	,	PUNCT
cana-2910	88	15	making	make	VERB
cana-2910	88	16	it	it	PRON
cana-2910	88	17	computationally	computationally	ADV
cana-2910	88	18	efficient	efficient	ADJ
cana-2910	88	19	and	and	CCONJ
cana-2910	88	20	effective	effective	ADJ
cana-2910	88	21	for	for	ADP
cana-2910	88	22	datasets	dataset	NOUN
cana-2910	88	23	with	with	ADP
cana-2910	88	24	linearly	linearly	ADV
cana-2910	88	25	separable	separable	ADJ
cana-2910	88	26	classes	class	NOUN
cana-2910	88	27	.	.	PUNCT
cana-2910	89	1	nonetheless	nonetheless	ADV
cana-2910	89	2	,	,	PUNCT
cana-2910	89	3	it	it	PRON
cana-2910	89	4	is	be	AUX
cana-2910	89	5	not	not	PART
cana-2910	89	6	suitable	suitable	ADJ
cana-2910	89	7	for	for	ADP
cana-2910	89	8	handling	handle	VERB
cana-2910	89	9	non	non	ADJ
cana-2910	89	10	-	-	ADJ
cana-2910	89	11	linearly	linearly	ADV
cana-2910	89	12	separable	separable	ADJ
cana-2910	89	13	data	datum	NOUN
cana-2910	89	14	.	.	PUNCT
cana-2910	90	1	fig	fig	NOUN
cana-2910	90	2	.	.	PUNCT
cana-2910	91	1	2	2	X
cana-2910	91	2	.	.	X
cana-2910	91	3	svm	svm	PROPN
cana-2910	91	4	linear	linear	PROPN
cana-2910	91	5	hyperplane	hyperplane	PROPN
cana-2910	91	6	this	this	DET
cana-2910	91	7	version	version	NOUN
cana-2910	91	8	utilizes	utilize	VERB
cana-2910	91	9	a	a	DET
cana-2910	91	10	gaussian	gaussian	ADJ
cana-2910	91	11	kernel	kernel	NOUN
cana-2910	91	12	function	function	VERB
cana-2910	91	13	with	with	ADP
cana-2910	91	14	a	a	DET
cana-2910	91	15	moderate	moderate	ADJ
cana-2910	91	16	width	width	NOUN
cana-2910	91	17	,	,	PUNCT
cana-2910	91	18	striking	strike	VERB
cana-2910	91	19	a	a	DET
cana-2910	91	20	balance	balance	NOUN
cana-2910	91	21	between	between	ADP
cana-2910	91	22	the	the	DET
cana-2910	91	23	smoothness	smoothness	NOUN
cana-2910	91	24	of	of	ADP
cana-2910	91	25	the	the	DET
cana-2910	91	26	coarse	coarse	ADJ
cana-2910	91	27	gaussian	gaussian	NOUN
cana-2910	91	28	and	and	CCONJ
cana-2910	91	29	the	the	DET
cana-2910	91	30	sensitivity	sensitivity	NOUN
cana-2910	91	31	of	of	ADP
cana-2910	91	32	the	the	DET
cana-2910	91	33	fine	fine	ADJ
cana-2910	91	34	gaussian	gaussian	NOUN
cana-2910	91	35	.	.	PUNCT
cana-2910	92	1	it	it	PRON
cana-2910	92	2	proves	prove	VERB
cana-2910	92	3	to	to	PART
cana-2910	92	4	be	be	AUX
cana-2910	92	5	effective	effective	ADJ
cana-2910	92	6	across	across	ADP
cana-2910	92	7	a	a	DET
cana-2910	92	8	broader	broad	ADJ
cana-2910	92	9	spectrum	spectrum	NOUN
cana-2910	92	10	of	of	ADP
cana-2910	92	11	datasets	dataset	NOUN
cana-2910	92	12	compared	compare	VERB
cana-2910	92	13	to	to	ADP
cana-2910	92	14	other	other	ADJ
cana-2910	92	15	gaussian	gaussian	ADJ
cana-2910	92	16	variations	variation	NOUN
cana-2910	92	17	.	.	PUNCT
cana-2910	93	1	the	the	DET
cana-2910	93	2	"	"	PUNCT
cana-2910	93	3	moderate	moderate	ADJ
cana-2910	93	4	gaussian	gaussian	NOUN
cana-2910	93	5	"	"	PUNCT
cana-2910	93	6	implies	imply	VERB
cana-2910	93	7	a	a	DET
cana-2910	93	8	middle	middle	ADJ
cana-2910	93	9	ground	ground	NOUN
cana-2910	93	10	for	for	ADP
cana-2910	93	11	the	the	DET
cana-2910	93	12	spread	spread	ADJ
cana-2910	93	13	parameter	parameter	NOUN
cana-2910	93	14	in	in	ADP
cana-2910	93	15	the	the	DET
cana-2910	93	16	gaussian	gaussian	ADJ
cana-2910	93	17	kernel	kernel	NOUN
cana-2910	94	1	[	[	X
cana-2910	94	2	12	12	NUM
cana-2910	94	3	]	]	PUNCT
cana-2910	94	4	.	.	PUNCT
cana-2910	95	1	the	the	DET
cana-2910	95	2	decision	decision	NOUN
cana-2910	95	3	boundary	boundary	NOUN
cana-2910	95	4	will	will	AUX
cana-2910	95	5	exhibit	exhibit	VERB
cana-2910	95	6	a	a	DET
cana-2910	95	7	moderate	moderate	ADJ
cana-2910	95	8	level	level	NOUN
cana-2910	95	9	of	of	ADP
cana-2910	95	10	smoothness	smoothness	NOUN
cana-2910	95	11	,	,	PUNCT
cana-2910	95	12	capturing	capture	VERB
cana-2910	95	13	patterns	pattern	NOUN
cana-2910	95	14	that	that	PRON
cana-2910	95	15	are	be	AUX
cana-2910	95	16	neither	neither	CCONJ
cana-2910	95	17	overly	overly	ADV
cana-2910	95	18	broad	broad	ADJ
cana-2910	95	19	nor	nor	CCONJ
cana-2910	95	20	excessively	excessively	ADV
cana-2910	95	21	detailed	detailed	ADJ
cana-2910	95	22	.	.	PUNCT
cana-2910	96	1	various	various	ADJ
cana-2910	96	2	svm	svm	ADJ
cana-2910	96	3	variants	variant	NOUN
cana-2910	96	4	with	with	ADP
cana-2910	96	5	diverse	diverse	ADJ
cana-2910	96	6	kernels	kernel	NOUN
cana-2910	96	7	and	and	CCONJ
cana-2910	96	8	parameter	parameter	NOUN
cana-2910	96	9	configurations	configuration	NOUN
cana-2910	96	10	may	may	AUX
cana-2910	96	11	exhibit	exhibit	VERB
cana-2910	96	12	varying	vary	VERB
cana-2910	96	13	performances	performance	NOUN
cana-2910	96	14	on	on	ADP
cana-2910	96	15	different	different	ADJ
cana-2910	96	16	dataset	dataset	NOUN
cana-2910	96	17	types	type	NOUN
cana-2910	96	18	.	.	PUNCT
cana-2910	97	1	the	the	DET
cana-2910	97	2	selection	selection	NOUN
cana-2910	97	3	of	of	ADP
cana-2910	97	4	the	the	DET
cana-2910	97	5	svm	svm	ADJ
cana-2910	97	6	variant	variant	NOUN
cana-2910	97	7	hinges	hinge	NOUN
cana-2910	97	8	on	on	ADP
cana-2910	97	9	the	the	DET
cana-2910	97	10	data	datum	NOUN
cana-2910	97	11	characteristics	characteristic	NOUN
cana-2910	97	12	and	and	CCONJ
cana-2910	97	13	the	the	DET
cana-2910	97	14	complexity	complexity	NOUN
cana-2910	97	15	of	of	ADP
cana-2910	97	16	the	the	DET
cana-2910	97	17	relationships	relationship	NOUN
cana-2910	97	18	between	between	ADP
cana-2910	97	19	features	feature	NOUN
cana-2910	97	20	.	.	PUNCT
cana-2910	98	1	it	it	PRON
cana-2910	98	2	is	be	AUX
cana-2910	98	3	customary	customary	ADJ
cana-2910	98	4	to	to	PART
cana-2910	98	5	experiment	experiment	VERB
cana-2910	98	6	with	with	ADP
cana-2910	98	7	different	different	ADJ
cana-2910	98	8	kernels	kernel	NOUN
cana-2910	98	9	and	and	CCONJ
cana-2910	98	10	parameters	parameter	NOUN
cana-2910	98	11	to	to	PART
cana-2910	98	12	determine	determine	VERB
cana-2910	98	13	the	the	DET
cana-2910	98	14	setup	setup	NOUN
cana-2910	98	15	that	that	PRON
cana-2910	98	16	best	well	ADV
cana-2910	98	17	fits	fit	VERB
cana-2910	98	18	the	the	DET
cana-2910	98	19	specific	specific	ADJ
cana-2910	98	20	problem	problem	NOUN
cana-2910	98	21	at	at	ADP
cana-2910	98	22	hand	hand	NOUN
cana-2910	98	23	.	.	PUNCT
cana-2910	99	1	2.4	2.4	NUM
cana-2910	99	2	.	.	PUNCT
cana-2910	100	1	svm	svm	ADJ
cana-2910	100	2	-	-	ADJ
cana-2910	100	3	fine	fine	ADJ
cana-2910	100	4	gaussian	gaussian	NOUN
cana-2910	100	5	2.5	2.5	NUM
cana-2910	100	6	.	.	PUNCT
cana-2910	101	1	svm	svm	ADJ
cana-2910	101	2	-	-	PROPN
cana-2910	101	3	linear	linear	ADJ
cana-2910	101	4	2.6	2.6	NUM
cana-2910	101	5	.	.	PUNCT
cana-2910	102	1	svm	svm	ADJ
cana-2910	102	2	-	-	ADJ
cana-2910	102	3	medium	medium	ADJ
cana-2910	102	4	gaussian	gaussian	ADJ
cana-2910	102	5	communications	communication	NOUN
cana-2910	102	6	on	on	ADP
cana-2910	102	7	applied	apply	VERB
cana-2910	102	8	nonlinear	nonlinear	ADJ
cana-2910	102	9	analysis	analysis	NOUN
cana-2910	102	10	issn	issn	NOUN
cana-2910	102	11	:	:	PUNCT
cana-2910	102	12	1074	1074	NUM
cana-2910	102	13	-	-	PUNCT
cana-2910	102	14	133x	133x	NUM
cana-2910	102	15	vol	vol	NOUN
cana-2910	102	16	32	32	NUM
cana-2910	102	17	no	no	NOUN
cana-2910	102	18	.	.	PUNCT
cana-2910	103	1	4s	4s	NUM
cana-2910	103	2	(	(	PUNCT
cana-2910	103	3	2025	2025	NUM
cana-2910	103	4	)	)	PUNCT
cana-2910	103	5	650	650	NUM
cana-2910	103	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	103	7	the	the	DET
cana-2910	103	8	study	study	NOUN
