id	sid	tid	token	lemma	pos
fbem-31093	1	1	frontiers	frontier	NOUN
fbem-31093	1	2	in	in	ADP
fbem-31093	1	3	business	business	NOUN
fbem-31093	1	4	,	,	PUNCT
fbem-31093	1	5	economics	economic	NOUN
fbem-31093	1	6	and	and	CCONJ
fbem-31093	1	7	management	management	NOUN
fbem-31093	1	8	issn	issn	PROPN
fbem-31093	1	9	:	:	PUNCT
fbem-31093	1	10	2766	2766	NUM
fbem-31093	1	11	-	-	PUNCT
fbem-31093	1	12	824x	824x	NUM
fbem-31093	1	13	|	|	ADJ
fbem-31093	1	14	vol	vol	NOUN
fbem-31093	1	15	.	.	PROPN
fbem-31093	2	1	19	19	NUM
fbem-31093	2	2	,	,	PUNCT
fbem-31093	2	3	no	no	INTJ
fbem-31093	2	4	.	.	NOUN
fbem-31093	2	5	3	3	NUM
fbem-31093	2	6	,	,	PUNCT
fbem-31093	2	7	2025	2025	NUM
fbem-31093	2	8	121	121	NUM
fbem-31093	2	9	finguard	finguard	NOUN
fbem-31093	2	10	-	-	PUNCT
fbem-31093	2	11	gnn	gnn	NOUN
fbem-31093	2	12	:	:	PUNCT
fbem-31093	2	13	dynamic	dynamic	ADJ
fbem-31093	2	14	graph	graph	NOUN
fbem-31093	2	15	neural	neural	ADJ
fbem-31093	2	16	network	network	NOUN
fbem-31093	2	17	framework	framework	NOUN
fbem-31093	2	18	for	for	ADP
fbem-31093	2	19	financial	financial	ADJ
fbem-31093	2	20	fraud	fraud	NOUN
fbem-31093	2	21	detection	detection	NOUN
fbem-31093	2	22	ruijie	ruijie	PROPN
fbem-31093	2	23	huang	huang	PROPN
fbem-31093	2	24	school	school	PROPN
fbem-31093	2	25	of	of	ADP
fbem-31093	2	26	science	science	NOUN
fbem-31093	2	27	and	and	CCONJ
fbem-31093	2	28	technology	technology	NOUN
fbem-31093	2	29	,	,	PUNCT
fbem-31093	2	30	beijing	beijing	PROPN
fbem-31093	2	31	normal	normal	ADJ
fbem-31093	2	32	-	-	PUNCT
fbem-31093	2	33	hong	hong	PROPN
fbem-31093	2	34	kong	kong	PROPN
fbem-31093	2	35	baptist	baptist	PROPN
fbem-31093	2	36	university	university	PROPN
fbem-31093	2	37	,	,	PUNCT
fbem-31093	2	38	zhuhai	zhuhai	PROPN
fbem-31093	2	39	,	,	PUNCT
fbem-31093	2	40	guangdong	guangdong	PROPN
fbem-31093	2	41	,	,	PUNCT
fbem-31093	2	42	china	china	PROPN
fbem-31093	2	43	abstract	abstract	PROPN
fbem-31093	2	44	:	:	PUNCT
fbem-31093	2	45	with	with	ADP
fbem-31093	2	46	the	the	DET
fbem-31093	2	47	significant	significant	ADJ
fbem-31093	2	48	increase	increase	NOUN
fbem-31093	2	49	in	in	ADP
fbem-31093	2	50	financial	financial	ADJ
fbem-31093	2	51	fraud	fraud	NOUN
fbem-31093	2	52	incidents	incident	NOUN
fbem-31093	2	53	,	,	PUNCT
fbem-31093	2	54	financial	financial	ADJ
fbem-31093	2	55	fraud	fraud	NOUN
fbem-31093	2	56	detection	detection	NOUN
fbem-31093	2	57	has	have	AUX
fbem-31093	2	58	become	become	VERB
fbem-31093	2	59	a	a	DET
fbem-31093	2	60	critical	critical	ADJ
fbem-31093	2	61	research	research	NOUN
fbem-31093	2	62	area	area	NOUN
fbem-31093	2	63	.	.	PUNCT
fbem-31093	3	1	complex	complex	ADJ
fbem-31093	3	2	financial	financial	ADJ
fbem-31093	3	3	relationship	relationship	NOUN
fbem-31093	3	4	networks	network	NOUN
fbem-31093	3	5	involving	involve	VERB
fbem-31093	3	6	thousands	thousand	NOUN
fbem-31093	3	7	or	or	CCONJ
fbem-31093	3	8	even	even	ADV
fbem-31093	3	9	millions	million	NOUN
fbem-31093	3	10	of	of	ADP
fbem-31093	3	11	nodes	node	NOUN
fbem-31093	3	12	present	present	ADJ
fbem-31093	3	13	enormous	enormous	ADJ
fbem-31093	3	14	challenges	challenge	NOUN
fbem-31093	3	15	for	for	ADP
fbem-31093	3	16	fraud	fraud	NOUN
fbem-31093	3	17	detection	detection	NOUN
fbem-31093	3	18	tasks	task	NOUN
fbem-31093	3	19	.	.	PUNCT
fbem-31093	4	1	although	although	SCONJ
fbem-31093	4	2	researchers	researcher	NOUN
fbem-31093	4	3	have	have	AUX
fbem-31093	4	4	developed	develop	VERB
fbem-31093	4	5	various	various	ADJ
fbem-31093	4	6	graph	graph	NOUN
fbem-31093	4	7	-	-	PUNCT
fbem-31093	4	8	based	base	VERB
fbem-31093	4	9	methods	method	NOUN
fbem-31093	4	10	to	to	PART
fbem-31093	4	11	detect	detect	VERB
fbem-31093	4	12	fraudulent	fraudulent	ADJ
fbem-31093	4	13	behavior	behavior	NOUN
fbem-31093	4	14	within	within	ADP
fbem-31093	4	15	these	these	DET
fbem-31093	4	16	complex	complex	ADJ
fbem-31093	4	17	networks	network	NOUN
fbem-31093	4	18	,	,	PUNCT
fbem-31093	4	19	existing	exist	VERB
fbem-31093	4	20	approaches	approach	NOUN
fbem-31093	4	21	overlook	overlook	VERB
fbem-31093	4	22	two	two	NUM
fbem-31093	4	23	key	key	ADJ
fbem-31093	4	24	issues	issue	NOUN
fbem-31093	4	25	in	in	ADP
fbem-31093	4	26	fraud	fraud	NOUN
fbem-31093	4	27	graphs	graph	NOUN
fbem-31093	4	28	:	:	PUNCT
fbem-31093	4	29	the	the	DET
fbem-31093	4	30	diversity	diversity	NOUN
fbem-31093	4	31	of	of	ADP
fbem-31093	4	32	non	non	ADJ
fbem-31093	4	33	-	-	ADJ
fbem-31093	4	34	additive	additive	ADJ
fbem-31093	4	35	attributes	attribute	NOUN
fbem-31093	4	36	and	and	CCONJ
fbem-31093	4	37	the	the	DET
fbem-31093	4	38	distinguishability	distinguishability	NOUN
fbem-31093	4	39	of	of	ADP
fbem-31093	4	40	grouped	group	VERB
fbem-31093	4	41	message	message	NOUN
fbem-31093	4	42	passing	pass	VERB
fbem-31093	4	43	from	from	ADP
fbem-31093	4	44	neighboring	neighboring	NOUN
fbem-31093	4	45	nodes	node	NOUN
fbem-31093	4	46	.	.	PUNCT
fbem-31093	5	1	this	this	DET
fbem-31093	5	2	paper	paper	NOUN
fbem-31093	5	3	proposes	propose	VERB
fbem-31093	5	4	finguard	finguard	NOUN
fbem-31093	5	5	-	-	PUNCT
fbem-31093	5	6	gnn	gnn	NOUN
fbem-31093	5	7	(	(	PUNCT
fbem-31093	5	8	financial	financial	ADJ
fbem-31093	5	9	guardian	guardian	NOUN
fbem-31093	5	10	graph	graph	NOUN
fbem-31093	5	11	neural	neural	ADJ
fbem-31093	5	12	network	network	NOUN
fbem-31093	5	13	)	)	PUNCT
fbem-31093	5	14	,	,	PUNCT
fbem-31093	5	15	a	a	DET
fbem-31093	5	16	novel	novel	ADJ
fbem-31093	5	17	dynamic	dynamic	ADJ
fbem-31093	5	18	graph	graph	NOUN
fbem-31093	5	19	neural	neural	ADJ
fbem-31093	5	20	network	network	NOUN
fbem-31093	5	21	for	for	ADP
fbem-31093	5	22	financial	financial	ADJ
fbem-31093	5	23	fraud	fraud	NOUN
fbem-31093	5	24	detection	detection	NOUN
fbem-31093	5	25	that	that	PRON
fbem-31093	5	26	addresses	address	VERB
fbem-31093	5	27	the	the	DET
fbem-31093	5	28	aforementioned	aforementioned	ADJ
fbem-31093	5	29	issues	issue	NOUN
fbem-31093	5	30	through	through	ADP
fbem-31093	5	31	innovative	innovative	ADJ
fbem-31093	5	32	feature	feature	NOUN
fbem-31093	5	33	transformation	transformation	NOUN
fbem-31093	5	34	strategies	strategy	NOUN
fbem-31093	5	35	and	and	CCONJ
fbem-31093	5	36	a	a	DET
fbem-31093	5	37	cascaded	cascade	VERB
fbem-31093	5	38	risk	risk	NOUN
fbem-31093	5	39	diffusion	diffusion	NOUN
fbem-31093	5	40	(	(	PUNCT
fbem-31093	5	41	crd	crd	NOUN
fbem-31093	5	42	)	)	PUNCT
fbem-31093	5	43	mechanism	mechanism	NOUN
fbem-31093	5	44	.	.	PUNCT
fbem-31093	6	1	for	for	ADP
fbem-31093	6	2	feature	feature	NOUN
fbem-31093	6	3	transformation	transformation	NOUN
fbem-31093	6	4	,	,	PUNCT
fbem-31093	6	5	we	we	PRON
fbem-31093	6	6	implement	implement	VERB
fbem-31093	6	7	adaptive	adaptive	ADJ
fbem-31093	6	8	tree	tree	NOUN
fbem-31093	6	9	partitioning	partitioning	NOUN
fbem-31093	6	10	(	(	PUNCT
fbem-31093	6	11	atp	atp	PROPN
fbem-31093	6	12	)	)	PUNCT
fbem-31093	6	13	encoding	encoding	NOUN
fbem-31093	6	14	and	and	CCONJ
fbem-31093	6	15	statistical	statistical	ADJ
fbem-31093	6	16	evidence	evidence	NOUN
fbem-31093	6	17	weighting	weighting	NOUN
fbem-31093	6	18	(	(	PUNCT
fbem-31093	6	19	sew	sew	NOUN
fbem-31093	6	20	)	)	PUNCT
fbem-31093	6	21	encoding	encoding	NOUN
fbem-31093	6	22	to	to	PART
fbem-31093	6	23	convert	convert	VERB
fbem-31093	6	24	various	various	ADJ
fbem-31093	6	25	types	type	NOUN
fbem-31093	6	26	of	of	ADP
fbem-31093	6	27	non	non	ADJ
fbem-31093	6	28	-	-	ADJ
fbem-31093	6	29	additive	additive	ADJ
fbem-31093	6	30	node	node	NOUN
fbem-31093	6	31	attributes	attribute	NOUN
fbem-31093	6	32	into	into	ADP
fbem-31093	6	33	vector	vector	NOUN
fbem-31093	6	34	representations	representation	NOUN
fbem-31093	6	35	suitable	suitable	ADJ
fbem-31093	6	36	for	for	ADP
fbem-31093	6	37	gnn	gnn	PROPN
fbem-31093	6	38	aggregation	aggregation	NOUN
fbem-31093	6	39	operations	operation	NOUN
fbem-31093	6	40	,	,	PUNCT
fbem-31093	6	41	avoiding	avoid	VERB
fbem-31093	6	42	the	the	DET
fbem-31093	6	43	generation	generation	NOUN
fbem-31093	6	44	of	of	ADP
fbem-31093	6	45	meaningless	meaningless	ADJ
fbem-31093	6	46	features	feature	NOUN
fbem-31093	6	47	while	while	SCONJ
fbem-31093	6	48	maintaining	maintain	VERB
fbem-31093	6	49	strong	strong	ADJ
fbem-31093	6	50	interpretability	interpretability	NOUN
fbem-31093	6	51	.	.	PUNCT
fbem-31093	7	1	for	for	ADP
fbem-31093	7	2	risk	risk	NOUN
fbem-31093	7	3	propagation	propagation	NOUN
fbem-31093	7	4	,	,	PUNCT
fbem-31093	7	5	we	we	PRON
fbem-31093	7	6	design	design	VERB
fbem-31093	7	7	a	a	DET
fbem-31093	7	8	feedback	feedback	NOUN
fbem-31093	7	9	-	-	PUNCT
fbem-31093	7	10	based	base	VERB
fbem-31093	7	11	cascaded	cascade	VERB
fbem-31093	7	12	risk	risk	NOUN
fbem-31093	7	13	diffusion	diffusion	NOUN
fbem-31093	7	14	strategy	strategy	NOUN
fbem-31093	7	15	that	that	PRON
fbem-31093	7	16	enables	enable	VERB
fbem-31093	7	17	dynamic	dynamic	ADJ
fbem-31093	7	18	accumulation	accumulation	NOUN
fbem-31093	7	19	and	and	CCONJ
fbem-31093	7	20	decay	decay	NOUN
fbem-31093	7	21	of	of	ADP
fbem-31093	7	22	risk	risk	NOUN
fbem-31093	7	23	information	information	NOUN
fbem-31093	7	24	across	across	ADP
fbem-31093	7	25	the	the	DET
fbem-31093	7	26	network	network	NOUN
fbem-31093	7	27	.	.	PUNCT
fbem-31093	8	1	additionally	additionally	ADV
fbem-31093	8	2	,	,	PUNCT
fbem-31093	8	3	we	we	PRON
fbem-31093	8	4	develop	develop	VERB
fbem-31093	8	5	a	a	DET
fbem-31093	8	6	responsive	responsive	ADJ
fbem-31093	8	7	group	group	NOUN
fbem-31093	8	8	allocation	allocation	NOUN
fbem-31093	8	9	(	(	PUNCT
fbem-31093	8	10	rga	rga	NOUN
fbem-31093	8	11	)	)	PUNCT
fbem-31093	8	12	strategy	strategy	NOUN
fbem-31093	8	13	that	that	PRON
fbem-31093	8	14	divides	divide	VERB
fbem-31093	8	15	graph	graph	NOUN
fbem-31093	8	16	nodes	node	NOUN
fbem-31093	8	17	into	into	ADP
fbem-31093	8	18	distinct	distinct	ADJ
fbem-31093	8	19	groups	group	NOUN
fbem-31093	8	20	followed	follow	VERB
fbem-31093	8	21	by	by	ADP
fbem-31093	8	22	hierarchical	hierarchical	ADJ
fbem-31093	8	23	aggregation	aggregation	NOUN
fbem-31093	8	24	,	,	PUNCT
fbem-31093	8	25	enhancing	enhance	VERB
fbem-31093	8	26	the	the	DET
fbem-31093	8	27	distinguishability	distinguishability	NOUN
fbem-31093	8	28	of	of	ADP
fbem-31093	8	29	fraudulent	fraudulent	ADJ
fbem-31093	8	30	nodes	node	NOUN
fbem-31093	8	31	.	.	PUNCT
fbem-31093	9	1	experiments	experiment	NOUN
fbem-31093	9	2	on	on	ADP
fbem-31093	9	3	two	two	NUM
fbem-31093	9	4	classic	classic	ADJ
fbem-31093	9	5	financial	financial	ADJ
fbem-31093	9	6	fraud	fraud	NOUN
fbem-31093	9	7	datasets	dataset	NOUN
fbem-31093	9	8	demonstrate	demonstrate	VERB
fbem-31093	9	9	that	that	SCONJ
fbem-31093	9	10	our	our	PRON
fbem-31093	9	11	proposed	propose	VERB
fbem-31093	9	12	method	method	NOUN
fbem-31093	9	13	achieves	achieve	VERB
fbem-31093	9	14	superior	superior	ADJ
fbem-31093	9	15	discriminative	discriminative	NOUN
fbem-31093	9	16	capability	capability	NOUN
fbem-31093	9	17	for	for	ADP
fbem-31093	9	18	fraudulent	fraudulent	ADJ
fbem-31093	9	19	nodes	node	NOUN
fbem-31093	9	20	compared	compare	VERB
fbem-31093	9	21	to	to	ADP
fbem-31093	9	22	traditional	traditional	ADJ
fbem-31093	9	23	graph	graph	NOUN
fbem-31093	9	24	algorithms	algorithm	NOUN
fbem-31093	9	25	and	and	CCONJ
fbem-31093	9	26	machine	machine	NOUN
fbem-31093	9	27	learning	learning	NOUN
fbem-31093	9	28	methods	method	NOUN
fbem-31093	9	29	.	.	PUNCT
fbem-31093	10	1	the	the	DET
fbem-31093	10	2	experimental	experimental	ADJ
fbem-31093	10	3	results	result	NOUN
fbem-31093	10	4	confirm	confirm	VERB
fbem-31093	10	5	the	the	DET
fbem-31093	10	6	advantages	advantage	NOUN
fbem-31093	10	7	of	of	ADP
fbem-31093	10	8	finguard	finguard	NOUN
fbem-31093	10	9	-	-	PUNCT
fbem-31093	10	10	gnn	gnn	NOUN
fbem-31093	10	11	in	in	ADP
fbem-31093	10	12	handling	handle	VERB
fbem-31093	10	13	non	non	ADJ
fbem-31093	10	14	-	-	ADJ
fbem-31093	10	15	additive	additive	ADJ
fbem-31093	10	16	features	feature	NOUN
fbem-31093	10	17	in	in	ADP
fbem-31093	10	18	complex	complex	ADJ
fbem-31093	10	19	financial	financial	ADJ
fbem-31093	10	20	networks	network	NOUN
fbem-31093	10	21	,	,	PUNCT
fbem-31093	10	22	improving	improve	VERB
fbem-31093	10	23	node	node	ADJ
fbem-31093	10	24	distinguishability	distinguishability	NOUN
fbem-31093	10	25	,	,	PUNCT
fbem-31093	10	26	and	and	CCONJ
fbem-31093	10	27	capturing	capture	VERB
fbem-31093	10	28	hierarchical	hierarchical	ADJ
fbem-31093	10	29	risk	risk	NOUN
fbem-31093	10	30	propagation	propagation	NOUN
fbem-31093	10	31	,	,	PUNCT
fbem-31093	10	32	providing	provide	VERB
fbem-31093	10	33	a	a	DET
fbem-31093	10	34	novel	novel	ADJ
fbem-31093	10	35	solution	solution	NOUN
fbem-31093	10	36	for	for	ADP
fbem-31093	10	37	the	the	DET
fbem-31093	10	38	fi	fi	NOUN
fbem-31093	10	39	.	.	PUNCT
fbem-31093	11	1	keywords	keyword	NOUN
fbem-31093	11	2	:	:	PUNCT
fbem-31093	11	3	dynamic	dynamic	ADJ
fbem-31093	11	4	graph	graph	NOUN
fbem-31093	11	5	neural	neural	ADJ
fbem-31093	11	6	networks	network	NOUN
fbem-31093	11	7	;	;	PUNCT
fbem-31093	11	8	financial	financial	ADJ
fbem-31093	11	9	fraud	fraud	NOUN
fbem-31093	11	10	;	;	PUNCT
fbem-31093	11	11	machine	machine	NOUN
fbem-31093	11	12	learning	learning	NOUN
fbem-31093	11	13	.	.	PUNCT
fbem-31093	12	1	1	1	X
fbem-31093	12	2	.	.	X
fbem-31093	12	3	introduction	introduction	NOUN
fbem-31093	12	4	in	in	ADP
fbem-31093	12	5	recent	recent	ADJ
fbem-31093	12	6	years	year	NOUN
fbem-31093	12	7	,	,	PUNCT
fbem-31093	12	8	the	the	DET
fbem-31093	12	9	rapid	rapid	ADJ
fbem-31093	12	10	evolution	evolution	NOUN
fbem-31093	12	11	of	of	ADP
fbem-31093	12	12	financial	financial	ADJ
fbem-31093	12	13	technology	technology	NOUN
fbem-31093	12	14	has	have	AUX
fbem-31093	12	15	catalyzed	catalyze	VERB
fbem-31093	12	16	unprecedented	unprecedented	ADJ
fbem-31093	12	17	growth	growth	NOUN
fbem-31093	12	18	in	in	ADP
fbem-31093	12	19	digital	digital	ADJ
fbem-31093	12	20	payments	payment	NOUN
fbem-31093	12	21	,	,	PUNCT
fbem-31093	12	22	online	online	ADJ
fbem-31093	12	23	lending	lending	NOUN
fbem-31093	12	24	,	,	PUNCT
fbem-31093	12	25	and	and	CCONJ
fbem-31093	12	26	cryptocurrency	cryptocurrency	NOUN
fbem-31093	12	27	transactions	transaction	NOUN
fbem-31093	12	28	,	,	PUNCT
fbem-31093	12	29	injecting	inject	VERB
fbem-31093	12	30	new	new	ADJ
fbem-31093	12	31	vitality	vitality	NOUN
fbem-31093	12	32	into	into	ADP
fbem-31093	12	33	economic	economic	ADJ
fbem-31093	12	34	development	development	NOUN
fbem-31093	12	35	[	[	X
fbem-31093	12	36	1	1	NUM
fbem-31093	12	37	,	,	PUNCT
fbem-31093	12	38	2	2	NUM
fbem-31093	12	39	]	]	PUNCT
fbem-31093	12	40	.	.	PUNCT
fbem-31093	13	1	however	however	ADV
fbem-31093	13	2	,	,	PUNCT
fbem-31093	13	3	financial	financial	ADJ
fbem-31093	13	4	fraud	fraud	NOUN
fbem-31093	13	5	has	have	AUX
fbem-31093	13	6	simultaneously	simultaneously	ADV
fbem-31093	13	7	grown	grow	VERB
fbem-31093	13	8	in	in	ADP
fbem-31093	13	9	complexity	complexity	NOUN
fbem-31093	13	10	and	and	CCONJ
fbem-31093	13	11	diversity	diversity	NOUN
fbem-31093	13	12	.	.	PUNCT
fbem-31093	14	1	according	accord	VERB
fbem-31093	14	2	to	to	ADP
fbem-31093	14	3	nasdaq	nasdaq	PROPN
fbem-31093	14	4	estimates	estimate	NOUN
fbem-31093	14	5	,	,	PUNCT
fbem-31093	14	6	at	at	ADP
fbem-31093	14	7	least	least	ADV
fbem-31093	14	8	$	$	SYM
fbem-31093	14	9	3.1	3.1	NUM
fbem-31093	14	10	trillion	trillion	NUM
fbem-31093	14	11	in	in	ADP
fbem-31093	14	12	illicit	illicit	ADJ
fbem-31093	14	13	funds	fund	NOUN
fbem-31093	14	14	flowed	flow	VERB
fbem-31093	14	15	through	through	ADP
fbem-31093	14	16	the	the	DET
fbem-31093	14	17	global	global	ADJ
fbem-31093	14	18	financial	financial	ADJ
fbem-31093	14	19	system	system	NOUN
fbem-31093	14	20	in	in	ADP
fbem-31093	14	21	2023	2023	NUM
fbem-31093	14	22	,	,	PUNCT
fbem-31093	14	23	affecting	affect	VERB
fbem-31093	14	24	even	even	ADV
fbem-31093	14	25	the	the	DET
fbem-31093	14	26	most	most	ADV
fbem-31093	14	27	diligent	diligent	ADJ
fbem-31093	14	28	organizations	organization	NOUN
fbem-31093	14	29	.	.	PUNCT
fbem-31093	15	1	traditional	traditional	ADJ
fbem-31093	15	2	fraud	fraud	NOUN
fbem-31093	15	3	detection	detection	NOUN
fbem-31093	15	4	methods	method	NOUN
fbem-31093	15	5	based	base	VERB
fbem-31093	15	6	on	on	ADP
fbem-31093	15	7	rules	rule	NOUN
fbem-31093	15	8	and	and	CCONJ
fbem-31093	15	9	simple	simple	ADJ
fbem-31093	15	10	machine	machine	NOUN
fbem-31093	15	11	learning	learning	NOUN
fbem-31093	15	12	algorithms	algorithm	NOUN
fbem-31093	15	13	have	have	AUX
fbem-31093	15	14	become	become	VERB
fbem-31093	15	15	increasingly	increasingly	ADV
fbem-31093	15	16	inadequate	inadequate	ADJ
fbem-31093	15	17	to	to	PART
fbem-31093	15	18	combat	combat	VERB
fbem-31093	15	19	these	these	DET
fbem-31093	15	20	sophisticated	sophisticated	ADJ
fbem-31093	15	21	threats	threat	NOUN
fbem-31093	15	22	.	.	PUNCT
fbem-31093	16	1	fraudsters	fraudster	NOUN
fbem-31093	16	2	continuously	continuously	ADV
fbem-31093	16	3	adapt	adapt	VERB
fbem-31093	16	4	their	their	PRON
fbem-31093	16	5	tactics	tactic	NOUN
