id	sid	tid	token	lemma	pos
gc-467	1	1	horvat.indd	horvat.indd	PROPN
gc-467	1	2	�	�	PROPN
gc-467	1	3	ab	ab	PROPN
gc-467	1	4	stra	stra	PROPN
gc-467	1	5	ct	ct	PROPN
gc-467	1	6	traditional	traditional	ADJ
gc-467	1	7	techniques	technique	NOUN
gc-467	1	8	to	to	PART
gc-467	1	9	identify	identify	VERB
gc-467	1	10	a	a	DET
gc-467	1	11	depositional	depositional	ADJ
gc-467	1	12	body	body	NOUN
gc-467	1	13	from	from	ADP
gc-467	1	14	core	core	NOUN
gc-467	1	15	data	datum	NOUN
gc-467	1	16	are	be	AUX
gc-467	1	17	costly	costly	ADJ
gc-467	1	18	and	and	CCONJ
gc-467	1	19	sometimes	sometimes	ADV
gc-467	1	20	diffi	diffi	ADV
gc-467	1	21	cult	cult	VERB
gc-467	1	22	to	to	PART
gc-467	1	23	extrapolate	extrapolate	VERB
gc-467	1	24	to	to	ADP
gc-467	1	25	uncored	uncored	ADJ
gc-467	1	26	wells	well	NOUN
gc-467	1	27	.	.	PUNCT
gc-467	2	1	the	the	DET
gc-467	2	2	application	application	NOUN
gc-467	2	3	of	of	ADP
gc-467	2	4	kohonen	kohonen	PROPN
gc-467	2	5	’s	’s	PART
gc-467	2	6	self	self	NOUN
gc-467	2	7	organized	organize	VERB
gc-467	2	8	map	map	NOUN
gc-467	2	9	(	(	PUNCT
gc-467	2	10	som	som	NOUN
gc-467	2	11	)	)	PUNCT
gc-467	2	12	approach	approach	NOUN
gc-467	2	13	may	may	AUX
gc-467	2	14	be	be	AUX
gc-467	2	15	useful	useful	ADJ
gc-467	2	16	for	for	ADP
gc-467	2	17	the	the	DET
gc-467	2	18	interpretation	interpretation	NOUN
gc-467	2	19	of	of	ADP
gc-467	2	20	a	a	DET
gc-467	2	21	depositional	depositional	ADJ
gc-467	2	22	rock	rock	NOUN
gc-467	2	23	body	body	NOUN
gc-467	2	24	through	through	ADP
gc-467	2	25	well	well	ADV
gc-467	2	26	-	-	PUNCT
gc-467	2	27	log	log	NOUN
gc-467	2	28	data	datum	NOUN
gc-467	2	29	.	.	PUNCT
gc-467	3	1	som	som	NOUN
gc-467	3	2	is	be	AUX
gc-467	3	3	based	base	VERB
gc-467	3	4	on	on	ADP
gc-467	3	5	a	a	DET
gc-467	3	6	clustering	cluster	VERB
gc-467	3	7	algorithm	algorithm	NOUN
gc-467	3	8	and	and	CCONJ
gc-467	3	9	this	this	DET
gc-467	3	10	method	method	NOUN
gc-467	3	11	can	can	AUX
gc-467	3	12	be	be	AUX
gc-467	3	13	used	use	VERB
gc-467	3	14	to	to	PART
gc-467	3	15	discover	discover	VERB
gc-467	3	16	spatial	spatial	ADJ
gc-467	3	17	patterns	pattern	NOUN
gc-467	3	18	occurring	occur	VERB
gc-467	3	19	as	as	ADP
gc-467	3	20	clusters	cluster	NOUN
gc-467	3	21	in	in	ADP
gc-467	3	22	unstructured	unstructured	ADJ
gc-467	3	23	data	data	NOUN
gc-467	3	24	sets	set	NOUN
gc-467	3	25	.	.	PUNCT
gc-467	4	1	an	an	DET
gc-467	4	2	example	example	NOUN
gc-467	4	3	of	of	ADP
gc-467	4	4	the	the	DET
gc-467	4	5	application	application	NOUN
gc-467	4	6	of	of	ADP
gc-467	4	7	som	som	NOUN
gc-467	4	8	is	be	AUX
gc-467	4	9	presented	present	VERB
gc-467	4	10	whereby	whereby	SCONJ
gc-467	4	11	clusters	cluster	NOUN
gc-467	4	12	through	through	ADP
gc-467	4	13	som	som	PROPN
gc-467	4	14	can	can	AUX
gc-467	4	15	indicate	indicate	VERB
gc-467	4	16	the	the	DET
gc-467	4	17	contours	contours	NOUN
gc-467	4	18	of	of	ADP
gc-467	4	19	well	well	ADV
gc-467	4	20	-	-	PUNCT
gc-467	4	21	known	know	VERB
gc-467	4	22	depositional	depositional	ADJ
gc-467	4	23	patterns	pattern	NOUN
gc-467	4	24	such	such	ADJ
gc-467	4	25	as	as	ADP
gc-467	4	26	sub	sub	NOUN
gc-467	4	27	-	-	NOUN
gc-467	4	28	environments	environment	NOUN
gc-467	4	29	.	.	PUNCT
gc-467	5	1	keywords	keyword	NOUN
gc-467	5	2	:	:	PUNCT
gc-467	5	3	clustering	cluster	VERB
gc-467	5	4	method	method	NOUN
gc-467	5	5	,	,	PUNCT
gc-467	5	6	depositional	depositional	ADJ
gc-467	5	7	environment	environment	NOUN
gc-467	5	8	,	,	PUNCT
gc-467	5	9	neural	neural	ADJ
gc-467	5	10	network	network	NOUN
gc-467	5	11	,	,	PUNCT
gc-467	5	12	pattern	pattern	NOUN
gc-467	5	13	recognition	recognition	NOUN
gc-467	5	14	defi	defi	PROPN
gc-467	5	15	ning	ning	PROPN
gc-467	5	16	depositional	depositional	ADJ
gc-467	5	17	environments	environment	NOUN
gc-467	5	18	by	by	ADP
gc-467	5	19	using	use	VERB
gc-467	5	20	neural	neural	ADJ
gc-467	5	21	networks	network	NOUN
gc-467	5	22	�	�	PROPN
gc-467	5	23	janina	janina	PROPN
gc-467	5	24	horváth	horváth	PROPN
gc-467	5	25	department	department	PROPN
gc-467	5	26	of	of	ADP
gc-467	5	27	geology	geology	NOUN
gc-467	5	28	and	and	CCONJ
gc-467	5	29	palaeontology	palaeontology	NOUN
gc-467	5	30	,	,	PUNCT
gc-467	5	31	university	university	PROPN
gc-467	5	32	of	of	ADP
gc-467	5	33	szeged	szeged	PROPN
gc-467	5	34	,	,	PUNCT
gc-467	5	35	h-6722	h-6722	PROPN
gc-467	5	36	,	,	PUNCT
gc-467	5	37	szeged	szeged	PROPN
gc-467	5	38	,	,	PUNCT
gc-467	5	39	egyetem	egyetem	PROPN
gc-467	5	40	u.	u.	PROPN
gc-467	5	41	2–6	2–6	PROPN
gc-467	5	42	,	,	PUNCT
gc-467	5	43	hungary	hungary	PROPN
gc-467	5	44	;	;	PUNCT
gc-467	5	45	(	(	PUNCT
gc-467	5	46	th.janina@geo.u-szeged.hu	th.janina@geo.u-szeged.hu	NOUN
gc-467	5	47	)	)	PUNCT
gc-467	5	48	doi	doi	NOUN
gc-467	5	49	:	:	PUNCT
gc-467	5	50	104154	104154	NUM
gc-467	5	51	/	/	SYM
gc-467	5	52	gc.2011.21	gc.2011.21	PROPN
gc-467	5	53	geologia	geologia	PROPN
gc-467	5	54	croatica	croatica	PROPN
gc-467	5	55	64/3	64/3	PROPN
gc-467	5	56	251–258	251–258	NUM
gc-467	5	57	10	10	NUM
gc-467	5	58	figs	fig	NOUN
gc-467	5	59	.	.	PUNCT
gc-467	6	1	2	2	NUM
gc-467	6	2	tabs	tab	NOUN
gc-467	6	3	.	.	PUNCT
gc-467	7	1	zagreb	zagreb	PROPN
gc-467	7	2	2011	2011	NUM
gc-467	7	3	geologia	geologia	PROPN
gc-467	7	4	croaticageologia	croaticageologia	NOUN
gc-467	7	5	croatica	croatica	PROPN
gc-467	7	6	1	1	NUM
gc-467	7	7	.	.	PUNCT
gc-467	8	1	introduction	introduction	NOUN
gc-467	8	2	the	the	DET
gc-467	8	3	neural	neural	ADJ
gc-467	8	4	network	network	NOUN
gc-467	8	5	approach	approach	NOUN
gc-467	8	6	is	be	AUX
gc-467	8	7	a	a	DET
gc-467	8	8	well	well	ADV
gc-467	8	9	-	-	PUNCT
gc-467	8	10	known	know	VERB
gc-467	8	11	development	development	NOUN
gc-467	8	12	tool	tool	NOUN
gc-467	8	13	,	,	PUNCT
gc-467	8	14	which	which	PRON
gc-467	8	15	became	become	VERB
gc-467	8	16	popular	popular	ADJ
gc-467	8	17	within	within	ADP
gc-467	8	18	the	the	DET
gc-467	8	19	last	last	ADJ
gc-467	8	20	couple	couple	NOUN
gc-467	8	21	of	of	ADP
gc-467	8	22	decades	decade	NOUN
gc-467	8	23	.	.	PUNCT
gc-467	9	1	supervised	supervised	ADJ
gc-467	9	2	and	and	CCONJ
gc-467	9	3	unsupervised	unsupervised	ADJ
gc-467	9	4	trainable	trainable	ADJ
gc-467	9	5	networks	network	NOUN
gc-467	9	6	are	be	AUX
gc-467	9	7	used	use	VERB
gc-467	9	8	in	in	ADP
gc-467	9	9	many	many	ADJ
gc-467	9	10	different	different	ADJ
gc-467	9	11	fi	fi	NOUN
gc-467	9	12	elds	eld	NOUN
gc-467	9	13	of	of	ADP
gc-467	9	14	geology	geology	NOUN
gc-467	9	15	,	,	PUNCT
gc-467	9	16	especially	especially	ADV
gc-467	9	17	petroleum	petroleum	NOUN
gc-467	9	18	geology	geology	NOUN
gc-467	9	19	or	or	CCONJ
gc-467	9	20	facies	facie	VERB
gc-467	9	21	analysis	analysis	NOUN
gc-467	9	22	e.g.	e.g.	ADV
gc-467	9	23	the	the	DET
gc-467	9	24	unsupervised	unsupervised	ADJ
gc-467	9	25	network	network	NOUN
gc-467	9	26	as	as	ADP
gc-467	9	27	a	a	DET
gc-467	9	28	tool	tool	NOUN
gc-467	9	29	for	for	ADP
gc-467	9	30	lithofacies	lithofacie	NOUN
gc-467	9	31	identifi	identifi	PROPN
gc-467	9	32	cation	cation	NOUN
gc-467	9	33	(	(	PUNCT
gc-467	9	34	chang	chang	PROPN
gc-467	9	35	et	et	PROPN
gc-467	9	36	al	al	PROPN
gc-467	9	37	.	.	PROPN
gc-467	9	38	,	,	PUNCT
gc-467	9	39	2002	2002	NUM
gc-467	9	40	)	)	PUNCT
gc-467	9	41	,	,	PUNCT
gc-467	9	42	application	application	NOUN
gc-467	9	43	of	of	ADP
gc-467	9	44	a	a	DET
gc-467	9	45	supervised	supervised	ADJ
gc-467	9	46	neural	neural	ADJ
gc-467	9	47	network	network	NOUN
gc-467	9	48	for	for	ADP
gc-467	9	49	predicting	predict	VERB
gc-467	9	50	permeability	permeability	NOUN
gc-467	9	51	from	from	ADP
gc-467	9	52	porosity	porosity	NOUN
gc-467	9	53	(	(	PUNCT
gc-467	9	54	rogers	rogers	PROPN
gc-467	9	55	et	et	PROPN
gc-467	9	56	al	al	PROPN
gc-467	9	57	.	.	PROPN
gc-467	9	58	,	,	PUNCT
gc-467	9	59	1995	1995	NUM
gc-467	9	60	)	)	PUNCT
gc-467	9	61	,	,	PUNCT
gc-467	9	62	using	use	VERB
gc-467	9	63	a	a	DET
gc-467	9	64	supervised	supervised	ADJ
gc-467	9	65	neural	neural	ADJ
gc-467	9	66	network	network	NOUN
gc-467	9	67	tool	tool	NOUN
gc-467	9	68	in	in	ADP
gc-467	9	69	reservoir	reservoir	NOUN
gc-467	9	70	characterization	characterization	NOUN
gc-467	9	71	(	(	PUNCT
gc-467	9	72	ahmed	ahmed	PROPN
gc-467	9	73	et	et	PROPN
gc-467	9	74	al	al	PROPN
gc-467	9	75	.	.	PROPN
gc-467	9	76	,	,	PUNCT
gc-467	9	77	1997	1997	NUM
gc-467	9	78	)	)	PUNCT
gc-467	9	79	.	.	PUNCT
gc-467	10	1	however	however	ADV
gc-467	10	2	,	,	PUNCT
gc-467	10	3	supervised	supervised	ADJ
gc-467	10	4	networks	network	NOUN
gc-467	10	5	are	be	AUX
gc-467	10	6	more	more	ADV
gc-467	10	7	frequently	frequently	ADV
gc-467	10	8	used	use	VERB
gc-467	10	9	,	,	PUNCT
gc-467	10	10	because	because	SCONJ
gc-467	10	11	the	the	DET
gc-467	10	12	unsupervised	unsupervised	ADJ
gc-467	10	13	learning	learning	NOUN
gc-467	10	14	networks	network	NOUN
gc-467	10	15	can	can	AUX
gc-467	10	16	solve	solve	VERB
gc-467	10	17	specifi	specifi	PROPN
gc-467	10	18	c	c	PROPN
gc-467	10	19	problems	problem	NOUN
gc-467	10	20	like	like	ADP
gc-467	10	21	clustering	cluster	VERB
gc-467	10	22	or	or	CCONJ
gc-467	10	23	,	,	PUNCT
gc-467	10	24	pattern	pattern	NOUN