cana-2910	103	9	report	report	NOUN
cana-2910	103	10	details	detail	NOUN
cana-2910	103	11	the	the	DET
cana-2910	103	12	use	use	NOUN
cana-2910	103	13	of	of	ADP
cana-2910	103	14	a	a	DET
cana-2910	103	15	unique	unique	ADJ
cana-2910	103	16	dataset	dataset	NOUN
cana-2910	103	17	with	with	ADP
cana-2910	103	18	five	five	NUM
cana-2910	103	19	thousand	thousand	NUM
cana-2910	103	20	records	record	NOUN
cana-2910	103	21	.	.	PUNCT
cana-2910	104	1	these	these	DET
cana-2910	104	2	files	file	NOUN
cana-2910	104	3	were	be	AUX
cana-2910	104	4	loaded	load	VERB
cana-2910	104	5	into	into	ADP
cana-2910	104	6	machine	machine	NOUN
cana-2910	104	7	learning	learning	NOUN
cana-2910	104	8	models	model	NOUN
cana-2910	104	9	could	could	AUX
cana-2910	104	10	be	be	AUX
cana-2910	104	11	built	build	VERB
cana-2910	104	12	.	.	PUNCT
cana-2910	105	1	the	the	DET
cana-2910	105	2	authors	author	NOUN
cana-2910	105	3	described	describe	VERB
cana-2910	105	4	a	a	DET
cana-2910	105	5	set	set	NOUN
cana-2910	105	6	of	of	ADP
cana-2910	105	7	procedures	procedure	NOUN
cana-2910	105	8	used	use	VERB
cana-2910	105	9	to	to	PART
cana-2910	105	10	identify	identify	VERB
cana-2910	105	11	and	and	CCONJ
cana-2910	105	12	categorize	categorize	VERB
cana-2910	105	13	instances	instance	NOUN
cana-2910	105	14	of	of	ADP
cana-2910	105	15	gst	gst	NOUN
cana-2910	105	16	fraud	fraud	NOUN
cana-2910	105	17	.	.	PUNCT
cana-2910	106	1	the	the	DET
cana-2910	106	2	dataset	dataset	NOUN
cana-2910	106	3	is	be	AUX
cana-2910	106	4	cleaned	clean	VERB
cana-2910	106	5	and	and	CCONJ
cana-2910	106	6	transformed	transform	VERB
cana-2910	106	7	during	during	ADP
cana-2910	106	8	the	the	DET
cana-2910	106	9	data	datum	NOUN
cana-2910	106	10	preprocessing	preprocesse	VERB
cana-2910	106	11	stage	stage	NOUN
cana-2910	106	12	in	in	ADP
cana-2910	106	13	order	order	NOUN
cana-2910	106	14	to	to	PART
cana-2910	106	15	make	make	VERB
cana-2910	106	16	it	it	PRON
cana-2910	106	17	ready	ready	ADJ
cana-2910	106	18	for	for	ADP
cana-2910	106	19	use	use	NOUN
cana-2910	106	20	as	as	ADP
cana-2910	106	21	an	an	DET
cana-2910	106	22	input	input	NOUN
cana-2910	106	23	for	for	ADP
cana-2910	106	24	machine	machine	NOUN
cana-2910	106	25	learning	learning	NOUN
cana-2910	106	26	models	model	NOUN
cana-2910	106	27	.	.	PUNCT
cana-2910	107	1	this	this	DET
cana-2910	107	2	procedure	procedure	NOUN
cana-2910	107	3	entails	entail	VERB
cana-2910	107	4	choosing	choose	VERB
cana-2910	107	5	the	the	DET
cana-2910	107	6	seven	seven	NUM
cana-2910	107	7	relevant	relevant	ADJ
cana-2910	107	8	columns	column	NOUN
cana-2910	107	9	as	as	SCONJ
cana-2910	107	10	shown	show	VERB
cana-2910	107	11	in	in	ADP
cana-2910	107	12	table	table	NOUN
cana-2910	107	13	1	1	NUM
cana-2910	107	14	.	.	PUNCT
cana-2910	108	1	the	the	DET
cana-2910	108	2	existence	existence	NOUN
cana-2910	108	3	of	of	ADP
cana-2910	108	4	null	null	ADJ
cana-2910	108	5	values	value	NOUN
cana-2910	108	6	is	be	AUX
cana-2910	108	7	then	then	ADV
cana-2910	108	8	checked	check	VERB
cana-2910	108	9	in	in	ADP
cana-2910	108	10	order	order	NOUN
cana-2910	108	11	to	to	PART
cana-2910	108	12	verify	verify	VERB
cana-2910	108	13	the	the	DET
cana-2910	108	14	accuracy	accuracy	NOUN
cana-2910	108	15	of	of	ADP
cana-2910	108	16	the	the	DET
cana-2910	108	17	results	result	NOUN
cana-2910	108	18	,	,	PUNCT
cana-2910	108	19	since	since	SCONJ
cana-2910	108	20	the	the	DET
cana-2910	108	21	algorithm	algorithm	NOUN
cana-2910	108	22	's	's	PART
cana-2910	108	23	conclusions	conclusion	NOUN
cana-2910	108	24	can	can	AUX
cana-2910	108	25	change	change	VERB
cana-2910	108	26	if	if	SCONJ
cana-2910	108	27	there	there	PRON
cana-2910	108	28	are	be	VERB
cana-2910	108	29	null	null	ADJ
cana-2910	108	30	values	value	NOUN
cana-2910	108	31	in	in	ADP
cana-2910	108	32	the	the	DET
cana-2910	108	33	data	datum	NOUN
cana-2910	108	34	.	.	PUNCT
cana-2910	109	1	thereafter	thereafter	ADV
cana-2910	109	2	the	the	DET
cana-2910	109	3	cross	cross	NOUN
cana-2910	109	4	tabulation	tabulation	NOUN
cana-2910	109	5	of	of	ADP
cana-2910	109	6	the	the	DET
cana-2910	109	7	data	datum	NOUN
cana-2910	109	8	based	base	VERB
cana-2910	109	9	on	on	ADP
cana-2910	109	10	several	several	ADJ
cana-2910	109	11	attributes	attribute	NOUN
cana-2910	109	12	may	may	AUX
cana-2910	109	13	be	be	AUX
cana-2910	109	14	examined	examine	VERB
cana-2910	109	15	to	to	PART
cana-2910	109	16	obtain	obtain	VERB
cana-2910	109	17	descriptive	descriptive	ADJ
cana-2910	109	18	visualization	visualization	NOUN
cana-2910	109	19	of	of	ADP
cana-2910	109	20	the	the	DET
cana-2910	109	21	data	datum	NOUN
cana-2910	109	22	.	.	PUNCT
cana-2910	110	1	table	table	NOUN
cana-2910	110	2	1	1	NUM
cana-2910	110	3	.	.	PUNCT
cana-2910	111	1	attributes	attribute	NOUN
cana-2910	111	2	associated	associate	VERB
cana-2910	111	3	with	with	ADP
cana-2910	111	4	gst	gst	PROPN
cana-2910	111	5	fraud	fraud	NOUN
cana-2910	111	6	attribute	attribute	NOUN
cana-2910	111	7	values	value	NOUN
cana-2910	111	8	gst	gst	PROPN
cana-2910	111	9	number	number	NOUN
cana-2910	111	10	15	15	NUM
cana-2910	111	11	digit	digit	NOUN
cana-2910	111	12	alphanumeric	alphanumeric	ADJ
cana-2910	111	13	number	number	NOUN
cana-2910	111	14	sales	sale	NOUN
cana-2910	111	15	sales	sale	NOUN
cana-2910	111	16	in	in	ADP
cana-2910	111	17	indian	indian	ADJ
cana-2910	111	18	rupees	rupee	NOUN
cana-2910	111	19	purchases	purchase	VERB
cana-2910	111	20	purchases	purchase	NOUN
cana-2910	111	21	in	in	ADP
cana-2910	111	22	indian	indian	ADJ
cana-2910	111	23	rupees	rupee	NOUN
cana-2910	111	24	total	total	ADJ
cana-2910	111	25	tax	tax	NOUN
cana-2910	111	26	liability	liability	NOUN
cana-2910	111	27	total	total	ADJ
cana-2910	111	28	tax	tax	NOUN
cana-2910	111	29	liability	liability	NOUN
cana-2910	111	30	in	in	ADP
cana-2910	111	31	indian	indian	ADJ
cana-2910	111	32	rupees	rupee	NOUN
cana-2910	111	33	total	total	ADJ
cana-2910	111	34	input	input	NOUN
cana-2910	111	35	tax	tax	NOUN
cana-2910	111	36	credit	credit	NOUN
cana-2910	111	37	total	total	NOUN
cana-2910	111	38	input	input	NOUN
cana-2910	111	39	tax	tax	NOUN
cana-2910	111	40	credit	credit	NOUN
cana-2910	111	41	in	in	ADP
cana-2910	111	42	indian	indian	ADJ
cana-2910	111	43	rupees	rupee	NOUN
cana-2910	111	44	percentage	percentage	NOUN
cana-2910	111	45	of	of	ADP
cana-2910	111	46	input	input	NOUN
cana-2910	111	47	tax	tax	NOUN
cana-2910	111	48	credit	credit	NOUN
cana-2910	111	49	percentage	percentage	NOUN
cana-2910	111	50	of	of	ADP
cana-2910	111	51	input	input	NOUN
cana-2910	111	52	tax	tax	NOUN
cana-2910	111	53	credit	credit	NOUN
cana-2910	111	54	(	(	PUNCT
cana-2910	111	55	0	0	NUM
cana-2910	111	56	-	-	SYM
cana-2910	111	57	100	100	NUM
cana-2910	111	58	)	)	PUNCT
cana-2910	111	59	lated	late	VERB
cana-2910	111	60	one	one	NUM
cana-2910	111	61	to	to	ADP
cana-2910	111	62	another	another	PRON
cana-2910	111	63	,	,	PUNCT
cana-2910	111	64	all	all	DET
cana-2910	111	65	7	7	NUM
cana-2910	111	66	attributes	attribute	NOUN
cana-2910	111	67	can	can	AUX
cana-2910	111	68	be	be	AUX
cana-2910	111	69	included	include	VERB
cana-2910	111	70	in	in	ADP
cana-2910	111	71	the	the	DET
cana-2910	111	72	model	model	NOUN
cana-2910	111	73	.	.	PUNCT
cana-2910	112	1	however	however	ADV
cana-2910	112	2	,	,	PUNCT
cana-2910	112	3	if	if	SCONJ
cana-2910	112	4	there	there	PRON
cana-2910	112	5	is	be	VERB
cana-2910	112	6	a	a	DET
cana-2910	112	7	strong	strong	ADJ