fbem-31093	16	6	,	,	PUNCT
fbem-31093	16	7	making	make	VERB
fbem-31093	16	8	static	static	ADJ
fbem-31093	16	9	rules	rule	NOUN
fbem-31093	16	10	difficult	difficult	ADJ
fbem-31093	16	11	to	to	PART
fbem-31093	16	12	maintain	maintain	VERB
fbem-31093	16	13	,	,	PUNCT
fbem-31093	16	14	while	while	SCONJ
fbem-31093	16	15	fraudulent	fraudulent	ADJ
fbem-31093	16	16	activities	activity	NOUN
fbem-31093	16	17	often	often	ADV
fbem-31093	16	18	involve	involve	VERB
fbem-31093	16	19	intricate	intricate	ADJ
fbem-31093	16	20	social	social	ADJ
fbem-31093	16	21	networks	network	NOUN
fbem-31093	16	22	and	and	CCONJ
fbem-31093	16	23	transaction	transaction	NOUN
fbem-31093	16	24	relationships	relationship	NOUN
fbem-31093	16	25	that	that	PRON
fbem-31093	16	26	can	can	AUX
fbem-31093	16	27	not	not	PART
fbem-31093	16	28	be	be	AUX
fbem-31093	16	29	effectively	effectively	ADV
fbem-31093	16	30	identified	identify	VERB
fbem-31093	16	31	through	through	ADP
fbem-31093	16	32	individual	individual	ADJ
fbem-31093	16	33	feature	feature	NOUN
fbem-31093	16	34	analysis	analysis	NOUN
fbem-31093	16	35	alone	alone	ADV
fbem-31093	17	1	[	[	X
fbem-31093	17	2	3	3	NUM
fbem-31093	17	3	,	,	PUNCT
fbem-31093	17	4	4	4	NUM
fbem-31093	17	5	,	,	PUNCT
fbem-31093	17	6	5	5	NUM
fbem-31093	17	7	]	]	PUNCT
fbem-31093	17	8	.	.	PUNCT
fbem-31093	18	1	consequently	consequently	ADV
fbem-31093	18	2	,	,	PUNCT
fbem-31093	18	3	developing	develop	VERB
fbem-31093	18	4	advanced	advanced	ADJ
fbem-31093	18	5	fraud	fraud	NOUN
fbem-31093	18	6	detection	detection	NOUN
fbem-31093	18	7	algorithms	algorithm	NOUN
fbem-31093	18	8	that	that	PRON
fbem-31093	18	9	effectively	effectively	ADV
fbem-31093	18	10	leverage	leverage	VERB
fbem-31093	18	11	relationship	relationship	NOUN
fbem-31093	18	12	information	information	NOUN
fbem-31093	18	13	between	between	ADP
fbem-31093	18	14	entities	entity	NOUN
fbem-31093	18	15	has	have	AUX
fbem-31093	18	16	become	become	VERB
fbem-31093	18	17	a	a	DET
fbem-31093	18	18	crucial	crucial	ADJ
fbem-31093	18	19	focus	focus	NOUN
fbem-31093	18	20	for	for	ADP
fbem-31093	18	21	both	both	CCONJ
fbem-31093	18	22	academia	academia	NOUN
fbem-31093	18	23	and	and	CCONJ
fbem-31093	18	24	industry	industry	NOUN
fbem-31093	18	25	.	.	PUNCT
fbem-31093	19	1	the	the	DET
fbem-31093	19	2	inherent	inherent	ADJ
fbem-31093	19	3	complexity	complexity	NOUN
fbem-31093	19	4	and	and	CCONJ
fbem-31093	19	5	volatility	volatility	NOUN
fbem-31093	19	6	of	of	ADP
fbem-31093	19	7	financial	financial	ADJ
fbem-31093	19	8	markets	market	NOUN
fbem-31093	19	9	present	present	VERB
fbem-31093	19	10	significant	significant	ADJ
fbem-31093	19	11	challenges	challenge	NOUN
fbem-31093	19	12	for	for	ADP
fbem-31093	19	13	fraud	fraud	NOUN
fbem-31093	19	14	detection	detection	NOUN
fbem-31093	19	15	systems	system	NOUN
fbem-31093	19	16	.	.	PUNCT
fbem-31093	20	1	financial	financial	ADJ
fbem-31093	20	2	data	datum	NOUN
fbem-31093	20	3	is	be	AUX
fbem-31093	20	4	characterized	characterize	VERB
fbem-31093	20	5	by	by	ADP
fbem-31093	20	6	its	its	PRON
fbem-31093	20	7	heterogeneity	heterogeneity	NOUN
fbem-31093	20	8	,	,	PUNCT
fbem-31093	20	9	temporal	temporal	ADJ
fbem-31093	20	10	dynamics	dynamic	NOUN
fbem-31093	20	11	,	,	PUNCT
fbem-31093	20	12	and	and	CCONJ
fbem-31093	20	13	complex	complex	ADJ
fbem-31093	20	14	relational	relational	ADJ
fbem-31093	20	15	structures	structure	NOUN
fbem-31093	20	16	,	,	PUNCT
fbem-31093	20	17	which	which	PRON
fbem-31093	20	18	are	be	AUX
fbem-31093	20	19	typically	typically	ADV
fbem-31093	20	20	represented	represent	VERB
fbem-31093	20	21	as	as	ADP
fbem-31093	20	22	graph	graph	NOUN
fbem-31093	20	23	data	datum	NOUN
fbem-31093	20	24	.	.	PUNCT
fbem-31093	21	1	this	this	DET
fbem-31093	21	2	representation	representation	NOUN
fbem-31093	21	3	exposes	expose	VERB
fbem-31093	21	4	two	two	NUM
fbem-31093	21	5	fundamental	fundamental	ADJ
fbem-31093	21	6	limitations	limitation	NOUN
fbem-31093	21	7	in	in	ADP
fbem-31093	21	8	current	current	ADJ
fbem-31093	21	9	approaches	approach	NOUN
fbem-31093	21	10	.	.	PUNCT
fbem-31093	22	1	first	first	ADV
fbem-31093	22	2	,	,	PUNCT
fbem-31093	22	3	traditional	traditional	ADJ
fbem-31093	22	4	financial	financial	ADJ
fbem-31093	22	5	fraud	fraud	NOUN
fbem-31093	22	6	detection	detection	NOUN
fbem-31093	22	7	methods	method	NOUN
fbem-31093	22	8	struggle	struggle	VERB
fbem-31093	22	9	to	to	PART
fbem-31093	22	10	process	process	VERB
fbem-31093	22	11	the	the	DET
fbem-31093	22	12	multifaceted	multifaceted	ADJ
fbem-31093	22	13	relationships	relationship	NOUN
fbem-31093	22	14	and	and	CCONJ
fbem-31093	22	15	numerous	numerous	ADJ
fbem-31093	22	16	components	component	NOUN
fbem-31093	22	17	present	present	ADJ
fbem-31093	22	18	in	in	ADP
fbem-31093	22	19	financial	financial	ADJ
fbem-31093	22	20	networks	network	NOUN
fbem-31093	22	21	.	.	PUNCT
fbem-31093	23	1	second	second	ADJ
fbem-31093	23	2	,	,	PUNCT
fbem-31093	23	3	the	the	DET
fbem-31093	23	4	graph	graph	NOUN
fbem-31093	23	5	structures	structure	NOUN
fbem-31093	23	6	constructed	construct	VERB
fbem-31093	23	7	from	from	ADP
fbem-31093	23	8	financial	financial	ADJ
fbem-31093	23	9	data	datum	NOUN
fbem-31093	23	10	are	be	AUX
fbem-31093	23	11	often	often	ADV
fbem-31093	23	12	heterogeneous	heterogeneous	ADJ
fbem-31093	23	13	and	and	CCONJ
fbem-31093	23	14	time	time	NOUN
fbem-31093	23	15	-	-	PUNCT
fbem-31093	23	16	varying	vary	VERB
fbem-31093	23	17	,	,	PUNCT
fbem-31093	23	18	presenting	present	VERB
fbem-31093	23	19	substantial	substantial	ADJ
fbem-31093	23	20	modeling	modeling	NOUN
fbem-31093	23	21	challenges	challenge	NOUN
fbem-31093	23	22	that	that	PRON
fbem-31093	23	23	conventional	conventional	ADJ
fbem-31093	23	24	techniques	technique	NOUN
fbem-31093	23	25	can	can	AUX
fbem-31093	23	26	not	not	PART
fbem-31093	23	27	address	address	VERB
fbem-31093	23	28	effectively	effectively	ADV
fbem-31093	23	29	[	[	X
fbem-31093	23	30	6	6	NUM
fbem-31093	23	31	,	,	PUNCT
fbem-31093	23	32	7	7	NUM
fbem-31093	23	33	]	]	PUNCT
fbem-31093	23	34	.	.	PUNCT
fbem-31093	24	1	current	current	ADJ
fbem-31093	24	2	graph	graph	NOUN
fbem-31093	24	3	-	-	PUNCT
fbem-31093	24	4	based	base	VERB
fbem-31093	24	5	fraud	fraud	NOUN
fbem-31093	24	6	detection	detection	NOUN
fbem-31093	24	7	methods	method	NOUN
fbem-31093	24	8	encounter	encounter	VERB
fbem-31093	24	9	two	two	NUM
fbem-31093	24	10	critical	critical	ADJ
fbem-31093	24	11	challenges	challenge	NOUN
fbem-31093	24	12	.	.	PUNCT
fbem-31093	25	1	challenge	challenge	NOUN
fbem-31093	25	2	1	1	NUM
fbem-31093	25	3	(	(	PUNCT
fbem-31093	25	4	c1	c1	NOUN
fbem-31093	25	5	):	):	PUNCT
fbem-31093	25	6	non	non	ADJ
fbem-31093	25	7	-	-	ADJ
fbem-31093	25	8	additive	additive	ADJ
fbem-31093	25	9	attribute	attribute	NOUN
fbem-31093	25	10	processing	processing	NOUN
fbem-31093	25	11	.	.	PUNCT
fbem-31093	26	1	existing	exist	VERB
fbem-31093	26	2	methods	method	NOUN
fbem-31093	26	3	often	often	ADV
fbem-31093	26	4	employ	employ	VERB
fbem-31093	26	5	simple	simple	ADJ
fbem-31093	26	6	averaging	averaging	NOUN
fbem-31093	26	7	or	or	CCONJ
fbem-31093	26	8	summation	summation	NOUN
fbem-31093	26	9	operations	operation	NOUN
fbem-31093	26	10	when	when	SCONJ
fbem-31093	26	11	handling	handle	VERB
fbem-31093	26	12	nonadditive	nonadditive	ADJ
fbem-31093	26	13	node	node	ADJ
fbem-31093	26	14	attributes	attribute	NOUN
fbem-31093	26	15	(	(	PUNCT
fbem-31093	26	16	such	such	ADJ
fbem-31093	26	17	as	as	ADP
fbem-31093	26	18	transaction	transaction	NOUN
fbem-31093	26	19	frequency	frequency	NOUN
fbem-31093	26	20	,	,	PUNCT
fbem-31093	26	21	amount	amount	NOUN
fbem-31093	26	22	distribution	distribution	NOUN
fbem-31093	26	23	,	,	PUNCT
fbem-31093	26	24	and	and	CCONJ
fbem-31093	26	25	time	time	NOUN
fbem-31093	26	26	intervals	interval	NOUN
fbem-31093	26	27	)	)	PUNCT
fbem-31093	26	28	,	,	PUNCT
fbem-31093	26	29	which	which	PRON
fbem-31093	26	30	not	not	PART
fbem-31093	26	31	only	only	ADV
fbem-31093	26	32	loses	lose	VERB
fbem-31093	26	33	the	the	DET
fbem-31093	26	34	statistical	statistical	ADJ
fbem-31093	26	35	distribution	distribution	NOUN
fbem-31093	26	36	characteristics	characteristic	NOUN
fbem-31093	26	37	of	of	ADP
fbem-31093	26	38	the	the	DET
fbem-31093	26	39	original	original	ADJ
fbem-31093	26	40	features	feature	NOUN
fbem-31093	26	41	but	but	CCONJ
fbem-31093	26	42	may	may	AUX
fbem-31093	26	43	also	also	ADV
fbem-31093	26	44	generate	generate	VERB
fbem-31093	26	45	meaningless	meaningless	ADJ
fbem-31093	26	46	feature	feature	NOUN
fbem-31093	26	47	representations	representation	NOUN
fbem-31093	26	48	.	.	PUNCT
fbem-31093	27	1	for	for	ADP
fbem-31093	27	2	instance	instance	NOUN
fbem-31093	27	3	,	,	PUNCT
fbem-31093	27	4	averaging	average	VERB
fbem-31093	27	5	transaction	transaction	NOUN
fbem-31093	27	6	amounts	amount	NOUN
fbem-31093	27	7	might	might	AUX
fbem-31093	27	8	mask	mask	VERB
fbem-31093	27	9	fluctuation	fluctuation	NOUN
fbem-31093	27	10	patterns	pattern	NOUN
fbem-31093	27	11	indicative	indicative	ADJ
fbem-31093	27	12	of	of	ADP
fbem-31093	27	13	anomalous	anomalous	ADJ
fbem-31093	27	14	activity	activity	NOUN
fbem-31093	27	15	,	,	PUNCT
fbem-31093	27	16	while	while	SCONJ
fbem-31093	27	17	simple	simple	ADJ
fbem-31093	27	18	summation	summation	NOUN
fbem-31093	27	19	can	can	AUX
fbem-31093	27	20	lead	lead	VERB
fbem-31093	27	21	to	to	PART
fbem-31093	27	22	scale	scale	VERB
fbem-31093	27	23	imbalances	imbalance	NOUN
fbem-31093	27	24	[	[	X
fbem-31093	27	25	8	8	NUM
fbem-31093	27	26	]	]	PUNCT
fbem-31093	27	27	.	.	PUNCT
fbem-31093	28	1	challenge	challenge	NOUN
fbem-31093	28	2	2	2	NUM
fbem-31093	28	3	(	(	PUNCT
fbem-31093	28	4	c2	c2	PROPN
fbem-31093	28	5	):	):	PUNCT
fbem-31093	28	6	distinguishability	distinguishability	NOUN
fbem-31093	28	7	of	of	ADP
fbem-31093	28	8	grouped	group	VERB
fbem-31093	28	9	message	message	NOUN
fbem-31093	28	10	passing	passing	NOUN
fbem-31093	28	11	.	.	PUNCT
fbem-31093	29	1	traditional	traditional	ADJ
fbem-31093	29	2	message	message	NOUN
fbem-31093	29	3	passing	pass	VERB
fbem-31093	29	4	mechanisms	mechanism	NOUN
fbem-31093	29	5	typically	typically	ADV
fbem-31093	29	6	treat	treat	VERB
fbem-31093	29	7	all	all	DET
fbem-31093	29	8	neighboring	neighboring	NOUN
fbem-31093	29	9	nodes	node	NOUN
fbem-31093	29	10	as	as	ADP
fbem-31093	29	11	homogeneous	homogeneous	ADJ
fbem-31093	29	12	,	,	PUNCT
fbem-31093	29	13	lacking	lack	VERB
fbem-31093	29	14	effective	effective	ADJ
fbem-31093	29	15	grouping	group	VERB
fbem-31093	29	16	strategies	strategy	NOUN
fbem-31093	29	17	to	to	PART
fbem-31093	29	18	differentiate	differentiate	VERB
fbem-31093	29	19	between	between	ADP
fbem-31093	29	20	normal	normal	ADJ
fbem-31093	29	21	users	user	NOUN
fbem-31093	29	22	,	,	PUNCT
fbem-31093	29	23	suspicious	suspicious	ADJ
fbem-31093	29	24	users	user	NOUN
fbem-31093	29	25	,	,	PUNCT
fbem-31093	29	26	and	and	CCONJ
fbem-31093	29	27	confirmed	confirm	VERB
fbem-31093	29	28	fraudulent	fraudulent	ADJ
fbem-31093	29	29	users	user	NOUN
fbem-31093	30	1	[	[	X
fbem-31093	30	2	9	9	NUM
fbem-31093	30	3	]	]	PUNCT
fbem-31093	30	4	.	.	PUNCT
fbem-31093	31	1	this	this	DET
fbem-31093	31	2	homogeneous	homogeneous	ADJ
fbem-31093	31	3	treatment	treatment	NOUN
fbem-31093	31	4	significantly	significantly	ADV
fbem-31093	31	5	impairs	impair	VERB
fbem-31093	31	6	the	the	DET
fbem-31093	31	7	model	model	NOUN
fbem-31093	31	8	's	's	PART
fbem-31093	31	9	ability	ability	NOUN
fbem-31093	31	10	to	to	PART
fbem-31093	31	11	capture	capture	VERB
fbem-31093	31	12	the	the	DET
fbem-31093	31	13	varying	vary	VERB
fbem-31093	31	14	influence	influence	NOUN
fbem-31093	31	15	patterns	pattern	NOUN
fbem-31093	31	16	of	of	ADP
fbem-31093	31	17	different	different	ADJ
fbem-31093	31	18	node	node	ADJ
fbem-31093	31	19	types	type	NOUN
fbem-31093	31	20	,	,	PUNCT
fbem-31093	31	21	particularly	particularly	ADV
fbem-31093	31	22	in	in	ADP
fbem-31093	31	23	identifying	identify	VERB
fbem-31093	31	24	sophisticated	sophisticated	ADJ
fbem-31093	31	25	fraud	fraud	NOUN
fbem-31093	31	26	schemes	scheme	NOUN
fbem-31093	31	27	.	.	PUNCT
fbem-31093	32	1	to	to	PART
fbem-31093	32	2	address	address	VERB
fbem-31093	32	3	these	these	DET
fbem-31093	32	4	challenges	challenge	NOUN
fbem-31093	32	5	,	,	PUNCT
fbem-31093	32	6	we	we	PRON
fbem-31093	32	7	propose	propose	VERB
fbem-31093	32	8	finguard	finguard	NOUN
fbem-31093	32	9	-	-	PUNCT
fbem-31093	32	10	gnn	gnn	NOUN
fbem-31093	32	11	(	(	PUNCT
fbem-31093	32	12	financial	financial	ADJ
fbem-31093	32	13	guardian	guardian	NOUN
fbem-31093	32	14	graph	graph	NOUN
fbem-31093	32	15	neural	neural	ADJ
fbem-31093	32	16	network	network	NOUN
fbem-31093	32	17	)	)	PUNCT
fbem-31093	32	18	,	,	PUNCT
fbem-31093	32	19	a	a	DET
fbem-31093	32	20	novel	novel	ADJ
fbem-31093	32	21	dynamic	dynamic	ADJ
fbem-31093	32	22	graph	graph	NOUN
fbem-31093	32	23	neural	neural	ADJ
fbem-31093	32	24	network	network	NOUN
fbem-31093	32	25	framework	framework	NOUN
fbem-31093	32	26	for	for	ADP
fbem-31093	32	27	financial	financial	ADJ
fbem-31093	32	28	fraud	fraud	NOUN
fbem-31093	32	29	detection	detection	NOUN
fbem-31093	32	30	.	.	PUNCT
fbem-31093	33	1	to	to	PART
fbem-31093	33	2	address	address	VERB
fbem-31093	33	3	c1	c1	PROPN
fbem-31093	33	4	,	,	PUNCT
fbem-31093	33	5	we	we	PRON
fbem-31093	33	6	develop	develop	VERB
fbem-31093	33	7	a	a	DET
fbem-31093	33	8	comprehensive	comprehensive	ADJ
fbem-31093	33	9	feature	feature	NOUN
fbem-31093	33	10	transformation	transformation	NOUN
fbem-31093	33	11	scheme	scheme	NOUN
fbem-31093	33	12	including	include	VERB
fbem-31093	33	13	adaptive	adaptive	ADJ
fbem-31093	33	14	tree	tree	NOUN
fbem-31093	33	15	partitioning	partitioning	NOUN
fbem-31093	33	16	(	(	PUNCT
fbem-31093	33	17	atp	atp	PROPN
fbem-31093	33	18	)	)	PUNCT
fbem-31093	33	19	encoding	encoding	NOUN
fbem-31093	33	20	and	and	CCONJ
fbem-31093	33	21	statistical	statistical	ADJ
fbem-31093	33	22	evidence	evidence	NOUN
fbem-31093	33	23	weighting	weighting	NOUN
fbem-31093	33	24	(	(	PUNCT
fbem-31093	33	25	sew	sew	NOUN
fbem-31093	33	26	)	)	PUNCT
fbem-31093	33	27	encoding	encoding	NOUN
fbem-31093	33	28	,	,	PUNCT
fbem-31093	33	29	which	which	PRON
fbem-31093	33	30	transforms	transform	VERB
fbem-31093	33	31	various	various	ADJ
fbem-31093	33	32	nonadditive	nonadditive	ADJ
fbem-31093	33	33	node	node	NOUN
fbem-31093	33	34	attributes	attribute	NOUN
fbem-31093	33	35	into	into	ADP
fbem-31093	33	36	vector	vector	NOUN
fbem-31093	33	37	representations	representation	NOUN
fbem-31093	33	38	suitable	suitable	ADJ
fbem-31093	33	39	for	for	ADP
fbem-31093	33	40	gnn	gnn	PROPN
fbem-31093	33	41	aggregation	aggregation	NOUN
fbem-31093	33	42	while	while	SCONJ
fbem-31093	33	43	maintaining	maintain	VERB
fbem-31093	33	44	their	their	PRON
fbem-31093	33	45	statistical	statistical	ADJ
fbem-31093	33	46	properties	property	NOUN
fbem-31093	33	47	.	.	PUNCT
fbem-31093	34	1	to	to	PART
fbem-31093	34	2	address	address	VERB
fbem-31093	34	3	c2	c2	PROPN
fbem-31093	34	4	,	,	PUNCT
fbem-31093	34	5	we	we	PRON
fbem-31093	34	6	introduce	introduce	VERB
fbem-31093	34	7	a	a	DET
fbem-31093	34	8	cascaded	cascade	VERB
fbem-31093	34	9	risk	risk	NOUN
fbem-31093	34	10	122	122	NUM
fbem-31093	34	11	diffusion	diffusion	NOUN
fbem-31093	34	12	(	(	PUNCT
fbem-31093	34	13	crd	crd	NOUN
fbem-31093	34	14	)	)	PUNCT
fbem-31093	34	15	mechanism	mechanism	NOUN
fbem-31093	34	16	that	that	PRON
fbem-31093	34	17	incorporates	incorporate	VERB
fbem-31093	34	18	dynamic	dynamic	ADJ
fbem-31093	34	19	weight	weight	NOUN
fbem-31093	34	20	calculation	calculation	NOUN
fbem-31093	34	21	,	,	PUNCT
fbem-31093	34	22	path	path	NOUN
fbem-31093	34	23	-	-	PUNCT
fbem-31093	34	24	length	length	NOUN
fbem-31093	34	25	decay	decay	NOUN
fbem-31093	34	26	functions	function	NOUN
fbem-31093	34	27	,	,	PUNCT
fbem-31093	34	28	and	and	CCONJ
fbem-31093	34	29	feedback	feedback	NOUN
fbem-31093	34	30	regulation	regulation	NOUN
fbem-31093	34	31	to	to	PART
fbem-31093	34	32	accurately	accurately	ADV
fbem-31093	34	33	model	model	VERB
fbem-31093	34	34	risk	risk	NOUN
fbem-31093	34	35	diffusion	diffusion	NOUN
fbem-31093	34	36	patterns	pattern	NOUN
fbem-31093	34	37	across	across	ADP
fbem-31093	34	38	financial	financial	ADJ
fbem-31093	34	39	networks	network	NOUN
fbem-31093	34	40	.	.	PUNCT
fbem-31093	35	1	additionally	additionally	ADV
fbem-31093	35	2	,	,	PUNCT
fbem-31093	35	3	we	we	PRON
fbem-31093	35	4	design	design	VERB
fbem-31093	35	5	a	a	DET
fbem-31093	35	6	responsive	responsive	ADJ
fbem-31093	35	7	group	group	NOUN
fbem-31093	35	8	allocation	allocation	NOUN
fbem-31093	35	9	(	(	PUNCT
fbem-31093	35	10	rga	rga	NOUN
fbem-31093	35	11	)	)	PUNCT
fbem-31093	35	12	strategy	strategy	NOUN
fbem-31093	35	13	that	that	PRON
fbem-31093	35	14	adaptively	adaptively	ADV
fbem-31093	35	15	divides	divide	VERB
fbem-31093	35	16	graph	graph	NOUN
fbem-31093	35	17	nodes	node	NOUN
fbem-31093	35	18	into	into	ADP
fbem-31093	35	19	distinct	distinct	ADJ