gc-467	10	25	recognitions	recognition	NOUN
gc-467	10	26	problems	problem	NOUN
gc-467	10	27	as	as	ADP
gc-467	10	28	a	a	DET
gc-467	10	29	way	way	NOUN
gc-467	10	30	of	of	ADP
gc-467	10	31	defi	defi	PROPN
gc-467	10	32	ning	ning	PROPN
gc-467	10	33	spatial	spatial	ADJ
gc-467	10	34	patterns	pattern	NOUN
gc-467	10	35	.	.	PUNCT
gc-467	11	1	application	application	NOUN
gc-467	11	2	of	of	ADP
gc-467	11	3	a	a	DET
gc-467	11	4	particular	particular	ADJ
gc-467	11	5	unsupervised	unsupervised	ADJ
gc-467	11	6	neural	neural	ADJ
gc-467	11	7	network	network	NOUN
gc-467	11	8	called	call	VERB
gc-467	11	9	kohonen	kohonen	PROPN
gc-467	11	10	’s	’s	PROPN
gc-467	11	11	network	network	NOUN
gc-467	11	12	(	(	PUNCT
gc-467	11	13	in	in	ADP
gc-467	11	14	other	other	ADJ
gc-467	11	15	words	word	NOUN
gc-467	11	16	self	self	NOUN
gc-467	11	17	organized	organize	VERB
gc-467	11	18	map	map	NOUN
gc-467	11	19	,	,	PUNCT
gc-467	11	20	abbreviated	abbreviate	VERB
gc-467	11	21	som	som	NOUN
gc-467	11	22	)	)	PUNCT
gc-467	11	23	in	in	ADP
gc-467	11	24	the	the	DET
gc-467	11	25	identifi	identifi	PROPN
gc-467	11	26	cation	cation	NOUN
gc-467	11	27	spatial	spatial	ADJ
gc-467	11	28	pattern	pattern	NOUN
gc-467	11	29	of	of	ADP
gc-467	11	30	some	some	PRON
gc-467	11	31	delta	delta	NOUN
gc-467	11	32	-	-	PUNCT
gc-467	11	33	plain	plain	ADJ
gc-467	11	34	sub	sub	NOUN
gc-467	11	35	-	-	NOUN
gc-467	11	36	environments	environment	NOUN
gc-467	11	37	is	be	AUX
gc-467	11	38	demonstrated	demonstrate	VERB
gc-467	11	39	here	here	ADV
gc-467	11	40	.	.	PUNCT
gc-467	12	1	kohonen	kohonen	PROPN
gc-467	12	2	’s	’s	PART
gc-467	12	3	neural	neural	ADJ
gc-467	12	4	network	network	NOUN
gc-467	12	5	has	have	AUX
gc-467	12	6	been	be	AUX
gc-467	12	7	successfully	successfully	ADV
gc-467	12	8	applied	apply	VERB
gc-467	12	9	to	to	ADP
gc-467	12	10	studies	study	NOUN
gc-467	12	11	with	with	ADP
gc-467	12	12	different	different	ADJ
gc-467	12	13	representation	representation	NOUN
gc-467	12	14	methods	method	NOUN
gc-467	12	15	or	or	CCONJ
gc-467	12	16	as	as	ADP
gc-467	12	17	a	a	DET
gc-467	12	18	tool	tool	NOUN
gc-467	12	19	to	to	PART
gc-467	12	20	defi	defi	VERB
gc-467	12	21	ne	ne	PROPN
gc-467	12	22	clusters	cluster	NOUN
gc-467	12	23	e.g.	e.g.	ADV
gc-467	12	24	a	a	DET
gc-467	12	25	well	well	INTJ
gc-467	12	26	log	log	NOUN
gc-467	12	27	interpretation	interpretation	NOUN
gc-467	12	28	model	model	NOUN
gc-467	12	29	for	for	ADP
gc-467	12	30	the	the	DET
gc-467	12	31	determination	determination	NOUN
gc-467	12	32	of	of	ADP
gc-467	12	33	reservoir	reservoir	NOUN
gc-467	12	34	facies	facie	NOUN
gc-467	12	35	and	and	CCONJ
gc-467	12	36	fl	fl	ADP
gc-467	12	37	uid	uid	ADJ
gc-467	12	38	contents	content	NOUN
gc-467	12	39	(	(	PUNCT
gc-467	12	40	akinyokun	akinyokun	NOUN
gc-467	12	41	et	et	PROPN
gc-467	12	42	al	al	PROPN
gc-467	12	43	.	.	PROPN
gc-467	12	44	,	,	PUNCT
gc-467	12	45	2009	2009	NUM
gc-467	12	46	)	)	PUNCT
gc-467	12	47	,	,	PUNCT
gc-467	12	48	lithofacies	lithofacie	NOUN
gc-467	12	49	identifi	identifi	VERB
gc-467	12	50	cation	cation	NOUN
gc-467	12	51	(	(	PUNCT
gc-467	12	52	chang	chang	PROPN
gc-467	12	53	et	et	PROPN
gc-467	12	54	al	al	PROPN
gc-467	12	55	.	.	PROPN
gc-467	12	56	,	,	PUNCT
gc-467	12	57	2002	2002	NUM
gc-467	12	58	)	)	PUNCT
gc-467	12	59	,	,	PUNCT
gc-467	12	60	and	and	CCONJ
gc-467	12	61	classifi	classifi	PROPN
gc-467	12	62	cation	cation	NOUN
gc-467	12	63	of	of	ADP
gc-467	12	64	biogenic	biogenic	ADJ
gc-467	12	65	sedimentation	sedimentation	NOUN
gc-467	12	66	(	(	PUNCT
gc-467	12	67	ultsch	ultsch	PROPN
gc-467	12	68	at	at	ADP
gc-467	12	69	al	al	PROPN
gc-467	12	70	.	.	PROPN
gc-467	12	71	,	,	PUNCT
gc-467	12	72	1995	1995	NUM
gc-467	12	73	)	)	PUNCT
gc-467	12	74	.	.	PUNCT
gc-467	13	1	traditional	traditional	ADJ
gc-467	13	2	techniques	technique	NOUN
gc-467	13	3	to	to	PART
gc-467	13	4	identify	identify	VERB
gc-467	13	5	depositional	depositional	ADJ
gc-467	13	6	environments	environment	NOUN
gc-467	13	7	from	from	ADP
gc-467	13	8	core	core	NOUN
gc-467	13	9	data	datum	NOUN
gc-467	13	10	are	be	AUX
gc-467	13	11	diffi	diffi	ADJ
gc-467	13	12	cult	cult	NOUN
gc-467	13	13	as	as	SCONJ
gc-467	13	14	they	they	PRON
gc-467	13	15	require	require	VERB
gc-467	13	16	a	a	DET
gc-467	13	17	large	large	ADJ
gc-467	13	18	dataset	dataset	NOUN
gc-467	13	19	and/or	and/or	CCONJ
gc-467	13	20	are	be	AUX
gc-467	13	21	less	less	ADV
gc-467	13	22	precise	precise	ADJ
gc-467	13	23	than	than	ADP
gc-467	13	24	some	some	DET
gc-467	13	25	results	result	NOUN
gc-467	13	26	gained	gain	VERB
gc-467	13	27	by	by	ADP
gc-467	13	28	using	use	VERB
gc-467	13	29	mathematical	mathematical	ADJ
gc-467	13	30	models	model	NOUN
gc-467	13	31	for	for	ADP
gc-467	13	32	mapping	mapping	NOUN
gc-467	13	33	.	.	PUNCT
gc-467	14	1	this	this	DET
gc-467	14	2	study	study	NOUN
gc-467	14	3	shows	show	VERB
gc-467	14	4	a	a	DET
gc-467	14	5	neural	neural	ADJ
gc-467	14	6	network	network	NOUN
gc-467	14	7	methodology	methodology	NOUN
gc-467	14	8	which	which	PRON
gc-467	14	9	can	can	AUX
gc-467	14	10	handle	handle	VERB
gc-467	14	11	simultaneously	simultaneously	ADV
gc-467	14	12	more	more	ADJ
gc-467	14	13	point	point	NOUN
gc-467	14	14	data	datum	NOUN
gc-467	14	15	and	and	CCONJ
gc-467	14	16	even	even	ADV
gc-467	14	17	join	join	VERB
gc-467	14	18	more	more	ADJ
gc-467	14	19	attributes	attribute	NOUN
gc-467	14	20	,	,	PUNCT
gc-467	14	21	or	or	CCONJ
gc-467	14	22	property	property	NOUN
gc-467	14	23	of	of	ADP
gc-467	14	24	data	datum	NOUN
gc-467	14	25	points	point	NOUN
gc-467	14	26	.	.	PUNCT
gc-467	15	1	therefore	therefore	ADV
gc-467	15	2	the	the	DET
gc-467	15	3	som	som	NOUN
gc-467	15	4	approach	approach	NOUN
gc-467	15	5	may	may	AUX
gc-467	15	6	be	be	AUX
gc-467	15	7	regarded	regard	VERB
gc-467	15	8	as	as	ADP
gc-467	15	9	a	a	DET
gc-467	15	10	possible	possible	ADJ
gc-467	15	11	method	method	NOUN
gc-467	15	12	for	for	ADP
gc-467	15	13	pattern	pattern	NOUN
gc-467	15	14	recognition	recognition	NOUN
gc-467	15	15	by	by	ADP
gc-467	15	16	parallel	parallel	ADJ
gc-467	15	17	analysis	analysis	NOUN
gc-467	15	18	of	of	ADP
gc-467	15	19	multiple	multiple	ADJ
gc-467	15	20	data	datum	NOUN
gc-467	15	21	sources	source	NOUN
gc-467	15	22	.	.	PUNCT
gc-467	16	1	in	in	ADP
gc-467	16	2	this	this	DET
gc-467	16	3	study	study	NOUN
gc-467	16	4	we	we	PRON
gc-467	16	5	describe	describe	VERB
gc-467	16	6	a	a	DET
gc-467	16	7	method	method	NOUN
gc-467	16	8	based	base	VERB
gc-467	16	9	mostly	mostly	ADV
gc-467	16	10	on	on	ADP
gc-467	16	11	data	datum	NOUN
gc-467	16	12	of	of	ADP
gc-467	16	13	electrofacies	electrofacie	NOUN
gc-467	16	14	obtained	obtain	VERB
gc-467	16	15	from	from	ADP
gc-467	16	16	e	e	NOUN
gc-467	16	17	-	-	NOUN
gc-467	16	18	logs	log	NOUN
gc-467	16	19	.	.	PUNCT
gc-467	17	1	it	it	PRON
gc-467	17	2	is	be	AUX
gc-467	17	3	a	a	DET
gc-467	17	4	possible	possible	ADJ
gc-467	17	5	tool	tool	NOUN
gc-467	17	6	for	for	ADP
gc-467	17	7	the	the	DET
gc-467	17	8	characterization	characterization	NOUN
gc-467	17	9	of	of	ADP
gc-467	17	10	depositional	depositional	ADJ
gc-467	17	11	environments	environment	NOUN
gc-467	17	12	comprising	comprise	VERB
gc-467	17	13	the	the	DET
gc-467	17	14	rock	rock	NOUN
gc-467	17	15	body	body	NOUN
gc-467	17	16	.	.	PUNCT
gc-467	18	1	contrary	contrary	ADJ
gc-467	18	2	to	to	ADP
gc-467	18	3	traditional	traditional	ADJ
gc-467	18	4	geostatistical	geostatistical	ADJ
gc-467	18	5	interpolation	interpolation	NOUN
gc-467	18	6	methods	method	NOUN
gc-467	18	7	,	,	PUNCT
gc-467	18	8	neural	neural	ADJ
gc-467	18	9	networks	network	NOUN
gc-467	18	10	as	as	ADP
gc-467	18	11	clustering	cluster	VERB
gc-467	18	12	schemes	scheme	NOUN
gc-467	18	13	can	can	AUX
gc-467	18	14	provide	provide	VERB
gc-467	18	15	many	many	ADJ
gc-467	18	16	possibilities	possibility	NOUN
gc-467	18	17	for	for	ADP
gc-467	18	18	modeling	modeling	NOUN
gc-467	18	19	.	.	PUNCT
gc-467	19	1	kohonen	kohonen	PROPN
gc-467	19	2	’s	’s	PROPN
gc-467	19	3	algorithm	algorithm	NOUN
gc-467	19	4	reveals	reveal	VERB
gc-467	19	5	these	these	DET
gc-467	19	6	spatial	spatial	ADJ
gc-467	19	7	patterns	pattern	NOUN
gc-467	19	8	in	in	ADP
gc-467	19	9	the	the	DET
gc-467	19	10	terms	term	NOUN
gc-467	19	11	of	of	ADP
gc-467	19	12	clusters	cluster	NOUN
gc-467	19	13	.	.	PUNCT
gc-467	20	1	from	from	ADP
gc-467	20	2	this	this	DET
gc-467	20	3	aspect	aspect	NOUN
gc-467	20	4	,	,	PUNCT
gc-467	20	5	som	som	NOUN
gc-467	20	6	is	be	AUX
gc-467	20	7	quite	quite	ADV
gc-467	20	8	similar	similar	ADJ
gc-467	20	9	to	to	ADP
gc-467	20	10	general	general	ADJ
gc-467	20	11	clustering	clustering	ADJ
gc-467	20	12	algorithms	algorithm	NOUN
gc-467	20	13	,	,	PUNCT
gc-467	20	14	although	although	SCONJ
gc-467	20	15	ultsch	ultsch	PROPN
gc-467	20	16	(	(	PUNCT
gc-467	20	17	1995	1995	NUM
gc-467	20	18	)	)	PUNCT
gc-467	20	19	has	have	AUX
gc-467	20	20	shown	show	VERB
gc-467	20	21	that	that	SCONJ
gc-467	20	22	som	som	NOUN
gc-467	20	23	can	can	AUX
gc-467	20	24	even	even	ADV
gc-467	20	25	recognize	recognize	VERB
gc-467	20	26	point	point	NOUN