cana-2910	112	8	correlation	correlation	NOUN
cana-2910	112	9	between	between	ADP
cana-2910	112	10	two	two	NUM
cana-2910	112	11	attributes	attribute	NOUN
cana-2910	112	12	,	,	PUNCT
cana-2910	112	13	one	one	NUM
cana-2910	112	14	of	of	ADP
cana-2910	112	15	them	they	PRON
cana-2910	112	16	should	should	AUX
cana-2910	112	17	be	be	AUX
cana-2910	112	18	dropped	drop	VERB
cana-2910	112	19	.	.	PUNCT
cana-2910	113	1	the	the	DET
cana-2910	113	2	correlation	correlation	NOUN
cana-2910	113	3	method	method	NOUN
cana-2910	113	4	utilizes	utilize	VERB
cana-2910	113	5	the	the	DET
cana-2910	113	6	pearson	pearson	PROPN
cana-2910	113	7	correlation	correlation	NOUN
cana-2910	113	8	.	.	PUNCT
cana-2910	114	1	the	the	DET
cana-2910	114	2	results	result	NOUN
cana-2910	114	3	of	of	ADP
cana-2910	114	4	the	the	DET
cana-2910	114	5	correlation	correlation	NOUN
cana-2910	114	6	study	study	NOUN
cana-2910	114	7	point	point	NOUN
cana-2910	114	8	to	to	ADP
cana-2910	114	9	the	the	DET
cana-2910	114	10	seven	seven	NUM
cana-2910	114	11	attributes	attribute	NOUN
cana-2910	114	12	'	'	PART
cana-2910	114	13	poor	poor	ADJ
cana-2910	114	14	relationships	relationship	NOUN
cana-2910	114	15	with	with	ADP
cana-2910	114	16	one	one	NUM
cana-2910	114	17	another	another	DET
cana-2910	114	18	,	,	PUNCT
cana-2910	114	19	indicating	indicate	VERB
cana-2910	114	20	their	their	PRON
cana-2910	114	21	independence	independence	NOUN
cana-2910	114	22	.	.	PUNCT
cana-2910	115	1	consequently	consequently	ADV
cana-2910	115	2	,	,	PUNCT
cana-2910	115	3	all	all	DET
cana-2910	115	4	seven	seven	NUM
cana-2910	115	5	characteristics	characteristic	NOUN
cana-2910	115	6	are	be	AUX
cana-2910	115	7	kept	keep	VERB
cana-2910	115	8	and	and	CCONJ
cana-2910	115	9	included	include	VERB
cana-2910	115	10	to	to	ADP
cana-2910	115	11	the	the	DET
cana-2910	115	12	model	model	NOUN
cana-2910	115	13	for	for	ADP
cana-2910	115	14	additional	additional	ADJ
cana-2910	115	15	examination	examination	NOUN
cana-2910	115	16	.	.	PUNCT
cana-2910	116	1	the	the	DET
cana-2910	116	2	5000	5000	NUM
cana-2910	116	3	-	-	PUNCT
cana-2910	116	4	record	record	NOUN
cana-2910	116	5	dataset	dataset	NOUN
cana-2910	116	6	is	be	AUX
cana-2910	116	7	split	split	VERB
cana-2910	116	8	into	into	ADP
cana-2910	116	9	training	training	NOUN
cana-2910	116	10	and	and	CCONJ
cana-2910	116	11	testing	testing	NOUN
cana-2910	116	12	subsets	subset	NOUN
cana-2910	116	13	at	at	ADP
cana-2910	116	14	this	this	DET
cana-2910	116	15	stage	stage	NOUN
cana-2910	116	16	.	.	PUNCT
cana-2910	117	1	the	the	DET
cana-2910	117	2	split	split	NOUN
cana-2910	117	3	is	be	AUX
cana-2910	117	4	done	do	VERB
cana-2910	117	5	at	at	ADP
cana-2910	117	6	random	random	ADJ
cana-2910	117	7	,	,	PUNCT
cana-2910	117	8	with	with	ADP
cana-2910	117	9	the	the	DET
cana-2910	117	10	train	train	NOUN
cana-2910	117	11	-	-	PUNCT
cana-2910	117	12	test	test	NOUN
cana-2910	117	13	data	datum	NOUN
cana-2910	117	14	division	division	NOUN
cana-2910	117	15	followed	follow	VERB
cana-2910	117	16	by	by	ADP
cana-2910	117	17	an	an	DET
cana-2910	117	18	80:20	80:20	NUM
cana-2910	117	19	ratio	ratio	NOUN
cana-2910	117	20	.	.	PUNCT
cana-2910	118	1	the	the	DET
cana-2910	118	2	ideal	ideal	ADJ
cana-2910	118	3	fraction	fraction	NOUN
cana-2910	118	4	for	for	ADP
cana-2910	118	5	the	the	DET
cana-2910	118	6	train	train	NOUN
cana-2910	118	7	-	-	PUNCT
cana-2910	118	8	test	test	NOUN
cana-2910	118	9	data	datum	NOUN
cana-2910	118	10	split	split	NOUN
cana-2910	118	11	is	be	AUX
cana-2910	118	12	found	find	VERB
cana-2910	118	13	to	to	PART
cana-2910	118	14	be	be	AUX
cana-2910	118	15	this	this	DET
cana-2910	118	16	ratio	ratio	NOUN
cana-2910	118	17	.	.	PUNCT
cana-2910	119	1	the	the	DET
cana-2910	119	2	training	training	NOUN
cana-2910	119	3	procedure	procedure	NOUN
cana-2910	119	4	begins	begin	VERB
cana-2910	119	5	with	with	ADP
cana-2910	119	6	the	the	DET
cana-2910	119	7	training	training	NOUN
cana-2910	119	8	data	datum	NOUN
cana-2910	119	9	as	as	ADP
cana-2910	119	10	input	input	NOUN
cana-2910	119	11	and	and	CCONJ
cana-2910	119	12	builds	build	VERB
cana-2910	119	13	the	the	DET
cana-2910	119	14	models	model	NOUN
cana-2910	119	15	.	.	PUNCT
cana-2910	120	1	for	for	ADP
cana-2910	120	2	this	this	PRON
cana-2910	120	3	,	,	PUNCT
cana-2910	120	4	different	different	ADJ
cana-2910	120	5	variants	variant	NOUN
cana-2910	120	6	of	of	ADP
cana-2910	120	7	the	the	DET
cana-2910	120	8	support	support	NOUN
cana-2910	120	9	vector	vector	NOUN
cana-2910	120	10	machine	machine	NOUN
cana-2910	120	11	(	(	PUNCT
cana-2910	120	12	svm	svm	ADJ
cana-2910	120	13	)	)	PUNCT
cana-2910	120	14	algorithms	algorithm	NOUN
cana-2910	120	15	are	be	AUX
cana-2910	120	16	used	use	VERB
cana-2910	120	17	separately	separately	ADV
cana-2910	120	18	.	.	PUNCT
cana-2910	121	1	these	these	DET
cana-2910	121	2	algorithms	algorithm	NOUN
cana-2910	121	3	'	'	PART
cana-2910	121	4	parameters	parameter	NOUN
cana-2910	121	5	are	be	AUX
cana-2910	121	6	adjusted	adjust	VERB
cana-2910	121	7	and	and	CCONJ
cana-2910	121	8	calibrated	calibrate	VERB
cana-2910	121	9	to	to	PART
cana-2910	121	10	improve	improve	VERB
cana-2910	121	11	the	the	DET
cana-2910	121	12	models	model	NOUN
cana-2910	121	13	'	'	PART
cana-2910	121	14	accuracy	accuracy	NOUN
cana-2910	121	15	.	.	PUNCT
cana-2910	122	1	3	3	X
cana-2910	122	2	.	.	X
cana-2910	122	3	research	research	NOUN
cana-2910	122	4	methodology	methodology	NOUN
cana-2910	122	5	3.1	3.1	NUM
cana-2910	122	6	.	.	PUNCT
cana-2910	123	1	data	datum	NOUN
cana-2910	123	2	preprocessing	preprocesse	VERB
cana-2910	123	3	3.2	3.2	NUM
cana-2910	123	4	.	.	PUNCT
cana-2910	124	1	feature	feature	NOUN
cana-2910	124	2	selection	selection	NOUN
cana-2910	124	3	the	the	DET
cana-2910	124	4	next	next	ADJ
cana-2910	124	5	step	step	NOUN
cana-2910	124	6	is	be	AUX
cana-2910	124	7	to	to	PART
cana-2910	124	8	investigate	investigate	VERB
cana-2910	124	9	the	the	DET
cana-2910	124	10	correlation	correlation	NOUN
cana-2910	124	11	between	between	ADP
cana-2910	124	12	the	the	DET
cana-2910	124	13	7	7	NUM
cana-2910	124	14	attributes	attribute	NOUN
cana-2910	124	15	.	.	PUNCT
cana-2910	125	1	if	if	SCONJ
cana-2910	125	2	the	the	DET
cana-2910	125	3	attributes	attribute	NOUN
cana-2910	125	4	are	be	AUX
cana-2910	125	5	not	not	PART
cana-2910	125	6	corre3.3	corre3.3	NOUN
cana-2910	125	7	.	.	PUNCT
cana-2910	126	1	data	datum	NOUN
cana-2910	126	2	splitting	split	VERB
cana-2910	126	3	3.4	3.4	NUM
cana-2910	126	4	.	.	PUNCT
cana-2910	126	5	model	model	NOUN
cana-2910	126	6	training	training	NOUN
cana-2910	126	7	communications	communication	NOUN
cana-2910	126	8	on	on	ADP
cana-2910	126	9	applied	apply	VERB
cana-2910	126	10	nonlinear	nonlinear	ADJ
cana-2910	126	11	analysis	analysis	NOUN
cana-2910	126	12	issn	issn	NOUN
cana-2910	126	13	:	:	PUNCT
cana-2910	126	14	1074	1074	NUM
cana-2910	126	15	-	-	PUNCT
cana-2910	126	16	133x	133x	NUM
cana-2910	126	17	vol	vol	NOUN
cana-2910	126	18	32	32	NUM
cana-2910	126	19	no	no	NOUN
cana-2910	126	20	.	.	PUNCT
cana-2910	127	1	4s	4s	NUM
cana-2910	127	2	(	(	PUNCT
cana-2910	127	3	2025	2025	NUM
cana-2910	127	4	)	)	PUNCT
cana-2910	127	5	651	651	NUM
cana-2910	127	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	127	7	fig	fig	NOUN
cana-2910	127	8	.	.	PUNCT
cana-2910	128	1	3	3	X
cana-2910	128	2	.	.	X
cana-2910	128	3	machine	machine	NOUN
cana-2910	128	4	learning	learning	NOUN