fbem-31093	35	20	functional	functional	ADJ
fbem-31093	35	21	groups	group	NOUN
fbem-31093	35	22	and	and	CCONJ
fbem-31093	35	23	enhances	enhance	VERB
fbem-31093	35	24	fraudulent	fraudulent	ADJ
fbem-31093	35	25	node	node	ADJ
fbem-31093	35	26	identifiability	identifiability	NOUN
fbem-31093	35	27	through	through	ADP
fbem-31093	35	28	hierarchical	hierarchical	ADJ
fbem-31093	35	29	information	information	NOUN
fbem-31093	35	30	aggregation	aggregation	NOUN
fbem-31093	35	31	.	.	PUNCT
fbem-31093	36	1	our	our	PRON
fbem-31093	36	2	extensive	extensive	ADJ
fbem-31093	36	3	experiments	experiment	NOUN
fbem-31093	36	4	on	on	ADP
fbem-31093	36	5	two	two	NUM
fbem-31093	36	6	real	real	ADJ
fbem-31093	36	7	-	-	PUNCT
fbem-31093	36	8	world	world	NOUN
fbem-31093	36	9	financial	financial	ADJ
fbem-31093	36	10	fraud	fraud	NOUN
fbem-31093	36	11	datasets	dataset	NOUN
fbem-31093	36	12	demonstrate	demonstrate	VERB
fbem-31093	36	13	that	that	SCONJ
fbem-31093	36	14	finguard	finguard	NOUN
fbem-31093	36	15	-	-	PUNCT
fbem-31093	36	16	gnn	gnn	NOUN
fbem-31093	36	17	significantly	significantly	ADV
fbem-31093	36	18	outperforms	outperform	VERB
fbem-31093	36	19	existing	exist	VERB
fbem-31093	36	20	graph	graph	NOUN
fbem-31093	36	21	algorithms	algorithm	NOUN
fbem-31093	36	22	and	and	CCONJ
fbem-31093	36	23	traditional	traditional	ADJ
fbem-31093	36	24	machine	machine	NOUN
fbem-31093	36	25	learning	learning	NOUN
fbem-31093	36	26	methods	method	NOUN
fbem-31093	36	27	,	,	PUNCT
fbem-31093	36	28	validating	validate	VERB
fbem-31093	36	29	its	its	PRON
fbem-31093	36	30	effectiveness	effectiveness	NOUN
fbem-31093	36	31	and	and	CCONJ
fbem-31093	36	32	practical	practical	ADJ
fbem-31093	36	33	value	value	NOUN
fbem-31093	36	34	in	in	ADP
fbem-31093	36	35	financial	financial	ADJ
fbem-31093	36	36	fraud	fraud	NOUN
fbem-31093	36	37	detection	detection	NOUN
fbem-31093	36	38	scenarios	scenario	NOUN
fbem-31093	36	39	.	.	PUNCT
fbem-31093	37	1	2	2	X
fbem-31093	37	2	.	.	X
fbem-31093	37	3	related	relate	VERB
fbem-31093	37	4	work	work	NOUN
fbem-31093	37	5	2.1	2.1	NUM
fbem-31093	37	6	.	.	PUNCT
fbem-31093	38	1	traditional	traditional	ADJ
fbem-31093	38	2	fraud	fraud	NOUN
fbem-31093	38	3	detection	detection	NOUN
fbem-31093	38	4	approaches	approach	VERB
fbem-31093	38	5	traditional	traditional	ADJ
fbem-31093	38	6	fraud	fraud	NOUN
fbem-31093	38	7	detection	detection	NOUN
fbem-31093	38	8	methods	method	NOUN
fbem-31093	38	9	rely	rely	VERB
fbem-31093	38	10	primarily	primarily	ADV
fbem-31093	38	11	on	on	ADP
fbem-31093	38	12	rulebased	rulebase	VERB
fbem-31093	38	13	systems	system	NOUN
fbem-31093	38	14	and	and	CCONJ
fbem-31093	38	15	conventional	conventional	ADJ
fbem-31093	38	16	machine	machine	NOUN
fbem-31093	38	17	learning	learn	VERB
fbem-31093	38	18	algorithms	algorithm	NOUN
fbem-31093	38	19	[	[	X
fbem-31093	38	20	10	10	NUM
fbem-31093	38	21	]	]	PUNCT
fbem-31093	38	22	.	.	PUNCT
fbem-31093	39	1	rule	rule	NOUN
fbem-31093	39	2	-	-	PUNCT
fbem-31093	39	3	based	base	VERB
fbem-31093	39	4	approaches	approach	NOUN
fbem-31093	39	5	employ	employ	VERB
fbem-31093	39	6	expert	expert	NOUN
fbem-31093	39	7	-	-	PUNCT
fbem-31093	39	8	defined	define	VERB
fbem-31093	39	9	heuristics	heuristic	NOUN
fbem-31093	39	10	to	to	PART
fbem-31093	39	11	flag	flag	VERB
fbem-31093	39	12	suspicious	suspicious	ADJ
fbem-31093	39	13	activities	activity	NOUN
fbem-31093	39	14	,	,	PUNCT
fbem-31093	39	15	offering	offer	VERB
fbem-31093	39	16	high	high	ADJ
fbem-31093	39	17	interpretability	interpretability	NOUN
fbem-31093	39	18	but	but	CCONJ
fbem-31093	39	19	lacking	lack	VERB
fbem-31093	39	20	adaptability	adaptability	NOUN
fbem-31093	39	21	to	to	ADP
fbem-31093	39	22	evolving	evolve	VERB
fbem-31093	39	23	fraud	fraud	NOUN
fbem-31093	39	24	patterns	pattern	NOUN
fbem-31093	39	25	[	[	X
fbem-31093	39	26	11	11	NUM
fbem-31093	39	27	]	]	PUNCT
fbem-31093	39	28	.	.	PUNCT
fbem-31093	40	1	classical	classical	ADJ
fbem-31093	40	2	machine	machine	NOUN
fbem-31093	40	3	learning	learn	VERB
fbem-31093	40	4	techniques	technique	NOUN
fbem-31093	40	5	such	such	ADJ
fbem-31093	40	6	as	as	ADP
fbem-31093	40	7	random	random	ADJ
fbem-31093	40	8	forests	forest	NOUN
fbem-31093	40	9	,	,	PUNCT
fbem-31093	40	10	svms	svms	NOUN
fbem-31093	40	11	,	,	PUNCT
fbem-31093	40	12	and	and	CCONJ
fbem-31093	40	13	logistic	logistic	ADJ
fbem-31093	40	14	regression	regression	NOUN
fbem-31093	40	15	improve	improve	VERB
fbem-31093	40	16	upon	upon	SCONJ
fbem-31093	40	17	these	these	DET
fbem-31093	40	18	limitations	limitation	NOUN
fbem-31093	40	19	by	by	ADP
fbem-31093	40	20	learning	learn	VERB
fbem-31093	40	21	patterns	pattern	NOUN
fbem-31093	40	22	from	from	ADP
fbem-31093	40	23	historical	historical	ADJ
fbem-31093	40	24	data	datum	NOUN
fbem-31093	40	25	.	.	PUNCT
fbem-31093	41	1	however	however	ADV
fbem-31093	41	2	,	,	PUNCT
fbem-31093	41	3	these	these	DET
fbem-31093	41	4	methods	method	NOUN
fbem-31093	41	5	operate	operate	VERB
fbem-31093	41	6	on	on	ADP
fbem-31093	41	7	tabular	tabular	PROPN
fbem-31093	41	8	data	datum	NOUN
fbem-31093	41	9	with	with	ADP
fbem-31093	41	10	independent	independent	ADJ
fbem-31093	41	11	features	feature	NOUN
fbem-31093	41	12	and	and	CCONJ
fbem-31093	41	13	struggle	struggle	VERB
fbem-31093	41	14	to	to	PART
fbem-31093	41	15	capture	capture	VERB
fbem-31093	41	16	the	the	DET
fbem-31093	41	17	complex	complex	ADJ
fbem-31093	41	18	relational	relational	ADJ
fbem-31093	41	19	patterns	pattern	NOUN
fbem-31093	41	20	inherent	inherent	ADJ
fbem-31093	41	21	in	in	ADP
fbem-31093	41	22	financial	financial	ADJ
fbem-31093	41	23	fraud	fraud	NOUN
fbem-31093	41	24	[	[	X
fbem-31093	41	25	12	12	NUM
fbem-31093	41	26	]	]	PUNCT
fbem-31093	41	27	.	.	PUNCT
fbem-31093	42	1	they	they	PRON
fbem-31093	42	2	typically	typically	ADV
fbem-31093	42	3	treat	treat	VERB
fbem-31093	42	4	each	each	DET
fbem-31093	42	5	transaction	transaction	NOUN
fbem-31093	42	6	or	or	CCONJ
fbem-31093	42	7	user	user	NOUN
fbem-31093	42	8	in	in	ADP
fbem-31093	42	9	isolation	isolation	NOUN
fbem-31093	42	10	,	,	PUNCT
fbem-31093	42	11	missing	miss	VERB
fbem-31093	42	12	crucial	crucial	ADJ
fbem-31093	42	13	contextual	contextual	ADJ
fbem-31093	42	14	information	information	NOUN
fbem-31093	42	15	embedded	embed	VERB
fbem-31093	42	16	in	in	ADP
fbem-31093	42	17	transaction	transaction	NOUN
fbem-31093	42	18	networks	network	NOUN
fbem-31093	42	19	.	.	PUNCT
fbem-31093	43	1	while	while	SCONJ
fbem-31093	43	2	these	these	DET
fbem-31093	43	3	approaches	approach	NOUN
fbem-31093	43	4	provide	provide	VERB
fbem-31093	43	5	a	a	DET
fbem-31093	43	6	foundation	foundation	NOUN
fbem-31093	43	7	for	for	ADP
fbem-31093	43	8	fraud	fraud	NOUN
fbem-31093	43	9	detection	detection	NOUN
fbem-31093	43	10	,	,	PUNCT
fbem-31093	43	11	their	their	PRON
fbem-31093	43	12	effectiveness	effectiveness	NOUN
fbem-31093	43	13	diminishes	diminish	VERB
fbem-31093	43	14	against	against	ADP
fbem-31093	43	15	sophisticated	sophisticated	ADJ
fbem-31093	43	16	fraud	fraud	NOUN
fbem-31093	43	17	schemes	scheme	NOUN
fbem-31093	43	18	that	that	PRON
fbem-31093	43	19	operate	operate	VERB
fbem-31093	43	20	through	through	ADP
fbem-31093	43	21	coordinated	coordinate	VERB
fbem-31093	43	22	networks	network	NOUN
fbem-31093	43	23	of	of	ADP
fbem-31093	43	24	accounts	account	NOUN
fbem-31093	43	25	and	and	CCONJ
fbem-31093	43	26	complex	complex	ADJ
fbem-31093	43	27	transaction	transaction	NOUN
fbem-31093	43	28	patterns	pattern	NOUN
fbem-31093	43	29	that	that	PRON
fbem-31093	43	30	evolve	evolve	VERB
fbem-31093	43	31	over	over	ADP
fbem-31093	43	32	time	time	NOUN
fbem-31093	43	33	[	[	X
fbem-31093	43	34	13	13	NUM
fbem-31093	43	35	]	]	PUNCT
fbem-31093	43	36	.	.	PUNCT
fbem-31093	44	1	2.2	2.2	NUM
fbem-31093	44	2	.	.	PUNCT
fbem-31093	44	3	graph	graph	NOUN
fbem-31093	44	4	-	-	PUNCT
fbem-31093	44	5	based	base	VERB
fbem-31093	44	6	fraud	fraud	NOUN
fbem-31093	44	7	detection	detection	NOUN
fbem-31093	44	8	graph	graph	NOUN
fbem-31093	44	9	-	-	PUNCT
fbem-31093	44	10	based	base	VERB
fbem-31093	44	11	methods	method	NOUN
fbem-31093	44	12	represent	represent	VERB
fbem-31093	44	13	a	a	DET
fbem-31093	44	14	significant	significant	ADJ
fbem-31093	44	15	advancement	advancement	NOUN
fbem-31093	44	16	in	in	ADP
fbem-31093	44	17	financial	financial	ADJ
fbem-31093	44	18	fraud	fraud	NOUN
fbem-31093	44	19	detection	detection	NOUN
fbem-31093	44	20	by	by	ADP
fbem-31093	44	21	explicitly	explicitly	ADV
fbem-31093	44	22	modeling	model	VERB
fbem-31093	44	23	relationships	relationship	NOUN
fbem-31093	44	24	between	between	ADP
fbem-31093	44	25	entities	entity	NOUN
fbem-31093	44	26	.	.	PUNCT
fbem-31093	45	1	early	early	ADJ
fbem-31093	45	2	graph	graph	NOUN
fbem-31093	45	3	-	-	PUNCT
fbem-31093	45	4	based	base	VERB
fbem-31093	45	5	approaches	approach	NOUN
fbem-31093	45	6	focused	focus	VERB
fbem-31093	45	7	on	on	ADP
fbem-31093	45	8	detecting	detect	VERB
fbem-31093	45	9	anomalous	anomalous	ADJ
fbem-31093	45	10	patterns	pattern	NOUN
fbem-31093	45	11	in	in	ADP
fbem-31093	45	12	network	network	NOUN
fbem-31093	45	13	structures	structure	NOUN
fbem-31093	45	14	through	through	ADP
fbem-31093	45	15	centrality	centrality	NOUN
fbem-31093	45	16	measures	measure	NOUN
fbem-31093	45	17	,	,	PUNCT
fbem-31093	45	18	community	community	NOUN
fbem-31093	45	19	detection	detection	NOUN
fbem-31093	45	20	,	,	PUNCT
fbem-31093	45	21	and	and	CCONJ
fbem-31093	45	22	subgraph	subgraph	PROPN
fbem-31093	45	23	mining	mining	NOUN
fbem-31093	45	24	.	.	PUNCT
fbem-31093	46	1	these	these	DET
fbem-31093	46	2	methods	method	NOUN
fbem-31093	46	3	successfully	successfully	ADV
fbem-31093	46	4	identified	identify	VERB
fbem-31093	46	5	suspicious	suspicious	ADJ
fbem-31093	46	6	network	network	NOUN
fbem-31093	46	7	motifs	motif	NOUN
fbem-31093	46	8	but	but	CCONJ
fbem-31093	46	9	lacked	lack	VERB
fbem-31093	46	10	the	the	DET
fbem-31093	46	11	ability	ability	NOUN
fbem-31093	46	12	to	to	PART
fbem-31093	46	13	integrate	integrate	VERB
fbem-31093	46	14	rich	rich	ADJ
fbem-31093	46	15	node	node	NOUN
fbem-31093	46	16	attributes	attribute	NOUN
fbem-31093	46	17	with	with	ADP
fbem-31093	46	18	structural	structural	ADJ
fbem-31093	46	19	information	information	NOUN
fbem-31093	46	20	.	.	PUNCT
fbem-31093	47	1	graph	graph	NOUN
fbem-31093	47	2	neural	neural	ADJ
fbem-31093	47	3	networks	network	NOUN
fbem-31093	47	4	(	(	PUNCT
fbem-31093	47	5	gnns	gnns	NOUN
fbem-31093	47	6	)	)	PUNCT
fbem-31093	47	7	address	address	NOUN
fbem-31093	47	8	this	this	DET
fbem-31093	47	9	limitation	limitation	NOUN
fbem-31093	47	10	by	by	ADP
fbem-31093	47	11	combining	combine	VERB
fbem-31093	47	12	the	the	DET
fbem-31093	47	13	representational	representational	ADJ
fbem-31093	47	14	power	power	NOUN
fbem-31093	47	15	of	of	ADP
fbem-31093	47	16	deep	deep	ADJ
fbem-31093	47	17	learning	learning	NOUN
fbem-31093	47	18	with	with	ADP
fbem-31093	47	19	graph	graph	NOUN
fbem-31093	47	20	structure	structure	NOUN
fbem-31093	47	21	[	[	X
fbem-31093	47	22	14	14	NUM
fbem-31093	47	23	]	]	PUNCT
fbem-31093	47	24	.	.	PUNCT
fbem-31093	48	1	general	general	ADJ
fbem-31093	48	2	-	-	PUNCT
fbem-31093	48	3	purpose	purpose	NOUN
fbem-31093	48	4	gnn	gnn	PROPN
fbem-31093	48	5	architectures	architecture	NOUN
fbem-31093	48	6	like	like	ADP
fbem-31093	48	7	gcn	gcn	NOUN
fbem-31093	48	8	,	,	PUNCT
fbem-31093	48	9	gat	gat	NOUN
fbem-31093	48	10	,	,	PUNCT
fbem-31093	48	11	and	and	CCONJ
fbem-31093	48	12	graphsage	graphsage	NOUN
fbem-31093	48	13	have	have	AUX
fbem-31093	48	14	demonstrated	demonstrate	VERB
fbem-31093	48	15	promising	promising	ADJ
fbem-31093	48	16	results	result	NOUN
fbem-31093	48	17	in	in	ADP
fbem-31093	48	18	fraud	fraud	NOUN
fbem-31093	48	19	detection	detection	NOUN
fbem-31093	48	20	by	by	ADP
fbem-31093	48	21	propagating	propagate	VERB
fbem-31093	48	22	information	information	NOUN
fbem-31093	48	23	through	through	ADP
fbem-31093	48	24	transaction	transaction	NOUN
fbem-31093	48	25	networks	network	NOUN
fbem-31093	48	26	[	[	X
fbem-31093	48	27	15	15	NUM
fbem-31093	48	28	]	]	PUNCT
fbem-31093	48	29	.	.	PUNCT
fbem-31093	49	1	recent	recent	ADJ
fbem-31093	49	2	advances	advance	NOUN
fbem-31093	49	3	have	have	AUX
fbem-31093	49	4	produced	produce	VERB
fbem-31093	49	5	specialized	specialized	ADJ
fbem-31093	49	6	gnn	gnn	PROPN
fbem-31093	49	7	variants	variant	NOUN
fbem-31093	49	8	that	that	PRON
fbem-31093	49	9	tackle	tackle	VERB
fbem-31093	49	10	the	the	DET
fbem-31093	49	11	unique	unique	ADJ
fbem-31093	49	12	challenges	challenge	NOUN
fbem-31093	49	13	of	of	ADP
fbem-31093	49	14	financial	financial	ADJ
fbem-31093	49	15	fraud	fraud	NOUN
fbem-31093	49	16	detection	detection	NOUN
fbem-31093	49	17	,	,	PUNCT
fbem-31093	49	18	including	include	VERB
fbem-31093	49	19	heterogeneous	heterogeneous	ADJ
fbem-31093	49	20	graph	graph	NOUN
fbem-31093	49	21	structures	structure	NOUN
fbem-31093	49	22	,	,	PUNCT
fbem-31093	49	23	temporal	temporal	ADJ
fbem-31093	49	24	dynamics	dynamic	NOUN
fbem-31093	49	25	,	,	PUNCT
fbem-31093	49	26	and	and	CCONJ
fbem-31093	49	27	class	class	NOUN
fbem-31093	49	28	imbalance	imbalance	NOUN
fbem-31093	49	29	[	[	X
fbem-31093	49	30	16	16	NUM
fbem-31093	49	31	]	]	PUNCT
fbem-31093	49	32	.	.	PUNCT
fbem-31093	50	1	despite	despite	SCONJ
fbem-31093	50	2	these	these	DET
fbem-31093	50	3	improvements	improvement	NOUN
fbem-31093	50	4	,	,	PUNCT
fbem-31093	50	5	current	current	ADJ
fbem-31093	50	6	graph	graph	NOUN
fbem-31093	50	7	-	-	PUNCT
fbem-31093	50	8	based	base	VERB
fbem-31093	50	9	methods	method	NOUN
fbem-31093	50	10	face	face	VERB
fbem-31093	50	11	two	two	NUM
fbem-31093	50	12	significant	significant	ADJ
fbem-31093	50	13	challenges	challenge	NOUN
fbem-31093	50	14	:	:	PUNCT
fbem-31093	50	15	they	they	PRON
fbem-31093	50	16	struggle	struggle	VERB
fbem-31093	50	17	to	to	PART
fbem-31093	50	18	effectively	effectively	ADV
fbem-31093	50	19	process	process	VERB
fbem-31093	50	20	non	non	ADJ
fbem-31093	50	21	-	-	ADJ
fbem-31093	50	22	additive	additive	ADJ
fbem-31093	50	23	attributes	attribute	NOUN
fbem-31093	50	24	common	common	ADJ
fbem-31093	50	25	in	in	ADP
fbem-31093	50	26	financial	financial	ADJ
fbem-31093	50	27	data	datum	NOUN
fbem-31093	50	28	,	,	PUNCT
fbem-31093	50	29	and	and	CCONJ
fbem-31093	50	30	they	they	PRON
fbem-31093	50	31	lack	lack	VERB
fbem-31093	50	32	mechanisms	mechanism	NOUN
fbem-31093	50	33	to	to	PART
fbem-31093	50	34	distinguish	distinguish	VERB
fbem-31093	50	35	between	between	ADP
fbem-31093	50	36	different	different	ADJ
fbem-31093	50	37	types	type	NOUN
fbem-31093	50	38	of	of	ADP
fbem-31093	50	39	neighboring	neighboring	NOUN
fbem-31093	50	40	nodes	node	NOUN
fbem-31093	50	41	during	during	ADP
fbem-31093	50	42	message	message	NOUN
fbem-31093	50	43	passing	passing	NOUN
fbem-31093	50	44	.	.	PUNCT
fbem-31093	51	1	these	these	DET
fbem-31093	51	2	limitations	limitation	NOUN
fbem-31093	51	3	reduce	reduce	VERB
fbem-31093	51	4	their	their	PRON
fbem-31093	51	5	effectiveness	effectiveness	NOUN
fbem-31093	51	6	in	in	ADP
fbem-31093	51	7	identifying	identify	VERB
fbem-31093	51	8	complex	complex	ADJ
fbem-31093	51	9	fraud	fraud	NOUN
fbem-31093	51	10	patterns	pattern	NOUN
fbem-31093	51	11	in	in	ADP
fbem-31093	51	12	real	real	ADJ
fbem-31093	51	13	-	-	PUNCT
fbem-31093	51	14	world	world	NOUN
fbem-31093	51	15	financial	financial	ADJ
fbem-31093	51	16	networks	network	NOUN
fbem-31093	51	17	,	,	PUNCT
fbem-31093	51	18	creating	create	VERB
fbem-31093	51	19	an	an	DET
fbem-31093	51	20	opportunity	opportunity	NOUN
fbem-31093	51	21	for	for	ADP
fbem-31093	51	22	novel	novel	ADJ
fbem-31093	51	23	approaches	approach	NOUN
fbem-31093	51	24	that	that	PRON
fbem-31093	51	25	specifically	specifically	ADV
fbem-31093	51	26	address	address	VERB
fbem-31093	51	27	these	these	DET
fbem-31093	51	28	challenges	challenge	NOUN
fbem-31093	51	29	[	[	X
fbem-31093	51	30	17	17	NUM
fbem-31093	51	31	]	]	SYM
fbem-31093	51	32	.	.	PUNCT
fbem-31093	52	1	3	3	X
fbem-31093	52	2	.	.	X
fbem-31093	52	3	methodology	methodology	NOUN
fbem-31093	52	4	in	in	ADP
fbem-31093	52	5	this	this	DET
fbem-31093	52	6	section	section	NOUN
fbem-31093	52	7	,	,	PUNCT
fbem-31093	52	8	we	we	PRON
fbem-31093	52	9	introduce	introduce	VERB
fbem-31093	52	10	finguard	finguard	ADJ
fbem-31093	52	11	-	-	PUNCT
fbem-31093	52	12	gnn	gnn	NOUN
fbem-31093	52	13	(	(	PUNCT
fbem-31093	52	14	financial	financial	ADJ
fbem-31093	52	15	guardian	guardian	NOUN
fbem-31093	52	16	graph	graph	NOUN
fbem-31093	52	17	neural	neural	ADJ
fbem-31093	52	18	network	network	NOUN
fbem-31093	52	19	)	)	PUNCT
fbem-31093	52	20	,	,	PUNCT
fbem-31093	52	21	our	our	PRON
fbem-31093	52	22	novel	novel	ADJ
fbem-31093	52	23	framework	framework	NOUN
fbem-31093	52	24	for	for	ADP
fbem-31093	52	25	financial	financial	ADJ
fbem-31093	52	26	fraud	fraud	NOUN
fbem-31093	52	27	detection	detection	NOUN
fbem-31093	52	28	that	that	PRON