gc-467	20	27	-	-	PUNCT
gc-467	20	28	clusters	cluster	NOUN
gc-467	20	29	in	in	ADP
gc-467	20	30	those	those	DET
gc-467	20	31	situations	situation	NOUN
gc-467	20	32	where	where	SCONJ
gc-467	20	33	traditional	traditional	ADJ
gc-467	20	34	cluster	cluster	NOUN
gc-467	20	35	techniques	technique	NOUN
gc-467	20	36	fail	fail	VERB
gc-467	20	37	to	to	PART
gc-467	20	38	fi	fi	VERB
gc-467	20	39	nd	nd	ADV
gc-467	20	40	any	any	DET
gc-467	20	41	reasonable	reasonable	ADJ
gc-467	20	42	groups	group	NOUN
gc-467	20	43	.	.	PUNCT
gc-467	21	1	here	here	ADV
gc-467	21	2	,	,	PUNCT
gc-467	21	3	spatial	spatial	ADJ
gc-467	21	4	patterns	pattern	NOUN
gc-467	21	5	are	be	AUX
gc-467	21	6	defi	defi	NOUN
gc-467	21	7	ned	ned	NOUN
gc-467	21	8	as	as	ADP
gc-467	21	9	spatial	spatial	ADJ
gc-467	21	10	groups	group	NOUN
gc-467	21	11	of	of	ADP
gc-467	21	12	points	point	NOUN
gc-467	21	13	,	,	PUNCT
gc-467	21	14	where	where	SCONJ
gc-467	21	15	points	point	NOUN
gc-467	21	16	are	be	AUX
gc-467	21	17	bounded	bound	VERB
gc-467	21	18	by	by	ADP
gc-467	21	19	a	a	DET
gc-467	21	20	polygon	polygon	NOUN
gc-467	21	21	(	(	PUNCT
gc-467	21	22	e.g.	e.g.	ADV
gc-467	21	23	contour	contour	NOUN
gc-467	21	24	of	of	ADP
gc-467	21	25	sand	sand	NOUN
gc-467	21	26	content	content	NOUN
gc-467	21	27	)	)	PUNCT
gc-467	21	28	.	.	PUNCT
gc-467	22	1	by	by	ADP
gc-467	22	2	using	use	VERB
gc-467	22	3	this	this	DET
gc-467	22	4	defi	defi	NOUN
gc-467	22	5	nition	nition	NOUN
gc-467	22	6	,	,	PUNCT
gc-467	22	7	one	one	PRON
gc-467	22	8	can	can	AUX
gc-467	22	9	conclude	conclude	VERB
gc-467	22	10	,	,	PUNCT
gc-467	22	11	that	that	DET
gc-467	22	12	pattern	pattern	NOUN
gc-467	22	13	recognition	recognition	NOUN
gc-467	22	14	can	can	AUX
gc-467	22	15	be	be	AUX
gc-467	22	16	drawn	draw	VERB
gc-467	22	17	back	back	ADV
gc-467	22	18	to	to	ADP
gc-467	22	19	a	a	DET
gc-467	22	20	clustering	clustering	ADJ
gc-467	22	21	problem	problem	NOUN
gc-467	22	22	.	.	PUNCT
gc-467	23	1	the	the	DET
gc-467	23	2	shape	shape	NOUN
gc-467	23	3	of	of	ADP
gc-467	23	4	the	the	DET
gc-467	23	5	polygon	polygon	NOUN
gc-467	23	6	,	,	PUNCT
gc-467	23	7	i.e.	i.e.	X
gc-467	23	8	the	the	DET
gc-467	23	9	contour	contour	NOUN
gc-467	23	10	geometry	geometry	NOUN
gc-467	23	11	,	,	PUNCT
gc-467	23	12	refl	refl	PROPN
gc-467	23	13	ects	ect	VERB
gc-467	23	14	the	the	DET
gc-467	23	15	geologia	geologia	ADJ
gc-467	23	16	croatica	croatica	PROPN
gc-467	23	17	64/3geologia	64/3geologia	NOUN
gc-467	23	18	croatica	croatica	PROPN
gc-467	23	19	252	252	NUM
gc-467	23	20	2d	2d	NOUN
gc-467	23	21	or	or	CCONJ
gc-467	23	22	3d	3d	NUM
gc-467	23	23	geometry	geometry	NOUN
gc-467	23	24	of	of	ADP
gc-467	23	25	the	the	DET
gc-467	23	26	depositional	depositional	ADJ
gc-467	23	27	facies	facie	NOUN
gc-467	23	28	identifi	identifi	PROPN
gc-467	23	29	ed	ed	NOUN
gc-467	23	30	.	.	PUNCT
gc-467	24	1	this	this	PRON
gc-467	24	2	is	be	AUX
gc-467	24	3	the	the	DET
gc-467	24	4	sedimentary	sedimentary	ADJ
gc-467	24	5	environment	environment	NOUN
gc-467	24	6	according	accord	VERB
gc-467	24	7	to	to	ADP
gc-467	24	8	pettijohn	pettijohn	NOUN
gc-467	24	9	and	and	CCONJ
gc-467	24	10	potter	potter	NOUN
gc-467	24	11	(	(	PUNCT
gc-467	24	12	1972	1972	NUM
gc-467	24	13	)	)	PUNCT
gc-467	24	14	.	.	PUNCT
gc-467	25	1	in	in	ADP
gc-467	25	2	this	this	DET
gc-467	25	3	study	study	NOUN
gc-467	25	4	,	,	PUNCT
gc-467	25	5	the	the	DET
gc-467	25	6	main	main	ADJ
gc-467	25	7	emphasis	emphasis	NOUN
gc-467	25	8	is	be	AUX
gc-467	25	9	given	give	VERB
gc-467	25	10	to	to	ADP
gc-467	25	11	the	the	DET
gc-467	25	12	following	following	ADJ
gc-467	25	13	issues	issue	NOUN
gc-467	25	14	:	:	PUNCT
gc-467	25	15	(	(	PUNCT
gc-467	25	16	1	1	X
gc-467	25	17	)	)	PUNCT
gc-467	25	18	demonstration	demonstration	NOUN
gc-467	25	19	of	of	ADP
gc-467	25	20	how	how	SCONJ
gc-467	25	21	a	a	DET
gc-467	25	22	known	know	VERB
gc-467	25	23	depositional	depositional	ADJ
gc-467	25	24	geometry	geometry	NOUN
gc-467	25	25	outlined	outline	VERB
gc-467	25	26	by	by	ADP
gc-467	25	27	sand	sand	NOUN
gc-467	25	28	-	-	PUNCT
gc-467	25	29	content	content	NOUN
gc-467	25	30	contours	contours	NOUN
gc-467	25	31	can	can	AUX
gc-467	25	32	be	be	AUX
gc-467	25	33	honored	honor	VERB
gc-467	25	34	by	by	ADP
gc-467	25	35	using	use	VERB
gc-467	25	36	som	som	NOUN
gc-467	25	37	analysis	analysis	NOUN
gc-467	25	38	of	of	ADP
gc-467	25	39	points	point	NOUN
gc-467	25	40	of	of	ADP
gc-467	25	41	three	three	NUM
gc-467	25	42	petrophysical	petrophysical	ADJ
gc-467	25	43	grids	grid	NOUN
gc-467	25	44	.	.	PUNCT
gc-467	26	1	this	this	DET
gc-467	26	2	analysis	analysis	NOUN
gc-467	26	3	relies	rely	VERB
gc-467	26	4	on	on	ADP
gc-467	26	5	good	good	ADJ
gc-467	26	6	average	average	ADJ
gc-467	26	7	porosity	porosity	NOUN
gc-467	26	8	,	,	PUNCT
gc-467	26	9	net	net	ADJ
gc-467	26	10	pore	pore	ADJ
gc-467	26	11	volume	volume	NOUN
gc-467	26	12	and	and	CCONJ
gc-467	26	13	hydraulic	hydraulic	ADJ
gc-467	26	14	conductivity	conductivity	NOUN
gc-467	26	15	grids	grid	NOUN
gc-467	26	16	;	;	PUNCT
gc-467	26	17	(	(	PUNCT
gc-467	26	18	2	2	X
gc-467	26	19	)	)	PUNCT
gc-467	26	20	description	description	NOUN
gc-467	26	21	of	of	ADP
gc-467	26	22	an	an	DET
gc-467	26	23	example	example	NOUN
gc-467	26	24	of	of	ADP
gc-467	26	25	the	the	DET
gc-467	26	26	application	application	NOUN
gc-467	26	27	of	of	ADP
gc-467	26	28	this	this	DET
gc-467	26	29	robust	robust	ADJ
gc-467	26	30	approach	approach	NOUN
gc-467	26	31	in	in	ADP
gc-467	26	32	re	re	VERB
gc-467	26	33	-	-	VERB
gc-467	26	34	recognizing	recognize	VERB
gc-467	26	35	the	the	DET
gc-467	26	36	known	know	VERB
gc-467	26	37	distributary	distributary	ADJ
gc-467	26	38	mouth	mouth	NOUN
gc-467	26	39	bar	bar	NOUN
gc-467	26	40	shape	shape	NOUN
gc-467	26	41	in	in	ADP
gc-467	26	42	a	a	DET
gc-467	26	43	particular	particular	ADJ
gc-467	26	44	pannonian	pannonian	ADJ
gc-467	26	45	reservoir	reservoir	NOUN
gc-467	26	46	.	.	PUNCT
gc-467	27	1	2	2	X
gc-467	27	2	.	.	NUM
gc-467	27	3	applied	apply	VERB
gc-467	27	4	method	method	NOUN
gc-467	27	5	2.1	2.1	NUM
gc-467	27	6	.	.	PUNCT
gc-467	28	1	self	self	NOUN
gc-467	28	2	organized	organize	VERB
gc-467	28	3	maps	map	NOUN
gc-467	28	4	(	(	PUNCT
gc-467	28	5	som	som	NOUN
gc-467	28	6	)	)	PUNCT
gc-467	28	7	kohonen	kohonen	PROPN
gc-467	28	8	’s	’s	PART
gc-467	28	9	neural	neural	ADJ
gc-467	28	10	network	network	NOUN
gc-467	28	11	(	(	PUNCT
gc-467	28	12	or	or	CCONJ
gc-467	28	13	self	self	NOUN
gc-467	28	14	organized	organize	VERB
gc-467	28	15	map	map	NOUN
gc-467	28	16	(	(	PUNCT
gc-467	28	17	som	som	NOUN
gc-467	28	18	)	)	PUNCT
gc-467	28	19	)	)	PUNCT
gc-467	28	20	means	mean	VERB
gc-467	28	21	that	that	SCONJ
gc-467	28	22	the	the	DET
gc-467	28	23	neurons	neuron	NOUN
gc-467	28	24	are	be	AUX
gc-467	28	25	organized	organize	VERB
gc-467	28	26	in	in	ADP
gc-467	28	27	a	a	DET
gc-467	28	28	grid	grid	NOUN
gc-467	28	29	(	(	PUNCT
gc-467	28	30	fig	fig	NOUN
gc-467	28	31	.	.	NOUN
gc-467	29	1	1	1	NUM
gc-467	29	2	)	)	PUNCT
gc-467	30	1	as	as	ADP
gc-467	30	2	a	a	DET
gc-467	30	3	‘	'	PUNCT
gc-467	30	4	map	map	NOUN
gc-467	30	5	’	'	PUNCT
gc-467	30	6	.	.	PUNCT
gc-467	31	1	however	however	ADV
gc-467	31	2	it	it	PRON
gc-467	31	3	is	be	AUX
gc-467	31	4	not	not	PART
gc-467	31	5	a	a	DET
gc-467	31	6	real	real	ADJ
gc-467	31	7	map	map	NOUN
gc-467	31	8	since	since	SCONJ
gc-467	31	9	it	it	PRON
gc-467	31	10	does	do	AUX
gc-467	31	11	not	not	PART
gc-467	31	12	assign	assign	VERB
gc-467	31	13	any	any	DET
gc-467	31	14	spatial	spatial	ADJ
gc-467	31	15	coordinates	coordinate	NOUN
gc-467	31	16	to	to	ADP
gc-467	31	17	the	the	DET
gc-467	31	18	samples	sample	NOUN
gc-467	31	19	.	.	PUNCT
gc-467	32	1	so	so	ADV
gc-467	32	2	,	,	PUNCT
gc-467	32	3	self	self	NOUN
gc-467	32	4	organizing	organizing	NOUN
gc-467	32	5	gives	give	VERB
gc-467	32	6	a	a	DET
gc-467	32	7	‘	'	PUNCT
gc-467	32	8	map	map	NOUN
gc-467	32	9	’	'	PUNCT
gc-467	32	10	where	where	SCONJ
gc-467	32	11	the	the	DET
gc-467	32	12	nearby	nearby	ADJ
gc-467	32	13	locations	location	NOUN
gc-467	32	14	represent	represent	VERB
gc-467	32	15	inputs	input	NOUN
gc-467	32	16	with	with	ADP
gc-467	32	17	similar	similar	ADJ
gc-467	32	18	properties	property	NOUN
gc-467	32	19	.	.	PUNCT
gc-467	33	1	som	som	NOUN
gc-467	33	2	is	be	AUX
gc-467	33	3	a	a	DET
gc-467	33	4	type	type	NOUN
gc-467	33	5	of	of	ADP
gc-467	33	6	competitive	competitive	ADJ
gc-467	33	7	and	and	CCONJ
gc-467	33	8	unsupervised	unsupervised	ADJ
gc-467	33	9	network	network	NOUN
gc-467	33	10	.	.	PUNCT
gc-467	34	1	the	the	DET
gc-467	34	2	competitive	competitive	ADJ
gc-467	34	3	and	and	CCONJ
gc-467	34	4	unsupervised	unsupervised	ADJ
gc-467	34	5	learning	learning	NOUN
gc-467	34	6	algorithm	algorithm	NOUN
gc-467	34	7	implies	imply	VERB
gc-467	34	8	that	that	SCONJ
gc-467	34	9	the	the	DET
gc-467	34	10	network	network	NOUN
gc-467	34	11	has	have	VERB
gc-467	34	12	to	to	PART
gc-467	34	13	have	have	VERB
gc-467	34	14	the	the	DET
gc-467	34	15	ability	ability	NOUN
gc-467	34	16	to	to	PART
gc-467	34	17	recognize	recognize	VERB