cana-2910	128	5	model	model	NOUN
cana-2910	128	6	the	the	DET
cana-2910	128	7	created	create	VERB
cana-2910	128	8	models	model	NOUN
cana-2910	128	9	are	be	AUX
cana-2910	128	10	finally	finally	ADV
cana-2910	128	11	applied	apply	VERB
cana-2910	128	12	to	to	ADP
cana-2910	128	13	the	the	DET
cana-2910	128	14	testing	testing	NOUN
cana-2910	128	15	data	datum	NOUN
cana-2910	128	16	.	.	PUNCT
cana-2910	129	1	the	the	DET
cana-2910	129	2	results	result	NOUN
cana-2910	129	3	are	be	AUX
cana-2910	129	4	displayed	display	VERB
cana-2910	129	5	as	as	ADP
cana-2910	129	6	a	a	DET
cana-2910	129	7	confusion	confusion	NOUN
cana-2910	129	8	matrix	matrix	NOUN
cana-2910	129	9	,	,	PUNCT
cana-2910	129	10	comparing	compare	VERB
cana-2910	129	11	the	the	DET
cana-2910	129	12	real	real	ADJ
cana-2910	129	13	positive	positive	ADJ
cana-2910	129	14	and	and	CCONJ
cana-2910	129	15	negative	negative	ADJ
cana-2910	129	16	examples	example	NOUN
cana-2910	129	17	with	with	ADP
cana-2910	129	18	the	the	DET
cana-2910	129	19	ones	one	NOUN
cana-2910	129	20	that	that	PRON
cana-2910	129	21	were	be	AUX
cana-2910	129	22	predicted	predict	VERB
cana-2910	129	23	.	.	PUNCT
cana-2910	130	1	in	in	ADP
cana-2910	130	2	this	this	DET
cana-2910	130	3	case	case	NOUN
cana-2910	130	4	,	,	PUNCT
cana-2910	130	5	"	"	PUNCT
cana-2910	130	6	negative	negative	ADJ
cana-2910	130	7	"	"	PUNCT
cana-2910	130	8	indicates	indicate	VERB
cana-2910	130	9	that	that	SCONJ
cana-2910	130	10	the	the	DET
cana-2910	130	11	gst	gst	PROPN
cana-2910	130	12	fraud	fraud	NOUN
cana-2910	130	13	class	class	NOUN
cana-2910	130	14	does	do	AUX
cana-2910	130	15	not	not	PART
cana-2910	130	16	exist	exist	VERB
cana-2910	130	17	,	,	PUNCT
cana-2910	130	18	whereas	whereas	SCONJ
cana-2910	130	19	"	"	PUNCT
cana-2910	130	20	positive	positive	ADJ
cana-2910	130	21	"	"	PUNCT
cana-2910	130	22	indicates	indicate	VERB
cana-2910	130	23	that	that	SCONJ
cana-2910	130	24	the	the	DET
cana-2910	130	25	gst	gst	PROPN
cana-2910	130	26	fraud	fraud	NOUN
cana-2910	130	27	class	class	NOUN
cana-2910	130	28	does	do	AUX
cana-2910	130	29	exist	exist	VERB
cana-2910	130	30	.	.	PUNCT
cana-2910	131	1	tp	tp	NOUN
cana-2910	131	2	(	(	PUNCT
cana-2910	131	3	true	true	ADJ
cana-2910	131	4	positive	positive	ADJ
cana-2910	131	5	:	:	PUNCT
cana-2910	131	6	actual	actual	ADJ
cana-2910	131	7	and	and	CCONJ
cana-2910	131	8	predicted	predict	VERB
cana-2910	131	9	values	value	NOUN
cana-2910	131	10	are	be	AUX
cana-2910	131	11	positive	positive	ADJ
cana-2910	131	12	)	)	PUNCT
cana-2910	131	13	,	,	PUNCT
cana-2910	131	14	fp	fp	INTJ
cana-2910	131	15	(	(	PUNCT
cana-2910	131	16	false	false	ADJ
cana-2910	131	17	positive	positive	ADJ
cana-2910	131	18	:	:	PUNCT
cana-2910	131	19	actual	actual	ADJ
cana-2910	131	20	value	value	NOUN
cana-2910	131	21	is	be	AUX
cana-2910	131	22	negative	negative	ADJ
cana-2910	131	23	but	but	CCONJ
cana-2910	131	24	predicted	predict	VERB
cana-2910	131	25	value	value	NOUN
cana-2910	131	26	is	be	AUX
cana-2910	131	27	positive	positive	ADJ
cana-2910	131	28	)	)	PUNCT
cana-2910	131	29	,	,	PUNCT
cana-2910	131	30	tn	tn	PROPN
cana-2910	131	31	(	(	PUNCT
cana-2910	131	32	true	true	ADJ
cana-2910	131	33	negative	negative	ADJ
cana-2910	131	34	:	:	PUNCT
cana-2910	131	35	actual	actual	ADJ
cana-2910	131	36	and	and	CCONJ
cana-2910	131	37	predicted	predict	VERB
cana-2910	131	38	values	value	NOUN
cana-2910	131	39	are	be	AUX
cana-2910	131	40	negative	negative	ADJ
cana-2910	131	41	)	)	PUNCT
cana-2910	131	42	,	,	PUNCT
cana-2910	131	43	and	and	CCONJ
cana-2910	131	44	fn	fn	INTJ
cana-2910	131	45	(	(	PUNCT
cana-2910	131	46	false	false	ADJ
cana-2910	131	47	negative	negative	ADJ
cana-2910	131	48	:	:	PUNCT
cana-2910	131	49	actual	actual	ADJ
cana-2910	131	50	value	value	NOUN
cana-2910	131	51	is	be	AUX
cana-2910	131	52	positive	positive	ADJ
cana-2910	131	53	but	but	CCONJ
cana-2910	131	54	predicted	predict	VERB
cana-2910	131	55	value	value	NOUN
cana-2910	131	56	is	be	AUX
cana-2910	131	57	negative	negative	ADJ
cana-2910	131	58	)	)	PUNCT
cana-2910	131	59	are	be	AUX
cana-2910	131	60	the	the	DET
cana-2910	131	61	four	four	NUM
cana-2910	131	62	categories	category	NOUN
cana-2910	131	63	that	that	PRON
cana-2910	131	64	make	make	VERB
cana-2910	131	65	up	up	ADP
cana-2910	131	66	the	the	DET
cana-2910	131	67	confusion	confusion	NOUN
cana-2910	131	68	matrix	matrix	NOUN
cana-2910	131	69	.	.	PUNCT
cana-2910	132	1	metrics	metric	NOUN
cana-2910	132	2	like	like	ADP
cana-2910	132	3	accuracy	accuracy	NOUN
cana-2910	132	4	,	,	PUNCT
cana-2910	132	5	precision	precision	NOUN
cana-2910	132	6	,	,	PUNCT
cana-2910	132	7	f	f	X
cana-2910	132	8	-	-	PUNCT
cana-2910	132	9	measure	measure	NOUN
cana-2910	132	10	,	,	PUNCT
cana-2910	132	11	and	and	CCONJ
cana-2910	132	12	recall	recall	VERB
cana-2910	132	13	for	for	ADP
cana-2910	132	14	different	different	ADJ
cana-2910	132	15	svm	svm	ADJ
cana-2910	132	16	versions	version	NOUN
cana-2910	132	17	can	can	AUX
cana-2910	132	18	be	be	AUX
cana-2910	132	19	computed	compute	VERB
cana-2910	132	20	using	use	VERB
cana-2910	132	21	the	the	DET
cana-2910	132	22	confusion	confusion	NOUN
cana-2910	132	23	matrix	matrix	NOUN
cana-2910	132	24	.	.	PUNCT
cana-2910	133	1	accuracy	accuracy	NOUN
cana-2910	134	1	=	=	PRON
cana-2910	134	2	tp	tp	X
cana-2910	134	3	+	+	X
cana-2910	134	4	in/	in/	ADV
cana-2910	135	1	(	(	PUNCT
cana-2910	135	2	tp+in+fp+	tp+in+fp+	PROPN
cana-2910	135	3	fn	fn	NOUN
cana-2910	135	4	)	)	PUNCT
cana-2910	135	5	precision	precision	NOUN
cana-2910	135	6	=	=	SYM
cana-2910	135	7	tp/(tp	tp/(tp	PROPN
cana-2910	135	8	+	+	CCONJ
cana-2910	135	9	fp	fp	X
cana-2910	135	10	)	)	PUNCT
cana-2910	135	11	recall	recall	NOUN
cana-2910	135	12	=	=	SYM
cana-2910	135	13	tp/(tp	tp/(tp	PROPN
cana-2910	135	14	+	+	CCONJ
cana-2910	135	15	fn	fn	NOUN
cana-2910	135	16	)	)	PUNCT
cana-2910	135	17	4	4	NUM
cana-2910	135	18	.	.	X
cana-2910	135	19	result	result	NOUN
cana-2910	135	20	and	and	CCONJ
cana-2910	135	21	discussion	discussion	NOUN
cana-2910	135	22	in	in	ADP
cana-2910	135	23	this	this	DET
cana-2910	135	24	paper	paper	NOUN
cana-2910	135	25	,	,	PUNCT
cana-2910	135	26	the	the	DET
cana-2910	135	27	results	result	NOUN
cana-2910	135	28	are	be	AUX
cana-2910	135	29	the	the	DET
cana-2910	135	30	most	most	ADV
cana-2910	135	31	significant	significant	ADJ
cana-2910	135	32	aspects	aspect	NOUN
cana-2910	135	33	associated	associate	VERB
cana-2910	135	34	with	with	ADP
cana-2910	135	35	gst	gst	NOUN
cana-2910	135	36	fraud	fraud	NOUN
cana-2910	135	37	and	and	CCONJ
cana-2910	135	38	models	model	NOUN
cana-2910	135	39	developed	develop	VERB
cana-2910	135	40	using	use	VERB
cana-2910	135	41	different	different	ADJ
cana-2910	135	42	variant	variant	NOUN
cana-2910	135	43	of	of	ADP
cana-2910	135	44	svm	svm	ADJ
cana-2910	135	45	algorithms	algorithm	NOUN
cana-2910	135	46	to	to	PART
cana-2910	135	47	predict	predict	VERB
cana-2910	135	48	the	the	DET
cana-2910	135	49	gst	gst	PROPN
cana-2910	135	50	fraud	fraud	NOUN
cana-2910	135	51	.	.	PUNCT
cana-2910	136	1	fig	fig	NOUN
cana-2910	136	2	.	.	PUNCT
cana-2910	137	1	4	4	X
cana-2910	137	2	.	.	X
cana-2910	137	3	accuracy	accuracy	NOUN
cana-2910	137	4	of	of	ADP
cana-2910	137	5	various	various	ADJ
cana-2910	137	6	svm	svm	ADJ
cana-2910	137	7	variants	variant	NOUN
cana-2910	137	8	3.5	3.5	NUM
cana-2910	137	9	.	.	PUNCT
cana-2910	138	1	model	model	NOUN