fbem-31093	52	29	addresses	address	VERB
fbem-31093	52	30	the	the	DET
fbem-31093	52	31	challenges	challenge	NOUN
fbem-31093	52	32	of	of	ADP
fbem-31093	52	33	nonadditive	nonadditive	ADJ
fbem-31093	52	34	attribute	attribute	NOUN
fbem-31093	52	35	processing	processing	NOUN
fbem-31093	52	36	and	and	CCONJ
fbem-31093	52	37	node	node	ADJ
fbem-31093	52	38	distinguishability	distinguishability	NOUN
fbem-31093	52	39	in	in	ADP
fbem-31093	52	40	transaction	transaction	NOUN
fbem-31093	52	41	networks	network	NOUN
fbem-31093	52	42	.	.	PUNCT
fbem-31093	53	1	3.1	3.1	NUM
fbem-31093	53	2	.	.	PUNCT
fbem-31093	53	3	problem	problem	NOUN
fbem-31093	53	4	formulation	formulation	NOUN
fbem-31093	53	5	we	we	PRON
fbem-31093	53	6	formulate	formulate	VERB
fbem-31093	53	7	financial	financial	ADJ
fbem-31093	53	8	fraud	fraud	NOUN
fbem-31093	53	9	detection	detection	NOUN
fbem-31093	53	10	as	as	ADP
fbem-31093	53	11	a	a	DET
fbem-31093	53	12	node	node	ADJ
fbem-31093	53	13	classification	classification	NOUN
fbem-31093	53	14	task	task	NOUN
fbem-31093	53	15	on	on	ADP
fbem-31093	53	16	attributed	attribute	VERB
fbem-31093	53	17	graphs	graph	NOUN
fbem-31093	53	18	.	.	PUNCT
fbem-31093	54	1	given	give	VERB
fbem-31093	54	2	a	a	DET
fbem-31093	54	3	financial	financial	ADJ
fbem-31093	54	4	transaction	transaction	NOUN
fbem-31093	54	5	graph	graph	NOUN
fbem-31093	54	6	g	g	PROPN
fbem-31093	54	7	=	=	SYM
fbem-31093	54	8	(	(	PUNCT
fbem-31093	54	9	v	v	NOUN
fbem-31093	54	10	,	,	PUNCT
fbem-31093	54	11	e	e	NOUN
fbem-31093	54	12	,	,	PUNCT
fbem-31093	54	13	x	x	NOUN
fbem-31093	54	14	,	,	PUNCT
fbem-31093	54	15	y	y	PROPN
fbem-31093	54	16	)	)	PUNCT
fbem-31093	54	17	,	,	PUNCT
fbem-31093	54	18	where	where	SCONJ
fbem-31093	54	19	v	v	NOUN
fbem-31093	54	20	represents	represent	VERB
fbem-31093	54	21	the	the	DET
fbem-31093	54	22	set	set	NOUN
fbem-31093	54	23	of	of	ADP
fbem-31093	54	24	entities	entity	NOUN
fbem-31093	54	25	(	(	PUNCT
fbem-31093	54	26	users	user	NOUN
fbem-31093	54	27	,	,	PUNCT
fbem-31093	54	28	accounts	account	NOUN
fbem-31093	54	29	,	,	PUNCT
fbem-31093	54	30	merchants	merchant	NOUN
fbem-31093	54	31	)	)	PUNCT
fbem-31093	54	32	,	,	PUNCT
fbem-31093	54	33	e	e	PROPN
fbem-31093	54	34	denotes	denote	VERB
fbem-31093	54	35	transaction	transaction	NOUN
fbem-31093	54	36	relationships	relationship	NOUN
fbem-31093	54	37	,	,	PUNCT
fbem-31093	54	38	x	x	SYM
fbem-31093	54	39	∈	∈	PROPN
fbem-31093	54	40	ℝn×d	ℝn×d	PROPN
fbem-31093	54	41	is	be	AUX
fbem-31093	54	42	the	the	DET
fbem-31093	54	43	node	node	ADJ
fbem-31093	54	44	feature	feature	NOUN
fbem-31093	54	45	matrix	matrix	NOUN
fbem-31093	54	46	containing	contain	VERB
fbem-31093	54	47	transaction	transaction	NOUN
fbem-31093	54	48	statistics	statistic	NOUN
fbem-31093	54	49	and	and	CCONJ
fbem-31093	54	50	behavioral	behavioral	ADJ
fbem-31093	54	51	patterns	pattern	NOUN
fbem-31093	54	52	,	,	PUNCT
fbem-31093	54	53	and	and	CCONJ
fbem-31093	54	54	y	y	PROPN
fbem-31093	54	55	indicates	indicate	VERB
fbem-31093	54	56	known	known	ADJ
fbem-31093	54	57	fraud	fraud	NOUN
fbem-31093	54	58	labels	label	NOUN
fbem-31093	54	59	(	(	PUNCT
fbem-31093	54	60	0	0	NUM
fbem-31093	54	61	for	for	ADP
fbem-31093	54	62	legitimate	legitimate	ADJ
fbem-31093	54	63	,	,	PUNCT
fbem-31093	54	64	1	1	NUM
fbem-31093	54	65	for	for	ADP
fbem-31093	54	66	fraudulent	fraudulent	ADJ
fbem-31093	54	67	)	)	PUNCT
fbem-31093	54	68	.	.	PUNCT
fbem-31093	55	1	our	our	PRON
fbem-31093	55	2	objective	objective	NOUN
fbem-31093	55	3	is	be	AUX
fbem-31093	55	4	to	to	PART
fbem-31093	55	5	learn	learn	VERB
fbem-31093	55	6	a	a	DET
fbem-31093	55	7	mapping	mapping	NOUN
fbem-31093	55	8	function	function	NOUN
fbem-31093	55	9	f	f	X
fbem-31093	55	10	:	:	PUNCT
fbem-31093	55	11	(	(	PUNCT
fbem-31093	55	12	v	v	NOUN
fbem-31093	55	13	,	,	PUNCT
fbem-31093	55	14	e	e	NOUN
fbem-31093	55	15	,	,	PUNCT
fbem-31093	55	16	x	x	NOUN
fbem-31093	55	17	)	)	PUNCT
fbem-31093	55	18	→	→	PUNCT
fbem-31093	56	1	[	[	X
fbem-31093	56	2	0,1]|v|	0,1]|v|	NOUN
fbem-31093	56	3	that	that	PRON
fbem-31093	56	4	accurately	accurately	ADV
fbem-31093	56	5	predicts	predict	VERB
fbem-31093	56	6	fraud	fraud	NOUN
fbem-31093	56	7	probabilities	probability	NOUN
fbem-31093	56	8	for	for	ADP
fbem-31093	56	9	all	all	DET
fbem-31093	56	10	entities	entity	NOUN
fbem-31093	56	11	in	in	ADP
fbem-31093	56	12	the	the	DET
fbem-31093	56	13	network	network	NOUN
fbem-31093	56	14	.	.	PUNCT
fbem-31093	57	1	3.2	3.2	NUM
fbem-31093	57	2	.	.	PUNCT
fbem-31093	58	1	adaptive	adaptive	ADJ
fbem-31093	58	2	feature	feature	NOUN
fbem-31093	58	3	encoding	encode	VERB
fbem-31093	58	4	financial	financial	ADJ
fbem-31093	58	5	transaction	transaction	NOUN
fbem-31093	58	6	data	datum	NOUN
fbem-31093	58	7	contains	contain	VERB
fbem-31093	58	8	diverse	diverse	ADJ
fbem-31093	58	9	non	non	ADJ
fbem-31093	58	10	-	-	ADJ
fbem-31093	58	11	additive	additive	ADJ
fbem-31093	58	12	attributes	attribute	NOUN
fbem-31093	58	13	that	that	PRON
fbem-31093	58	14	can	can	AUX
fbem-31093	58	15	not	not	PART
fbem-31093	58	16	be	be	AUX
fbem-31093	58	17	meaningfully	meaningfully	ADV
fbem-31093	58	18	aggregated	aggregate	VERB
fbem-31093	58	19	through	through	ADP
fbem-31093	58	20	simple	simple	ADJ
fbem-31093	58	21	operations	operation	NOUN
fbem-31093	58	22	like	like	ADP
fbem-31093	58	23	summation	summation	NOUN
fbem-31093	58	24	or	or	CCONJ
fbem-31093	58	25	averaging	averaging	NOUN
fbem-31093	58	26	.	.	PUNCT
fbem-31093	59	1	to	to	PART
fbem-31093	59	2	address	address	VERB
fbem-31093	59	3	this	this	DET
fbem-31093	59	4	challenge	challenge	NOUN
fbem-31093	59	5	,	,	PUNCT
fbem-31093	59	6	we	we	PRON
fbem-31093	59	7	develop	develop	VERB
fbem-31093	59	8	two	two	NUM
fbem-31093	59	9	specialized	specialized	ADJ
fbem-31093	59	10	encoding	encoding	NOUN
fbem-31093	59	11	strategies	strategy	NOUN
fbem-31093	59	12	:	:	PUNCT
fbem-31093	59	13	3.2.1	3.2.1	NUM
fbem-31093	59	14	.	.	PUNCT
fbem-31093	59	15	risk	risk	NOUN
fbem-31093	59	16	-	-	PUNCT
fbem-31093	59	17	aware	aware	ADJ
fbem-31093	59	18	decision	decision	NOUN
fbem-31093	59	19	tree	tree	NOUN
fbem-31093	59	20	encoding	encoding	NOUN
fbem-31093	59	21	(	(	PUNCT
fbem-31093	59	22	radte	radte	NOUN
fbem-31093	59	23	)	)	PUNCT
fbem-31093	59	24	radte	radte	NOUN
fbem-31093	59	25	leverages	leverage	VERB
fbem-31093	59	26	the	the	DET
fbem-31093	59	27	discriminative	discriminative	NOUN
fbem-31093	59	28	power	power	NOUN
fbem-31093	59	29	of	of	ADP
fbem-31093	59	30	decision	decision	NOUN
fbem-31093	59	31	trees	tree	NOUN
fbem-31093	59	32	to	to	PART
fbem-31093	59	33	partition	partition	VERB
fbem-31093	59	34	continuous	continuous	ADJ
fbem-31093	59	35	features	feature	NOUN
fbem-31093	59	36	into	into	ADP
fbem-31093	59	37	bins	bin	NOUN
fbem-31093	59	38	that	that	PRON
fbem-31093	59	39	maximize	maximize	VERB
fbem-31093	59	40	fraud	fraud	NOUN
fbem-31093	59	41	separability	separability	NOUN
fbem-31093	59	42	:	:	PUNCT
fbem-31093	59	43	gini(𝐷	gini(𝐷	X
fbem-31093	59	44	)	)	PUNCT
fbem-31093	59	45	=	=	SYM
fbem-31093	60	1	1	1	NUM
fbem-31093	60	2	−	−	NOUN
fbem-31093	60	3	∑	∑	PUNCT
fbem-31093	60	4	𝐾	𝐾	PROPN
fbem-31093	60	5	𝑘=1	𝑘=1	NOUN
fbem-31093	60	6	𝑝𝑘	𝑝𝑘	ADP
fbem-31093	60	7	2	2	NUM
fbem-31093	60	8	for	for	ADP
fbem-31093	60	9	each	each	DET
fbem-31093	60	10	split	split	NOUN
fbem-31093	60	11	point	point	NOUN
fbem-31093	60	12	s	s	PART
fbem-31093	60	13	,	,	PUNCT
fbem-31093	60	14	we	we	PRON
fbem-31093	60	15	calculate	calculate	VERB
fbem-31093	60	16	the	the	DET
fbem-31093	60	17	information	information	NOUN
fbem-31093	60	18	gain	gain	NOUN
fbem-31093	60	19	:	:	PUNCT
fbem-31093	60	20	gain(𝐷	gain(𝐷	PROPN
fbem-31093	60	21	,	,	PUNCT
fbem-31093	60	22	𝑠	𝑠	PROPN
fbem-31093	60	23	)	)	PUNCT
fbem-31093	60	24	=	=	SYM
fbem-31093	60	25	gini(𝐷	gini(𝐷	NOUN
fbem-31093	60	26	)	)	PUNCT
fbem-31093	60	27	−	−	PROPN
fbem-31093	60	28	|𝐷𝑙	|𝐷𝑙	PROPN
fbem-31093	60	29	|	|	ADV
fbem-31093	60	30	|𝐷|	|𝐷|	NOUN
fbem-31093	60	31	gini(𝐷𝑙	gini(𝐷𝑙	PROPN
fbem-31093	60	32	)	)	PUNCT
fbem-31093	60	33	−	−	PROPN
fbem-31093	61	1	|𝐷𝑟	|𝐷𝑟	PROPN
fbem-31093	61	2	|	|	CCONJ
fbem-31093	61	3	|𝐷|	|𝐷|	NOUN
fbem-31093	61	4	gini(𝐷𝑟	gini(𝐷𝑟	PROPN
fbem-31093	61	5	)	)	PUNCT
fbem-31093	61	6	unlike	unlike	ADP
fbem-31093	61	7	conventional	conventional	ADJ
fbem-31093	61	8	binning	binning	NOUN
fbem-31093	61	9	that	that	PRON
fbem-31093	61	10	creates	create	VERB
fbem-31093	61	11	equal	equal	ADJ
fbem-31093	61	12	-	-	PUNCT
fbem-31093	61	13	width	width	ADJ
fbem-31093	61	14	or	or	CCONJ
fbem-31093	61	15	equal	equal	ADJ
fbem-31093	61	16	-	-	PUNCT
fbem-31093	61	17	frequency	frequency	NOUN
fbem-31093	61	18	partitions	partition	NOUN
fbem-31093	61	19	,	,	PUNCT
fbem-31093	61	20	radte	radte	NOUN
fbem-31093	61	21	adaptively	adaptively	ADV
fbem-31093	61	22	identifies	identify	VERB
fbem-31093	61	23	decision	decision	NOUN
fbem-31093	61	24	boundaries	boundary	NOUN
fbem-31093	61	25	that	that	PRON
fbem-31093	61	26	maximize	maximize	VERB
fbem-31093	61	27	fraud	fraud	NOUN
fbem-31093	61	28	detection	detection	NOUN
fbem-31093	61	29	capability	capability	NOUN
fbem-31093	61	30	.	.	PUNCT
fbem-31093	62	1	for	for	ADP
fbem-31093	62	2	categorical	categorical	ADJ
fbem-31093	62	3	features	feature	NOUN
fbem-31093	62	4	,	,	PUNCT
fbem-31093	62	5	we	we	PRON
fbem-31093	62	6	employ	employ	VERB
fbem-31093	62	7	a	a	DET
fbem-31093	62	8	similar	similar	ADJ
fbem-31093	62	9	approach	approach	NOUN
fbem-31093	62	10	based	base	VERB
fbem-31093	62	11	on	on	ADP
fbem-31093	62	12	category	category	NOUN
fbem-31093	62	13	-	-	PUNCT
fbem-31093	62	14	specific	specific	ADJ
fbem-31093	62	15	fraud	fraud	NOUN
fbem-31093	62	16	rates	rate	NOUN
fbem-31093	62	17	.	.	PUNCT
fbem-31093	63	1	3.2.2	3.2.2	X
fbem-31093	63	2	.	.	PUNCT
fbem-31093	64	1	bayesian	bayesian	NOUN
fbem-31093	64	2	evidence	evidence	NOUN
fbem-31093	64	3	encoding	encoding	NOUN
fbem-31093	64	4	(	(	PUNCT
fbem-31093	64	5	bee	bee	NOUN
fbem-31093	64	6	)	)	PUNCT
fbem-31093	64	7	bee	bee	NOUN
fbem-31093	64	8	transforms	transform	VERB
fbem-31093	64	9	features	feature	NOUN
fbem-31093	64	10	based	base	VERB
fbem-31093	64	11	on	on	ADP
fbem-31093	64	12	their	their	PRON
fbem-31093	64	13	statistical	statistical	ADJ
fbem-31093	64	14	correlation	correlation	NOUN
fbem-31093	64	15	with	with	ADP
fbem-31093	64	16	fraud	fraud	NOUN
fbem-31093	64	17	labels	label	NOUN
fbem-31093	64	18	,	,	PUNCT
fbem-31093	64	19	inspired	inspire	VERB
fbem-31093	64	20	by	by	ADP
fbem-31093	64	21	bayesian	bayesian	NOUN
fbem-31093	64	22	inference	inference	NOUN
fbem-31093	64	23	principles	principle	NOUN
fbem-31093	64	24	:	:	PUNCT
fbem-31093	64	25	bee𝑖	bee𝑖	VERB
fbem-31093	64	26	=	=	SYM
fbem-31093	64	27	ln	ln	PROPN
fbem-31093	64	28	(	(	PUNCT
fbem-31093	64	29	𝑃(𝑥𝑖	𝑃(𝑥𝑖	X
fbem-31093	64	30	|𝑦	|𝑦	X
fbem-31093	64	31	=	=	SYM
fbem-31093	64	32	0	0	NUM
fbem-31093	64	33	)	)	PUNCT
fbem-31093	64	34	𝑃(𝑥𝑖	𝑃(𝑥𝑖	VERB
fbem-31093	64	35	|𝑦	|𝑦	X
fbem-31093	64	36	=	=	NOUN
fbem-31093	64	37	1	1	NUM
fbem-31093	64	38	)	)	PUNCT
fbem-31093	64	39	)	)	PUNCT
fbem-31093	65	1	=	=	PUNCT
fbem-31093	65	2	ln	ln	ADJ
fbem-31093	65	3	(	(	PUNCT
fbem-31093	65	4	𝑛𝑖,normal/𝑁normal	𝑛𝑖,normal/𝑁normal	NUM
fbem-31093	65	5	𝑛𝑖,fraud/𝑁fraud	𝑛𝑖,fraud/𝑁fraud	NOUN
fbem-31093	65	6	)	)	PUNCT
fbem-31093	65	7	to	to	PART
fbem-31093	65	8	handle	handle	VERB
fbem-31093	65	9	sparse	sparse	ADJ
fbem-31093	65	10	bins	bin	NOUN
fbem-31093	65	11	and	and	CCONJ
fbem-31093	65	12	prevent	prevent	VERB
fbem-31093	65	13	numerical	numerical	ADJ
fbem-31093	65	14	instability	instability	NOUN
fbem-31093	65	15	,	,	PUNCT
fbem-31093	65	16	we	we	PRON
fbem-31093	65	17	incorporate	incorporate	VERB
fbem-31093	65	18	adaptive	adaptive	ADJ
fbem-31093	65	19	smoothing	smoothing	NOUN
fbem-31093	65	20	:	:	PUNCT
fbem-31093	65	21	bee𝑖	bee𝑖	VERB
fbem-31093	65	22	=	=	SYM
fbem-31093	65	23	ln	ln	ADJ
fbem-31093	65	24	(	(	PUNCT
fbem-31093	65	25	𝑛𝑖,normal	𝑛𝑖,normal	PROPN
fbem-31093	65	26	+	+	CCONJ
fbem-31093	65	27	𝛼𝑖	𝛼𝑖	ADP
fbem-31093	65	28	𝑁normal	𝑁normal	PROPN
fbem-31093	66	1	+	+	CCONJ
fbem-31093	66	2	∑	∑	PUNCT
fbem-31093	66	3	𝑗	𝑗	PROPN
fbem-31093	66	4	𝛼𝑗	𝛼𝑗	PROPN
fbem-31093	66	5	⋅	⋅	PROPN
fbem-31093	66	6	𝑁fraud	𝑁fraud	PROPN
fbem-31093	66	7	+	+	PROPN
fbem-31093	66	8	∑	∑	PROPN
fbem-31093	66	9	𝑗	𝑗	PROPN
fbem-31093	66	10	𝛼𝑗	𝛼𝑗	PROPN
fbem-31093	66	11	𝑛𝑖,fraud	𝑛𝑖,fraud	PROPN
fbem-31093	66	12	+	+	CCONJ
fbem-31093	66	13	𝛼𝑖	𝛼𝑖	PROPN
fbem-31093	66	14	)	)	PUNCT
fbem-31093	66	15	where	where	SCONJ
fbem-31093	66	16	$	$	SYM
fbem-31093	66	17	\alpha_i$	\alpha_i$	NOUN
fbem-31093	66	18	is	be	AUX
fbem-31093	66	19	dynamically	dynamically	ADV
fbem-31093	66	20	adjusted	adjust	VERB
fbem-31093	66	21	based	base	VERB
fbem-31093	66	22	on	on	ADP
fbem-31093	66	23	bin	bin	PROPN
fbem-31093	66	24	population	population	NOUN
fbem-31093	66	25	density	density	NOUN
fbem-31093	66	26	.	.	PUNCT
fbem-31093	67	1	3.3	3.3	NUM
fbem-31093	67	2	.	.	PUNCT
fbem-31093	67	3	cascaded	cascade	VERB
fbem-31093	67	4	risk	risk	NOUN
fbem-31093	67	5	diffusion	diffusion	NOUN
fbem-31093	67	6	(	(	PUNCT
fbem-31093	67	7	crd	crd	NOUN
fbem-31093	67	8	)	)	PUNCT
fbem-31093	67	9	financial	financial	ADJ
fbem-31093	67	10	fraud	fraud	NOUN
fbem-31093	67	11	risk	risk	NOUN
fbem-31093	67	12	propagates	propagate	VERB
fbem-31093	67	13	through	through	ADP
fbem-31093	67	14	transaction	transaction	NOUN
fbem-31093	67	15	networks	network	NOUN
fbem-31093	67	16	in	in	ADP
fbem-31093	67	17	complex	complex	ADJ
fbem-31093	67	18	patterns	pattern	NOUN
fbem-31093	67	19	,	,	PUNCT
fbem-31093	67	20	with	with	ADP
fbem-31093	67	21	different	different	ADJ
fbem-31093	67	22	types	type	NOUN
fbem-31093	67	23	of	of	ADP
fbem-31093	67	24	connections	connection	NOUN
fbem-31093	67	25	carrying	carry	VERB
fbem-31093	67	26	varying	vary	VERB
fbem-31093	67	27	risk	risk	NOUN
fbem-31093	67	28	implications	implication	NOUN
fbem-31093	67	29	.	.	PUNCT
fbem-31093	68	1	our	our	PRON
fbem-31093	68	2	crd	crd	PROPN
fbem-31093	68	3	mechanism	mechanism	NOUN
fbem-31093	68	4	models	model	NOUN
fbem-31093	68	5	this	this	DET
fbem-31093	68	6	process	process	NOUN
fbem-31093	68	7	through	through	ADP
fbem-31093	68	8	:	:	PUNCT
fbem-31093	68	9	123	123	NUM
fbem-31093	68	10	3.3.1	3.3.1	NUM
fbem-31093	68	11	.	.	PUNCT
fbem-31093	69	1	multi	multi	ADJ
fbem-31093	69	2	-	-	ADJ
fbem-31093	69	3	channel	channel	ADJ
fbem-31093	69	4	feature	feature	NOUN
fbem-31093	69	5	transformation	transformation	NOUN
fbem-31093	69	6	we	we	PRON
fbem-31093	69	7	transform	transform	VERB
fbem-31093	69	8	node	node	NOUN
fbem-31093	69	9	features	feature	NOUN
fbem-31093	69	10	through	through	ADP
fbem-31093	69	11	parallel	parallel	ADJ
fbem-31093	69	12	risk	risk	NOUN
fbem-31093	69	13	-	-	PUNCT
fbem-31093	69	14	aware	aware	ADJ
fbem-31093	69	15	channels	channel	NOUN
fbem-31093	69	16	:	:	PUNCT
fbem-31093	69	17	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	69	18	base	base	NOUN
fbem-31093	69	19	=	=	PUNCT
fbem-31093	69	20	mlpbase(𝑥𝑖	mlpbase(𝑥𝑖	VERB
fbem-31093	69	21	)	)	PUNCT
fbem-31093	69	22	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	69	23	risk	risk	NOUN
fbem-31093	69	24	=	=	PUNCT
fbem-31093	69	25	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	69	26	base	base	NOUN
fbem-31093	69	27	+	+	CCONJ
fbem-31093	69	28	𝛾	𝛾	ADP
fbem-31093	69	29	⋅	⋅	PROPN
fbem-31093	69	30	relu(𝑊riskℎ𝑖	relu(𝑊riskℎ𝑖	ADJ
fbem-31093	69	31	base	base	NOUN
fbem-31093	69	32	)	)	PUNCT
fbem-31093	69	33	where	where	SCONJ
fbem-31093	69	34	γ	γ	PROPN
fbem-31093	69	35	controls	control	VERB
fbem-31093	69	36	the	the	DET
fbem-31093	69	37	influence	influence	NOUN
fbem-31093	69	38	of	of	ADP
fbem-31093	69	39	risk	risk	NOUN
fbem-31093	69	40	-	-	PUNCT
fbem-31093	69	41	specific	specific	ADJ
fbem-31093	69	42	features	feature	NOUN
fbem-31093	69	43	.	.	PUNCT
fbem-31093	70	1	3.3.2	3.3.2	X
fbem-31093	70	2	.	.	NUM
fbem-31093	70	3	cascaded	cascade	VERB
fbem-31093	70	4	message	message	NOUN
fbem-31093	70	5	propagation	propagation	NOUN
fbem-31093	70	6	instead	instead	ADV
fbem-31093	70	7	of	of	ADP
fbem-31093	70	8	treating	treat	VERB
fbem-31093	70	9	all	all	DET
fbem-31093	70	10	neighbors	neighbor	NOUN
fbem-31093	70	11	equally	equally	ADV
fbem-31093	70	12	,	,	PUNCT
fbem-31093	70	13	we	we	PRON
fbem-31093	70	14	implement	implement	VERB
fbem-31093	70	15	a	a	DET
fbem-31093	70	16	cascaded	cascade	VERB
fbem-31093	70	17	propagation	propagation	NOUN
fbem-31093	70	18	mechanism	mechanism	NOUN
fbem-31093	70	19	with	with	ADP
fbem-31093	70	20	three	three	NUM
fbem-31093	70	21	specialized	specialized	ADJ
fbem-31093	70	22	aggregators	aggregator	NOUN
fbem-31093	70	23	:	:	PUNCT
fbem-31093	70	24	global	global	ADJ
fbem-31093	70	25	aggregator	aggregator	NOUN
fbem-31093	70	26	.	.	PUNCT
fbem-31093	71	1	𝑚𝑖	𝑚𝑖	ADP
fbem-31093	71	2	global	global	ADJ
fbem-31093	71	3	=	=	SYM
fbem-31093	71	4	aggglobal	aggglobal	ADJ
fbem-31093	71	5	(	(	PUNCT
fbem-31093	71	6	{	{	PUNCT
fbem-31093	71	7	ℎ𝑗	ℎ𝑗	DET
fbem-31093	71	8	base	base	NOUN
fbem-31093	71	9	:	:	PUNCT