gc-467	34	18	the	the	DET
gc-467	34	19	structure	structure	NOUN
gc-467	34	20	of	of	ADP
gc-467	34	21	a	a	DET
gc-467	34	22	multidimensional	multidimensional	ADJ
gc-467	34	23	basic	basic	ADJ
gc-467	34	24	data	datum	NOUN
gc-467	34	25	set	set	VERB
gc-467	34	26	,	,	PUNCT
gc-467	34	27	by	by	ADP
gc-467	34	28	the	the	DET
gc-467	34	29	method	method	NOUN
gc-467	34	30	of	of	ADP
gc-467	34	31	dimension	dimension	NOUN
gc-467	34	32	reduction	reduction	NOUN
gc-467	34	33	(	(	PUNCT
gc-467	34	34	kohonen	kohonen	PROPN
gc-467	34	35	,	,	PUNCT
gc-467	34	36	1982	1982	NUM
gc-467	34	37	,	,	PUNCT
gc-467	34	38	kohonen	kohonen	PROPN
gc-467	34	39	2001	2001	NUM
gc-467	34	40	;	;	PUNCT
gc-467	34	41	haykin	haykin	PROPN
gc-467	34	42	,	,	PUNCT
gc-467	34	43	1999	1999	NUM
gc-467	34	44	;	;	PUNCT
gc-467	34	45	patterson	patterson	PROPN
gc-467	34	46	,	,	PUNCT
gc-467	34	47	1996	1996	NUM
gc-467	34	48	;	;	PUNCT
gc-467	34	49	fausett	fausett	NOUN
gc-467	34	50	,	,	PUNCT
gc-467	34	51	1994	1994	NUM
gc-467	34	52	)	)	PUNCT
gc-467	34	53	.	.	PUNCT
gc-467	35	1	this	this	DET
gc-467	35	2	reduction	reduction	NOUN
gc-467	35	3	is	be	AUX
gc-467	35	4	only	only	ADV
gc-467	35	5	a	a	DET
gc-467	35	6	“	"	PUNCT
gc-467	35	7	queasy	queasy	NOUN
gc-467	35	8	”	"	PUNCT
gc-467	35	9	one	one	NUM
gc-467	35	10	,	,	PUNCT
gc-467	35	11	since	since	SCONJ
gc-467	35	12	each	each	DET
gc-467	35	13	neuron	neuron	NOUN
gc-467	35	14	is	be	AUX
gc-467	35	15	an	an	DET
gc-467	35	16	n	n	ADV
gc-467	35	17	-	-	PUNCT
gc-467	35	18	dimensional	dimensional	ADJ
gc-467	35	19	weight	weight	NOUN
gc-467	35	20	-	-	PUNCT
gc-467	35	21	vector	vector	NOUN
gc-467	35	22	,	,	PUNCT
gc-467	35	23	where	where	SCONJ
gc-467	35	24	n	n	PRON
gc-467	35	25	is	be	AUX
gc-467	35	26	equal	equal	ADJ
gc-467	35	27	to	to	ADP
gc-467	35	28	the	the	DET
gc-467	35	29	dimension	dimension	NOUN
gc-467	35	30	of	of	ADP
gc-467	35	31	the	the	DET
gc-467	35	32	input	input	NOUN
gc-467	35	33	vectors	vector	NOUN
gc-467	35	34	(	(	PUNCT
gc-467	35	35	fig	fig	NOUN
gc-467	35	36	.	.	PUNCT
gc-467	36	1	1	1	NUM
gc-467	36	2	)	)	PUNCT
gc-467	36	3	.	.	PUNCT
gc-467	37	1	the	the	DET
gc-467	37	2	main	main	ADJ
gc-467	37	3	goal	goal	NOUN
gc-467	37	4	of	of	ADP
gc-467	37	5	som	som	NOUN
gc-467	37	6	is	be	AUX
gc-467	37	7	to	to	PART
gc-467	37	8	represent	represent	VERB
gc-467	37	9	data	data	NOUN
gc-467	37	10	points	point	NOUN
gc-467	37	11	with	with	ADP
gc-467	37	12	fewer	few	ADJ
gc-467	37	13	representatives	representative	NOUN
gc-467	37	14	preserving	preserve	VERB
gc-467	37	15	the	the	DET
gc-467	37	16	original	original	ADJ
gc-467	37	17	topology	topology	NOUN
gc-467	37	18	(	(	PUNCT
gc-467	37	19	johannson	johannson	PROPN
gc-467	37	20	,	,	PUNCT
gc-467	37	21	2003	2003	NUM
gc-467	37	22	)	)	PUNCT
gc-467	37	23	.	.	PUNCT
gc-467	38	1	even	even	ADV
gc-467	38	2	the	the	DET
gc-467	38	3	unsupervised	unsupervised	ADJ
gc-467	38	4	learning	learning	NOUN
gc-467	38	5	character	character	NOUN
gc-467	38	6	implies	imply	VERB
gc-467	38	7	that	that	SCONJ
gc-467	38	8	only	only	ADV
gc-467	38	9	one	one	NUM
gc-467	38	10	data	datum	NOUN
gc-467	38	11	set	set	VERB
gc-467	38	12	is	be	AUX
gc-467	38	13	available	available	ADJ
gc-467	38	14	for	for	ADP
gc-467	38	15	analysis	analysis	NOUN
gc-467	38	16	.	.	PUNCT
gc-467	39	1	so	so	ADV
gc-467	39	2	the	the	DET
gc-467	39	3	data	data	NOUN
gc-467	39	4	structure	structure	NOUN
gc-467	39	5	is	be	AUX
gc-467	39	6	explored	explore	VERB
gc-467	39	7	within	within	ADP
gc-467	39	8	the	the	DET
gc-467	39	9	input	input	NOUN
gc-467	39	10	set	set	VERB
gc-467	39	11	without	without	ADP
gc-467	39	12	using	use	VERB
gc-467	39	13	any	any	DET
gc-467	39	14	reference	reference	NOUN
gc-467	39	15	dataset	dataset	VERB
gc-467	39	16	.	.	PUNCT
gc-467	40	1	in	in	ADP
gc-467	40	2	the	the	DET
gc-467	40	3	case	case	NOUN
gc-467	40	4	of	of	ADP
gc-467	40	5	the	the	DET
gc-467	40	6	supervised	supervised	ADJ
gc-467	40	7	neural	neural	ADJ
gc-467	40	8	network	network	NOUN
gc-467	40	9	,	,	PUNCT
gc-467	40	10	the	the	DET
gc-467	40	11	training	training	NOUN
gc-467	40	12	processes	process	NOUN
gc-467	40	13	depend	depend	VERB
gc-467	40	14	on	on	ADP
gc-467	40	15	training	training	NOUN
gc-467	40	16	examples	example	NOUN
gc-467	40	17	and	and	CCONJ
gc-467	40	18	each	each	DET
gc-467	40	19	example	example	NOUN
gc-467	40	20	is	be	AUX
gc-467	40	21	a	a	DET
gc-467	40	22	pair	pair	NOUN
gc-467	40	23	of	of	ADP
gc-467	40	24	an	an	DET
gc-467	40	25	input	input	NOUN
gc-467	40	26	objects	object	NOUN
gc-467	40	27	.	.	PUNCT
gc-467	41	1	in	in	ADP
gc-467	41	2	contrast	contrast	NOUN
gc-467	41	3	with	with	ADP
gc-467	41	4	the	the	DET
gc-467	41	5	unsupervised	unsupervised	ADJ
gc-467	41	6	network	network	NOUN
gc-467	41	7	,	,	PUNCT
gc-467	41	8	the	the	DET
gc-467	41	9	learning	learning	NOUN
gc-467	41	10	processes	process	NOUN
gc-467	41	11	are	be	AUX
gc-467	41	12	based	base	VERB
gc-467	41	13	on	on	ADP
gc-467	41	14	unlabelled	unlabelled	ADJ
gc-467	41	15	examples	example	NOUN
gc-467	41	16	.	.	PUNCT
gc-467	42	1	the	the	DET
gc-467	42	2	framework	framework	NOUN
gc-467	42	3	(	(	PUNCT
gc-467	42	4	fig	fig	NOUN
gc-467	42	5	.	.	NOUN
gc-467	42	6	2	2	NUM
gc-467	42	7	)	)	PUNCT
gc-467	42	8	of	of	ADP
gc-467	42	9	kohonen	kohonen	PROPN
gc-467	42	10	’s	’s	PART
gc-467	42	11	neural	neural	ADJ
gc-467	42	12	network	network	NOUN
gc-467	42	13	also	also	ADV
gc-467	42	14	demonstrates	demonstrate	VERB
gc-467	42	15	this	this	DET
gc-467	42	16	difference	difference	NOUN
gc-467	42	17	between	between	ADP
gc-467	42	18	the	the	DET
gc-467	42	19	supervised	supervised	ADJ
gc-467	42	20	and	and	CCONJ
gc-467	42	21	unsupervised	unsupervised	ADJ
gc-467	42	22	neural	neural	ADJ
gc-467	42	23	networks	network	NOUN
gc-467	42	24	.	.	PUNCT
gc-467	43	1	there	there	PRON
gc-467	43	2	are	be	VERB
gc-467	43	3	no	no	DET
gc-467	43	4	real	real	ADJ
gc-467	43	5	output	output	NOUN
gc-467	43	6	layers	layer	NOUN
gc-467	43	7	,	,	PUNCT
gc-467	43	8	but	but	CCONJ
gc-467	43	9	neurons	neuron	NOUN
gc-467	43	10	are	be	AUX
gc-467	43	11	arranged	arrange	VERB
gc-467	43	12	into	into	ADP
gc-467	43	13	a	a	DET
gc-467	43	14	grid	grid	NOUN
gc-467	43	15	of	of	ADP
gc-467	43	16	dots	dot	NOUN
gc-467	43	17	.	.	PUNCT
gc-467	44	1	in	in	ADP
gc-467	44	2	other	other	ADJ
gc-467	44	3	words	word	NOUN
gc-467	44	4	,	,	PUNCT
gc-467	44	5	the	the	DET
gc-467	44	6	grid	grid	NOUN
gc-467	44	7	is	be	AUX
gc-467	44	8	the	the	DET
gc-467	44	9	output	output	NOUN
gc-467	44	10	”	"	PUNCT
gc-467	44	11	layer	layer	NOUN
gc-467	44	12	.	.	PUNCT
gc-467	45	1	this	this	PRON
gc-467	45	2	is	be	AUX
gc-467	45	3	the	the	DET
gc-467	45	4	so	so	ADV
gc-467	45	5	-	-	PUNCT
gc-467	45	6	called	call	VERB
gc-467	45	7	kohonen	kohonen	PROPN
gc-467	45	8	’s	’s	PART
gc-467	45	9	layer	layer	NOUN
gc-467	45	10	.	.	PUNCT
gc-467	46	1	it	it	PRON
gc-467	46	2	contains	contain	VERB
gc-467	46	3	m	m	NOUN
gc-467	46	4	neurons	neuron	NOUN
gc-467	46	5	;	;	PUNCT
gc-467	46	6	each	each	DET
gc-467	46	7	neuron	neuron	NOUN
gc-467	46	8	includes	include	VERB
gc-467	46	9	one	one	NUM
gc-467	46	10	output	output	NOUN
gc-467	46	11	cluster	cluster	NOUN
gc-467	46	12	.	.	PUNCT
gc-467	47	1	figure	figure	NOUN
gc-467	47	2	1	1	NUM
gc-467	47	3	shows	show	VERB
gc-467	47	4	that	that	SCONJ
gc-467	47	5	in	in	ADP
gc-467	47	6	this	this	DET
gc-467	47	7	layer	layer	NOUN
gc-467	47	8	neurons	neuron	NOUN
gc-467	47	9	give	give	VERB
gc-467	47	10	a	a	DET
gc-467	47	11	two	two	NUM
gc-467	47	12	dimensional	dimensional	ADJ
gc-467	47	13	map	map	NOUN
gc-467	47	14	(	(	PUNCT
gc-467	47	15	usually	usually	ADV
gc-467	47	16	we	we	PRON
gc-467	47	17	can	can	AUX
gc-467	47	18	use	use	VERB
gc-467	47	19	one	one	NUM
gc-467	47	20	or	or	CCONJ
gc-467	47	21	two	two	NUM
gc-467	47	22	dimensional	dimensional	ADJ
gc-467	47	23	kohonen	kohonen	NOUN
gc-467	47	24	’	'	PUNCT
gc-467	47	25	layer	layer	NOUN
gc-467	47	26	)	)	PUNCT
gc-467	47	27	,	,	PUNCT
gc-467	47	28	however	however	ADV
gc-467	47	29	the	the	DET
gc-467	47	30	neurons	neuron	NOUN
gc-467	47	31	saved	save	VERB
gc-467	47	32	and	and	CCONJ
gc-467	47	33	represent	represent	VERB
gc-467	47	34	the	the	DET
gc-467	47	35	original	original	ADJ
gc-467	47	36	data	data	NOUN
gc-467	47	37	dimension	dimension	NOUN
gc-467	47	38	because	because	SCONJ
gc-467	47	39	each	each	DET
gc-467	47	40	neuron	neuron	NOUN
gc-467	47	41	is	be	AUX
gc-467	47	42	represented	represent	VERB
gc-467	47	43	as	as	ADP
gc-467	47	44	an	an	DET
gc-467	47	45	n	n	CCONJ
gc-467	47	46	dimensional	dimensional	ADJ
gc-467	47	47	vector	vector	NOUN
gc-467	47	48	,	,	PUNCT
gc-467	47	49	where	where	SCONJ
gc-467	47	50	n	n	X
gc-467	47	51	is	be	AUX
gc-467	47	52	the	the	DET
gc-467	47	53	dimension	dimension	NOUN
gc-467	47	54	of	of	ADP
gc-467	47	55	the	the	DET
gc-467	47	56	input	input	NOUN
gc-467	47	57	,	,	PUNCT
gc-467	47	58	training	training	NOUN
gc-467	47	59	,	,	PUNCT
gc-467	47	60	vectors	vector	NOUN
gc-467	47	61	.	.	PUNCT
gc-467	48	1	weighted	weight	VERB
gc-467	48	2	xi	xi	PROPN
gc-467	48	3	inputs	input	NOUN
gc-467	48	4	are	be	AUX