cana-2910	138	2	evaluation	evaluation	NOUN
cana-2910	138	3	communications	communication	NOUN
cana-2910	138	4	on	on	ADP
cana-2910	138	5	applied	apply	VERB
cana-2910	138	6	nonlinear	nonlinear	ADJ
cana-2910	138	7	analysis	analysis	NOUN
cana-2910	138	8	issn	issn	NOUN
cana-2910	138	9	:	:	PUNCT
cana-2910	138	10	1074	1074	NUM
cana-2910	138	11	-	-	PUNCT
cana-2910	138	12	133x	133x	NUM
cana-2910	138	13	vol	vol	NOUN
cana-2910	138	14	32	32	NUM
cana-2910	138	15	no	no	NOUN
cana-2910	138	16	.	.	PUNCT
cana-2910	139	1	4s	4s	NUM
cana-2910	139	2	(	(	PUNCT
cana-2910	139	3	2025	2025	NUM
cana-2910	139	4	)	)	PUNCT
cana-2910	139	5	652	652	NUM
cana-2910	139	6	https://internationalpubls.com	https://internationalpubls.com	X
cana-2910	139	7	as	as	ADP
cana-2910	139	8	per	per	ADP
cana-2910	139	9	methodology	methodology	NOUN
cana-2910	139	10	used	use	VERB
cana-2910	139	11	different	different	ADJ
cana-2910	139	12	types	type	NOUN
cana-2910	139	13	of	of	ADP
cana-2910	139	14	support	support	NOUN
cana-2910	139	15	vector	vector	NOUN
cana-2910	139	16	machines	machine	NOUN
cana-2910	139	17	(	(	PUNCT
cana-2910	139	18	svm	svm	PROPN
cana-2910	139	19	)	)	PUNCT
cana-2910	139	20	with	with	ADP
cana-2910	139	21	various	various	ADJ
cana-2910	139	22	kernel	kernel	NOUN
cana-2910	139	23	functions	function	NOUN
cana-2910	139	24	.	.	PUNCT
cana-2910	140	1	svm	svm	PROPN
cana-2910	140	2	is	be	AUX
cana-2910	140	3	a	a	DET
cana-2910	140	4	supervised	supervised	ADJ
cana-2910	140	5	machine	machine	NOUN
cana-2910	140	6	learning	learning	NOUN
cana-2910	140	7	algorithm	algorithm	NOUN
cana-2910	140	8	used	use	VERB
cana-2910	140	9	for	for	ADP
cana-2910	140	10	classification	classification	NOUN
cana-2910	140	11	and	and	CCONJ
cana-2910	140	12	regression	regression	NOUN
cana-2910	140	13	tasks	task	NOUN
cana-2910	140	14	.	.	PUNCT
cana-2910	141	1	the	the	DET
cana-2910	141	2	kernel	kernel	PROPN
cana-2910	141	3	function	function	NOUN
cana-2910	141	4	in	in	ADP
cana-2910	141	5	svm	svm	PROPN
cana-2910	141	6	determines	determine	VERB
cana-2910	141	7	the	the	DET
cana-2910	141	8	type	type	NOUN
cana-2910	141	9	of	of	ADP
cana-2910	141	10	decision	decision	NOUN
cana-2910	141	11	boundary	boundary	ADJ
cana-2910	141	12	that	that	SCONJ
cana-2910	141	13	the	the	DET
cana-2910	141	14	algorithm	algorithm	NOUN
cana-2910	141	15	creates	create	VERB
cana-2910	141	16	to	to	PART
cana-2910	141	17	separate	separate	VERB
cana-2910	141	18	different	different	ADJ
cana-2910	141	19	classes	class	NOUN
cana-2910	141	20	.	.	PUNCT
cana-2910	142	1	in	in	ADP
cana-2910	142	2	this	this	DET
cana-2910	142	3	work	work	NOUN
cana-2910	142	4	gst	gst	PROPN
cana-2910	142	5	data	datum	NOUN
cana-2910	142	6	has	have	AUX
cana-2910	142	7	been	be	AUX
cana-2910	142	8	trained	train	VERB
cana-2910	142	9	and	and	CCONJ
cana-2910	142	10	tested	test	VERB
cana-2910	142	11	06	06	NUM
cana-2910	142	12	different	different	ADJ
cana-2910	142	13	regression	regression	NOUN
cana-2910	142	14	models	model	NOUN
cana-2910	142	15	,	,	PUNCT
cana-2910	142	16	including	include	VERB
cana-2910	142	17	quadratic	quadratic	ADJ
cana-2910	142	18	support	support	NOUN
cana-2910	142	19	vector	vector	NOUN
cana-2910	142	20	machine	machine	NOUN
cana-2910	142	21	(	(	PUNCT
cana-2910	142	22	svm	svm	VERB
cana-2910	142	23	quadratic	quadratic	ADJ
cana-2910	142	24	)	)	PUNCT
cana-2910	142	25	,	,	PUNCT
cana-2910	142	26	coarse	coarse	ADJ
cana-2910	142	27	gaussian	gaussian	ADJ
cana-2910	142	28	process	process	NOUN
cana-2910	142	29	regression	regression	NOUN
cana-2910	142	30	(	(	PUNCT
cana-2910	142	31	gpr	gpr	PROPN
cana-2910	142	32	coarse	coarse	NOUN
cana-2910	142	33	)	)	PUNCT
cana-2910	142	34	,	,	PUNCT
cana-2910	142	35	fine	fine	ADJ
cana-2910	142	36	gaussian	gaussian	ADJ
cana-2910	142	37	support	support	NOUN
cana-2910	142	38	vector	vector	NOUN
cana-2910	142	39	machine	machine	NOUN
cana-2910	142	40	(	(	PUNCT
cana-2910	142	41	svm	svm	PROPN
cana-2910	142	42	fine	fine	PROPN
cana-2910	142	43	gaussian	gaussian	PROPN
cana-2910	142	44	)	)	PUNCT
cana-2910	142	45	,	,	PUNCT
cana-2910	142	46	linear	linear	ADJ
cana-2910	142	47	support	support	NOUN
cana-2910	142	48	vector	vector	NOUN
cana-2910	142	49	machine	machine	NOUN
cana-2910	142	50	(	(	PUNCT
cana-2910	142	51	svm	svm	PROPN
cana-2910	142	52	linear	linear	PROPN
cana-2910	142	53	)	)	PUNCT
cana-2910	142	54	,	,	PUNCT
cana-2910	142	55	and	and	CCONJ
cana-2910	142	56	quadratic	quadratic	ADJ
cana-2910	142	57	support	support	NOUN
cana-2910	142	58	vector	vector	NOUN
cana-2910	142	59	machine	machine	NOUN
cana-2910	142	60	with	with	ADP
cana-2910	142	61	gaussian	gaussian	ADJ
cana-2910	142	62	process	process	NOUN
cana-2910	142	63	regression	regression	NOUN
cana-2910	142	64	(	(	PUNCT
cana-2910	142	65	svm	svm	VERB
cana-2910	142	66	quadratic	quadratic	ADJ
cana-2910	142	67	gpr	gpr	PROPN
cana-2910	142	68	)	)	PUNCT
cana-2910	142	69	.	.	PUNCT
cana-2910	143	1	gst	gst	PROPN
cana-2910	143	2	data	data	PROPN
cana-2910	143	3	comprehensive	comprehensive	ADJ
cana-2910	143	4	analysis	analysis	NOUN
cana-2910	143	5	using	use	VERB
cana-2910	143	6	various	various	ADJ
cana-2910	143	7	machine	machine	NOUN
cana-2910	143	8	learning	learn	VERB
cana-2910	143	9	algorithms	algorithm	NOUN
cana-2910	143	10	.	.	PUNCT
cana-2910	144	1	5	5	X
cana-2910	144	2	.	.	X
cana-2910	144	3	conclusion	conclusion	NOUN
cana-2910	144	4	this	this	DET
cana-2910	144	5	article	article	NOUN
cana-2910	144	6	focuses	focus	VERB
cana-2910	144	7	on	on	ADP
cana-2910	144	8	the	the	DET
cana-2910	144	9	use	use	NOUN
cana-2910	144	10	of	of	ADP
cana-2910	144	11	support	support	NOUN
cana-2910	144	12	vactor	vactor	NOUN
cana-2910	144	13	machine	machine	NOUN
cana-2910	144	14	for	for	ADP
cana-2910	144	15	the	the	DET
cana-2910	144	16	detection	detection	NOUN
cana-2910	144	17	of	of	ADP
cana-2910	144	18	goods	good	NOUN
cana-2910	144	19	and	and	CCONJ
cana-2910	144	20	services	service	NOUN
cana-2910	144	21	tax	tax	NOUN
cana-2910	144	22	(	(	PUNCT
cana-2910	144	23	gst	gst	NOUN
cana-2910	144	24	)	)	PUNCT
cana-2910	144	25	fraud	fraud	NOUN
cana-2910	144	26	at	at	ADP
cana-2910	144	27	the	the	DET
cana-2910	144	28	early	early	ADJ
cana-2910	144	29	stages	stage	NOUN
cana-2910	144	30	.	.	PUNCT
cana-2910	145	1	the	the	DET
cana-2910	145	2	study	study	NOUN
cana-2910	145	3	highlights	highlight	NOUN
cana-2910	145	4	machine	machine	NOUN
cana-2910	145	5	learning	learning	NOUN
cana-2910	145	6	tools	tool	NOUN
cana-2910	145	7	are	be	AUX
cana-2910	145	8	very	very	ADV
cana-2910	145	9	helpful	helpful	ADJ
cana-2910	145	10	for	for	ADP
cana-2910	145	11	the	the	DET
cana-2910	145	12	gst	gst	PROPN
cana-2910	145	13	fraud	fraud	PROPN
cana-2910	145	14	detection	detection	PROPN
cana-2910	145	15	.	.	PUNCT
cana-2910	146	1	by	by	ADP
cana-2910	146	2	employing	employ	VERB
cana-2910	146	3	support	support	NOUN
cana-2910	146	4	vector	vector	NOUN
cana-2910	146	5	machine	machine	NOUN
cana-2910	146	6	performance	performance	NOUN
cana-2910	146	7	of	of	ADP
cana-2910	146	8	various	various	ADJ
cana-2910	146	9	gst	gst	NOUN
cana-2910	146	10	fraud	fraud	NOUN
cana-2910	146	11	metrics	metric	NOUN
cana-2910	146	12	like	like	ADP
cana-2910	146	13	sales	sale	NOUN
cana-2910	146	14	,	,	PUNCT
cana-2910	146	15	purchases	purchase	NOUN
cana-2910	146	16	,	,	PUNCT
cana-2910	146	17	input	input	NOUN
cana-2910	146	18	tax	tax	NOUN
cana-2910	146	19	credit	credit	NOUN