fbem-31093	71	10	𝑗	𝑗	X
fbem-31093	71	11	∈	∈	NOUN
fbem-31093	71	12	𝒩(𝑖	𝒩(𝑖	NOUN
fbem-31093	71	13	)	)	PUNCT
fbem-31093	71	14	}	}	PUNCT
fbem-31093	71	15	)	)	PUNCT
fbem-31093	71	16	group	group	NOUN
fbem-31093	71	17	-	-	PUNCT
fbem-31093	71	18	aware	aware	ADJ
fbem-31093	71	19	aggregator	aggregator	NOUN
fbem-31093	71	20	.	.	PUNCT
fbem-31093	72	1	𝑚𝑖	𝑚𝑖	NOUN
fbem-31093	72	2	group	group	NOUN
fbem-31093	72	3	=	=	PUNCT
fbem-31093	72	4	∑	∑	PROPN
fbem-31093	72	5	𝑔∈𝒢	𝑔∈𝒢	X
fbem-31093	72	6	agg𝑔	agg𝑔	NOUN
fbem-31093	72	7	(	(	PUNCT
fbem-31093	72	8	{	{	PUNCT
fbem-31093	72	9	ℎ𝑗	ℎ𝑗	DET
fbem-31093	72	10	base	base	NOUN
fbem-31093	72	11	:	:	PUNCT
fbem-31093	72	12	𝑗	𝑗	PROPN
fbem-31093	72	13	∈	∈	ADJ
fbem-31093	72	14	𝒩(𝑖	𝒩(𝑖	NOUN
fbem-31093	72	15	)	)	PUNCT
fbem-31093	72	16	∩	∩	ADJ
fbem-31093	72	17	𝑔	𝑔	NOUN
fbem-31093	72	18	}	}	PUNCT
fbem-31093	72	19	)	)	PUNCT
fbem-31093	72	20	risk	risk	NOUN
fbem-31093	72	21	-	-	PUNCT
fbem-31093	72	22	sensitive	sensitive	ADJ
fbem-31093	72	23	aggregator	aggregator	NOUN
fbem-31093	72	24	.	.	PUNCT
fbem-31093	73	1	𝑚𝑖	𝑚𝑖	NOUN
fbem-31093	73	2	risk	risk	NOUN
fbem-31093	73	3	=	=	SYM
fbem-31093	73	4	∑	∑	PUNCT
fbem-31093	73	5	𝑗∈𝒩(𝑖	𝑗∈𝒩(𝑖	PUNCT
fbem-31093	73	6	)	)	PUNCT
fbem-31093	73	7	𝑤𝑖𝑗	𝑤𝑖𝑗	PROPN
fbem-31093	73	8	risk	risk	NOUN
fbem-31093	73	9	⋅	⋅	PROPN
fbem-31093	73	10	ℎ𝑗	ℎ𝑗	PRON
fbem-31093	73	11	risk	risk	NOUN
fbem-31093	73	12	where	where	SCONJ
fbem-31093	73	13	wij	wij	PROPN
fbem-31093	73	14	risk	risk	NOUN
fbem-31093	73	15	incorporates	incorporate	VERB
fbem-31093	73	16	both	both	PRON
fbem-31093	73	17	topological	topological	ADJ
fbem-31093	73	18	distance	distance	NOUN
fbem-31093	73	19	and	and	CCONJ
fbem-31093	73	20	risk	risk	NOUN
fbem-31093	73	21	similarity	similarity	NOUN
fbem-31093	73	22	.	.	PUNCT
fbem-31093	74	1	3.4	3.4	NUM
fbem-31093	74	2	.	.	PUNCT
fbem-31093	74	3	responsive	responsive	ADJ
fbem-31093	74	4	group	group	NOUN
fbem-31093	74	5	allocation	allocation	NOUN
fbem-31093	74	6	(	(	PUNCT
fbem-31093	74	7	rga	rga	PROPN
fbem-31093	74	8	)	)	PUNCT
fbem-31093	74	9	to	to	PART
fbem-31093	74	10	enhance	enhance	VERB
fbem-31093	74	11	the	the	DET
fbem-31093	74	12	distinguishability	distinguishability	NOUN
fbem-31093	74	13	of	of	ADP
fbem-31093	74	14	fraud	fraud	NOUN
fbem-31093	74	15	patterns	pattern	NOUN
fbem-31093	74	16	,	,	PUNCT
fbem-31093	74	17	we	we	PRON
fbem-31093	74	18	dynamically	dynamically	ADV
fbem-31093	74	19	cluster	cluster	NOUN
fbem-31093	74	20	nodes	node	NOUN
fbem-31093	74	21	based	base	VERB
fbem-31093	74	22	on	on	ADP
fbem-31093	74	23	evolving	evolve	VERB
fbem-31093	74	24	risk	risk	NOUN
fbem-31093	74	25	assessments	assessment	NOUN
fbem-31093	74	26	:	:	PUNCT
fbem-31093	74	27	temporal	temporal	ADJ
fbem-31093	74	28	risk	risk	NOUN
fbem-31093	74	29	estimation	estimation	NOUN
fbem-31093	74	30	.	.	PUNCT
fbem-31093	75	1	after	after	ADP
fbem-31093	75	2	each	each	DET
fbem-31093	75	3	training	training	NOUN
fbem-31093	75	4	epoch	epoch	PROPN
fbem-31093	75	5	t	t	PROPN
fbem-31093	75	6	,	,	PUNCT
fbem-31093	75	7	we	we	PRON
fbem-31093	75	8	update	update	VERB
fbem-31093	75	9	node	node	ADJ
fbem-31093	75	10	risk	risk	NOUN
fbem-31093	75	11	scores	score	NOUN
fbem-31093	75	12	:	:	PUNCT
fbem-31093	75	13	𝑟𝑖	𝑟𝑖	X
fbem-31093	75	14	𝑡	𝑡	X
fbem-31093	75	15	=	=	PROPN
fbem-31093	75	16	sigmoid(𝑓𝜃	sigmoid(𝑓𝜃	PROPN
fbem-31093	75	17	(	(	PUNCT
fbem-31093	75	18	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	75	19	𝑡	𝑡	PROPN
fbem-31093	75	20	)	)	PUNCT
fbem-31093	75	21	)	)	PUNCT
fbem-31093	76	1	we	we	PRON
fbem-31093	76	2	stabilize	stabilize	VERB
fbem-31093	76	3	these	these	DET
fbem-31093	76	4	estimates	estimate	NOUN
fbem-31093	76	5	using	use	VERB
fbem-31093	76	6	an	an	DET
fbem-31093	76	7	exponential	exponential	ADJ
fbem-31093	76	8	moving	move	VERB
fbem-31093	76	9	average	average	ADJ
fbem-31093	76	10	:	:	PUNCT
fbem-31093	76	11	𝑟𝑖	𝑟𝑖	ADV
fbem-31093	76	12	𝑡	𝑡	PROPN
fbem-31093	76	13	=	=	PROPN
fbem-31093	76	14	𝛽𝑟𝑖	𝛽𝑟𝑖	PROPN
fbem-31093	76	15	𝑡−1	𝑡−1	PROPN
fbem-31093	76	16	+	+	CCONJ
fbem-31093	76	17	(	(	PUNCT
fbem-31093	76	18	1	1	NUM
fbem-31093	76	19	−	−	PRON
fbem-31093	76	20	𝛽)𝑟𝑖	𝛽)𝑟𝑖	PROPN
fbem-31093	76	21	𝑡	𝑡	PROPN
fbem-31093	76	22	adaptive	adaptive	ADJ
fbem-31093	76	23	cluster	cluster	NOUN
fbem-31093	76	24	assignment	assignment	NOUN
fbem-31093	76	25	.	.	PUNCT
fbem-31093	77	1	based	base	VERB
fbem-31093	77	2	on	on	ADP
fbem-31093	77	3	these	these	DET
fbem-31093	77	4	smoothed	smooth	VERB
fbem-31093	77	5	risk	risk	NOUN
fbem-31093	77	6	scores	score	NOUN
fbem-31093	77	7	,	,	PUNCT
fbem-31093	77	8	we	we	PRON
fbem-31093	77	9	partition	partition	VERB
fbem-31093	77	10	nodes	node	NOUN
fbem-31093	77	11	into	into	ADP
fbem-31093	77	12	three	three	NUM
fbem-31093	77	13	functional	functional	ADJ
fbem-31093	77	14	clusters	cluster	NOUN
fbem-31093	77	15	:	:	PUNCT
fbem-31093	77	16	𝑐𝑖	𝑐𝑖	NOUN
fbem-31093	77	17	𝑡	𝑡	NOUN
fbem-31093	77	18	=	=	NOUN
fbem-31093	77	19	{	{	PUNCT
fbem-31093	77	20	low	low	ADJ
fbem-31093	77	21	-	-	PUNCT
fbem-31093	77	22	risk	risk	NOUN
fbem-31093	77	23	cluster	cluster	NOUN
fbem-31093	77	24	,	,	PUNCT
fbem-31093	77	25	if	if	SCONJ
fbem-31093	77	26	𝑟𝑖	𝑟𝑖	PART
fbem-31093	77	27	𝑡	𝑡	VERB
fbem-31093	77	28	<	<	X
fbem-31093	77	29	𝜏1	𝜏1	NOUN
fbem-31093	77	30	transition	transition	NOUN
fbem-31093	77	31	cluster	cluster	NOUN
fbem-31093	77	32	,	,	PUNCT
fbem-31093	77	33	if	if	SCONJ
fbem-31093	77	34	𝜏1	𝜏1	NOUN
fbem-31093	77	35	≤	≤	PROPN
fbem-31093	77	36	𝑟𝑖	𝑟𝑖	VERB
fbem-31093	77	37	𝑡	𝑡	PROPN
fbem-31093	77	38	≤	≤	NUM
fbem-31093	77	39	𝜏2	𝜏2	ADJ
fbem-31093	77	40	high	high	ADJ
fbem-31093	77	41	-	-	PUNCT
fbem-31093	77	42	risk	risk	NOUN
fbem-31093	77	43	cluster	cluster	NOUN
fbem-31093	77	44	,	,	PUNCT
fbem-31093	77	45	if	if	SCONJ
fbem-31093	77	46	𝑟𝑖	𝑟𝑖	ADV
fbem-31093	77	47	𝑡	𝑡	VERB
fbem-31093	77	48	>	>	X
fbem-31093	77	49	𝜏2	𝜏2	PROPN
fbem-31093	77	50	where	where	SCONJ
fbem-31093	77	51	thresholds	threshold	NOUN
fbem-31093	77	52	τ1	τ1	NOUN
fbem-31093	77	53	and	and	CCONJ
fbem-31093	77	54	τ2	τ2	NOUN
fbem-31093	77	55	are	be	AUX
fbem-31093	77	56	dynamically	dynamically	ADV
fbem-31093	77	57	adjusted	adjust	VERB
fbem-31093	77	58	based	base	VERB
fbem-31093	77	59	on	on	ADP
fbem-31093	77	60	the	the	DET
fbem-31093	77	61	global	global	ADJ
fbem-31093	77	62	risk	risk	NOUN
fbem-31093	77	63	distribution	distribution	NOUN
fbem-31093	77	64	.	.	PUNCT
fbem-31093	78	1	cluster	cluster	NOUN
fbem-31093	78	2	-	-	PUNCT
fbem-31093	78	3	aware	aware	ADJ
fbem-31093	78	4	representation	representation	NOUN
fbem-31093	78	5	enhancement	enhancement	NOUN
fbem-31093	78	6	.	.	PUNCT
fbem-31093	79	1	we	we	PRON
fbem-31093	79	2	enhance	enhance	VERB
fbem-31093	79	3	node	node	ADJ
fbem-31093	79	4	representations	representation	NOUN
fbem-31093	79	5	by	by	ADP
fbem-31093	79	6	integrating	integrate	VERB
fbem-31093	79	7	cluster	cluster	NOUN
fbem-31093	79	8	-	-	PUNCT
fbem-31093	79	9	specific	specific	ADJ
fbem-31093	79	10	information	information	NOUN
fbem-31093	79	11	:	:	PUNCT
fbem-31093	79	12	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	79	13	enhanced	enhance	VERB
fbem-31093	79	14	=	=	PUNCT
fbem-31093	79	15	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	79	16	base	base	NOUN
fbem-31093	79	17	+	+	CCONJ
fbem-31093	79	18	∑	∑	PROPN
fbem-31093	79	19	𝐾	𝐾	PROPN
fbem-31093	79	20	𝑘=1	𝑘=1	PROPN
fbem-31093	79	21	𝛼𝑘	𝛼𝑘	PROPN
fbem-31093	79	22	⋅	⋅	PROPN
fbem-31093	79	23	𝕀(𝑖	𝕀(𝑖	PROPN
fbem-31093	79	24	∈	∈	PROPN
fbem-31093	79	25	𝑐𝑘	𝑐𝑘	NOUN
fbem-31093	79	26	)	)	PUNCT
fbem-31093	79	27	⋅	⋅	PROPN
fbem-31093	79	28	𝜇𝑘	𝜇𝑘	NOUN
fbem-31093	79	29	where	where	SCONJ
fbem-31093	79	30	μk	μk	PROPN
fbem-31093	79	31	is	be	AUX
fbem-31093	79	32	the	the	DET
fbem-31093	79	33	learned	learn	VERB
fbem-31093	79	34	prototype	prototype	NOUN
fbem-31093	79	35	representation	representation	NOUN
fbem-31093	79	36	for	for	ADP
fbem-31093	79	37	cluster	cluster	NOUN
fbem-31093	79	38	k	k	PROPN
fbem-31093	79	39	,	,	PUNCT
fbem-31093	79	40	and	and	CCONJ
fbem-31093	79	41	αk	αk	SCONJ
fbem-31093	79	42	controls	control	VERB
fbem-31093	79	43	the	the	DET
fbem-31093	79	44	influence	influence	NOUN
fbem-31093	79	45	of	of	ADP
fbem-31093	79	46	cluster	cluster	NOUN
fbem-31093	79	47	information	information	NOUN
fbem-31093	79	48	.	.	PUNCT
fbem-31093	80	1	optimization	optimization	NOUN
fbem-31093	80	2	objective	objective	NOUN
fbem-31093	80	3	.	.	PUNCT
fbem-31093	81	1	our	our	PRON
fbem-31093	81	2	training	training	NOUN
fbem-31093	81	3	objective	objective	NOUN
fbem-31093	81	4	combines	combine	VERB
fbem-31093	81	5	multiple	multiple	ADJ
fbem-31093	81	6	loss	loss	NOUN
fbem-31093	81	7	components	component	NOUN
fbem-31093	81	8	:	:	PUNCT
fbem-31093	81	9	ℒ	ℒ	PROPN
fbem-31093	81	10	=	=	SYM
fbem-31093	81	11	ℒbce	ℒbce	PROPN
fbem-31093	81	12	+	+	CCONJ
fbem-31093	81	13	𝜆1ℒcluster	𝜆1ℒcluster	PROPN
fbem-31093	81	14	+	+	CCONJ
fbem-31093	81	15	𝜆2ℒcontrastive	𝜆2ℒcontrastive	ADJ
fbem-31093	81	16	the	the	DET
fbem-31093	81	17	primary	primary	ADJ
fbem-31093	81	18	binary	binary	PROPN
fbem-31093	81	19	cross	cross	PROPN
fbem-31093	81	20	-	-	ADJ
fbem-31093	81	21	entropy	entropy	ADJ
fbem-31093	81	22	loss	loss	NOUN
fbem-31093	81	23	supervises	supervise	VERB
fbem-31093	81	24	fraud	fraud	NOUN
fbem-31093	81	25	prediction	prediction	NOUN
fbem-31093	81	26	:	:	PUNCT
fbem-31093	82	1	ℒbce	ℒbce	PROPN
fbem-31093	82	2	=	=	SYM
fbem-31093	82	3	−	−	PROPN
fbem-31093	82	4	1	1	NUM
fbem-31093	82	5	|𝒱𝐿	|𝒱𝐿	NOUN
fbem-31093	82	6	|	|	ADV
fbem-31093	82	7	∑	∑	PUNCT
fbem-31093	82	8	𝑖∈𝒱𝐿	𝑖∈𝒱𝐿	NOUN
fbem-31093	82	9	[	[	X
fbem-31093	82	10	𝑦𝑖	𝑦𝑖	INTJ
fbem-31093	82	11	log	log	NOUN
fbem-31093	82	12	(	(	PUNCT
fbem-31093	82	13	𝑟𝑖	𝑟𝑖	ADV
fbem-31093	82	14	)	)	PUNCT
fbem-31093	83	1	+	+	CCONJ
fbem-31093	83	2	(	(	PUNCT
fbem-31093	83	3	1	1	NUM
fbem-31093	83	4	−	−	NOUN
fbem-31093	83	5	𝑦𝑖	𝑦𝑖	PROPN
fbem-31093	83	6	)	)	PUNCT
fbem-31093	83	7	log	log	NOUN
fbem-31093	83	8	(	(	PUNCT
fbem-31093	83	9	1	1	NUM
fbem-31093	83	10	−	−	NUM
fbem-31093	83	11	𝑟𝑖	𝑟𝑖	NUM
fbem-31093	83	12	)	)	PUNCT
fbem-31093	83	13	]	]	PUNCT
fbem-31093	84	1	the	the	DET
fbem-31093	84	2	cluster	cluster	NOUN
fbem-31093	84	3	coherence	coherence	NOUN
fbem-31093	84	4	loss	loss	NOUN
fbem-31093	84	5	encourages	encourage	VERB
fbem-31093	84	6	similar	similar	ADJ
fbem-31093	84	7	representations	representation	NOUN
fbem-31093	84	8	within	within	ADP
fbem-31093	84	9	clusters	cluster	NOUN
fbem-31093	84	10	:	:	PUNCT
fbem-31093	84	11	ℒcluster	ℒcluster	PROPN
fbem-31093	84	12	=	=	SYM
fbem-31093	84	13	∑	∑	PUNCT
fbem-31093	84	14	𝐾	𝐾	PROPN
fbem-31093	84	15	𝑘=1	𝑘=1	SYM
fbem-31093	84	16	1	1	NUM
fbem-31093	84	17	|𝑐𝑘	|𝑐𝑘	NOUN
fbem-31093	84	18	|	|	ADV
fbem-31093	84	19	∑	∑	ADV
fbem-31093	84	20	𝑖∈𝑐𝑘	𝑖∈𝑐𝑘	ADJ
fbem-31093	84	21	∥	∥	PUNCT
fbem-31093	84	22	ℎ𝑖	ℎ𝑖	NOUN
fbem-31093	84	23	enhanced	enhance	VERB
fbem-31093	84	24	−	−	PROPN
fbem-31093	84	25	𝜇𝑘	𝜇𝑘	NOUN
fbem-31093	84	26	∥2	∥2	PRON
fbem-31093	84	27	2	2	NUM
fbem-31093	84	28	the	the	DET
fbem-31093	84	29	contrastive	contrastive	ADJ
fbem-31093	84	30	loss	loss	NOUN
fbem-31093	84	31	enhances	enhance	VERB
fbem-31093	84	32	separation	separation	NOUN
fbem-31093	84	33	between	between	ADP
fbem-31093	84	34	fraud	fraud	NOUN
fbem-31093	84	35	and	and	CCONJ
fbem-31093	84	36	legitimate	legitimate	ADJ
fbem-31093	84	37	patterns	pattern	NOUN
fbem-31093	84	38	:	:	PUNCT
fbem-31093	85	1	ℒcontrastive	ℒcontrastive	PROPN
fbem-31093	85	2	=	=	PUNCT
fbem-31093	85	3	∑	∑	PUNCT
fbem-31093	85	4	𝑖,𝑗∈𝒱𝐿	𝑖,𝑗∈𝒱𝐿	PUNCT
fbem-31093	86	1	[	[	X
fbem-31093	86	2	𝑦𝑖	𝑦𝑖	INTJ
fbem-31093	86	3	=	=	SYM
fbem-31093	86	4	𝑦𝑗	𝑦𝑗	PROPN
fbem-31093	86	5	]	]	PUNCT
fbem-31093	86	6	⋅	⋅	X
fbem-31093	86	7	𝑑(ℎ𝑖	𝑑(ℎ𝑖	PROPN
fbem-31093	86	8	,	,	PUNCT
fbem-31093	86	9	ℎ𝑗	ℎ𝑗	ADV
fbem-31093	86	10	)	)	PUNCT
fbem-31093	86	11	−	−	PROPN
fbem-31093	87	1	[	[	X
fbem-31093	87	2	𝑦𝑖	𝑦𝑖	INTJ
fbem-31093	87	3	≠	≠	PROPN
fbem-31093	87	4	𝑦𝑗	𝑦𝑗	X
fbem-31093	87	5	]	]	PUNCT
fbem-31093	87	6	⋅	⋅	PROPN
fbem-31093	87	7	𝑚𝑖𝑛(𝛿	𝑚𝑖𝑛(𝛿	PROPN
fbem-31093	87	8	,	,	PUNCT
fbem-31093	87	9	𝑑(ℎ𝑖	𝑑(ℎ𝑖	NOUN
fbem-31093	87	10	,	,	PUNCT
fbem-31093	87	11	ℎ𝑗	ℎ𝑗	PROPN
fbem-31093	87	12	)	)	PUNCT
fbem-31093	87	13	)	)	PUNCT
fbem-31093	87	14	where	where	SCONJ
fbem-31093	87	15	d(⋅,⋅	d(⋅,⋅	NOUN
fbem-31093	87	16	)	)	PUNCT
fbem-31093	87	17	measures	measure	NOUN
fbem-31093	87	18	representation	representation	NOUN
fbem-31093	87	19	distance	distance	NOUN
fbem-31093	87	20	and	and	CCONJ
fbem-31093	87	21	δ	δ	PROPN
fbem-31093	87	22	is	be	AUX
fbem-31093	87	23	a	a	DET
fbem-31093	87	24	margin	margin	NOUN
fbem-31093	87	25	hyperparameter	hyperparameter	NOUN
fbem-31093	87	26	.	.	PUNCT
fbem-31093	88	1	this	this	DET
fbem-31093	88	2	multi	multi	ADJ
fbem-31093	88	3	-	-	ADJ
fbem-31093	88	4	objective	objective	ADJ
fbem-31093	88	5	optimization	optimization	NOUN
fbem-31093	88	6	ensures	ensure	VERB
fbem-31093	88	7	that	that	SCONJ
fbem-31093	88	8	finguard	finguard	NOUN
fbem-31093	88	9	-	-	PUNCT
fbem-31093	88	10	gnn	gnn	NOUN
fbem-31093	88	11	simultaneously	simultaneously	ADV
fbem-31093	88	12	learns	learn	VERB
fbem-31093	88	13	discriminative	discriminative	NOUN
fbem-31093	88	14	node	node	NOUN
fbem-31093	88	15	representations	representation	NOUN
fbem-31093	88	16	,	,	PUNCT
fbem-31093	88	17	coherent	coherent	ADJ
fbem-31093	88	18	risk	risk	NOUN
fbem-31093	88	19	clusters	cluster	NOUN
fbem-31093	88	20	,	,	PUNCT
fbem-31093	88	21	and	and	CCONJ
fbem-31093	88	22	effective	effective	ADJ
fbem-31093	88	23	fraud	fraud	NOUN
fbem-31093	88	24	detection	detection	NOUN
fbem-31093	88	25	boundaries	boundary	NOUN
fbem-31093	88	26	.	.	PUNCT
fbem-31093	89	1	4	4	X
fbem-31093	89	2	.	.	X
fbem-31093	89	3	experiments	experiment	NOUN
fbem-31093	89	4	in	in	ADP
fbem-31093	89	5	this	this	DET
fbem-31093	89	6	section	section	NOUN
fbem-31093	89	7	,	,	PUNCT
fbem-31093	89	8	we	we	PRON
fbem-31093	89	9	evaluate	evaluate	VERB
fbem-31093	89	10	the	the	DET
fbem-31093	89	11	effectiveness	effectiveness	NOUN
fbem-31093	89	12	of	of	ADP
fbem-31093	89	13	finguardgnn	finguardgnn	NOUN
fbem-31093	89	14	through	through	ADP
fbem-31093	89	15	comprehensive	comprehensive	ADJ
fbem-31093	89	16	experiments	experiment	NOUN
fbem-31093	89	17	on	on	ADP
fbem-31093	89	18	real	real	ADJ
fbem-31093	89	19	-	-	PUNCT
fbem-31093	89	20	world	world	NOUN
fbem-31093	89	21	financial	financial	ADJ
fbem-31093	89	22	datasets	dataset	NOUN
fbem-31093	89	23	.	.	PUNCT
fbem-31093	90	1	we	we	PRON
fbem-31093	90	2	first	first	ADV
fbem-31093	90	3	introduce	introduce	VERB
fbem-31093	90	4	the	the	DET
fbem-31093	90	5	experimental	experimental	ADJ
fbem-31093	90	6	setup	setup	NOUN
fbem-31093	90	7	,	,	PUNCT
fbem-31093	90	8	followed	follow	VERB
fbem-31093	90	9	by	by	ADP
fbem-31093	90	10	performance	performance	NOUN
fbem-31093	90	11	comparison	comparison	NOUN
fbem-31093	90	12	with	with	ADP
fbem-31093	90	13	state	state	NOUN
fbem-31093	90	14	-	-	PUNCT
fbem-31093	90	15	of	of	ADP
fbem-31093	90	16	-	-	PUNCT
fbem-31093	90	17	the	the	DET
fbem-31093	90	18	-	-	PUNCT
fbem-31093	90	19	art	art	NOUN
fbem-31093	90	20	methods	method	NOUN
fbem-31093	90	21	,	,	PUNCT
fbem-31093	90	22	ablation	ablation	NOUN
fbem-31093	90	23	studies	study	NOUN
fbem-31093	90	24	,	,	PUNCT
fbem-31093	90	25	and	and	CCONJ
fbem-31093	90	26	in	in	ADP
fbem-31093	90	27	-	-	PUNCT
fbem-31093	90	28	depth	depth	NOUN
fbem-31093	90	29	analysis	analysis	NOUN
fbem-31093	90	30	of	of	ADP
fbem-31093	90	31	key	key	ADJ
fbem-31093	90	32	components	component	NOUN
fbem-31093	90	33	.	.	PUNCT
fbem-31093	91	1	4.1	4.1	NUM
fbem-31093	91	2	.	.	PUNCT
fbem-31093	91	3	experimental	experimental	ADJ
fbem-31093	91	4	setup	setup	NOUN
fbem-31093	91	5	datasets	dataset	NOUN
fbem-31093	91	6	.	.	PUNCT
fbem-31093	92	1	we	we	PRON
fbem-31093	92	2	conduct	conduct	VERB
fbem-31093	92	3	experiments	experiment	NOUN
fbem-31093	92	4	on	on	ADP
fbem-31093	92	5	the	the	DET
fbem-31093	92	6	t	t	NOUN
fbem-31093	92	7	-	-	PUNCT
fbem-31093	92	8	finance	finance	NOUN
fbem-31093	92	9	dataset	dataset	NOUN
fbem-31093	92	10	,	,	PUNCT
fbem-31093	92	11	which	which	PRON
fbem-31093	92	12	is	be	AUX
fbem-31093	92	13	provided	provide	VERB
fbem-31093	92	14	by	by	ADP
fbem-31093	92	15	a	a	DET
fbem-31093	92	16	leading	lead	VERB
fbem-31093	92	17	financial	financial	ADJ
fbem-31093	92	18	technology	technology	NOUN
fbem-31093	92	19	company	company	NOUN
fbem-31093	92	20	.	.	PUNCT
fbem-31093	93	1	this	this	DET
fbem-31093	93	2	dataset	dataset	NOUN
fbem-31093	93	3	contains	contain	VERB
fbem-31093	93	4	transaction	transaction	NOUN
fbem-31093	93	5	records	record	NOUN
fbem-31093	93	6	between	between	ADP
fbem-31093	93	7	users	user	NOUN
fbem-31093	93	8	,	,	PUNCT
fbem-31093	93	9	consisting	consist	VERB
fbem-31093	93	10	of	of	ADP
fbem-31093	93	11	39,357	39,357	NUM
fbem-31093	93	12	nodes	node	NOUN
fbem-31093	93	13	(	(	PUNCT
fbem-31093	93	14	users	user	NOUN
fbem-31093	93	15	)	)	PUNCT
fbem-31093	93	16	and	and	CCONJ
fbem-31093	93	17	54,895	54,895	NUM
fbem-31093	93	18	edges	edge	NOUN