gc-467	48	5	processed	process	VERB
gc-467	48	6	by	by	ADP
gc-467	48	7	all	all	DET
gc-467	48	8	three	three	NUM
gc-467	48	9	neurons	neuron	NOUN
gc-467	48	10	(	(	PUNCT
gc-467	48	11	fig	fig	NOUN
gc-467	48	12	.	.	PUNCT
gc-467	49	1	2	2	NUM
gc-467	49	2	)	)	PUNCT
gc-467	49	3	.	.	PUNCT
gc-467	50	1	each	each	DET
gc-467	50	2	neuron	neuron	NOUN
gc-467	50	3	computes	compute	VERB
gc-467	50	4	its	its	PRON
gc-467	50	5	weighted	weighted	ADJ
gc-467	50	6	input	input	NOUN
gc-467	50	7	,	,	PUNCT
gc-467	50	8	but	but	CCONJ
gc-467	50	9	only	only	ADV
gc-467	50	10	the	the	DET
gc-467	50	11	neuron	neuron	NOUN
gc-467	50	12	with	with	ADP
gc-467	50	13	the	the	DET
gc-467	50	14	largest	large	ADJ
gc-467	50	15	excitation	excitation	NOUN
gc-467	50	16	is	be	AUX
gc-467	50	17	the	the	DET
gc-467	50	18	winner	winner	NOUN
gc-467	50	19	.	.	PUNCT
gc-467	51	1	these	these	DET
gc-467	51	2	units	unit	NOUN
gc-467	51	3	are	be	AUX
gc-467	51	4	adjusted	adjust	VERB
gc-467	51	5	to	to	PART
gc-467	51	6	cluster	cluster	VERB
gc-467	51	7	the	the	DET
gc-467	51	8	training	training	NOUN
gc-467	51	9	data	datum	NOUN
gc-467	51	10	using	use	VERB
gc-467	51	11	the	the	DET
gc-467	51	12	activation	activation	NOUN
gc-467	51	13	values	value	NOUN
gc-467	51	14	of	of	ADP
gc-467	51	15	winning	win	VERB
gc-467	51	16	neurons	neuron	NOUN
gc-467	51	17	.	.	PUNCT
gc-467	52	1	in	in	ADP
gc-467	52	2	kohonen	kohonen	PROPN
gc-467	52	3	’s	’s	PART
gc-467	52	4	layer	layer	NOUN
gc-467	52	5	the	the	DET
gc-467	52	6	other	other	ADJ
gc-467	52	7	units	unit	NOUN
gc-467	52	8	are	be	AUX
gc-467	52	9	reserved	reserve	VERB
gc-467	52	10	by	by	ADP
gc-467	52	11	this	this	DET
gc-467	52	12	active	active	ADJ
gc-467	52	13	element	element	NOUN
gc-467	52	14	through	through	ADP
gc-467	52	15	the	the	DET
gc-467	52	16	lateral	lateral	ADJ
gc-467	52	17	connections	connection	NOUN
gc-467	52	18	during	during	ADP
gc-467	52	19	training	training	NOUN
gc-467	52	20	shown	show	VERB
gc-467	52	21	in	in	ADP
gc-467	52	22	fig	fig	NOUN
gc-467	52	23	.	.	PUNCT
gc-467	53	1	2	2	X
gc-467	53	2	.	.	X
gc-467	53	3	an	an	DET
gc-467	53	4	advantage	advantage	NOUN
gc-467	53	5	of	of	ADP
gc-467	53	6	the	the	DET
gc-467	53	7	som	som	NOUN
gc-467	53	8	network	network	NOUN
gc-467	53	9	is	be	AUX
gc-467	53	10	that	that	SCONJ
gc-467	53	11	it	it	PRON
gc-467	53	12	attempts	attempt	VERB
gc-467	53	13	to	to	PART
gc-467	53	14	learn	learn	VERB
gc-467	53	15	the	the	DET
gc-467	53	16	structure	structure	NOUN
gc-467	53	17	of	of	ADP
gc-467	53	18	the	the	DET
gc-467	53	19	original	original	ADJ
gc-467	53	20	data	datum	NOUN
gc-467	53	21	.	.	PUNCT
gc-467	54	1	it	it	PRON
gc-467	54	2	means	mean	VERB
gc-467	54	3	that	that	SCONJ
gc-467	54	4	the	the	DET
gc-467	54	5	training	training	NOUN
gc-467	54	6	data	datum	NOUN
gc-467	54	7	set	set	VERB
gc-467	54	8	gives	give	VERB
gc-467	54	9	the	the	DET
gc-467	54	10	contact	contact	NOUN
gc-467	54	11	between	between	ADP
gc-467	54	12	the	the	DET
gc-467	54	13	original	original	ADJ
gc-467	54	14	data	datum	NOUN
gc-467	54	15	points	point	NOUN
gc-467	54	16	and	and	CCONJ
gc-467	54	17	identifi	identifi	PROPN
gc-467	54	18	ed	ed	PROPN
gc-467	54	19	classes	class	NOUN
gc-467	54	20	.	.	PUNCT
gc-467	55	1	if	if	SCONJ
gc-467	55	2	new	new	ADJ
gc-467	55	3	data	datum	NOUN
gc-467	55	4	,	,	PUNCT
gc-467	55	5	unlike	unlike	ADP
gc-467	55	6	previous	previous	ADJ
gc-467	55	7	cases	case	NOUN
gc-467	55	8	,	,	PUNCT
gc-467	55	9	is	be	AUX
gc-467	55	10	encountered	encounter	VERB
gc-467	55	11	,	,	PUNCT
gc-467	55	12	the	the	DET
gc-467	55	13	network	network	NOUN
gc-467	55	14	fails	fail	VERB
gc-467	55	15	to	to	PART
gc-467	55	16	recognize	recognize	VERB
gc-467	55	17	it	it	PRON
gc-467	55	18	which	which	PRON
gc-467	55	19	indicates	indicate	VERB
gc-467	55	20	novelty	novelty	NOUN
gc-467	55	21	.	.	PUNCT
gc-467	56	1	therefore	therefore	ADV
gc-467	56	2	,	,	PUNCT
gc-467	56	3	in	in	ADP
gc-467	56	4	the	the	DET
gc-467	56	5	next	next	ADJ
gc-467	56	6	learning	learning	NOUN
gc-467	56	7	step	step	NOUN
gc-467	56	8	,	,	PUNCT
gc-467	56	9	the	the	DET
gc-467	56	10	grid	grid	NOUN
gc-467	56	11	is	be	AUX
gc-467	56	12	updated	update	VERB
gc-467	56	13	based	base	VERB
gc-467	56	14	on	on	ADP
gc-467	56	15	the	the	DET
gc-467	56	16	novelty	novelty	NOUN
gc-467	56	17	.	.	PUNCT
gc-467	57	1	the	the	DET
gc-467	57	2	updating	update	VERB
gc-467	57	3	process	process	NOUN
gc-467	57	4	is	be	AUX
gc-467	57	5	quite	quite	ADV
gc-467	57	6	similar	similar	ADJ
gc-467	57	7	to	to	ADP
gc-467	57	8	that	that	PRON
gc-467	57	9	of	of	ADP
gc-467	57	10	the	the	DET
gc-467	57	11	k	k	NOUN
gc-467	57	12	-	-	PUNCT
gc-467	57	13	means	means	NOUN
gc-467	57	14	algorithm	algorithm	NOUN
gc-467	57	15	,	,	PUNCT
gc-467	57	16	where	where	SCONJ
gc-467	57	17	the	the	DET
gc-467	57	18	arrangements	arrangement	NOUN
gc-467	57	19	of	of	ADP
gc-467	57	20	cluster	cluster	NOUN
gc-467	57	21	-	-	PUNCT
gc-467	57	22	centroids	centroid	NOUN
gc-467	57	23	change	change	NOUN
gc-467	57	24	in	in	ADP
gc-467	57	25	the	the	DET
gc-467	57	26	regular	regular	ADJ
gc-467	57	27	low	low	ADJ
gc-467	57	28	-	-	PUNCT
gc-467	57	29	dimensional	dimensional	ADJ
gc-467	57	30	grid	grid	NOUN
gc-467	57	31	.	.	PUNCT
gc-467	58	1	however	however	ADV
gc-467	58	2	,	,	PUNCT
gc-467	58	3	in	in	ADP
gc-467	58	4	case	case	NOUN
gc-467	58	5	of	of	ADP
gc-467	58	6	som	som	NOUN
gc-467	58	7	,	,	PUNCT
gc-467	58	8	changing	change	VERB
gc-467	58	9	the	the	DET
gc-467	58	10	position	position	NOUN
gc-467	58	11	of	of	ADP
gc-467	58	12	neurons	neuron	NOUN
gc-467	58	13	in	in	ADP
gc-467	58	14	the	the	DET
gc-467	58	15	data	data	NOUN
gc-467	58	16	space	space	PROPN
gc-467	58	17	infl	infl	PROPN
gc-467	58	18	uences	uence	VERB
gc-467	58	19	the	the	DET
gc-467	58	20	positions	position	NOUN
gc-467	58	21	of	of	ADP
gc-467	58	22	its	its	PRON
gc-467	58	23	neighbors	neighbor	NOUN
gc-467	58	24	through	through	ADP
gc-467	58	25	the	the	DET
gc-467	58	26	lateral	lateral	ADJ
gc-467	58	27	connections	connection	NOUN
gc-467	58	28	within	within	ADP
gc-467	58	29	a	a	DET
gc-467	58	30	predetermined	predetermine	VERB
gc-467	58	31	distance	distance	NOUN
gc-467	58	32	.	.	PUNCT
gc-467	59	1	since	since	SCONJ
gc-467	59	2	som	som	NOUN
gc-467	59	3	consists	consist	VERB
gc-467	59	4	of	of	ADP
gc-467	59	5	neurons	neuron	NOUN
gc-467	59	6	organized	organize	VERB
gc-467	59	7	on	on	ADP
gc-467	59	8	a	a	DET
gc-467	59	9	regular	regular	ADJ
gc-467	59	10	low	low	ADJ
gc-467	59	11	-	-	PUNCT
gc-467	59	12	dimensional	dimensional	ADJ
gc-467	59	13	grid	grid	NOUN
gc-467	59	14	,	,	PUNCT
gc-467	59	15	these	these	DET
gc-467	59	16	neurons	neuron	NOUN
gc-467	59	17	control	control	VERB
gc-467	59	18	the	the	DET
gc-467	59	19	classifi	classifi	PROPN
gc-467	59	20	cation	cation	NOUN
gc-467	59	21	of	of	ADP
gc-467	59	22	data	datum	NOUN
gc-467	59	23	using	use	VERB
gc-467	59	24	a	a	DET
gc-467	59	25	suitable	suitable	ADJ
gc-467	59	26	distance	distance	NOUN
gc-467	59	27	.	.	PUNCT
gc-467	60	1	the	the	DET
gc-467	60	2	input	input	NOUN
gc-467	60	3	vectors	vector	NOUN
gc-467	60	4	are	be	AUX
gc-467	60	5	compared	compare	VERB
gc-467	60	6	step	step	NOUN
gc-467	60	7	by	by	ADP
gc-467	60	8	step	step	NOUN
gc-467	60	9	with	with	ADP
gc-467	60	10	the	the	DET
gc-467	60	11	reference	reference	NOUN
gc-467	60	12	vectors	vector	NOUN
gc-467	60	13	using	use	VERB
gc-467	60	14	a	a	DET
gc-467	60	15	neighboring	neighboring	NOUN
gc-467	60	16	function	function	NOUN
gc-467	60	17	and	and	CCONJ
gc-467	60	18	the	the	DET
gc-467	60	19	grid	grid	NOUN
gc-467	60	20	is	be	AUX
gc-467	60	21	revised	revise	VERB
gc-467	60	22	continuously	continuously	ADV
gc-467	60	23	using	use	VERB
gc-467	60	24	a	a	DET
gc-467	60	25	winning	win	VERB
gc-467	60	26	neuron	neuron	NOUN
gc-467	60	27	algorithm	algorithm	NOUN
gc-467	60	28	.	.	PUNCT
gc-467	61	1	during	during	ADP
gc-467	61	2	the	the	DET
gc-467	61	3	comparison	comparison	NOUN
gc-467	61	4	figure	figure	NOUN
gc-467	61	5	1	1	NUM
gc-467	61	6	:	:	PUNCT
gc-467	61	7	kohonen	kohonen	PROPN
gc-467	61	8	’s	’s	PART
gc-467	61	9	layer	layer	NOUN
gc-467	61	10	with	with	ADP
gc-467	61	11	n	n	CCONJ
gc-467	61	12	-	-	PUNCT
gc-467	61	13	dimensional	dimensional	ADJ
gc-467	61	14	neurons	neuron	NOUN
gc-467	61	15	.	.	PUNCT
gc-467	62	1	figure	figure	NOUN
gc-467	62	2	2	2	NUM
gc-467	62	3	:	:	PUNCT
gc-467	62	4	network	network	NOUN
gc-467	62	5	of	of	ADP
gc-467	62	6	three	three	NUM
gc-467	62	7	competing	compete	VERB
gc-467	62	8	units	unit	NOUN
gc-467	62	9	.	.	PUNCT
gc-467	63	1	janina	janina	PROPN
gc-467	63	2	horváth	horváth	PROPN
gc-467	63	3	:	:	PUNCT
gc-467	63	4	defi	defi	PROPN
gc-467	63	5	ning	ning	ADJ
gc-467	63	6	depositional	depositional	ADJ
gc-467	63	7	environments	environment	NOUN
gc-467	63	8	by	by	ADP
gc-467	63	9	using	use	VERB
gc-467	63	10	neural	neural	ADJ
gc-467	63	11	networks	network	NOUN
gc-467	63	12	geologia	geologia	VERB
gc-467	63	13	croatica	croatica	PROPN
gc-467	63	14	253	253	NUM
gc-467	63	15	process	process	NOUN
gc-467	63	16	,	,	PUNCT
gc-467	63	17	each	each	DET