cana-2910	146	20	and	and	CCONJ
cana-2910	146	21	tax	tax	NOUN
cana-2910	146	22	liability	liability	NOUN
cana-2910	146	23	have	have	AUX
cana-2910	146	24	been	be	AUX
cana-2910	146	25	analyzed	analyze	VERB
cana-2910	146	26	and	and	CCONJ
cana-2910	146	27	we	we	PRON
cana-2910	146	28	got	get	VERB
cana-2910	146	29	the	the	DET
cana-2910	146	30	98.5	98.5	NUM
cana-2910	146	31	%	%	NOUN
cana-2910	146	32	accuracy	accuracy	NOUN
cana-2910	146	33	for	for	ADP
cana-2910	146	34	svm	svm	ADJ
cana-2910	146	35	-	-	NOUN
cana-2910	146	36	linear	linear	NOUN
cana-2910	146	37	.	.	PUNCT
cana-2910	147	1	further	further	ADJ
cana-2910	147	2	research	research	NOUN
cana-2910	147	3	can	can	AUX
cana-2910	147	4	be	be	AUX
cana-2910	147	5	carried	carry	VERB
cana-2910	147	6	out	out	ADP
cana-2910	147	7	on	on	ADP
cana-2910	147	8	the	the	DET
cana-2910	147	9	use	use	NOUN
cana-2910	147	10	of	of	ADP
cana-2910	147	11	different	different	ADJ
cana-2910	147	12	machine	machine	NOUN
cana-2910	147	13	learning	learning	NOUN
cana-2910	147	14	tools	tool	NOUN
cana-2910	147	15	for	for	ADP
cana-2910	147	16	anomaly	anomaly	NOUN
cana-2910	147	17	detection	detection	NOUN
cana-2910	147	18	in	in	ADP
cana-2910	147	19	the	the	DET
cana-2910	147	20	gst	gst	NOUN
cana-2910	147	21	fraud	fraud	NOUN
cana-2910	147	22	.	.	PUNCT
cana-2910	148	1	in	in	ADP
cana-2910	148	2	addition	addition	NOUN
cana-2910	148	3	,	,	PUNCT
cana-2910	148	4	integration	integration	NOUN
cana-2910	148	5	of	of	ADP
cana-2910	148	6	machine	machine	NOUN
cana-2910	148	7	learning	learning	NOUN
cana-2910	148	8	tools	tool	NOUN
cana-2910	148	9	can	can	AUX
cana-2910	148	10	be	be	AUX
cana-2910	148	11	explored	explore	VERB
cana-2910	148	12	to	to	PART
cana-2910	148	13	ensure	ensure	VERB
cana-2910	148	14	real	real	ADJ
cana-2910	148	15	time	time	NOUN
cana-2910	148	16	fraud	fraud	NOUN
cana-2910	148	17	detection	detection	NOUN
cana-2910	148	18	by	by	ADP
cana-2910	148	19	the	the	DET
cana-2910	148	20	gst	gst	PROPN
cana-2910	148	21	investigation	investigation	PROPN
cana-2910	148	22	department	department	PROPN
cana-2910	148	23	.	.	PUNCT
cana-2910	149	1	references	reference	NOUN
cana-2910	149	2	[	[	X
cana-2910	149	3	1	1	NUM
cana-2910	149	4	]	]	X
cana-2910	149	5	carrillo	carrillo	PROPN
cana-2910	149	6	,	,	PUNCT
cana-2910	149	7	p.	p.	PROPN
cana-2910	149	8	,	,	PUNCT
cana-2910	149	9	donaldson	donaldson	PROPN
cana-2910	149	10	,	,	PUNCT
cana-2910	149	11	d.	d.	PROPN
cana-2910	149	12	,	,	PUNCT
cana-2910	149	13	pomeranz	pomeranz	PROPN
cana-2910	149	14	,	,	PUNCT
cana-2910	149	15	d.	d.	PROPN
cana-2910	149	16	,	,	PUNCT
cana-2910	149	17	&	&	CCONJ
cana-2910	149	18	singhal	singhal	PROPN
cana-2910	149	19	,	,	PUNCT
cana-2910	149	20	m.	m.	NOUN
cana-2910	149	21	ghosting	ghost	VERB
cana-2910	149	22	the	the	DET
cana-2910	149	23	tax	tax	NOUN
cana-2910	149	24	authority	authority	NOUN
cana-2910	149	25	:	:	PUNCT
cana-2910	149	26	fake	fake	ADJ
cana-2910	149	27	firms	firm	NOUN
cana-2910	149	28	and	and	CCONJ
cana-2910	149	29	tax	tax	NOUN
cana-2910	149	30	fraud	fraud	NOUN
cana-2910	149	31	in	in	ADP
cana-2910	149	32	ecuador	ecuador	PROPN
cana-2910	149	33	(	(	PUNCT
cana-2910	149	34	2022	2022	NUM
cana-2910	149	35	)	)	PUNCT
cana-2910	149	36	.	.	PUNCT
cana-2910	150	1	[	[	X
cana-2910	150	2	2	2	NUM
cana-2910	150	3	]	]	X
cana-2910	150	4	mehta	mehta	PROPN
cana-2910	150	5	,	,	PUNCT
cana-2910	150	6	p.	p.	PROPN
cana-2910	150	7	,	,	PUNCT
cana-2910	150	8	mathews	mathews	PROPN
cana-2910	150	9	,	,	PUNCT
cana-2910	150	10	j.	j.	PROPN
cana-2910	150	11	,	,	PUNCT
cana-2910	150	12	rao	rao	PROPN
cana-2910	150	13	,	,	PUNCT
cana-2910	151	1	s.	s.	PROPN
cana-2910	151	2	k.	k.	PROPN
cana-2910	152	1	v.	v.	PROPN
cana-2910	152	2	,	,	PUNCT
cana-2910	152	3	kumar	kumar	PROPN
cana-2910	152	4	,	,	PUNCT
cana-2910	152	5	k.	k.	PROPN
cana-2910	152	6	s.	s.	PROPN
cana-2910	152	7	,	,	PUNCT
cana-2910	152	8	suryamukhi	suryamukhi	PROPN
cana-2910	152	9	,	,	PUNCT
cana-2910	152	10	k.	k.	PROPN
cana-2910	152	11	,	,	PUNCT
cana-2910	152	12	&	&	CCONJ
cana-2910	152	13	babu	babu	PROPN
cana-2910	152	14	,	,	PUNCT
cana-2910	152	15	c.	c.	PROPN
cana-2910	152	16	s.	s.	PROPN
cana-2910	152	17	identifying	identify	VERB
cana-2910	152	18	malicious	malicious	ADJ
cana-2910	152	19	dealers	dealer	NOUN
cana-2910	152	20	in	in	ADP
cana-2910	152	21	goods	good	NOUN
cana-2910	152	22	and	and	CCONJ
cana-2910	152	23	services	service	NOUN
cana-2910	152	24	tax	tax	NOUN
cana-2910	152	25	.	.	PUNCT
cana-2910	153	1	in	in	ADP
cana-2910	153	2	2019	2019	NUM
cana-2910	153	3	ieee	ieee	NOUN
cana-2910	153	4	4th	4th	ADJ
cana-2910	153	5	international	international	ADJ
cana-2910	153	6	conference	conference	NOUN
cana-2910	153	7	on	on	ADP
cana-2910	153	8	big	big	ADJ
cana-2910	153	9	data	datum	NOUN
cana-2910	153	10	analytics	analytic	NOUN
cana-2910	153	11	(	(	PUNCT
cana-2910	153	12	icbda	icbda	NOUN
cana-2910	153	13	)	)	PUNCT
cana-2910	153	14	(	(	PUNCT
cana-2910	153	15	pp	pp	ADP
cana-2910	153	16	.	.	PUNCT
cana-2910	153	17	312316	312316	NUM
cana-2910	153	18	)	)	PUNCT
cana-2910	153	19	.	.	PUNCT
cana-2910	154	1	ieee	ieee	PROPN
cana-2910	154	2	.	.	PUNCT
cana-2910	155	1	(	(	PUNCT
cana-2910	155	2	2019	2019	NUM
cana-2910	155	3	,	,	PUNCT
cana-2910	155	4	march	march	PROPN
cana-2910	155	5	)	)	PUNCT
cana-2910	155	6	.	.	PUNCT
cana-2910	156	1	[	[	X
cana-2910	156	2	3	3	X
cana-2910	156	3	]	]	X
cana-2910	156	4	mehta	mehta	PROPN
cana-2910	156	5	,	,	PUNCT
cana-2910	156	6	p.	p.	PROPN
cana-2910	156	7	,	,	PUNCT
cana-2910	156	8	mathews	mathews	PROPN
cana-2910	156	9	,	,	PUNCT
cana-2910	156	10	j.	j.	PROPN
cana-2910	156	11	,	,	PUNCT
cana-2910	156	12	kumar	kumar	PROPN
cana-2910	156	13	,	,	PUNCT
cana-2910	156	14	s.	s.	PROPN
cana-2910	156	15	,	,	PUNCT
cana-2910	156	16	suryamukhi	suryamukhi	PROPN
cana-2910	156	17	,	,	PUNCT
cana-2910	156	18	k.	k.	PROPN
cana-2910	156	19	,	,	PUNCT
cana-2910	156	20	sobhan	sobhan	PROPN
cana-2910	156	21	babu	babu	PROPN
cana-2910	156	22	,	,	PUNCT
cana-2910	156	23	ch	ch	PROPN
cana-2910	156	24	.	.	PROPN
cana-2910	156	25	,	,	PUNCT
cana-2910	156	26	&	&	CCONJ
cana-2910	156	27	kasi	kasi	PROPN
cana-2910	156	28	visweswara	visweswara	PROPN
cana-2910	156	29	rao	rao	PROPN
cana-2910	156	30	,	,	PUNCT
cana-2910	156	31	s.	s.	PROPN
cana-2910	156	32	v.	v.	ADP
cana-2910	156	33	big	big	ADJ
cana-2910	156	34	data	datum	NOUN
cana-2910	156	35	analytics	analytic	NOUN
cana-2910	156	36	for	for	ADP
cana-2910	156	37	nabbing	nab	VERB
cana-2910	156	38	fraudulent	fraudulent	ADJ
cana-2910	156	39	transactions	transaction	NOUN
cana-2910	156	40	in	in	ADP
cana-2910	156	41	taxation	taxation	NOUN
cana-2910	156	42	system	system	NOUN
cana-2910	156	43	.	.	PUNCT
cana-2910	157	1	lecture	lecture	NOUN
cana-2910	157	2	notes	note	NOUN
cana-2910	157	3	in	in	ADP
cana-2910	157	4	computer	computer	NOUN
cana-2910	157	5	science	science	NOUN
cana-2910	157	6	,	,	PUNCT
cana-2910	157	7	95–109	95–109	PROPN
cana-2910	157	8	.	.	PUNCT
cana-2910	157	9	(	(	PUNCT
cana-2910	157	10	2019	2019	NUM
cana-2910	157	11	)	)	PUNCT
cana-2910	157	12	.	.	PUNCT
cana-2910	158	1	[	[	X
cana-2910	158	2	4	4	NUM
cana-2910	158	3	]	]	X
cana-2910	158	4	othman	othman	PROPN
cana-2910	158	5	,	,	PUNCT
cana-2910	158	6	z.	z.	PROPN
cana-2910	158	7	,	,	PUNCT
cana-2910	158	8	nordin	nordin	PROPN
cana-2910	158	9	,	,	PUNCT
cana-2910	158	10	f.f	f.f	PROPN
cana-2910	158	11	.	.	PROPN
cana-2910	158	12	,	,	PUNCT