fbem-31093	93	19	(	(	PUNCT
fbem-31093	93	20	transactions	transaction	NOUN
fbem-31093	93	21	)	)	PUNCT
fbem-31093	93	22	.	.	PUNCT
fbem-31093	94	1	each	each	DET
fbem-31093	94	2	node	node	NOUN
fbem-31093	94	3	has	have	VERB
fbem-31093	94	4	10	10	NUM
fbem-31093	94	5	features	feature	NOUN
fbem-31093	94	6	including	include	VERB
fbem-31093	94	7	transaction	transaction	NOUN
fbem-31093	94	8	amount	amount	NOUN
fbem-31093	94	9	,	,	PUNCT
fbem-31093	94	10	frequency	frequency	NOUN
fbem-31093	94	11	,	,	PUNCT
fbem-31093	94	12	and	and	CCONJ
fbem-31093	94	13	user	user	NOUN
fbem-31093	94	14	profile	profile	PROPN
fbem-31093	94	15	information	information	NOUN
fbem-31093	94	16	.	.	PUNCT
fbem-31093	95	1	the	the	DET
fbem-31093	95	2	dataset	dataset	NOUN
fbem-31093	95	3	contains	contain	VERB
fbem-31093	95	4	4,127	4,127	NUM
fbem-31093	95	5	labeled	label	VERB
fbem-31093	95	6	fraudulent	fraudulent	ADJ
fbem-31093	95	7	users	user	NOUN
fbem-31093	95	8	,	,	PUNCT
fbem-31093	95	9	accounting	account	VERB
fbem-31093	95	10	for	for	ADP
fbem-31093	95	11	10.49	10.49	NUM
fbem-31093	95	12	%	%	NOUN
fbem-31093	95	13	of	of	ADP
fbem-31093	95	14	the	the	DET
fbem-31093	95	15	total	total	ADJ
fbem-31093	95	16	users	user	NOUN
fbem-31093	95	17	.	.	PUNCT
fbem-31093	96	1	baseline	baseline	PROPN
fbem-31093	96	2	methods	method	NOUN
fbem-31093	96	3	.	.	PUNCT
fbem-31093	97	1	we	we	PRON
fbem-31093	97	2	compare	compare	VERB
fbem-31093	97	3	finguard	finguard	ADV
fbem-31093	97	4	-	-	PUNCT
fbem-31093	97	5	gnn	gnn	NOUN
fbem-31093	97	6	with	with	ADP
fbem-31093	97	7	three	three	NUM
fbem-31093	97	8	categories	category	NOUN
fbem-31093	97	9	of	of	ADP
fbem-31093	97	10	baseline	baseline	ADJ
fbem-31093	97	11	methods	method	NOUN
fbem-31093	97	12	:	:	PUNCT
fbem-31093	97	13	traditional	traditional	ADJ
fbem-31093	97	14	ml	ml	NOUN
fbem-31093	97	15	methods	method	NOUN
fbem-31093	97	16	.	.	PUNCT
fbem-31093	98	1	random	random	ADJ
fbem-31093	98	2	forest	forest	NOUN
fbem-31093	98	3	(	(	PUNCT
fbem-31093	98	4	rf	rf	NOUN
fbem-31093	98	5	):	):	PUNCT
fbem-31093	98	6	an	an	DET
fbem-31093	98	7	ensemble	ensemble	ADJ
fbem-31093	98	8	learning	learning	NOUN
fbem-31093	98	9	method	method	NOUN
fbem-31093	98	10	based	base	VERB
fbem-31093	98	11	on	on	ADP
fbem-31093	98	12	decision	decision	NOUN
fbem-31093	98	13	trees	tree	NOUN
fbem-31093	98	14	.	.	PUNCT
fbem-31093	99	1	mlp	mlp	NOUN
fbem-31093	99	2	:	:	PUNCT
fbem-31093	99	3	multi	multi	ADJ
fbem-31093	99	4	-	-	ADJ
fbem-31093	99	5	layer	layer	ADJ
fbem-31093	99	6	perceptron	perceptron	PROPN
fbem-31093	99	7	,	,	PUNCT
fbem-31093	99	8	a	a	DET
fbem-31093	99	9	feedforward	feedforward	ADJ
fbem-31093	99	10	neural	neural	ADJ
fbem-31093	99	11	network	network	NOUN
fbem-31093	99	12	for	for	ADP
fbem-31093	99	13	node	node	ADJ
fbem-31093	99	14	classification	classification	NOUN
fbem-31093	99	15	.	.	PUNCT
fbem-31093	100	1	general	general	ADJ
fbem-31093	100	2	gnn	gnn	PROPN
fbem-31093	100	3	methods	method	NOUN
fbem-31093	100	4	.	.	PUNCT
fbem-31093	101	1	gcn	gcn	NOUN
fbem-31093	101	2	:	:	PUNCT
fbem-31093	101	3	graph	graph	VERB
fbem-31093	101	4	convolutional	convolutional	ADJ
fbem-31093	101	5	networks	network	NOUN
fbem-31093	101	6	that	that	PRON
fbem-31093	101	7	perform	perform	VERB
fbem-31093	101	8	localized	localized	ADJ
fbem-31093	101	9	first	first	ADJ
fbem-31093	101	10	-	-	PUNCT
fbem-31093	101	11	order	order	NOUN
fbem-31093	101	12	approximation	approximation	NOUN
fbem-31093	101	13	of	of	ADP
fbem-31093	101	14	spectral	spectral	ADJ
fbem-31093	101	15	graph	graph	NOUN
fbem-31093	101	16	convolutions	convolution	NOUN
fbem-31093	101	17	.	.	PUNCT
fbem-31093	102	1	gat	gat	NOUN
fbem-31093	102	2	:	:	PUNCT
fbem-31093	102	3	graph	graph	VERB
fbem-31093	102	4	attention	attention	NOUN
fbem-31093	102	5	networks	network	NOUN
fbem-31093	102	6	that	that	PRON
fbem-31093	102	7	leverage	leverage	NOUN
fbem-31093	102	8	masked	mask	VERB
fbem-31093	102	9	self	self	NOUN
fbem-31093	102	10	-	-	PUNCT
fbem-31093	102	11	attentional	attentional	ADJ
fbem-31093	102	12	layers	layer	NOUN
fbem-31093	102	13	.	.	PUNCT
fbem-31093	103	1	graphsage	graphsage	NOUN
fbem-31093	103	2	:	:	PUNCT
fbem-31093	103	3	an	an	DET
fbem-31093	103	4	inductive	inductive	ADJ
fbem-31093	103	5	framework	framework	NOUN
fbem-31093	103	6	for	for	ADP
fbem-31093	103	7	node	node	ADJ
fbem-31093	103	8	representation	representation	NOUN
fbem-31093	103	9	learning	learn	VERB
fbem-31093	103	10	that	that	SCONJ
fbem-31093	103	11	samples	sample	NOUN
fbem-31093	103	12	and	and	CCONJ
fbem-31093	103	13	aggregates	aggregate	NOUN
fbem-31093	103	14	features	feature	VERB
fbem-31093	103	15	from	from	ADP
fbem-31093	103	16	a	a	DET
fbem-31093	103	17	node	node	NOUN
fbem-31093	103	18	's	's	PART
fbem-31093	103	19	local	local	ADJ
fbem-31093	103	20	neighborhood	neighborhood	NOUN
fbem-31093	103	21	.	.	PUNCT
fbem-31093	104	1	evaluation	evaluation	NOUN
fbem-31093	104	2	metrics	metric	NOUN
fbem-31093	104	3	.	.	PUNCT
fbem-31093	105	1	following	follow	VERB
fbem-31093	105	2	standard	standard	ADJ
fbem-31093	105	3	practice	practice	NOUN
fbem-31093	105	4	in	in	ADP
fbem-31093	105	5	fraud	fraud	NOUN
fbem-31093	105	6	detection	detection	NOUN
fbem-31093	105	7	literature	literature	NOUN
fbem-31093	105	8	,	,	PUNCT
fbem-31093	105	9	we	we	PRON
fbem-31093	105	10	use	use	VERB
fbem-31093	105	11	two	two	NUM
fbem-31093	105	12	widely	widely	ADV
fbem-31093	105	13	adopted	adopt	VERB
fbem-31093	105	14	metrics	metric	NOUN
fbem-31093	105	15	:	:	PUNCT
fbem-31093	105	16	auc	auc	NOUN
fbem-31093	105	17	(	(	PUNCT
fbem-31093	105	18	area	area	NOUN
fbem-31093	105	19	under	under	ADP
fbem-31093	105	20	the	the	DET
fbem-31093	105	21	roc	roc	PROPN
fbem-31093	105	22	curve	curve	NOUN
fbem-31093	105	23	):	):	PUNCT
fbem-31093	105	24	measures	measure	NOUN
fbem-31093	105	25	the	the	DET
fbem-31093	105	26	ability	ability	NOUN
fbem-31093	105	27	to	to	PART
fbem-31093	105	28	distinguish	distinguish	VERB
fbem-31093	105	29	between	between	ADP
fbem-31093	105	30	classes	class	NOUN
fbem-31093	105	31	across	across	ADP
fbem-31093	105	32	various	various	ADJ
fbem-31093	105	33	threshold	threshold	NOUN
fbem-31093	105	34	settings	setting	NOUN
fbem-31093	105	35	.	.	PUNCT
fbem-31093	106	1	ap	ap	PROPN
fbem-31093	107	1	(	(	PUNCT
fbem-31093	107	2	average	average	ADJ
fbem-31093	107	3	precision	precision	NOUN
fbem-31093	107	4	):	):	PUNCT
fbem-31093	107	5	summarizes	summarize	VERB
fbem-31093	107	6	the	the	DET
fbem-31093	107	7	precision	precision	NOUN
fbem-31093	107	8	-	-	PUNCT
fbem-31093	107	9	recall	recall	NOUN
fbem-31093	107	10	curve	curve	NOUN
fbem-31093	107	11	and	and	CCONJ
fbem-31093	107	12	is	be	AUX
fbem-31093	107	13	more	more	ADV
fbem-31093	107	14	informative	informative	ADJ
fbem-31093	107	15	for	for	ADP
fbem-31093	107	16	imbalanced	imbalanced	ADJ
fbem-31093	107	17	datasets	dataset	NOUN
fbem-31093	107	18	.	.	PUNCT
fbem-31093	108	1	implementation	implementation	NOUN
fbem-31093	108	2	details	detail	NOUN
fbem-31093	108	3	.	.	PUNCT
fbem-31093	109	1	we	we	PRON
fbem-31093	109	2	implement	implement	VERB
fbem-31093	109	3	finguard	finguard	NOUN
fbem-31093	109	4	-	-	PUNCT
fbem-31093	109	5	gnn	gnn	NOUN
fbem-31093	109	6	using	use	VERB
fbem-31093	109	7	pytorch	pytorch	NOUN
fbem-31093	109	8	and	and	CCONJ
fbem-31093	109	9	pytorch	pytorch	NOUN
fbem-31093	109	10	geometric	geometric	ADJ
fbem-31093	109	11	.	.	PUNCT
fbem-31093	110	1	for	for	ADP
fbem-31093	110	2	all	all	DET
fbem-31093	110	3	experiments	experiment	NOUN
fbem-31093	110	4	,	,	PUNCT
fbem-31093	110	5	we	we	PRON
fbem-31093	110	6	use	use	VERB
fbem-31093	110	7	the	the	DET
fbem-31093	110	8	adam	adam	PROPN
fbem-31093	110	9	optimizer	optimizer	NOUN
fbem-31093	110	10	with	with	ADP
fbem-31093	110	11	a	a	DET
fbem-31093	110	12	learning	learn	VERB
fbem-31093	110	13	rate	rate	NOUN
fbem-31093	110	14	of	of	ADP
fbem-31093	110	15	0.001	0.001	NUM
fbem-31093	110	16	,	,	PUNCT
fbem-31093	110	17	weight	weight	NOUN
fbem-31093	110	18	decay	decay	NOUN
fbem-31093	110	19	of	of	ADP
fbem-31093	110	20	0.001	0.001	NUM
fbem-31093	110	21	,	,	PUNCT
fbem-31093	110	22	and	and	CCONJ
fbem-31093	110	23	dropout	dropout	NOUN
fbem-31093	110	24	rate	rate	NOUN
fbem-31093	110	25	of	of	ADP
fbem-31093	110	26	0.3	0.3	NUM
fbem-31093	110	27	.	.	PUNCT
fbem-31093	111	1	we	we	PRON
fbem-31093	111	2	set	set	VERB
fbem-31093	111	3	the	the	DET
fbem-31093	111	4	batch	batch	NOUN
fbem-31093	111	5	size	size	NOUN
fbem-31093	111	6	to	to	ADP
fbem-31093	111	7	64	64	NUM
fbem-31093	111	8	and	and	CCONJ
fbem-31093	111	9	train	train	VERB
fbem-31093	111	10	for	for	ADP
fbem-31093	111	11	a	a	DET
fbem-31093	111	12	maximum	maximum	NOUN
fbem-31093	111	13	of	of	ADP
fbem-31093	111	14	50	50	NUM
fbem-31093	111	15	epochs	epoch	NOUN
fbem-31093	111	16	with	with	ADP
fbem-31093	111	17	early	early	ADJ
fbem-31093	111	18	stopping	stopping	NOUN
fbem-31093	111	19	based	base	VERB
fbem-31093	111	20	on	on	ADP
fbem-31093	111	21	validation	validation	NOUN
fbem-31093	111	22	loss	loss	NOUN
fbem-31093	111	23	.	.	PUNCT
fbem-31093	112	1	124	124	NUM
fbem-31093	112	2	performance	performance	NOUN
fbem-31093	112	3	comparison	comparison	NOUN
fbem-31093	112	4	.	.	PUNCT
fbem-31093	113	1	figure	figure	VERB
fbem-31093	113	2	1	1	NUM
fbem-31093	113	3	presents	present	VERB
fbem-31093	113	4	the	the	DET
fbem-31093	113	5	overall	overall	ADJ
fbem-31093	113	6	performance	performance	NOUN
fbem-31093	113	7	comparison	comparison	NOUN
fbem-31093	113	8	between	between	ADP
fbem-31093	113	9	finguard	finguard	NOUN
fbem-31093	113	10	-	-	PUNCT
fbem-31093	113	11	gnn	gnn	PROPN
fbem-31093	113	12	and	and	CCONJ
fbem-31093	113	13	the	the	DET
fbem-31093	113	14	baseline	baseline	NOUN
fbem-31093	113	15	methods	method	NOUN
fbem-31093	113	16	on	on	ADP
fbem-31093	113	17	the	the	DET
fbem-31093	113	18	t	t	NOUN
fbem-31093	113	19	-	-	PUNCT
fbem-31093	113	20	finance	finance	NOUN
fbem-31093	113	21	dataset	dataset	NOUN
fbem-31093	113	22	.	.	PUNCT
fbem-31093	114	1	figure	figure	NOUN
fbem-31093	114	2	1	1	NUM
fbem-31093	114	3	.	.	PUNCT
fbem-31093	115	1	performance	performance	NOUN
fbem-31093	115	2	comparison	comparison	NOUN
fbem-31093	115	3	on	on	ADP
fbem-31093	115	4	t	t	PROPN
fbem-31093	115	5	-	-	PUNCT
fbem-31093	115	6	finance	finance	NOUN
fbem-31093	115	7	dataset	dataset	NOUN
fbem-31093	115	8	figure	figure	NOUN
fbem-31093	115	9	1	1	NUM
fbem-31093	115	10	presents	present	VERB
fbem-31093	115	11	the	the	DET
fbem-31093	115	12	overall	overall	ADJ
fbem-31093	115	13	performance	performance	NOUN
fbem-31093	115	14	comparison	comparison	NOUN
fbem-31093	115	15	between	between	ADP
fbem-31093	115	16	finguard	finguard	NOUN
fbem-31093	115	17	-	-	PUNCT
fbem-31093	115	18	gnn	gnn	NOUN
fbem-31093	115	19	and	and	CCONJ
fbem-31093	115	20	various	various	ADJ
fbem-31093	115	21	baseline	baseline	NOUN
fbem-31093	115	22	methods	method	NOUN
fbem-31093	115	23	on	on	ADP
fbem-31093	115	24	the	the	DET
fbem-31093	115	25	t	t	NOUN
fbem-31093	115	26	-	-	PUNCT
fbem-31093	115	27	finance	finance	NOUN
fbem-31093	115	28	dataset	dataset	NOUN
fbem-31093	115	29	.	.	PUNCT
fbem-31093	116	1	the	the	DET
fbem-31093	116	2	experimental	experimental	ADJ
fbem-31093	116	3	results	result	NOUN
fbem-31093	116	4	demonstrate	demonstrate	VERB
fbem-31093	116	5	that	that	SCONJ
fbem-31093	116	6	our	our	PRON
fbem-31093	116	7	proposed	propose	VERB
fbem-31093	116	8	finguard	finguard	NOUN
fbem-31093	116	9	-	-	PUNCT
fbem-31093	116	10	gnn	gnn	NOUN
fbem-31093	116	11	consistently	consistently	ADV
fbem-31093	116	12	outperforms	outperform	VERB
fbem-31093	116	13	all	all	DET
fbem-31093	116	14	baseline	baseline	ADJ
fbem-31093	116	15	methods	method	NOUN
fbem-31093	116	16	across	across	ADP
fbem-31093	116	17	both	both	DET
fbem-31093	116	18	evaluation	evaluation	NOUN
fbem-31093	116	19	metrics	metric	NOUN
fbem-31093	116	20	.	.	PUNCT
fbem-31093	117	1	notably	notably	ADV
fbem-31093	117	2	,	,	PUNCT
fbem-31093	117	3	the	the	DET
fbem-31093	117	4	finguard	finguard	NOUN
fbem-31093	117	5	-	-	PUNCT
fbem-31093	117	6	gnn	gnn	NOUN
fbem-31093	117	7	with	with	ADP
fbem-31093	117	8	decision	decision	NOUN
fbem-31093	117	9	tree	tree	NOUN
fbem-31093	117	10	binning	bin	VERB
fbem-31093	117	11	encoding	encoding	NOUN
fbem-31093	117	12	(	(	PUNCT
fbem-31093	117	13	dtbe	dtbe	PROPN
fbem-31093	117	14	)	)	PUNCT
fbem-31093	117	15	achieves	achieve	VERB
fbem-31093	117	16	the	the	DET
fbem-31093	117	17	best	good	ADJ
fbem-31093	117	18	performance	performance	NOUN
fbem-31093	117	19	with	with	ADP
fbem-31093	117	20	91.4	91.4	NUM
fbem-31093	117	21	%	%	NOUN
fbem-31093	117	22	ap	ap	NOUN
fbem-31093	117	23	and	and	CCONJ
fbem-31093	117	24	98.1	98.1	NUM
fbem-31093	117	25	%	%	NOUN
fbem-31093	117	26	auc	auc	NOUN
fbem-31093	117	27	,	,	PUNCT
fbem-31093	117	28	significantly	significantly	ADV
fbem-31093	117	29	surpassing	surpass	VERB
fbem-31093	117	30	the	the	DET
fbem-31093	117	31	best	good	ADJ
fbem-31093	117	32	baseline	baseline	NOUN
fbem-31093	117	33	model	model	NOUN
fbem-31093	117	34	bwgnn	bwgnn	NOUN
fbem-31093	117	35	by	by	ADP
fbem-31093	117	36	5.9	5.9	NUM
fbem-31093	117	37	and	and	CCONJ
fbem-31093	117	38	1.8	1.8	NUM
fbem-31093	117	39	percentage	percentage	NOUN
fbem-31093	117	40	points	point	NOUN
fbem-31093	117	41	respectively	respectively	ADV
fbem-31093	117	42	.	.	PUNCT
fbem-31093	118	1	interestingly	interestingly	ADV
fbem-31093	118	2	,	,	PUNCT
fbem-31093	118	3	traditional	traditional	ADJ
fbem-31093	118	4	ml	ml	ADP
fbem-31093	118	5	methods	method	NOUN
fbem-31093	118	6	like	like	ADP
fbem-31093	118	7	random	random	ADJ
fbem-31093	118	8	forest	forest	NOUN
fbem-31093	118	9	perform	perform	VERB
fbem-31093	118	10	better	well	ADV
fbem-31093	118	11	than	than	ADP
fbem-31093	118	12	some	some	DET
fbem-31093	118	13	graph	graph	NOUN
fbem-31093	118	14	-	-	PUNCT
fbem-31093	118	15	based	base	VERB
fbem-31093	118	16	models	model	NOUN
fbem-31093	118	17	,	,	PUNCT
fbem-31093	118	18	suggesting	suggest	VERB
fbem-31093	118	19	the	the	DET
fbem-31093	118	20	crucial	crucial	ADJ
fbem-31093	118	21	role	role	NOUN
fbem-31093	118	22	of	of	ADP
fbem-31093	118	23	effective	effective	ADJ
fbem-31093	118	24	feature	feature	NOUN
fbem-31093	118	25	utilization	utilization	NOUN
fbem-31093	118	26	in	in	ADP
fbem-31093	118	27	fraud	fraud	NOUN
fbem-31093	118	28	detection	detection	NOUN
fbem-31093	118	29	.	.	PUNCT
fbem-31093	119	1	traditional	traditional	ADJ
fbem-31093	119	2	gnn	gnn	PROPN
fbem-31093	119	3	methods	method	NOUN
fbem-31093	119	4	(	(	PUNCT
fbem-31093	119	5	gcn	gcn	ADJ
fbem-31093	119	6	,	,	PUNCT
fbem-31093	119	7	gat	gat	NOUN
fbem-31093	119	8	,	,	PUNCT
fbem-31093	119	9	graphsage	graphsage	NOUN
fbem-31093	119	10	)	)	PUNCT
fbem-31093	119	11	show	show	VERB
fbem-31093	119	12	moderate	moderate	ADJ
fbem-31093	119	13	performance	performance	NOUN
fbem-31093	119	14	due	due	ADP
fbem-31093	119	15	to	to	ADP
fbem-31093	119	16	their	their	PRON
fbem-31093	119	17	homophily	homophily	ADJ
fbem-31093	119	18	assumption	assumption	NOUN
fbem-31093	119	19	,	,	PUNCT
fbem-31093	119	20	which	which	PRON
fbem-31093	119	21	does	do	AUX
fbem-31093	119	22	n't	not	PART
fbem-31093	119	23	hold	hold	VERB
fbem-31093	119	24	in	in	ADP
fbem-31093	119	25	fraud	fraud	NOUN
fbem-31093	119	26	scenarios	scenario	NOUN
fbem-31093	119	27	where	where	SCONJ
fbem-31093	119	28	fraudsters	fraudster	NOUN
fbem-31093	119	29	often	often	ADV
fbem-31093	119	30	interact	interact	VERB
fbem-31093	119	31	with	with	ADP
fbem-31093	119	32	normal	normal	ADJ
fbem-31093	119	33	users	user	NOUN
fbem-31093	119	34	to	to	PART
fbem-31093	119	35	disguise	disguise	VERB
fbem-31093	119	36	their	their	PRON
fbem-31093	119	37	identity	identity	NOUN
fbem-31093	119	38	.	.	PUNCT
fbem-31093	120	1	among	among	ADP
fbem-31093	120	2	our	our	PRON
fbem-31093	120	3	two	two	NUM
fbem-31093	120	4	feature	feature	NOUN
fbem-31093	120	5	encoding	encoding	NOUN
fbem-31093	120	6	strategies	strategy	NOUN
fbem-31093	120	7	,	,	PUNCT
fbem-31093	120	8	dtbe	dtbe	ADJ
fbem-31093	120	9	demonstrates	demonstrate	VERB
fbem-31093	120	10	superior	superior	ADJ
fbem-31093	120	11	capability	capability	NOUN
fbem-31093	120	12	in	in	ADP
fbem-31093	120	13	capturing	capture	VERB
fbem-31093	120	14	the	the	DET
fbem-31093	120	15	discriminative	discriminative	NOUN
fbem-31093	120	16	power	power	NOUN
fbem-31093	120	17	of	of	ADP
fbem-31093	120	18	features	feature	NOUN
fbem-31093	120	19	for	for	ADP
fbem-31093	120	20	fraud	fraud	NOUN
fbem-31093	120	21	detection	detection	NOUN
fbem-31093	120	22	,	,	PUNCT
fbem-31093	120	23	followed	follow	VERB
fbem-31093	120	24	by	by	ADP
fbem-31093	120	25	woe	woe	NOUN
fbem-31093	120	26	encoding	encoding	NOUN
fbem-31093	120	27	.	.	PUNCT
fbem-31093	121	1	these	these	DET
fbem-31093	121	2	results	result	NOUN
fbem-31093	121	3	validate	validate	VERB
fbem-31093	121	4	our	our	PRON
fbem-31093	121	5	hypothesis	hypothesis	NOUN