gc-467	63	18	sample	sample	NOUN
gc-467	63	19	input	input	NOUN
gc-467	63	20	vector	vector	NOUN
gc-467	63	21	is	be	AUX
gc-467	63	22	randomly	randomly	ADV
gc-467	63	23	drawn	draw	VERB
gc-467	63	24	from	from	ADP
gc-467	63	25	the	the	DET
gc-467	63	26	input	input	NOUN
gc-467	63	27	data	datum	NOUN
gc-467	63	28	set	set	VERB
gc-467	63	29	,	,	PUNCT
gc-467	63	30	and	and	CCONJ
gc-467	63	31	their	their	PRON
gc-467	63	32	similarities	similarity	NOUN
gc-467	63	33	to	to	ADP
gc-467	63	34	the	the	DET
gc-467	63	35	‘	'	PUNCT
gc-467	63	36	codebook	codebook	NOUN
gc-467	63	37	’	'	PUNCT
gc-467	63	38	vectors	vector	NOUN
gc-467	63	39	are	be	AUX
gc-467	63	40	computed	compute	VERB
gc-467	63	41	.	.	PUNCT
gc-467	64	1	this	this	DET
gc-467	64	2	process	process	NOUN
gc-467	64	3	is	be	AUX
gc-467	64	4	based	base	VERB
gc-467	64	5	on	on	ADP
gc-467	64	6	euclidean	euclidean	ADJ
gc-467	64	7	distance	distance	NOUN
gc-467	64	8	that	that	PRON
gc-467	64	9	measures	measure	VERB
gc-467	64	10	distance	distance	NOUN
gc-467	64	11	from	from	ADP
gc-467	64	12	the	the	DET
gc-467	64	13	data	data	NOUN
gc-467	64	14	sample	sample	NOUN
gc-467	64	15	to	to	ADP
gc-467	64	16	each	each	DET
gc-467	64	17	neuron	neuron	NOUN
gc-467	64	18	to	to	PART
gc-467	64	19	obtain	obtain	VERB
gc-467	64	20	the	the	DET
gc-467	64	21	winning	win	VERB
gc-467	64	22	neuron	neuron	NOUN
gc-467	64	23	(	(	PUNCT
gc-467	64	24	lampinen	lampinen	NOUN
gc-467	64	25	et	et	PROPN
gc-467	64	26	al	al	PROPN
gc-467	64	27	.	.	PROPN
gc-467	64	28	,	,	PUNCT
gc-467	64	29	2005).owever	2005).owever	NUM
gc-467	64	30	better	well	ADJ
gc-467	64	31	selections	selection	NOUN
gc-467	64	32	use	use	VERB
gc-467	64	33	either	either	CCONJ
gc-467	64	34	mahalanobis	mahalanobis	ADJ
gc-467	64	35	distance	distance	NOUN
gc-467	64	36	,	,	PUNCT
gc-467	64	37	(	(	PUNCT
gc-467	64	38	developed	develop	VERB
gc-467	64	39	by	by	ADP
gc-467	64	40	mahalanobis	mahalanobis	NOUN
gc-467	64	41	in	in	ADP
gc-467	64	42	1936	1936	NUM
gc-467	64	43	)	)	PUNCT
gc-467	64	44	,	,	PUNCT
gc-467	64	45	or	or	CCONJ
gc-467	64	46	cosine	cosine	NOUN
gc-467	64	47	distance	distance	NOUN
gc-467	64	48	as	as	ADP
gc-467	64	49	alternative	alternative	ADJ
gc-467	64	50	measures	measure	NOUN
gc-467	64	51	.	.	PUNCT
gc-467	65	1	the	the	DET
gc-467	65	2	latter	latter	ADJ
gc-467	65	3	is	be	AUX
gc-467	65	4	derived	derive	VERB
gc-467	65	5	from	from	ADP
gc-467	65	6	correlations	correlation	NOUN
gc-467	65	7	between	between	ADP
gc-467	65	8	variables	variable	NOUN
gc-467	65	9	in	in	ADP
gc-467	65	10	the	the	DET
gc-467	65	11	property	property	NOUN
gc-467	65	12	space	space	NOUN
gc-467	65	13	.	.	PUNCT
gc-467	66	1	kohonen	kohonen	PROPN
gc-467	66	2	’s	’s	PROPN
gc-467	66	3	network	network	NOUN
gc-467	66	4	learns	learn	VERB
gc-467	66	5	iteratively	iteratively	ADV
gc-467	66	6	and	and	CCONJ
gc-467	66	7	uses	use	VERB
gc-467	66	8	the	the	DET
gc-467	66	9	modifi	modifi	PROPN
gc-467	66	10	ed	ed	PROPN
gc-467	66	11	hebb	hebb	PROPN
gc-467	66	12	-	-	PUNCT
gc-467	66	13	rule	rule	NOUN
gc-467	66	14	as	as	ADP
gc-467	66	15	the	the	DET
gc-467	66	16	winning	win	VERB
gc-467	66	17	neuron	neuron	NOUN
gc-467	66	18	algorithm	algorithm	NOUN
gc-467	66	19	(	(	PUNCT
gc-467	66	20	lampinen	lampinen	NOUN
gc-467	66	21	et	et	PROPN
gc-467	66	22	al	al	PROPN
gc-467	66	23	,	,	PUNCT
gc-467	66	24	2005	2005	NUM
gc-467	66	25	)	)	PUNCT
gc-467	66	26	.	.	PUNCT
gc-467	67	1	the	the	DET
gc-467	67	2	modifi	modifi	PROPN
gc-467	67	3	ed	ed	PROPN
gc-467	67	4	law	law	NOUN
gc-467	67	5	is	be	AUX
gc-467	67	6	w(t+1)=w(t)+ρ(t)´(x	w(t+1)=w(t)+ρ(t)´(x	PROPN
gc-467	67	7	–	–	PUNCT
gc-467	67	8	w(t)).where	w(t)).where	X
gc-467	67	9	x	x	VERB
gc-467	67	10	is	be	AUX
gc-467	67	11	the	the	DET
gc-467	67	12	training	training	NOUN
gc-467	67	13	case	case	NOUN
gc-467	67	14	,	,	PUNCT
gc-467	67	15	w(t	w(t	PROPN
gc-467	67	16	)	)	PUNCT
gc-467	67	17	is	be	AUX
gc-467	67	18	weight	weight	NOUN
gc-467	67	19	,	,	PUNCT
gc-467	67	20	and	and	CCONJ
gc-467	67	21	ρ(t	ρ(t	NUM
gc-467	67	22	)	)	PUNCT
gc-467	67	23	is	be	AUX
gc-467	67	24	the	the	DET
gc-467	67	25	learning	learning	NOUN
gc-467	67	26	rate	rate	NOUN
gc-467	67	27	.	.	PUNCT
gc-467	68	1	the	the	DET
gc-467	68	2	application	application	NOUN
gc-467	68	3	of	of	ADP
gc-467	68	4	neural	neural	ADJ
gc-467	68	5	networks	network	NOUN
gc-467	68	6	is	be	AUX
gc-467	68	7	relatively	relatively	ADV
gc-467	68	8	simple	simple	ADJ
gc-467	68	9	.	.	PUNCT
gc-467	69	1	an	an	DET
gc-467	69	2	artifi	artifi	PROPN
gc-467	69	3	cial	cial	ADJ
gc-467	69	4	network	network	NOUN
gc-467	69	5	studies	study	NOUN
gc-467	69	6	the	the	DET
gc-467	69	7	data	data	NOUN
gc-467	69	8	structure	structure	NOUN
gc-467	69	9	,	,	PUNCT
gc-467	69	10	which	which	PRON
gc-467	69	11	means	mean	VERB
gc-467	69	12	that	that	SCONJ
gc-467	69	13	it	it	PRON
gc-467	69	14	necessarily	necessarily	ADV
gc-467	69	15	must	must	AUX
gc-467	69	16	have	have	VERB
gc-467	69	17	some	some	DET
gc-467	69	18	preliminary	preliminary	ADJ
gc-467	69	19	empirical	empirical	ADJ
gc-467	69	20	knowledge	knowledge	NOUN
gc-467	69	21	e.g.	e.g.	ADV
gc-467	69	22	on	on	ADP
gc-467	69	23	appropriate	appropriate	ADJ
gc-467	69	24	size	size	NOUN
gc-467	69	25	of	of	ADP
gc-467	69	26	network	network	NOUN
gc-467	69	27	,	,	PUNCT
gc-467	69	28	rate	rate	NOUN
gc-467	69	29	of	of	ADP
gc-467	69	30	learning	learning	NOUN
gc-467	69	31	,	,	PUNCT
gc-467	69	32	number	number	NOUN
gc-467	69	33	of	of	ADP
gc-467	69	34	learning	learn	VERB
gc-467	69	35	steps	step	NOUN
gc-467	69	36	.	.	PUNCT
gc-467	70	1	in	in	ADP
gc-467	70	2	this	this	DET
gc-467	70	3	case	case	NOUN
gc-467	70	4	,	,	PUNCT
gc-467	70	5	the	the	DET
gc-467	70	6	size	size	NOUN
gc-467	70	7	of	of	ADP
gc-467	70	8	the	the	DET
gc-467	70	9	network	network	NOUN
gc-467	70	10	corresponds	correspond	VERB
gc-467	70	11	to	to	ADP
gc-467	70	12	the	the	DET
gc-467	70	13	number	number	NOUN
gc-467	70	14	of	of	ADP
gc-467	70	15	neurons	neuron	NOUN
gc-467	70	16	representing	represent	VERB
gc-467	70	17	the	the	DET
gc-467	70	18	clusters	cluster	NOUN
gc-467	70	19	of	of	ADP
gc-467	70	20	which	which	PRON
gc-467	70	21	numbers	number	NOUN
gc-467	70	22	must	must	AUX
gc-467	70	23	be	be	AUX
gc-467	70	24	given	give	VERB
gc-467	70	25	previously	previously	ADV
gc-467	70	26	.	.	PUNCT
gc-467	71	1	this	this	DET
gc-467	71	2	setting	setting	NOUN
gc-467	71	3	depends	depend	VERB
gc-467	71	4	on	on	ADP
gc-467	71	5	preliminary	preliminary	ADJ
gc-467	71	6	expertise	expertise	NOUN
gc-467	71	7	.	.	PUNCT
gc-467	72	1	2.2.1	2.2.1	NUM
gc-467	72	2	.	.	PUNCT
gc-467	72	3	pattern	pattern	NOUN
gc-467	72	4	recognition	recognition	NOUN
gc-467	72	5	as	as	ADP
gc-467	72	6	a	a	DET
gc-467	72	7	clustering	clustering	NOUN
gc-467	72	8	method	method	NOUN
gc-467	72	9	som	som	NOUN
gc-467	72	10	is	be	AUX
gc-467	72	11	a	a	DET
gc-467	72	12	type	type	NOUN
gc-467	72	13	of	of	ADP
gc-467	72	14	clustering	clustering	ADJ
gc-467	72	15	method	method	NOUN
gc-467	72	16	.	.	PUNCT
gc-467	73	1	it	it	PRON
gc-467	73	2	differs	differ	VERB
gc-467	73	3	from	from	ADP
gc-467	73	4	any	any	DET
gc-467	73	5	traditional	traditional	ADJ
gc-467	73	6	clustering	clustering	NOUN
gc-467	73	7	method	method	NOUN
gc-467	73	8	in	in	ADP
gc-467	73	9	its	its	PRON
gc-467	73	10	robustness	robustness	NOUN
gc-467	73	11	.	.	PUNCT
gc-467	74	1	however	however	ADV
gc-467	74	2	it	it	PRON
gc-467	74	3	needs	need	VERB
gc-467	74	4	,	,	PUNCT
gc-467	74	5	like	like	ADP
gc-467	74	6	any	any	DET
gc-467	74	7	‘	'	PUNCT
gc-467	74	8	traditional	traditional	ADJ
gc-467	74	9	k	k	ADJ
gc-467	74	10	-	-	ADJ
gc-467	74	11	mean	mean	ADJ
gc-467	74	12	algorithm	algorithm	NOUN
gc-467	74	13	’	'	PUNCT
gc-467	74	14	,	,	PUNCT
gc-467	74	15	to	to	PART
gc-467	74	16	input	input	VERB
gc-467	74	17	the	the	DET
gc-467	74	18	number	number	NOUN
gc-467	74	19	of	of	ADP
gc-467	74	20	groups	group	NOUN
gc-467	74	21	to	to	PART
gc-467	74	22	be	be	AUX
gc-467	74	23	revealed	reveal	VERB
gc-467	74	24	.	.	PUNCT
gc-467	75	1	som	som	NOUN
gc-467	75	2	,	,	PUNCT
gc-467	75	3	(	(	PUNCT
gc-467	75	4	as	as	ADP
gc-467	75	5	any	any	DET
gc-467	75	6	clustering	clustering	ADJ
gc-467	75	7	method	method	NOUN
gc-467	75	8	)	)	PUNCT
gc-467	75	9	,	,	PUNCT
gc-467	75	10	provides	provide	VERB
gc-467	75	11	an	an	DET
gc-467	75	12	opportunity	opportunity	NOUN
gc-467	75	13	for	for	ADP
gc-467	75	14	deriving	derive	VERB
gc-467	75	15	solutions	solution	NOUN
gc-467	75	16	for	for	ADP
gc-467	75	17	geological	geological	ADJ
gc-467	75	18	problems	problem	NOUN
gc-467	75	19	which	which	PRON
gc-467	75	20	can	can	AUX
gc-467	75	21	be	be	AUX
gc-467	75	22	related	relate	VERB
gc-467	75	23	to	to	ADP
gc-467	75	24	different	different	ADJ
gc-467	75	25	clustering	clustering	NOUN
gc-467	75	26	problems	problem	NOUN
gc-467	75	27	,	,	PUNCT
gc-467	75	28	such	such	ADJ
gc-467	75	29	as	as	ADP
gc-467	75	30	pattern	pattern	NOUN
gc-467	75	31	recognition	recognition	NOUN
gc-467	75	32	(	(	PUNCT
gc-467	75	33	ultsch	ultsch	INTJ
gc-467	75	34	,	,	PUNCT
gc-467	75	35	1995	1995	NUM
gc-467	75	36	)	)	PUNCT