cana-2910	158	13	bidin	bidin	PROPN
cana-2910	158	14	,	,	PUNCT
cana-2910	158	15	z.	z.	PROPN
cana-2910	158	16	and	and	CCONJ
cana-2910	158	17	mansor	mansor	PROPN
cana-2910	158	18	,	,	PUNCT
cana-2910	158	19	m.	m.	NOUN
cana-2910	158	20	“	"	PUNCT
cana-2910	158	21	gst	gst	NOUN
cana-2910	158	22	fraud	fraud	NOUN
cana-2910	158	23	:	:	PUNCT
cana-2910	158	24	unveiling	unveil	VERB
cana-2910	158	25	the	the	DET
cana-2910	158	26	truth	truth	NOUN
cana-2910	158	27	”	"	PUNCT
cana-2910	158	28	,	,	PUNCT
cana-2910	158	29	international	international	ADJ
cana-2910	158	30	journal	journal	NOUN
cana-2910	158	31	of	of	ADP
cana-2910	158	32	supply	supply	NOUN
cana-2910	158	33	chain	chain	NOUN
cana-2910	158	34	management	management	NOUN
cana-2910	158	35	,	,	PUNCT
cana-2910	158	36	vol	vol	NOUN
cana-2910	158	37	.	.	PROPN
cana-2910	158	38	8	8	NUM
cana-2910	159	1	no	no	NOUN
cana-2910	159	2	.	.	NOUN
cana-2910	159	3	1	1	NUM
cana-2910	159	4	,	,	PUNCT
cana-2910	159	5	pp	pp	ADJ
cana-2910	159	6	.	.	PUNCT
cana-2910	160	1	941	941	NUM
cana-2910	160	2	-	-	SYM
cana-2910	160	3	950	950	NUM
cana-2910	160	4	.	.	PUNCT
cana-2910	161	1	(	(	PUNCT
cana-2910	161	2	2019	2019	NUM
cana-2910	161	3	)	)	PUNCT
cana-2910	161	4	,	,	PUNCT
cana-2910	162	1	[	[	X
cana-2910	162	2	5	5	NUM
cana-2910	162	3	]	]	X
cana-2910	162	4	halbouni	halbouni	ADJ
cana-2910	162	5	,	,	PUNCT
cana-2910	162	6	s.s	s.s	PROPN
cana-2910	162	7	.	.	PROPN
cana-2910	162	8	,	,	PUNCT
cana-2910	162	9	obeid	obeid	PROPN
cana-2910	162	10	,	,	PUNCT
cana-2910	162	11	n.	n.	NOUN
cana-2910	162	12	and	and	CCONJ
cana-2910	162	13	garbou	garbou	PROPN
cana-2910	162	14	,	,	PUNCT
cana-2910	162	15	a.	a.	NOUN
cana-2910	162	16	“	"	PUNCT
cana-2910	162	17	corporate	corporate	ADJ
cana-2910	162	18	governance	governance	NOUN
cana-2910	162	19	and	and	CCONJ
cana-2910	162	20	information	information	NOUN
cana-2910	162	21	technology	technology	NOUN
cana-2910	162	22	in	in	ADP
cana-2910	162	23	fraud	fraud	NOUN
cana-2910	162	24	prevention	prevention	NOUN
cana-2910	162	25	and	and	CCONJ
cana-2910	162	26	detection	detection	NOUN
cana-2910	162	27	evidence	evidence	NOUN
cana-2910	162	28	from	from	ADP
cana-2910	162	29	the	the	DET
cana-2910	162	30	uae	uae	PROPN
cana-2910	162	31	”	"	PUNCT
cana-2910	162	32	,	,	PUNCT
cana-2910	162	33	managerial	managerial	ADJ
cana-2910	162	34	auditing	auditing	NOUN
cana-2910	162	35	journal	journal	NOUN
cana-2910	162	36	,	,	PUNCT
cana-2910	162	37	vol	vol	NOUN
cana-2910	162	38	.	.	PROPN
cana-2910	163	1	31	31	NUM
cana-2910	163	2	no	no	NOUN
cana-2910	163	3	.	.	NOUN
cana-2910	164	1	6	6	NUM
cana-2910	164	2	-	-	SYM
cana-2910	164	3	7	7	NUM
cana-2910	164	4	,	,	PUNCT
cana-2910	164	5	pp	pp	ADJ
cana-2910	164	6	.	.	PUNCT
cana-2910	165	1	589	589	NUM
cana-2910	165	2	-	-	SYM
cana-2910	165	3	628	628	NUM
cana-2910	165	4	(	(	PUNCT
cana-2910	165	5	2016	2016	NUM
cana-2910	165	6	)	)	PUNCT
cana-2910	165	7	.	.	PUNCT
cana-2910	166	1	[	[	X
cana-2910	166	2	6	6	NUM
cana-2910	166	3	]	]	X
cana-2910	166	4	sen	sen	PROPN
cana-2910	166	5	,	,	PUNCT
cana-2910	166	6	p.c	p.c	PROPN
cana-2910	166	7	.	.	PROPN
cana-2910	166	8	,	,	PUNCT
cana-2910	166	9	hajra	hajra	PROPN
cana-2910	166	10	,	,	PUNCT
cana-2910	166	11	m.	m.	NOUN
cana-2910	166	12	,	,	PUNCT
cana-2910	166	13	ghosh	ghosh	PROPN
cana-2910	166	14	,	,	PUNCT
cana-2910	166	15	m.	m.	NOUN
cana-2910	166	16	supervised	supervise	VERB
cana-2910	166	17	classification	classification	NOUN
cana-2910	166	18	algorithms	algorithm	NOUN
cana-2910	166	19	in	in	ADP
cana-2910	166	20	machine	machine	NOUN
cana-2910	166	21	learning	learning	NOUN
cana-2910	166	22	:	:	PUNCT
cana-2910	166	23	a	a	DET
cana-2910	166	24	survey	survey	NOUN
cana-2910	166	25	and	and	CCONJ
cana-2910	166	26	review	review	NOUN
cana-2910	166	27	.	.	PUNCT
cana-2910	167	1	in	in	ADP
cana-2910	167	2	:	:	PUNCT
cana-2910	167	3	mandal	mandal	PROPN
cana-2910	167	4	,	,	PUNCT
cana-2910	167	5	j.	j.	PROPN
cana-2910	167	6	,	,	PUNCT
cana-2910	167	7	bhattacharya	bhattacharya	PROPN
cana-2910	167	8	,	,	PUNCT
cana-2910	167	9	d.	d.	PROPN
cana-2910	167	10	(	(	PUNCT
cana-2910	167	11	eds	eds	PROPN
cana-2910	167	12	)	)	PUNCT
cana-2910	167	13	emerging	emerge	VERB
cana-2910	167	14	technology	technology	NOUN
cana-2910	167	15	in	in	ADP
cana-2910	167	16	modelling	modelling	NOUN
cana-2910	167	17	and	and	CCONJ
cana-2910	167	18	graphics	graphic	NOUN
cana-2910	167	19	.	.	PUNCT
cana-2910	168	1	advances	advance	NOUN
cana-2910	168	2	in	in	ADP
cana-2910	168	3	intelligent	intelligent	ADJ
cana-2910	168	4	systems	system	NOUN
cana-2910	168	5	and	and	CCONJ
cana-2910	168	6	computing	computing	NOUN
cana-2910	168	7	,	,	PUNCT
cana-2910	168	8	vol	vol	NOUN
cana-2910	168	9	937	937	NUM
cana-2910	168	10	.	.	PUNCT
cana-2910	169	1	springer	springer	NOUN
cana-2910	169	2	,	,	PUNCT
cana-2910	169	3	singapore	singapore	PROPN
cana-2910	169	4	(	(	PUNCT
cana-2910	169	5	2020	2020	NUM
cana-2910	169	6	)	)	PUNCT
cana-2910	169	7	.	.	PUNCT
cana-2910	170	1	[	[	X
cana-2910	170	2	7	7	NUM
cana-2910	170	3	]	]	X
cana-2910	170	4	zhou	zhou	PROPN
cana-2910	170	5	,	,	PUNCT
cana-2910	170	6	j.	j.	PROPN
cana-2910	170	7	,	,	PUNCT
cana-2910	170	8	tian	tian	PROPN
cana-2910	170	9	,	,	PUNCT
cana-2910	170	10	y.	y.	PROPN
cana-2910	170	11	,	,	PUNCT
cana-2910	170	12	luo	luo	PROPN
cana-2910	170	13	,	,	PUNCT
cana-2910	170	14	j.	j.	PROPN
cana-2910	170	15	et	et	PROPN
cana-2910	170	16	al	al	PROPN
cana-2910	170	17	.	.	PROPN
cana-2910	170	18	novel	novel	PROPN
cana-2910	170	19	non	non	ADJ
cana-2910	170	20	-	-	ADJ
cana-2910	170	21	kernel	kernel	ADJ
cana-2910	170	22	quadratic	quadratic	ADJ
cana-2910	170	23	surface	surface	NOUN
cana-2910	170	24	support	support	NOUN
cana-2910	170	25	vector	vector	NOUN
cana-2910	170	26	machines	machine	NOUN
cana-2910	170	27	based	base	VERB
cana-2910	170	28	on	on	ADP
cana-2910	170	29	optimal	optimal	ADJ
cana-2910	170	30	margin	margin	NOUN
cana-2910	170	31	distribution	distribution	NOUN
cana-2910	170	32	.	.	PUNCT
cana-2910	171	1	soft	soft	ADJ
cana-2910	171	2	comput	comput	NOUN
cana-2910	171	3	26	26	NUM
cana-2910	171	4	,	,	PUNCT
cana-2910	171	5	9215–9227	9215–9227	NUM
cana-2910	171	6	(	(	PUNCT
cana-2910	171	7	2022	2022	NUM
cana-2910	171	8	)	)	PUNCT
cana-2910	171	9	.	.	PUNCT
cana-2910	172	1	[	[	X
cana-2910	172	2	8	8	X
cana-2910	172	3	]	]	X
cana-2910	172	4	bhoopesh	bhoopesh	PROPN
cana-2910	172	5	singh	singh	PROPN
cana-2910	172	6	bhati	bhati	PROPN
cana-2910	172	7	and	and	CCONJ
cana-2910	172	8	c.s	c.s	PROPN
cana-2910	172	9	.	.	PROPN
cana-2910	172	10	rai	rai	PROPN
cana-2910	172	11	,	,	PUNCT
cana-2910	172	12	intrusion	intrusion	NOUN
cana-2910	172	13	detection	detection	NOUN
cana-2910	172	14	technique	technique	NOUN
cana-2910	172	15	using	use	VERB
cana-2910	172	16	coarse	coarse	ADJ
cana-2910	172	17	gaussian	gaussian	ADJ
cana-2910	172	18	svm	svm	PROPN
cana-2910	172	19	,	,	PUNCT
cana-2910	172	20	international	international	ADJ
cana-2910	172	21	journal	journal	NOUN
cana-2910	172	22	of	of	ADP
cana-2910	172	23	grid	grid	NOUN
cana-2910	172	24	and	and	CCONJ
cana-2910	172	25	utility	utility	NOUN
cana-2910	172	26	computing	computing	NOUN
cana-2910	172	27	vol	vol	NOUN
cana-2910	172	28	.	.	PROPN
cana-2910	172	29	12	12	NUM
cana-2910	172	30	,	,	PUNCT
cana-2910	172	31	issue	issue	NOUN
cana-2910	172	32	.	.	PUNCT
cana-2910	173	1	1	1	NUM
cana-2910	173	2	,	,	PUNCT
cana-2910	173	3	2021	2021	NUM
cana-2910	173	4	[	[	X