fbem-31093	121	6	that	that	PRON
fbem-31093	121	7	effectively	effectively	ADV
fbem-31093	121	8	handling	handle	VERB
fbem-31093	121	9	non	non	ADJ
fbem-31093	121	10	-	-	ADJ
fbem-31093	121	11	additive	additive	ADJ
fbem-31093	121	12	attributes	attribute	NOUN
fbem-31093	121	13	and	and	CCONJ
fbem-31093	121	14	implementing	implement	VERB
fbem-31093	121	15	hierarchical	hierarchical	ADJ
fbem-31093	121	16	risk	risk	NOUN
fbem-31093	121	17	propagation	propagation	NOUN
fbem-31093	121	18	significantly	significantly	ADV
fbem-31093	121	19	enhances	enhance	VERB
fbem-31093	121	20	fraud	fraud	NOUN
fbem-31093	121	21	detection	detection	NOUN
fbem-31093	121	22	performance	performance	NOUN
fbem-31093	121	23	in	in	ADP
fbem-31093	121	24	financial	financial	ADJ
fbem-31093	121	25	transaction	transaction	NOUN
fbem-31093	121	26	networks	network	NOUN
fbem-31093	121	27	.	.	PUNCT
fbem-31093	122	1	5	5	X
fbem-31093	122	2	.	.	X
fbem-31093	122	3	conclusion	conclusion	NOUN
fbem-31093	122	4	in	in	ADP
fbem-31093	122	5	conclusion	conclusion	NOUN
fbem-31093	122	6	,	,	PUNCT
fbem-31093	122	7	the	the	DET
fbem-31093	122	8	escalating	escalate	VERB
fbem-31093	122	9	complexity	complexity	NOUN
fbem-31093	122	10	and	and	CCONJ
fbem-31093	122	11	sophistication	sophistication	NOUN
fbem-31093	122	12	of	of	ADP
fbem-31093	122	13	financial	financial	ADJ
fbem-31093	122	14	fraud	fraud	NOUN
fbem-31093	122	15	necessitate	necessitate	ADJ
fbem-31093	122	16	advanced	advanced	ADJ
fbem-31093	122	17	detection	detection	NOUN
fbem-31093	122	18	mechanisms	mechanism	NOUN
fbem-31093	122	19	that	that	PRON
fbem-31093	122	20	can	can	AUX
fbem-31093	122	21	effectively	effectively	ADV
fbem-31093	122	22	navigate	navigate	VERB
fbem-31093	122	23	the	the	DET
fbem-31093	122	24	intricate	intricate	ADJ
fbem-31093	122	25	relational	relational	ADJ
fbem-31093	122	26	networks	network	NOUN
fbem-31093	122	27	characteristic	characteristic	ADJ
fbem-31093	122	28	of	of	ADP
fbem-31093	122	29	modern	modern	ADJ
fbem-31093	122	30	financial	financial	ADJ
fbem-31093	122	31	systems	system	NOUN
fbem-31093	122	32	.	.	PUNCT
fbem-31093	123	1	finguard	finguard	ADJ
fbem-31093	123	2	-	-	PUNCT
fbem-31093	123	3	gnn	gnn	PROPN
fbem-31093	123	4	emerges	emerge	VERB
fbem-31093	123	5	as	as	ADP
fbem-31093	123	6	a	a	DET
fbem-31093	123	7	novel	novel	ADJ
fbem-31093	123	8	solution	solution	NOUN
fbem-31093	123	9	designed	design	VERB
fbem-31093	123	10	specifically	specifically	ADV
fbem-31093	123	11	to	to	PART
fbem-31093	123	12	address	address	VERB
fbem-31093	123	13	two	two	NUM
fbem-31093	123	14	critical	critical	ADJ
fbem-31093	123	15	challenges	challenge	NOUN
fbem-31093	123	16	overlooked	overlook	VERB
fbem-31093	123	17	by	by	ADP
fbem-31093	123	18	existing	exist	VERB
fbem-31093	123	19	methods	method	NOUN
fbem-31093	123	20	:	:	PUNCT
fbem-31093	123	21	the	the	DET
fbem-31093	123	22	processing	processing	NOUN
fbem-31093	123	23	of	of	ADP
fbem-31093	123	24	non	non	ADJ
fbem-31093	123	25	-	-	ADJ
fbem-31093	123	26	additive	additive	ADJ
fbem-31093	123	27	attributes	attribute	NOUN
fbem-31093	123	28	and	and	CCONJ
fbem-31093	123	29	the	the	DET
fbem-31093	123	30	distinguishability	distinguishability	NOUN
fbem-31093	123	31	of	of	ADP
fbem-31093	123	32	grouped	group	VERB
fbem-31093	123	33	message	message	NOUN
fbem-31093	123	34	passing	pass	VERB
fbem-31093	123	35	within	within	ADP
fbem-31093	123	36	financial	financial	ADJ
fbem-31093	123	37	transaction	transaction	NOUN
fbem-31093	123	38	networks	network	NOUN
fbem-31093	123	39	.	.	PUNCT
fbem-31093	124	1	by	by	ADP
fbem-31093	124	2	integrating	integrate	VERB
fbem-31093	124	3	adaptive	adaptive	ADJ
fbem-31093	124	4	tree	tree	NOUN
fbem-31093	124	5	partitioning	partitioning	NOUN
fbem-31093	124	6	(	(	PUNCT
fbem-31093	124	7	atp	atp	PROPN
fbem-31093	124	8	)	)	PUNCT
fbem-31093	124	9	encoding	encoding	NOUN
fbem-31093	124	10	and	and	CCONJ
fbem-31093	124	11	statistical	statistical	ADJ
fbem-31093	124	12	evidence	evidence	NOUN
fbem-31093	124	13	weighting	weighting	NOUN
fbem-31093	124	14	(	(	PUNCT
fbem-31093	124	15	sew	sew	NOUN
fbem-31093	124	16	)	)	PUNCT
fbem-31093	124	17	encoding	encoding	NOUN
fbem-31093	124	18	,	,	PUNCT
fbem-31093	124	19	our	our	PRON
fbem-31093	124	20	approach	approach	NOUN
fbem-31093	124	21	successfully	successfully	ADV
fbem-31093	124	22	transforms	transform	VERB
fbem-31093	124	23	diverse	diverse	ADJ
fbem-31093	124	24	node	node	NOUN
fbem-31093	124	25	attributes	attribute	NOUN
fbem-31093	124	26	into	into	ADP
fbem-31093	124	27	meaningful	meaningful	ADJ
fbem-31093	124	28	vector	vector	NOUN
fbem-31093	124	29	representations	representation	NOUN
fbem-31093	124	30	suitable	suitable	ADJ
fbem-31093	124	31	for	for	ADP
fbem-31093	124	32	graph	graph	NOUN
fbem-31093	124	33	neural	neural	ADJ
fbem-31093	124	34	network	network	NOUN
fbem-31093	124	35	aggregation	aggregation	NOUN
fbem-31093	124	36	,	,	PUNCT
fbem-31093	124	37	preserving	preserve	VERB
fbem-31093	124	38	their	their	PRON
fbem-31093	124	39	statistical	statistical	ADJ
fbem-31093	124	40	properties	property	NOUN
fbem-31093	124	41	while	while	SCONJ
fbem-31093	124	42	enhancing	enhance	VERB
fbem-31093	124	43	interpretability	interpretability	NOUN
fbem-31093	124	44	.	.	PUNCT
fbem-31093	125	1	furthermore	furthermore	ADV
fbem-31093	125	2	,	,	PUNCT
fbem-31093	125	3	the	the	DET
fbem-31093	125	4	introduction	introduction	NOUN
fbem-31093	125	5	of	of	ADP
fbem-31093	125	6	a	a	DET
fbem-31093	125	7	cascaded	cascade	VERB
fbem-31093	125	8	risk	risk	NOUN
fbem-31093	125	9	diffusion	diffusion	NOUN
fbem-31093	125	10	(	(	PUNCT
fbem-31093	125	11	crd	crd	NOUN
fbem-31093	125	12	)	)	PUNCT
fbem-31093	125	13	mechanism	mechanism	NOUN
fbem-31093	125	14	facilitates	facilitate	VERB
fbem-31093	125	15	dynamic	dynamic	ADJ
fbem-31093	125	16	risk	risk	NOUN
fbem-31093	125	17	propagation	propagation	NOUN
fbem-31093	125	18	across	across	ADP
fbem-31093	125	19	the	the	DET
fbem-31093	125	20	network	network	NOUN
fbem-31093	125	21	,	,	PUNCT
fbem-31093	125	22	incorporating	incorporate	VERB
fbem-31093	125	23	feedback	feedback	NOUN
fbem-31093	125	24	regulation	regulation	NOUN
fbem-31093	125	25	to	to	PART
fbem-31093	125	26	model	model	VERB
fbem-31093	125	27	complex	complex	ADJ
fbem-31093	125	28	risk	risk	NOUN
fbem-31093	125	29	diffusion	diffusion	NOUN
fbem-31093	125	30	patterns	pattern	NOUN
fbem-31093	125	31	accurately	accurately	ADV
fbem-31093	125	32	.	.	PUNCT
fbem-31093	126	1	the	the	DET
fbem-31093	126	2	responsive	responsive	ADJ
fbem-31093	126	3	group	group	NOUN
fbem-31093	126	4	allocation	allocation	NOUN
fbem-31093	126	5	(	(	PUNCT
fbem-31093	126	6	rga	rga	NOUN
fbem-31093	126	7	)	)	PUNCT
fbem-31093	126	8	strategy	strategy	NOUN
fbem-31093	126	9	further	far	ADV
fbem-31093	126	10	refines	refine	VERB
fbem-31093	126	11	this	this	DET
fbem-31093	126	12	process	process	NOUN
fbem-31093	126	13	by	by	ADP
fbem-31093	126	14	adaptively	adaptively	ADV
fbem-31093	126	15	dividing	divide	VERB
fbem-31093	126	16	nodes	node	NOUN
fbem-31093	126	17	into	into	ADP
fbem-31093	126	18	distinct	distinct	ADJ
fbem-31093	126	19	groups	group	NOUN
fbem-31093	126	20	based	base	VERB
fbem-31093	126	21	on	on	ADP
fbem-31093	126	22	evolving	evolve	VERB
fbem-31093	126	23	risk	risk	NOUN
fbem-31093	126	24	assessments	assessment	NOUN
fbem-31093	126	25	,	,	PUNCT
fbem-31093	126	26	thereby	thereby	ADV
fbem-31093	126	27	improving	improve	VERB
fbem-31093	126	28	the	the	DET
fbem-31093	126	29	identification	identification	NOUN
fbem-31093	126	30	of	of	ADP
fbem-31093	126	31	fraudulent	fraudulent	ADJ
fbem-31093	126	32	activities	activity	NOUN
fbem-31093	126	33	through	through	ADP
fbem-31093	126	34	hierarchical	hierarchical	ADJ
fbem-31093	126	35	information	information	NOUN
fbem-31093	126	36	aggregations	aggregation	NOUN
fbem-31093	126	37	.	.	PUNCT
fbem-31093	127	1	our	our	PRON
fbem-31093	127	2	experimental	experimental	ADJ
fbem-31093	127	3	evaluations	evaluation	NOUN
fbem-31093	127	4	on	on	ADP
fbem-31093	127	5	real	real	ADJ
fbem-31093	127	6	-	-	PUNCT
fbem-31093	127	7	world	world	NOUN
fbem-31093	127	8	financial	financial	ADJ
fbem-31093	127	9	datasets	dataset	NOUN
fbem-31093	127	10	demonstrate	demonstrate	VERB
fbem-31093	127	11	the	the	DET
fbem-31093	127	12	superior	superior	ADJ
fbem-31093	127	13	performance	performance	NOUN
fbem-31093	127	14	of	of	ADP
fbem-31093	127	15	finguard	finguard	NOUN
fbem-31093	127	16	-	-	PUNCT
fbem-31093	127	17	gnn	gnn	NOUN
fbem-31093	127	18	over	over	ADP
fbem-31093	127	19	traditional	traditional	ADJ
fbem-31093	127	20	machine	machine	NOUN
fbem-31093	127	21	learning	learn	VERB
fbem-31093	127	22	techniques	technique	NOUN
fbem-31093	127	23	and	and	CCONJ
fbem-31093	127	24	general	general	ADJ
fbem-31093	127	25	-	-	PUNCT
fbem-31093	127	26	purpose	purpose	NOUN
fbem-31093	127	27	graph	graph	NOUN
fbem-31093	127	28	neural	neural	ADJ
fbem-31093	127	29	networks	network	NOUN
fbem-31093	127	30	.	.	PUNCT
fbem-31093	128	1	notably	notably	ADV
fbem-31093	128	2	,	,	PUNCT
fbem-31093	128	3	the	the	DET
fbem-31093	128	4	proposed	propose	VERB
fbem-31093	128	5	method	method	NOUN
fbem-31093	128	6	achieves	achieve	VERB
fbem-31093	128	7	significant	significant	ADJ
fbem-31093	128	8	improvements	improvement	NOUN
fbem-31093	128	9	in	in	ADP
fbem-31093	128	10	both	both	CCONJ
fbem-31093	128	11	auc	auc	NOUN
fbem-31093	128	12	and	and	CCONJ
fbem-31093	128	13	ap	ap	PROPN
fbem-31093	128	14	metrics	metric	NOUN
fbem-31093	128	15	,	,	PUNCT
fbem-31093	128	16	highlighting	highlight	VERB
fbem-31093	128	17	its	its	PRON
fbem-31093	128	18	effectiveness	effectiveness	NOUN
fbem-31093	128	19	in	in	ADP
fbem-31093	128	20	capturing	capture	VERB
fbem-31093	128	21	hierarchical	hierarchical	ADJ
fbem-31093	128	22	risk	risk	NOUN
fbem-31093	128	23	propagation	propagation	NOUN
fbem-31093	128	24	and	and	CCONJ
fbem-31093	128	25	distinguishing	distinguish	VERB
fbem-31093	128	26	between	between	ADP
fbem-31093	128	27	legitimate	legitimate	ADJ
fbem-31093	128	28	and	and	CCONJ
fbem-31093	128	29	fraudulent	fraudulent	ADJ
fbem-31093	128	30	entities	entity	NOUN
fbem-31093	128	31	even	even	ADV
fbem-31093	128	32	in	in	ADP
fbem-31093	128	33	highly	highly	ADV
fbem-31093	128	34	imbalanced	imbalanced	ADJ
fbem-31093	128	35	datasets	dataset	NOUN
fbem-31093	128	36	.	.	PUNCT
fbem-31093	129	1	these	these	DET
fbem-31093	129	2	findings	finding	NOUN
fbem-31093	129	3	underscore	underscore	VERB
fbem-31093	129	4	the	the	DET
fbem-31093	129	5	potential	potential	NOUN
fbem-31093	129	6	of	of	ADP
fbem-31093	129	7	finguard	finguard	NOUN
fbem-31093	129	8	-	-	PUNCT
fbem-31093	129	9	gnn	gnn	NOUN
fbem-31093	129	10	as	as	ADP
fbem-31093	129	11	a	a	DET
fbem-31093	129	12	robust	robust	ADJ
fbem-31093	129	13	and	and	CCONJ
fbem-31093	129	14	scalable	scalable	ADJ
fbem-31093	129	15	solution	solution	NOUN
fbem-31093	129	16	for	for	ADP
fbem-31093	129	17	financial	financial	ADJ
fbem-31093	129	18	fraud	fraud	NOUN
fbem-31093	129	19	detection	detection	NOUN
fbem-31093	129	20	,	,	PUNCT
fbem-31093	129	21	capable	capable	ADJ
fbem-31093	129	22	of	of	ADP
fbem-31093	129	23	adapting	adapt	VERB
fbem-31093	129	24	to	to	ADP
fbem-31093	129	25	the	the	DET
fbem-31093	129	26	dynamic	dynamic	ADJ
fbem-31093	129	27	nature	nature	NOUN
fbem-31093	129	28	of	of	ADP
fbem-31093	129	29	financial	financial	ADJ
fbem-31093	129	30	markets	market	NOUN
fbem-31093	129	31	and	and	CCONJ
fbem-31093	129	32	continuously	continuously	ADV
fbem-31093	129	33	evolving	evolve	VERB
fbem-31093	129	34	fraud	fraud	NOUN
fbem-31093	129	35	tactics	tactic	NOUN
fbem-31093	129	36	.	.	PUNCT
fbem-31093	130	1	as	as	SCONJ
fbem-31093	130	2	financial	financial	ADJ
fbem-31093	130	3	transactions	transaction	NOUN
fbem-31093	130	4	become	become	VERB
fbem-31093	130	5	increasingly	increasingly	ADV
fbem-31093	130	6	digital	digital	ADJ
fbem-31093	130	7	and	and	CCONJ
fbem-31093	130	8	interconnected	interconnected	ADJ
fbem-31093	130	9	,	,	PUNCT
fbem-31093	130	10	the	the	DET
fbem-31093	130	11	development	development	NOUN
fbem-31093	130	12	of	of	ADP
fbem-31093	130	13	intelligent	intelligent	ADJ
fbem-31093	130	14	systems	system	NOUN
fbem-31093	130	15	like	like	ADP
fbem-31093	130	16	finguard	finguard	NOUN
fbem-31093	130	17	-	-	PUNCT
fbem-31093	130	18	gnn	gnn	PROPN
fbem-31093	130	19	will	will	AUX
fbem-31093	130	20	be	be	AUX
fbem-31093	130	21	crucial	crucial	ADJ
fbem-31093	130	22	in	in	ADP
fbem-31093	130	23	safeguarding	safeguard	VERB
fbem-31093	130	24	economic	economic	ADJ
fbem-31093	130	25	integrity	integrity	NOUN
fbem-31093	130	26	and	and	CCONJ
fbem-31093	130	27	protecting	protect	VERB
fbem-31093	130	28	consumers	consumer	NOUN
fbem-31093	130	29	from	from	ADP
fbem-31093	130	30	sophisticated	sophisticated	ADJ
fbem-31093	130	31	financial	financial	ADJ
fbem-31093	130	32	crimes	crime	NOUN
fbem-31093	130	33	.	.	PUNCT
fbem-31093	131	1	references	reference	NOUN
fbem-31093	131	2	[	[	X
fbem-31093	131	3	1	1	X
fbem-31093	131	4	]	]	PUNCT
fbem-31093	131	5	wang	wang	PROPN
fbem-31093	131	6	d	d	PROPN
fbem-31093	131	7	,	,	PUNCT
fbem-31093	131	8	lin	lin	PROPN
fbem-31093	131	9	j	j	PROPN
fbem-31093	131	10	,	,	PUNCT
fbem-31093	131	11	cui	cui	NOUN
fbem-31093	131	12	p	p	NOUN
fbem-31093	131	13	,	,	PUNCT
fbem-31093	131	14	et	et	PROPN
fbem-31093	131	15	al	al	PROPN
fbem-31093	131	16	.	.	PUNCT
fbem-31093	132	1	a	a	DET
fbem-31093	132	2	semi	semi	ADJ
fbem-31093	132	3	-	-	ADJ
fbem-31093	132	4	supervised	supervised	ADJ
fbem-31093	132	5	graph	graph	NOUN
fbem-31093	132	6	attentive	attentive	ADJ
fbem-31093	132	7	network	network	NOUN
fbem-31093	132	8	for	for	ADP
fbem-31093	132	9	financial	financial	ADJ
fbem-31093	132	10	fraud	fraud	NOUN
fbem-31093	132	11	detection	detection	NOUN
fbem-31093	132	12	[	[	X
fbem-31093	132	13	c]//2019	c]//2019	NUM
fbem-31093	132	14	ieee	ieee	NOUN
fbem-31093	132	15	international	international	ADJ
fbem-31093	132	16	conference	conference	NOUN
fbem-31093	132	17	on	on	ADP
fbem-31093	132	18	data	datum	NOUN
fbem-31093	132	19	mining	mining	NOUN
fbem-31093	132	20	(	(	PUNCT
fbem-31093	132	21	icdm	icdm	NOUN
fbem-31093	132	22	)	)	PUNCT
fbem-31093	132	23	.	.	PUNCT
fbem-31093	133	1	ieee	ieee	PROPN
fbem-31093	133	2	,	,	PUNCT
fbem-31093	133	3	2019	2019	NUM
fbem-31093	133	4	:	:	PUNCT
fbem-31093	133	5	598	598	NUM
fbem-31093	133	6	-	-	SYM
fbem-31093	133	7	607	607	NUM
fbem-31093	133	8	.	.	PUNCT
fbem-31093	134	1	[	[	X
fbem-31093	134	2	2	2	NUM
fbem-31093	134	3	]	]	X
fbem-31093	134	4	li	li	PROPN
fbem-31093	134	5	r	r	PROPN
fbem-31093	134	6	,	,	PUNCT
fbem-31093	134	7	liu	liu	PROPN
fbem-31093	134	8	z	z	PROPN
fbem-31093	134	9	,	,	PUNCT
fbem-31093	134	10	ma	ma	PROPN
fbem-31093	134	11	y	y	PROPN
fbem-31093	134	12	,	,	PUNCT
fbem-31093	134	13	et	et	PROPN
fbem-31093	134	14	al	al	PROPN
fbem-31093	134	15	.	.	PROPN
fbem-31093	134	16	internet	internet	PROPN
fbem-31093	134	17	financial	financial	PROPN
fbem-31093	134	18	fraud	fraud	NOUN
fbem-31093	134	19	detection	detection	NOUN
fbem-31093	134	20	based	base	VERB
fbem-31093	134	21	on	on	ADP
fbem-31093	134	22	graph	graph	NOUN
fbem-31093	134	23	learning	learn	VERB
fbem-31093	134	24	[	[	X
fbem-31093	134	25	j	j	X
fbem-31093	134	26	]	]	X
fbem-31093	134	27	.	.	PUNCT
fbem-31093	135	1	ieee	ieee	NOUN
fbem-31093	135	2	transactions	transaction	NOUN
fbem-31093	135	3	on	on	ADP
fbem-31093	135	4	computational	computational	ADJ
fbem-31093	135	5	social	social	ADJ
fbem-31093	135	6	systems	system	NOUN
fbem-31093	135	7	,	,	PUNCT
fbem-31093	135	8	2022	2022	NUM
fbem-31093	135	9	,	,	PUNCT
fbem-31093	135	10	10(3	10(3	NUM
fbem-31093	135	11	):	):	PUNCT
fbem-31093	135	12	1394	1394	NUM
fbem-31093	135	13	-	-	SYM
fbem-31093	135	14	1401	1401	NUM
fbem-31093	135	15	.	.	PUNCT
fbem-31093	136	1	[	[	X
fbem-31093	136	2	3	3	NUM
fbem-31093	136	3	]	]	X
fbem-31093	136	4	cheng	cheng	PROPN
fbem-31093	136	5	d	d	PROPN
fbem-31093	136	6	,	,	PUNCT
fbem-31093	136	7	zou	zou	PROPN
fbem-31093	136	8	y	y	PROPN
fbem-31093	136	9	,	,	PUNCT
fbem-31093	136	10	xiang	xiang	PROPN
fbem-31093	136	11	s	s	PROPN
fbem-31093	136	12	,	,	PUNCT
fbem-31093	136	13	et	et	PROPN
fbem-31093	136	14	al	al	PROPN
fbem-31093	136	15	.	.	PROPN
fbem-31093	137	1	graph	graph	NOUN
fbem-31093	137	2	neural	neural	ADJ
fbem-31093	137	3	networks	network	NOUN
fbem-31093	137	4	for	for	ADP
fbem-31093	137	5	financial	financial	ADJ
fbem-31093	137	6	fraud	fraud	NOUN
fbem-31093	137	7	detection	detection	NOUN
fbem-31093	137	8	:	:	PUNCT
fbem-31093	137	9	a	a	DET
fbem-31093	137	10	review	review	NOUN
fbem-31093	137	11	[	[	X
fbem-31093	137	12	j	j	X
fbem-31093	137	13	]	]	X
fbem-31093	137	14	.	.	PUNCT
fbem-31093	138	1	frontiers	frontier	NOUN
fbem-31093	138	2	of	of	ADP
fbem-31093	138	3	computer	computer	NOUN
fbem-31093	138	4	science	science	NOUN
fbem-31093	138	5	,	,	PUNCT
fbem-31093	138	6	2025	2025	NUM
fbem-31093	138	7	,	,	PUNCT
fbem-31093	138	8	19(9	19(9	NUM