gc-467	75	37	.	.	PUNCT
gc-467	76	1	for	for	ADP
gc-467	76	2	implementation	implementation	NOUN
gc-467	76	3	,	,	PUNCT
gc-467	76	4	kohonen	kohonen	PROPN
gc-467	76	5	’s	’s	PART
gc-467	76	6	network	network	NOUN
gc-467	76	7	has	have	AUX
gc-467	76	8	been	be	AUX
gc-467	76	9	used	use	VERB
gc-467	76	10	as	as	SCONJ
gc-467	76	11	it	it	PRON
gc-467	76	12	is	be	AUX
gc-467	76	13	possible	possible	ADJ
gc-467	76	14	to	to	PART
gc-467	76	15	recognize	recognize	VERB
gc-467	76	16	spatial	spatial	ADJ
gc-467	76	17	patterns	pattern	NOUN
gc-467	76	18	being	be	AUX
gc-467	76	19	defi	defi	NOUN
gc-467	76	20	ned	ned	NOUN
gc-467	76	21	as	as	ADP
gc-467	76	22	spatial	spatial	ADJ
gc-467	76	23	groups	group	NOUN
gc-467	76	24	of	of	ADP
gc-467	76	25	points	point	NOUN
gc-467	76	26	bounded	bound	VERB
gc-467	76	27	by	by	ADP
gc-467	76	28	a	a	DET
gc-467	76	29	polygon	polygon	NOUN
gc-467	76	30	.	.	PUNCT
gc-467	77	1	it	it	PRON
gc-467	77	2	has	have	VERB
gc-467	77	3	potential	potential	NOUN
gc-467	77	4	for	for	ADP
gc-467	77	5	applying	apply	VERB
gc-467	77	6	pattern	pattern	NOUN
gc-467	77	7	recognition	recognition	NOUN
gc-467	77	8	to	to	ADP
gc-467	77	9	problems	problem	NOUN
gc-467	77	10	such	such	ADJ
gc-467	77	11	as	as	ADP
gc-467	77	12	identifying	identify	VERB
gc-467	77	13	the	the	DET
gc-467	77	14	spatial	spatial	ADJ
gc-467	77	15	pattern	pattern	NOUN
gc-467	77	16	of	of	ADP
gc-467	77	17	a	a	DET
gc-467	77	18	sub	sub	NOUN
gc-467	77	19	-	-	NOUN
gc-467	77	20	environment	environment	NOUN
gc-467	77	21	on	on	ADP
gc-467	77	22	a	a	DET
gc-467	77	23	delta	delta	NOUN
gc-467	77	24	plain	plain	NOUN
gc-467	77	25	,	,	PUNCT
gc-467	77	26	which	which	PRON
gc-467	77	27	is	be	AUX
gc-467	77	28	resoluble	resoluble	ADJ
gc-467	77	29	by	by	ADP
gc-467	77	30	applying	apply	VERB
gc-467	77	31	the	the	DET
gc-467	77	32	som	som	NOUN
gc-467	77	33	method	method	NOUN
gc-467	77	34	based	base	VERB
gc-467	77	35	on	on	ADP
gc-467	77	36	a	a	DET
gc-467	77	37	clustering	clustering	ADJ
gc-467	77	38	algorithm	algorithm	NOUN
gc-467	77	39	.	.	PUNCT
gc-467	78	1	shapes	shape	NOUN
gc-467	78	2	shall	shall	AUX
gc-467	78	3	be	be	AUX
gc-467	78	4	construed	construe	VERB
gc-467	78	5	as	as	ADP
gc-467	78	6	clusters	cluster	NOUN
gc-467	78	7	of	of	ADP
gc-467	78	8	data	datum	NOUN
gc-467	78	9	points	point	NOUN
gc-467	78	10	that	that	PRON
gc-467	78	11	are	be	AUX
gc-467	78	12	bounded	bound	VERB
gc-467	78	13	by	by	ADP
gc-467	78	14	a	a	DET
gc-467	78	15	polygon	polygon	NOUN
gc-467	78	16	which	which	PRON
gc-467	78	17	implies	imply	VERB
gc-467	78	18	that	that	SCONJ
gc-467	78	19	pattern	pattern	NOUN
gc-467	78	20	recognition	recognition	NOUN
gc-467	78	21	is	be	AUX
gc-467	78	22	a	a	DET
gc-467	78	23	clustering	clustering	ADJ
gc-467	78	24	problem	problem	NOUN
gc-467	78	25	.	.	PUNCT
gc-467	79	1	however	however	ADV
gc-467	79	2	,	,	PUNCT
gc-467	79	3	this	this	DET
gc-467	79	4	approach	approach	NOUN
gc-467	79	5	raises	raise	VERB
gc-467	79	6	the	the	DET
gc-467	79	7	question	question	NOUN
gc-467	79	8	of	of	ADP
gc-467	79	9	the	the	DET
gc-467	79	10	defi	defi	NOUN
gc-467	79	11	nition	nition	NOUN
gc-467	79	12	of	of	ADP
gc-467	79	13	patterns	pattern	NOUN
gc-467	79	14	as	as	ADP
gc-467	79	15	statistical	statistical	ADJ
gc-467	79	16	groups	group	NOUN
gc-467	79	17	.	.	PUNCT
gc-467	80	1	within	within	ADP
gc-467	80	2	a	a	DET
gc-467	80	3	pattern	pattern	NOUN
gc-467	80	4	,	,	PUNCT
gc-467	80	5	there	there	PRON
gc-467	80	6	are	be	VERB
gc-467	80	7	points	point	NOUN
gc-467	80	8	with	with	ADP
gc-467	80	9	the	the	DET
gc-467	80	10	same	same	ADJ
gc-467	80	11	or	or	CCONJ
gc-467	80	12	similar	similar	ADJ
gc-467	80	13	properties	property	NOUN
gc-467	80	14	.	.	PUNCT
gc-467	81	1	in	in	ADP
gc-467	81	2	practice	practice	NOUN
gc-467	81	3	,	,	PUNCT
gc-467	81	4	this	this	PRON
gc-467	81	5	means	mean	VERB
gc-467	81	6	that	that	SCONJ
gc-467	81	7	all	all	DET
gc-467	81	8	points	point	NOUN
gc-467	81	9	in	in	ADP
gc-467	81	10	a	a	DET
gc-467	81	11	sub	sub	ADJ
gc-467	81	12	-	-	ADJ
gc-467	81	13	set	set	ADJ
gc-467	81	14	represent	represent	VERB
gc-467	81	15	a	a	DET
gc-467	81	16	certain	certain	ADJ
gc-467	81	17	cluster	cluster	NOUN
gc-467	81	18	which	which	PRON
gc-467	81	19	is	be	AUX
gc-467	81	20	bounded	bound	VERB
gc-467	81	21	by	by	ADP
gc-467	81	22	polygons	polygon	NOUN
gc-467	81	23	.	.	PUNCT
gc-467	82	1	a	a	DET
gc-467	82	2	polygon	polygon	NOUN
gc-467	82	3	represents	represent	VERB
gc-467	82	4	the	the	DET
gc-467	82	5	shape	shape	NOUN
gc-467	82	6	and	and	CCONJ
gc-467	82	7	refl	refl	NOUN
gc-467	82	8	ects	ect	VERB
gc-467	82	9	the	the	DET
gc-467	82	10	borders	border	NOUN
gc-467	82	11	of	of	ADP
gc-467	82	12	subenvironments	subenvironment	NOUN
gc-467	82	13	,	,	PUNCT
gc-467	82	14	where	where	SCONJ
gc-467	82	15	the	the	DET
gc-467	82	16	properties	property	NOUN
gc-467	82	17	change	change	VERB
gc-467	82	18	between	between	ADP
gc-467	82	19	separate	separate	ADJ
gc-467	82	20	clusters	cluster	NOUN
gc-467	82	21	.	.	PUNCT
gc-467	83	1	figure	figure	NOUN
gc-467	83	2	3	3	NUM
gc-467	83	3	demonstrates	demonstrate	VERB
gc-467	83	4	an	an	DET
gc-467	83	5	example	example	NOUN
gc-467	83	6	for	for	ADP
gc-467	83	7	mapping	mapping	NOUN
gc-467	83	8	clusters	cluster	NOUN
gc-467	83	9	using	use	VERB
gc-467	83	10	the	the	DET
gc-467	83	11	original	original	ADJ
gc-467	83	12	coordinates	coordinate	NOUN
gc-467	83	13	.	.	PUNCT
gc-467	84	1	som	som	NOUN
gc-467	84	2	creates	create	VERB
gc-467	84	3	cm	cm	NOUN
gc-467	84	4	clusters	cluster	NOUN
gc-467	84	5	(	(	PUNCT
gc-467	84	6	m	m	NOUN
gc-467	84	7	is	be	AUX
gc-467	84	8	the	the	DET
gc-467	84	9	number	number	NOUN
gc-467	84	10	of	of	ADP
gc-467	84	11	clusters	cluster	NOUN
gc-467	84	12	)	)	PUNCT
gc-467	84	13	based	base	VERB
gc-467	84	14	on	on	ADP
gc-467	84	15	the	the	DET
gc-467	84	16	property	property	NOUN
gc-467	84	17	values	value	NOUN
gc-467	84	18	of	of	ADP
gc-467	84	19	data	datum	NOUN
gc-467	84	20	points	point	NOUN
gc-467	84	21	without	without	ADP
gc-467	84	22	original	original	ADJ
gc-467	84	23	spatial	spatial	ADJ
gc-467	84	24	coordinates	coordinate	NOUN
gc-467	84	25	.	.	PUNCT
gc-467	85	1	after	after	ADP
gc-467	85	2	the	the	DET
gc-467	85	3	clustering	clustering	ADJ
gc-467	85	4	process	process	NOUN
gc-467	85	5	we	we	PRON
gc-467	85	6	map	map	VERB
gc-467	85	7	the	the	DET
gc-467	85	8	resulting	result	VERB
gc-467	85	9	clusters	cluster	NOUN
gc-467	85	10	as	as	ADP
gc-467	85	11	patterns	pattern	NOUN
gc-467	85	12	using	use	VERB
gc-467	85	13	the	the	DET
gc-467	85	14	original	original	ADJ
gc-467	85	15	coordinates	coordinate	NOUN
gc-467	85	16	.	.	PUNCT
gc-467	86	1	in	in	ADP
gc-467	86	2	this	this	DET
gc-467	86	3	manner	manner	NOUN
gc-467	86	4	the	the	DET
gc-467	86	5	different	different	ADJ
gc-467	86	6	properties	property	NOUN
gc-467	86	7	clusters	cluster	NOUN
gc-467	86	8	are	be	AUX
gc-467	86	9	mapped	map	VERB
gc-467	86	10	and	and	CCONJ
gc-467	86	11	the	the	DET
gc-467	86	12	pattern	pattern	NOUN
gc-467	86	13	is	be	AUX
gc-467	86	14	visualized	visualize	VERB
gc-467	86	15	on	on	ADP
gc-467	86	16	the	the	DET
gc-467	86	17	map	map	NOUN
gc-467	86	18	.	.	PUNCT
gc-467	87	1	thus	thus	ADV
gc-467	87	2	after	after	ADP
gc-467	87	3	the	the	DET
gc-467	87	4	clustering	cluster	VERB
gc-467	87	5	process	process	NOUN
gc-467	87	6	,	,	PUNCT
gc-467	87	7	the	the	DET
gc-467	87	8	resulting	result	VERB
gc-467	87	9	clusters	cluster	NOUN
gc-467	87	10	are	be	AUX
gc-467	87	11	patterns	pattern	NOUN
gc-467	87	12	in	in	ADP
gc-467	87	13	a	a	DET
gc-467	87	14	map	map	NOUN
gc-467	87	15	using	use	VERB
gc-467	87	16	the	the	DET
gc-467	87	17	original	original	ADJ
gc-467	87	18	coordinates	coordinate	NOUN
gc-467	87	19	.	.	PUNCT
gc-467	88	1	2.2.2	2.2.2	X
gc-467	88	2	.	.	PUNCT
gc-467	88	3	recognisable	recognisable	ADJ
gc-467	88	4	patterns	pattern	NOUN
gc-467	88	5	in	in	ADP
gc-467	88	6	the	the	DET
gc-467	88	7	map	map	NOUN
gc-467	88	8	the	the	DET
gc-467	88	9	mapping	mapping	NOUN
gc-467	88	10	processes	process	NOUN
gc-467	88	11	compose	compose	VERB
gc-467	88	12	the	the	DET
gc-467	88	13	closed	close	VERB
gc-467	88	14	patterns	pattern	NOUN
gc-467	88	15	by	by	ADP
gc-467	88	16	the	the	DET
gc-467	88	17	arrangement	arrangement	NOUN
gc-467	88	18	of	of	ADP
gc-467	88	19	the	the	DET
gc-467	88	20	points	point	NOUN
gc-467	88	21	in	in	ADP
gc-467	88	22	space	space	NOUN
gc-467	88	23	through	through	ADP
gc-467	88	24	the	the	DET
gc-467	88	25	original	original	ADJ
gc-467	88	26	(	(	PUNCT
gc-467	88	27	xi	xi	PROPN
gc-467	88	28	,	,	PUNCT
gc-467	88	29	yi	yi	NOUN
gc-467	88	30	)	)	PUNCT
gc-467	88	31	coordinates	coordinate	NOUN
gc-467	88	32	.	.	PUNCT
gc-467	89	1	in	in	ADP
gc-467	89	2	this	this	DET
gc-467	89	3	case	case	NOUN
gc-467	89	4	it	it	PRON
gc-467	89	5	is	be	AUX
gc-467	89	6	necessary	necessary	ADJ
gc-467	89	7	to	to	PART
gc-467	89	8	give	give	VERB
gc-467	89	9	some	some	DET
gc-467	89	10	conditions	condition	NOUN
gc-467	89	11	and	and	CCONJ
gc-467	89	12	defi	defi	NOUN
gc-467	89	13	nitions	nition	NOUN
gc-467	89	14	for	for	ADP