cana-2910	173	5	9	9	NUM
cana-2910	173	6	]	]	X
cana-2910	173	7	u.	u.	PROPN
cana-2910	173	8	jain	jain	PROPN
cana-2910	173	9	,	,	PUNCT
cana-2910	173	10	k.	k.	PROPN
cana-2910	173	11	nathani	nathani	PROPN
cana-2910	173	12	,	,	PUNCT
cana-2910	173	13	n.	n.	PROPN
cana-2910	173	14	ruban	ruban	PROPN
cana-2910	173	15	,	,	PUNCT
cana-2910	173	16	a.	a.	PROPN
cana-2910	173	17	n.	n.	PROPN
cana-2910	173	18	joseph	joseph	PROPN
cana-2910	173	19	raj	raj	PROPN
cana-2910	173	20	,	,	PUNCT
cana-2910	173	21	z.	z.	PROPN
cana-2910	173	22	zhuang	zhuang	PROPN
cana-2910	173	23	and	and	CCONJ
cana-2910	173	24	v.	v.	PROPN
cana-2910	173	25	g.v	g.v	PROPN
cana-2910	173	26	.	.	PROPN
cana-2910	173	27	mahesh	mahesh	PROPN
cana-2910	173	28	,	,	PUNCT
cana-2910	173	29	"	"	PUNCT
cana-2910	173	30	cubic	cubic	ADJ
cana-2910	173	31	svm	svm	NOUN
cana-2910	173	32	classifier	classifier	NOUN
cana-2910	173	33	based	base	VERB
cana-2910	173	34	feature	feature	NOUN
cana-2910	173	35	extraction	extraction	NOUN
cana-2910	173	36	and	and	CCONJ
cana-2910	173	37	emotion	emotion	NOUN
cana-2910	173	38	detection	detection	NOUN
cana-2910	173	39	from	from	ADP
cana-2910	173	40	speech	speech	NOUN
cana-2910	173	41	signals	signal	NOUN
cana-2910	173	42	,	,	PUNCT
cana-2910	173	43	"	"	PUNCT
cana-2910	173	44	2018	2018	NUM
cana-2910	173	45	international	international	ADJ
cana-2910	173	46	conference	conference	NOUN
cana-2910	173	47	on	on	ADP
cana-2910	173	48	sensor	sensor	NOUN
cana-2910	173	49	networks	network	NOUN
cana-2910	173	50	and	and	CCONJ
cana-2910	173	51	signal	signal	NOUN
cana-2910	173	52	processing	processing	NOUN
cana-2910	173	53	(	(	PUNCT
cana-2910	173	54	snsp	snsp	PROPN
cana-2910	173	55	)	)	PUNCT
cana-2910	173	56	,	,	PUNCT
cana-2910	173	57	xi'an	xi'an	PROPN
cana-2910	173	58	,	,	PUNCT
cana-2910	173	59	china	china	PROPN
cana-2910	173	60	,	,	PUNCT
cana-2910	173	61	pp	pp	PROPN
cana-2910	173	62	.	.	PUNCT
cana-2910	174	1	386	386	NUM
cana-2910	174	2	-	-	SYM
cana-2910	174	3	391	391	NUM
cana-2910	174	4	,	,	PUNCT
cana-2910	174	5	2018	2018	NUM
cana-2910	174	6	.	.	PUNCT
cana-2910	175	1	[	[	X
cana-2910	175	2	10	10	NUM
cana-2910	175	3	]	]	X
cana-2910	175	4	omar	omar	PROPN
cana-2910	175	5	chamorro	chamorro	PROPN
cana-2910	175	6	-	-	PUNCT
cana-2910	175	7	atalaya	atalaya	PROPN
cana-2910	175	8	,	,	PUNCT
cana-2910	175	9	dora	dora	PROPN
cana-2910	175	10	arce	arce	PROPN
cana-2910	175	11	-	-	PUNCT
cana-2910	175	12	santillan	santillan	PROPN
cana-2910	175	13	,	,	PUNCT
cana-2910	175	14	guillermo	guillermo	PROPN
cana-2910	175	15	morales	morales	PROPN
cana-2910	175	16	-	-	PUNCT
cana-2910	175	17	romero	romero	PROPN
cana-2910	175	18	,	,	PUNCT
cana-2910	175	19	césar	césar	PROPN
cana-2910	175	20	león	león	PROPN
cana-2910	175	21	-	-	PUNCT
cana-2910	175	22	velarde	velarde	PROPN
cana-2910	175	23	,	,	PUNCT
cana-2910	175	24	primitiva	primitiva	PROPN
cana-2910	175	25	ramossalaza	ramossalaza	PROPN
cana-2910	175	26	,	,	PUNCT
cana-2910	175	27	elizabeth	elizabeth	PROPN
cana-2910	175	28	auqui	auqui	PROPN
cana-2910	175	29	-	-	PUNCT
cana-2910	175	30	ramos	ramos	PROPN
cana-2910	175	31	,	,	PUNCT
cana-2910	175	32	miguel	miguel	PROPN
cana-2910	175	33	levano	levano	PROPN
cana-2910	175	34	-	-	PUNCT
cana-2910	175	35	stella	stella	NOUN
cana-2910	175	36	,	,	PUNCT
cana-2910	175	37	sentiment	sentiment	NOUN
cana-2910	175	38	analysis	analysis	NOUN
cana-2910	175	39	through	through	ADP
cana-2910	175	40	twitter	twitter	NOUN
cana-2910	175	41	as	as	ADP
cana-2910	175	42	a	a	DET
cana-2910	175	43	mechanism	mechanism	NOUN
cana-2910	175	44	for	for	ADP
cana-2910	175	45	assessing	assess	VERB
cana-2910	175	46	university	university	NOUN
cana-2910	175	47	satisfaction	satisfaction	NOUN
cana-2910	175	48	,	,	PUNCT
cana-2910	175	49	vol	vol	NOUN
cana-2910	175	50	.	.	PROPN
cana-2910	175	51	28	28	NUM
cana-2910	175	52	,	,	PUNCT
cana-2910	175	53	no	no	INTJ
cana-2910	175	54	.	.	NOUN
cana-2910	175	55	1	1	NUM
cana-2910	175	56	,	,	PUNCT
cana-2910	175	57	pp	pp	ADJ
cana-2910	175	58	.	.	PUNCT
cana-2910	176	1	516~524	516~524	NUM
cana-2910	176	2	,	,	PUNCT
cana-2910	176	3	issn	issn	PROPN
cana-2910	176	4	:	:	PUNCT
cana-2910	176	5	2502	2502	NUM
cana-2910	176	6	-	-	SYM
cana-2910	176	7	4752	4752	NUM
cana-2910	176	8	,	,	PUNCT
cana-2910	176	9	october	october	PROPN
cana-2910	176	10	2022	2022	NUM
cana-2910	177	1	[	[	X
cana-2910	177	2	11	11	NUM
cana-2910	177	3	]	]	PUNCT
cana-2910	177	4	s.	s.	PROPN
cana-2910	177	5	ghosh	ghosh	PROPN
cana-2910	177	6	,	,	PUNCT
cana-2910	177	7	a.	a.	PROPN
cana-2910	177	8	dasgupta	dasgupta	PROPN
cana-2910	177	9	and	and	CCONJ
cana-2910	177	10	a.	a.	NOUN
cana-2910	177	11	swetapadma	swetapadma	NOUN
cana-2910	177	12	,	,	PUNCT
cana-2910	177	13	"	"	PUNCT
cana-2910	177	14	a	a	DET
cana-2910	177	15	study	study	NOUN
cana-2910	177	16	on	on	ADP
cana-2910	177	17	support	support	NOUN
cana-2910	177	18	vector	vector	NOUN
cana-2910	177	19	machine	machine	NOUN
cana-2910	177	20	based	base	VERB
cana-2910	177	21	linear	linear	PROPN
cana-2910	177	22	and	and	CCONJ
cana-2910	177	23	non	non	ADJ
cana-2910	177	24	-	-	ADJ
cana-2910	177	25	linear	linear	ADJ
cana-2910	177	26	pattern	pattern	NOUN
cana-2910	177	27	classification	classification	NOUN
cana-2910	177	28	,	,	PUNCT
cana-2910	177	29	"	"	PUNCT
cana-2910	177	30	2019	2019	NUM
cana-2910	177	31	international	international	ADJ
cana-2910	177	32	conference	conference	NOUN
cana-2910	177	33	on	on	ADP
cana-2910	177	34	intelligent	intelligent	ADJ
cana-2910	177	35	sustainable	sustainable	ADJ
cana-2910	177	36	systems	system	NOUN
cana-2910	177	37	(	(	PUNCT
cana-2910	177	38	iciss	iciss	ADJ
cana-2910	177	39	)	)	PUNCT
cana-2910	177	40	,	,	PUNCT
cana-2910	177	41	palladam	palladam	PROPN
cana-2910	177	42	,	,	PUNCT
cana-2910	177	43	india	india	PROPN
cana-2910	177	44	,	,	PUNCT
cana-2910	177	45	pp	pp	ADJ
cana-2910	177	46	.	.	PUNCT
cana-2910	178	1	24	24	NUM
cana-2910	178	2	-	-	SYM
cana-2910	178	3	28	28	NUM
cana-2910	178	4	,	,	PUNCT
cana-2910	178	5	2019	2019	NUM
cana-2910	178	6	.	.	PUNCT
cana-2910	179	1	[	[	X
cana-2910	179	2	12	12	NUM
cana-2910	179	3	]	]	X
cana-2910	179	4	tao	tao	PROPN
cana-2910	179	5	wang	wang	PROPN
cana-2910	179	6	,	,	PUNCT
cana-2910	179	7	chia	chia	PROPN
cana-2910	179	8	-	-	PUNCT
cana-2910	179	9	hung	hung	PROPN
cana-2910	179	10	su	su	PROPN
cana-2910	179	11	,	,	PUNCT
cana-2910	179	12	medium	medium	ADJ
cana-2910	179	13	gaussian	gaussian	ADJ
cana-2910	179	14	svm	svm	NOUN
cana-2910	179	15	,	,	PUNCT
cana-2910	179	16	wide	wide	ADJ
cana-2910	179	17	neural	neural	ADJ
cana-2910	179	18	network	network	NOUN
cana-2910	179	19	and	and	CCONJ
cana-2910	179	20	stepwise	stepwise	ADJ
cana-2910	179	21	linear	linear	PROPN
cana-2910	179	22	method	method	NOUN
cana-2910	179	23	in	in	ADP
cana-2910	179	24	estimation	estimation	NOUN
cana-2910	179	25	of	of	ADP
cana-2910	179	26	lornoxicam	lornoxicam	NOUN
cana-2910	179	27	pharmaceutical	pharmaceutical	NOUN
cana-2910	179	28	solubility	solubility	NOUN
cana-2910	179	29	in	in	ADP
cana-2910	179	30	supercritical	supercritical	ADJ
cana-2910	179	31	solvent	solvent	NOUN
cana-2910	179	32	,	,	PUNCT
cana-2910	179	33	journal	journal	NOUN
cana-2910	179	34	of	of	ADP
cana-2910	179	35	molecular	molecular	ADJ
cana-2910	179	36	liquids	liquid	NOUN
cana-2910	179	37	,	,	PUNCT
cana-2910	179	38	volume	volume	NOUN
cana-2910	179	39	349	349	NUM
cana-2910	179	40	untitled	untitled	ADJ