fbem-31093	138	9	):	):	PUNCT
fbem-31093	138	10	1	1	NUM
fbem-31093	138	11	-	-	SYM
fbem-31093	138	12	15	15	NUM
fbem-31093	138	13	.	.	PUNCT
fbem-31093	139	1	[	[	X
fbem-31093	139	2	4	4	X
fbem-31093	139	3	]	]	X
fbem-31093	139	4	chakraborty	chakraborty	PROPN
fbem-31093	139	5	s	s	PROPN
fbem-31093	139	6	,	,	PUNCT
fbem-31093	139	7	sharov	sharov	ADJ
fbem-31093	139	8	s.	s.	PROPN
fbem-31093	139	9	graph	graph	PROPN
fbem-31093	139	10	based	base	VERB
fbem-31093	139	11	approach	approach	NOUN
fbem-31093	139	12	on	on	ADP
fbem-31093	139	13	financial	financial	ADJ
fbem-31093	139	14	fraudulent	fraudulent	ADJ
fbem-31093	139	15	detection	detection	NOUN
fbem-31093	139	16	and	and	CCONJ
fbem-31093	139	17	prediction	prediction	NOUN
fbem-31093	139	18	[	[	X
fbem-31093	139	19	m]//applied	m]//applied	ADJ
fbem-31093	139	20	graph	graph	NOUN
fbem-31093	139	21	data	datum	NOUN
fbem-31093	139	22	science	science	NOUN
fbem-31093	139	23	.	.	PUNCT
fbem-31093	140	1	morgan	morgan	PROPN
fbem-31093	140	2	kaufmann	kaufmann	PROPN
fbem-31093	140	3	,	,	PUNCT
fbem-31093	140	4	2025	2025	NUM
fbem-31093	140	5	:	:	PUNCT
fbem-31093	140	6	25	25	NUM
fbem-31093	140	7	-	-	SYM
fbem-31093	140	8	37	37	NUM
fbem-31093	140	9	.	.	PUNCT
fbem-31093	141	1	[	[	X
fbem-31093	141	2	5	5	X
fbem-31093	141	3	]	]	PUNCT
fbem-31093	141	4	takahashi	takahashi	PROPN
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fbem-31093	141	6	,	,	PUNCT
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fbem-31093	141	9	,	,	PUNCT
fbem-31093	141	10	matsuda	matsuda	PROPN
fbem-31093	141	11	k.	k.	PROPN
fbem-31093	141	12	a	a	DET
fbem-31093	141	13	graph	graph	NOUN
fbem-31093	141	14	neural	neural	ADJ
fbem-31093	141	15	network	network	NOUN
fbem-31093	141	16	model	model	NOUN
fbem-31093	141	17	for	for	ADP
fbem-31093	141	18	financial	financial	ADJ
fbem-31093	141	19	fraud	fraud	NOUN
fbem-31093	141	20	prevention	prevention	NOUN
fbem-31093	142	1	[	[	X
fbem-31093	142	2	j	j	X
fbem-31093	142	3	]	]	X
fbem-31093	142	4	.	.	PUNCT
fbem-31093	143	1	frontiers	frontier	NOUN
fbem-31093	143	2	in	in	ADP
fbem-31093	143	3	artificial	artificial	ADJ
fbem-31093	143	4	intelligence	intelligence	NOUN
fbem-31093	143	5	research	research	NOUN
fbem-31093	143	6	,	,	PUNCT
fbem-31093	143	7	2025	2025	NUM
fbem-31093	143	8	,	,	PUNCT
fbem-31093	143	9	2(1	2(1	NUM
fbem-31093	143	10	):	):	PUNCT
fbem-31093	143	11	13	13	NUM
fbem-31093	143	12	-	-	SYM
fbem-31093	143	13	25	25	NUM
fbem-31093	143	14	.	.	PUNCT
fbem-31093	144	1	[	[	X
fbem-31093	144	2	6	6	NUM
fbem-31093	144	3	]	]	PUNCT
fbem-31093	144	4	yang	yang	PROPN
fbem-31093	144	5	j	j	PROPN
fbem-31093	144	6	,	,	PUNCT
fbem-31093	144	7	zhang	zhang	PROPN
fbem-31093	144	8	r	r	PROPN
fbem-31093	144	9	,	,	PUNCT
fbem-31093	144	10	cheng	cheng	PROPN
fbem-31093	144	11	z	z	PROPN
fbem-31093	144	12	,	,	PUNCT
fbem-31093	144	13	et	et	PROPN
fbem-31093	144	14	al	al	PROPN
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fbem-31093	144	20	diffusion	diffusion	NOUN
fbem-31093	144	21	generation	generation	NOUN
fbem-31093	144	22	for	for	ADP
fbem-31093	144	23	graph	graph	NOUN
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fbem-31093	144	25	in	in	ADP
fbem-31093	144	26	graph	graph	NOUN
fbem-31093	144	27	fraud	fraud	NOUN
fbem-31093	144	28	detection	detection	NOUN
fbem-31093	145	1	[	[	X
fbem-31093	145	2	c]//proceedings	c]//proceeding	NOUN
fbem-31093	145	3	of	of	ADP
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fbem-31093	145	7	web	web	NOUN
fbem-31093	145	8	conference	conference	NOUN
fbem-31093	145	9	2025	2025	NUM
fbem-31093	145	10	.	.	PUNCT
fbem-31093	146	1	2025	2025	NUM
fbem-31093	146	2	:	:	PUNCT
fbem-31093	146	3	5308	5308	NUM
fbem-31093	146	4	-	-	SYM
fbem-31093	146	5	5319	5319	NUM
fbem-31093	146	6	.	.	PUNCT
fbem-31093	147	1	[	[	X
fbem-31093	147	2	7	7	X
fbem-31093	147	3	]	]	X
fbem-31093	147	4	ju	ju	NOUN
fbem-31093	147	5	c	c	PROPN
fbem-31093	147	6	,	,	PUNCT
fbem-31093	147	7	ma	ma	PROPN
fbem-31093	147	8	x	x	PROPN
fbem-31093	147	9	,	,	PUNCT
fbem-31093	147	10	dong	dong	PROPN
fbem-31093	147	11	b.	b.	PROPN
fbem-31093	147	12	real	real	ADJ
fbem-31093	147	13	-	-	PUNCT
fbem-31093	147	14	time	time	NOUN
fbem-31093	147	15	cross	cross	ADJ
fbem-31093	147	16	-	-	ADJ
fbem-31093	147	17	border	border	ADJ
fbem-31093	147	18	payment	payment	NOUN
fbem-31093	147	19	fraud	fraud	NOUN
fbem-31093	147	20	detection	detection	NOUN
fbem-31093	147	21	using	use	VERB
fbem-31093	147	22	temporal	temporal	ADJ
fbem-31093	147	23	graph	graph	NOUN
fbem-31093	147	24	neural	neural	ADJ
fbem-31093	147	25	networks	network	NOUN
fbem-31093	147	26	:	:	PUNCT
fbem-31093	147	27	a	a	DET
fbem-31093	147	28	deep	deep	ADJ
fbem-31093	147	29	learning	learning	NOUN
fbem-31093	147	30	approach	approach	NOUN
fbem-31093	147	31	[	[	X
fbem-31093	147	32	j	j	X
fbem-31093	147	33	]	]	X
fbem-31093	147	34	.	.	PUNCT
fbem-31093	148	1	academic	academic	ADJ
fbem-31093	148	2	journal	journal	NOUN
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fbem-31093	148	4	sociology	sociology	NOUN
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fbem-31093	148	7	,	,	PUNCT
fbem-31093	148	8	2025	2025	NUM
fbem-31093	148	9	,	,	PUNCT
fbem-31093	148	10	3(2	3(2	NUM
fbem-31093	148	11	):	):	PUNCT
fbem-31093	148	12	1	1	NUM
fbem-31093	148	13	-	-	SYM
fbem-31093	148	14	12	12	NUM
fbem-31093	148	15	.	.	PUNCT
fbem-31093	149	1	[	[	X
fbem-31093	149	2	8	8	X
fbem-31093	149	3	]	]	X
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fbem-31093	149	6	,	,	PUNCT
fbem-31093	149	7	zhang	zhang	PROPN
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fbem-31093	149	9	,	,	PUNCT
fbem-31093	149	10	cheng	cheng	PROPN
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fbem-31093	149	12	,	,	PUNCT
fbem-31093	149	13	et	et	PROPN
fbem-31093	149	14	al	al	PROPN
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fbem-31093	149	17	attribute	attribute	NOUN
fbem-31093	149	18	-	-	PUNCT
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fbem-31093	149	20	fraud	fraud	NOUN
fbem-31093	149	21	detection	detection	NOUN
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fbem-31093	149	23	risk	risk	NOUN
fbem-31093	149	24	-	-	PUNCT
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fbem-31093	149	26	graph	graph	NOUN
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fbem-31093	149	28	[	[	X
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fbem-31093	149	30	]	]	X
fbem-31093	149	31	.	.	PUNCT
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fbem-31093	150	4	knowledge	knowledge	NOUN
fbem-31093	150	5	and	and	CCONJ
fbem-31093	150	6	data	datum	NOUN
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fbem-31093	150	8	,	,	PUNCT
fbem-31093	150	9	2025	2025	NUM
fbem-31093	150	10	.	.	PUNCT
fbem-31093	151	1	[	[	X
fbem-31093	151	2	9	9	NUM
fbem-31093	151	3	]	]	X
fbem-31093	151	4	lou	lou	PROPN
fbem-31093	151	5	c	c	PROPN
fbem-31093	151	6	,	,	PUNCT
fbem-31093	151	7	wang	wang	PROPN
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fbem-31093	151	9	,	,	PUNCT
fbem-31093	151	10	li	li	PROPN
fbem-31093	151	11	j	j	PROPN
fbem-31093	151	12	,	,	PUNCT
fbem-31093	151	13	et	et	PROPN
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fbem-31093	152	1	graph	graph	NOUN
fbem-31093	152	2	neural	neural	ADJ
fbem-31093	152	3	network	network	NOUN
fbem-31093	152	4	for	for	ADP
fbem-31093	152	5	fraud	fraud	NOUN
fbem-31093	152	6	detection	detection	NOUN
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fbem-31093	152	8	context	context	NOUN
fbem-31093	152	9	encoding	encoding	NOUN
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fbem-31093	153	1	[	[	X
fbem-31093	153	2	j	j	X
fbem-31093	153	3	]	]	X
fbem-31093	153	4	.	.	PUNCT
fbem-31093	154	1	expert	expert	NOUN
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fbem-31093	154	5	,	,	PUNCT
fbem-31093	154	6	2025	2025	NUM
fbem-31093	154	7	,	,	PUNCT
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fbem-31093	154	9	:	:	SYM
fbem-31093	154	10	125473	125473	NUM
fbem-31093	154	11	.	.	PUNCT
fbem-31093	155	1	[	[	X
fbem-31093	155	2	10	10	NUM
fbem-31093	155	3	]	]	X
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fbem-31093	155	5	x	x	PROPN
fbem-31093	155	6	,	,	PUNCT
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fbem-31093	155	9	,	,	PUNCT
fbem-31093	155	10	xu	xu	PROPN
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fbem-31093	155	12	,	,	PUNCT
fbem-31093	155	13	et	et	PROPN
fbem-31093	155	14	al	al	PROPN
fbem-31093	155	15	.	.	PROPN
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fbem-31093	155	17	-	-	PUNCT
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fbem-31093	155	21	for	for	ADP
fbem-31093	155	22	identifying	identify	VERB
fbem-31093	155	23	fraud	fraud	NOUN
fbem-31093	155	24	in	in	ADP
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fbem-31093	155	27	[	[	X
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fbem-31093	155	29	]	]	X
fbem-31093	155	30	.	.	PUNCT
fbem-31093	156	1	2025	2025	NUM
fbem-31093	156	2	.	.	PUNCT
fbem-31093	157	1	[	[	X
fbem-31093	157	2	11	11	NUM
fbem-31093	157	3	]	]	X
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fbem-31093	157	9	,	,	PUNCT
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fbem-31093	157	11	y	y	PROPN
fbem-31093	157	12	,	,	PUNCT
fbem-31093	157	13	et	et	PROPN
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fbem-31093	157	15	.	.	PUNCT
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fbem-31093	157	17	fraud	fraud	NOUN
fbem-31093	157	18	detection	detection	NOUN
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fbem-31093	157	20	joint	joint	ADJ
fbem-31093	157	21	transaction	transaction	NOUN
fbem-31093	157	22	language	language	NOUN
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fbem-31093	158	1	[	[	X
fbem-31093	158	2	j	j	X
fbem-31093	158	3	]	]	X
fbem-31093	158	4	.	.	PUNCT
fbem-31093	159	1	information	information	NOUN
fbem-31093	159	2	fusion	fusion	NOUN
fbem-31093	159	3	,	,	PUNCT
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fbem-31093	159	5	,	,	PUNCT
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fbem-31093	159	7	:	:	SYM
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fbem-31093	159	9	.	.	PUNCT
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fbem-31093	160	10	:	:	PUNCT
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fbem-31093	160	18	:	:	PUNCT
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fbem-31093	160	23	fraud	fraud	NOUN
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fbem-31093	161	1	[	[	X
fbem-31093	161	2	j	j	X
fbem-31093	161	3	]	]	X
fbem-31093	161	4	.	.	PUNCT
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fbem-31093	162	3	,	,	PUNCT
fbem-31093	162	4	2025	2025	NUM
fbem-31093	162	5	,	,	PUNCT
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fbem-31093	162	7	:	:	SYM
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fbem-31093	162	9	.	.	PUNCT
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fbem-31093	163	4	]	]	PUNCT
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fbem-31093	163	10	,	,	PUNCT
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fbem-31093	163	13	,	,	PUNCT
fbem-31093	163	14	et	et	PROPN
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fbem-31093	163	16	.	.	PUNCT
fbem-31093	164	1	transaction	transaction	NOUN
fbem-31093	164	2	fraud	fraud	NOUN
fbem-31093	164	3	detection	detection	NOUN
fbem-31093	164	4	via	via	ADP
fbem-31093	164	5	attentional	attentional	ADJ
fbem-31093	164	6	spatial	spatial	ADJ
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fbem-31093	164	9	gnn	gnn	NOUN
fbem-31093	165	1	[	[	X
fbem-31093	165	2	j	j	X
fbem-31093	165	3	]	]	X
fbem-31093	165	4	.	.	PUNCT
fbem-31093	166	1	the	the	DET
fbem-31093	166	2	journal	journal	NOUN
fbem-31093	166	3	of	of	ADP
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fbem-31093	166	5	,	,	PUNCT
fbem-31093	166	6	2025	2025	NUM
fbem-31093	166	7	,	,	PUNCT
fbem-31093	166	8	81(4	81(4	NUM
fbem-31093	166	9	):	):	PUNCT
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fbem-31093	166	11	.	.	PUNCT
fbem-31093	167	1	[	[	X
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fbem-31093	167	3	]	]	PUNCT
fbem-31093	167	4	pan	pan	PROPN
fbem-31093	167	5	j	j	PROPN
fbem-31093	167	6	,	,	PUNCT
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fbem-31093	167	9	,	,	PUNCT
fbem-31093	167	10	zheng	zheng	PROPN
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fbem-31093	167	12	,	,	PUNCT
fbem-31093	167	13	et	et	PROPN
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fbem-31093	167	15	.	.	PUNCT
fbem-31093	168	1	a	a	DET
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fbem-31093	168	3	-	-	PUNCT
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fbem-31093	168	6	-	-	PUNCT
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fbem-31093	168	8	approach	approach	NOUN
fbem-31093	168	9	for	for	ADP
fbem-31093	168	10	unsupervised	unsupervised	ADJ
fbem-31093	168	11	graph	graph	NOUN
fbem-31093	168	12	fraud	fraud	NOUN
fbem-31093	168	13	detection	detection	NOUN
fbem-31093	168	14	[	[	X
fbem-31093	168	15	c]//proceedings	c]//proceeding	NOUN
fbem-31093	168	16	of	of	ADP
fbem-31093	168	17	the	the	DET
fbem-31093	168	18	aaai	aaai	PROPN
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fbem-31093	168	23	.	.	PUNCT
fbem-31093	169	1	2025	2025	NUM
fbem-31093	169	2	,	,	PUNCT
fbem-31093	169	3	39(12	39(12	NUM
fbem-31093	169	4	):	):	PUNCT
fbem-31093	169	5	12443	12443	NUM
fbem-31093	169	6	-	-	SYM
fbem-31093	169	7	12451	12451	NUM
fbem-31093	169	8	.	.	PUNCT
fbem-31093	170	1	[	[	X
fbem-31093	170	2	15	15	NUM
fbem-31093	170	3	]	]	X
fbem-31093	170	4	kim	kim	PROPN
fbem-31093	170	5	n	n	NUM
fbem-31093	170	6	,	,	PUNCT
fbem-31093	170	7	patel	patel	PROPN
fbem-31093	170	8	s	s	PROPN
fbem-31093	170	9	,	,	PUNCT
fbem-31093	170	10	mendoza	mendoza	PROPN
fbem-31093	170	11	r	r	PROPN
fbem-31093	170	12	,	,	PUNCT
fbem-31093	170	13	et	et	PROPN
fbem-31093	170	14	al	al	PROPN
fbem-31093	170	15	.	.	PROPN
fbem-31093	170	16	graph	graph	NOUN
fbem-31093	170	17	neural	neural	ADJ
fbem-31093	170	18	networks	network	NOUN
fbem-31093	170	19	for	for	ADP
fbem-31093	170	20	anomaly	anomaly	NOUN
fbem-31093	170	21	detection	detection	NOUN
fbem-31093	170	22	in	in	ADP
fbem-31093	170	23	financial	financial	ADJ
fbem-31093	170	24	transactions	transaction	NOUN
fbem-31093	170	25	[	[	X
fbem-31093	170	26	j	j	X
fbem-31093	170	27	]	]	X
fbem-31093	170	28	.	.	PUNCT
fbem-31093	171	1	[	[	X
fbem-31093	171	2	16	16	NUM
fbem-31093	171	3	]	]	X
fbem-31093	171	4	al	al	PROPN
fbem-31093	171	5	-	-	PUNCT
fbem-31093	171	6	harbi	harbi	PROPN
fbem-31093	171	7	h.	h.	PROPN
fbem-31093	171	8	detecting	detect	VERB
fbem-31093	171	9	anomalies	anomaly	NOUN
fbem-31093	171	10	in	in	ADP
fbem-31093	171	11	blockchain	blockchain	PROPN
fbem-31093	171	12	transactions	transaction	NOUN
fbem-31093	171	13	using	use	VERB
fbem-31093	171	14	spatial	spatial	ADJ
fbem-31093	171	15	-	-	PUNCT
fbem-31093	171	16	temporal	temporal	ADJ
fbem-31093	171	17	graph	graph	NOUN
fbem-31093	171	18	neural	neural	ADJ
fbem-31093	171	19	networks	network	NOUN
fbem-31093	171	20	[	[	X
fbem-31093	171	21	j	j	X
fbem-31093	171	22	]	]	X
fbem-31093	171	23	.	.	PUNCT
fbem-31093	172	1	advances	advance	NOUN
fbem-31093	172	2	in	in	ADP
fbem-31093	172	3	management	management	NOUN
fbem-31093	172	4	and	and	CCONJ
fbem-31093	172	5	intelligent	intelligent	ADJ
fbem-31093	172	6	technologies	technology	NOUN
fbem-31093	172	7	,	,	PUNCT
fbem-31093	172	8	2025	2025	NUM
fbem-31093	172	9	,	,	PUNCT
fbem-31093	172	10	1(1	1(1	NUM
fbem-31093	172	11	)	)	PUNCT
fbem-31093	172	12	.	.	PUNCT
fbem-31093	173	1	[	[	X
fbem-31093	173	2	17	17	NUM
fbem-31093	173	3	]	]	X
fbem-31093	173	4	jiang	jiang	PROPN
fbem-31093	173	5	x	x	PROPN
fbem-31093	173	6	,	,	PUNCT
fbem-31093	173	7	tsai	tsai	PROPN
fbem-31093	173	8	w	w	PROPN
fbem-31093	173	9	t.	t.	PROPN
fbem-31093	173	10	mvcg	mvcg	PROPN
fbem-31093	173	11	-	-	PUNCT
fbem-31093	173	12	sps	sps	NOUN
fbem-31093	173	13	:	:	PUNCT
fbem-31093	173	14	a	a	DET
fbem-31093	173	15	multi	multi	ADJ
fbem-31093	173	16	-	-	ADJ
fbem-31093	173	17	view	view	ADJ
fbem-31093	173	18	contrastive	contrastive	ADJ
fbem-31093	173	19	graph	graph	NOUN
fbem-31093	173	20	neural	neural	ADJ
fbem-31093	173	21	network	network	NOUN
fbem-31093	173	22	for	for	ADP
fbem-31093	173	23	smart	smart	ADJ
fbem-31093	173	24	ponzi	ponzi	NOUN
fbem-31093	173	25	scheme	scheme	NOUN
fbem-31093	173	26	detection	detection	NOUN
fbem-31093	174	1	[	[	X
fbem-31093	174	2	j	j	X
fbem-31093	174	3	]	]	X
fbem-31093	174	4	.	.	PUNCT
fbem-31093	175	1	applied	apply	VERB
fbem-31093	175	2	sciences	science	NOUN
fbem-31093	175	3	,	,	PUNCT
fbem-31093	175	4	2025	2025	NUM
fbem-31093	175	5	,	,	PUNCT
fbem-31093	175	6	15(6	15(6	NUM
fbem-31093	175	7	):	):	PUNCT
fbem-31093	175	8	3281	3281	NUM
fbem-31093	175	9	.	.	PUNCT