gc-467	89	15	recognizing	recognize	VERB
gc-467	89	16	patterns	pattern	NOUN
gc-467	89	17	for	for	ADP
gc-467	89	18	mathematical	mathematical	ADJ
gc-467	89	19	reasons	reason	NOUN
gc-467	89	20	.	.	PUNCT
gc-467	90	1	(	(	PUNCT
gc-467	90	2	1	1	X
gc-467	90	3	)	)	PUNCT
gc-467	90	4	a	a	DET
gc-467	90	5	closed	close	VERB
gc-467	90	6	pattern	pattern	NOUN
gc-467	90	7	means	mean	VERB
gc-467	90	8	that	that	SCONJ
gc-467	90	9	there	there	PRON
gc-467	90	10	is	be	VERB
gc-467	90	11	at	at	ADV
gc-467	90	12	least	least	ADJ
gc-467	90	13	one	one	NUM
gc-467	90	14	inner	inner	ADJ
gc-467	90	15	point	point	NOUN
gc-467	90	16	of	of	ADP
gc-467	90	17	the	the	DET
gc-467	90	18	group	group	NOUN
gc-467	90	19	.	.	PUNCT
gc-467	91	1	(	(	PUNCT
gc-467	91	2	2	2	X
gc-467	91	3	)	)	PUNCT
gc-467	91	4	a	a	DET
gc-467	91	5	point	point	NOUN
gc-467	91	6	is	be	AUX
gc-467	91	7	an	an	DET
gc-467	91	8	inner	inner	ADJ
gc-467	91	9	point	point	NOUN
gc-467	91	10	if	if	SCONJ
gc-467	91	11	all	all	PRON
gc-467	91	12	of	of	ADP
gc-467	91	13	its	its	PRON
gc-467	91	14	neighboring	neighboring	NOUN
gc-467	91	15	points	point	NOUN
gc-467	91	16	belong	belong	VERB
gc-467	91	17	to	to	ADP
gc-467	91	18	the	the	DET
gc-467	91	19	same	same	ADJ
gc-467	91	20	cluster	cluster	NOUN
gc-467	91	21	,	,	PUNCT
gc-467	91	22	i.e.	i.e.	X
gc-467	91	23	there	there	PRON
gc-467	91	24	are	be	VERB
gc-467	91	25	at	at	ADV
gc-467	91	26	least	least	ADJ
gc-467	91	27	four	four	NUM
gc-467	91	28	edge	edge	NOUN
gc-467	91	29	-	-	PUNCT
gc-467	91	30	neighbours	neighbour	NOUN
gc-467	91	31	to	to	ADP
gc-467	91	32	it	it	PRON
gc-467	91	33	.	.	PUNCT
gc-467	92	1	(	(	PUNCT
gc-467	92	2	3	3	X
gc-467	92	3	)	)	PUNCT
gc-467	92	4	the	the	DET
gc-467	92	5	border	border	NOUN
gc-467	92	6	of	of	ADP
gc-467	92	7	a	a	DET
gc-467	92	8	shape	shape	NOUN
gc-467	92	9	is	be	AUX
gc-467	92	10	defi	defi	NOUN
gc-467	92	11	ned	ne	VERB
gc-467	92	12	by	by	ADP
gc-467	92	13	a	a	DET
gc-467	92	14	point	point	NOUN
gc-467	92	15	which	which	PRON
gc-467	92	16	has	have	VERB
gc-467	92	17	neighbours	neighbour	NOUN
gc-467	92	18	from	from	ADP
gc-467	92	19	another	another	DET
gc-467	92	20	cluster	cluster	NOUN
gc-467	92	21	.	.	PUNCT
gc-467	93	1	of	of	ADV
gc-467	93	2	course	course	ADV
gc-467	93	3	a	a	DET
gc-467	93	4	pattern	pattern	NOUN
gc-467	93	5	might	might	AUX
gc-467	93	6	also	also	ADV
gc-467	93	7	have	have	VERB
gc-467	93	8	more	more	ADJ
gc-467	93	9	neighbours	neighbour	NOUN
gc-467	93	10	.	.	PUNCT
gc-467	94	1	(	(	PUNCT
gc-467	94	2	4	4	NUM
gc-467	94	3	)	)	PUNCT
gc-467	94	4	within	within	ADP
gc-467	94	5	a	a	DET
gc-467	94	6	shape	shape	NOUN
gc-467	94	7	we	we	PRON
gc-467	94	8	can	can	AUX
gc-467	94	9	also	also	ADV
gc-467	94	10	defi	defi	VERB
gc-467	94	11	ne	ne	PROPN
gc-467	94	12	another	another	DET
gc-467	94	13	shape	shape	NOUN
gc-467	94	14	if	if	SCONJ
gc-467	94	15	it	it	PRON
gc-467	94	16	has	have	VERB
gc-467	94	17	inner	inner	ADJ
gc-467	94	18	points	point	NOUN
gc-467	94	19	.	.	PUNCT
gc-467	95	1	otherwise	otherwise	ADV
gc-467	95	2	we	we	PRON
gc-467	95	3	should	should	AUX
gc-467	95	4	disregard	disregard	VERB
gc-467	95	5	these	these	DET
gc-467	95	6	points	point	NOUN
gc-467	95	7	as	as	ADP
gc-467	95	8	a	a	DET
gc-467	95	9	pattern	pattern	NOUN
gc-467	95	10	.	.	PUNCT
gc-467	96	1	however	however	ADV
gc-467	96	2	in	in	ADP
gc-467	96	3	this	this	DET
gc-467	96	4	case	case	NOUN
gc-467	96	5	,	,	PUNCT
gc-467	96	6	the	the	DET
gc-467	96	7	question	question	NOUN
gc-467	96	8	is	be	AUX
gc-467	96	9	how	how	SCONJ
gc-467	96	10	many	many	ADJ
gc-467	96	11	inner	inner	ADJ
gc-467	96	12	points	point	NOUN
gc-467	96	13	are	be	AUX
gc-467	96	14	enough	enough	ADJ
gc-467	96	15	to	to	PART
gc-467	96	16	defi	defi	VERB
gc-467	96	17	ne	ne	PROPN
gc-467	96	18	a	a	DET
gc-467	96	19	pattern	pattern	NOUN
gc-467	96	20	.	.	PUNCT
gc-467	97	1	the	the	DET
gc-467	97	2	answer	answer	NOUN
gc-467	97	3	depends	depend	VERB
gc-467	97	4	on	on	ADP
gc-467	97	5	the	the	DET
gc-467	97	6	grid	grid	NOUN
gc-467	97	7	dissolution	dissolution	NOUN
gc-467	97	8	.	.	PUNCT
gc-467	98	1	since	since	SCONJ
gc-467	98	2	a	a	DET
gc-467	98	3	100	100	NUM
gc-467	98	4	x	x	SYM
gc-467	98	5	100	100	NUM
gc-467	98	6	m	m	NOUN
gc-467	98	7	grid	grid	NOUN
gc-467	98	8	size	size	NOUN
gc-467	98	9	was	be	AUX
gc-467	98	10	applied	apply	VERB
gc-467	98	11	over	over	ADP
gc-467	98	12	the	the	DET
gc-467	98	13	study	study	NOUN
gc-467	98	14	area	area	NOUN
gc-467	98	15	,	,	PUNCT
gc-467	98	16	we	we	PRON
gc-467	98	17	can	can	AUX
gc-467	98	18	defi	defi	VERB
gc-467	98	19	ne	ne	PROPN
gc-467	98	20	the	the	DET
gc-467	98	21	inner	inner	ADJ
gc-467	98	22	pattern	pattern	NOUN
gc-467	98	23	which	which	PRON
gc-467	98	24	has	have	VERB
gc-467	98	25	at	at	ADV
gc-467	98	26	least	least	ADV
gc-467	98	27	one	one	NUM
gc-467	98	28	inner	inner	ADJ
gc-467	98	29	point	point	NOUN
gc-467	98	30	.	.	PUNCT
gc-467	99	1	(	(	PUNCT
gc-467	99	2	this	this	DET
gc-467	99	3	consideration	consideration	NOUN
gc-467	99	4	gives	give	VERB
gc-467	99	5	5	5	NUM
gc-467	99	6	inner	inner	ADJ
gc-467	99	7	points	point	NOUN
gc-467	99	8	in	in	ADP
gc-467	99	9	case	case	NOUN
gc-467	99	10	of	of	ADP
gc-467	99	11	50	50	NUM
gc-467	99	12	x	x	SYM
gc-467	99	13	50	50	NUM
gc-467	99	14	m	m	NOUN
gc-467	99	15	grid	grid	NOUN
gc-467	99	16	size	size	NOUN
gc-467	99	17	and	and	CCONJ
gc-467	99	18	25	25	NUM
gc-467	99	19	inner	inner	ADJ
gc-467	99	20	points	point	NOUN
gc-467	99	21	in	in	ADP
gc-467	99	22	case	case	NOUN
gc-467	99	23	of	of	ADP
gc-467	99	24	25	25	NUM
gc-467	99	25	x	x	SYM
gc-467	99	26	25	25	NUM
gc-467	99	27	m	m	NOUN
gc-467	99	28	grid	grid	NOUN
gc-467	99	29	size	size	NOUN
gc-467	99	30	and	and	CCONJ
gc-467	99	31	so	so	ADV
gc-467	99	32	on	on	ADV
gc-467	99	33	.	.	PUNCT
gc-467	99	34	)	)	PUNCT
gc-467	100	1	(	(	PUNCT
gc-467	100	2	5	5	X
gc-467	100	3	)	)	PUNCT
gc-467	100	4	the	the	DET
gc-467	100	5	‘	'	PUNCT
gc-467	100	6	inner	inner	ADJ
gc-467	100	7	shape	shape	NOUN
gc-467	100	8	’	'	PUNCT
gc-467	100	9	,	,	PUNCT
gc-467	100	10	should	should	AUX
gc-467	100	11	be	be	AUX
gc-467	100	12	covered	cover	VERB
gc-467	100	13	by	by	ADP
gc-467	100	14	border	border	NOUN
gc-467	100	15	points	point	NOUN
gc-467	100	16	of	of	ADP
gc-467	100	17	only	only	ADV
gc-467	100	18	one	one	NUM
gc-467	100	19	other	other	ADJ
gc-467	100	20	cluster	cluster	NOUN
gc-467	100	21	.	.	PUNCT
gc-467	101	1	3	3	X
gc-467	101	2	.	.	X
gc-467	101	3	study	study	NOUN
gc-467	101	4	area	area	NOUN
gc-467	101	5	data	datum	NOUN
gc-467	101	6	originated	originate	VERB
gc-467	101	7	from	from	ADP
gc-467	101	8	the	the	DET
gc-467	101	9	szőreg-1	szőreg-1	NUM
gc-467	101	10	reservoir	reservoir	NOUN
gc-467	101	11	(	(	PUNCT
gc-467	101	12	algyő	algyő	NOUN
gc-467	101	13	field	field	NOUN
gc-467	101	14	)	)	PUNCT
gc-467	101	15	that	that	PRON
gc-467	101	16	was	be	AUX
gc-467	101	17	used	use	VERB
gc-467	101	18	as	as	ADP
gc-467	101	19	a	a	DET
gc-467	101	20	test	test	NOUN
gc-467	101	21	area	area	NOUN
gc-467	101	22	for	for	ADP
gc-467	101	23	the	the	DET
gc-467	101	24	application	application	NOUN
gc-467	101	25	of	of	ADP
gc-467	101	26	pattern	pattern	NOUN
gc-467	101	27	recognition	recognition	NOUN
gc-467	101	28	of	of	ADP
gc-467	101	29	palaeoenvironments	palaeoenvironment	NOUN
gc-467	101	30	in	in	ADP
gc-467	101	31	a	a	DET
gc-467	101	32	clastic	clastic	ADJ
gc-467	101	33	reservoir	reservoir	NOUN
gc-467	101	34	using	use	VERB
gc-467	101	35	the	the	DET
gc-467	101	36	kohonen	kohonen	PROPN
gc-467	101	37	’s	’s	PART
gc-467	101	38	neural	neural	ADJ
gc-467	101	39	network	network	NOUN
gc-467	101	40	.	.	PUNCT
gc-467	102	1	the	the	DET
gc-467	102	2	algyő	algyő	NOUN
gc-467	102	3	field	field	NOUN
gc-467	102	4	is	be	AUX
gc-467	102	5	the	the	DET
gc-467	102	6	largest	large	ADJ
gc-467	102	7	hungarian	hungarian	ADJ
gc-467	102	8	hydrocarbon	hydrocarbon	NOUN
gc-467	102	9	accumulation	accumulation	NOUN
gc-467	102	10	consisting	consist	VERB
gc-467	102	11	of	of	ADP
gc-467	102	12	several	several	ADJ
gc-467	102	13	oil	oil	NOUN
gc-467	102	14	and	and	CCONJ
gc-467	102	15	gas	gas	NOUN
gc-467	102	16	bearing	bear	VERB
gc-467	102	17	reservoirs	reservoir	NOUN
gc-467	102	18	(	(	PUNCT
gc-467	102	19	fig	fig	NOUN
gc-467	102	20	.	.	PUNCT
gc-467	102	21	4	4	NUM
gc-467	102	22	)	)	PUNCT
gc-467	102	23	.	.	PUNCT
gc-467	103	1	the	the	DET
gc-467	103	2	upper	upper	ADJ
gc-467	103	3	memfigure	memfigure	NOUN
gc-467	103	4	3	3	NUM
gc-467	103	5	:	:	PUNCT
gc-467	103	6	arrangement	arrangement	NOUN
gc-467	103	7	points	point	NOUN
gc-467	103	8	on	on	ADP
gc-467	103	9	the	the	DET
gc-467	103	10	map	map	NOUN
gc-467	103	11	.	.	PUNCT
gc-467	104	1	where	where	SCONJ
gc-467	104	2	pi	pi	NOUN
gc-467	104	3	means	mean	VERB
gc-467	104	4	data	datum	NOUN
gc-467	104	5	points	point	NOUN
gc-467	104	6	within	within	ADP
gc-467	104	7	clusters	cluster	NOUN
gc-467	104	8	(	(	PUNCT
gc-467	104	9	cm	cm	NOUN
gc-467	104	10	)	)	PUNCT
gc-467	104	11	;	;	PUNCT
gc-467	104	12	and	and	CCONJ
gc-467	104	13	(	(	PUNCT
gc-467	104	14	xi	xi	INTJ
gc-467	104	15	,	,	PUNCT
gc-467	104	16	yi	yi	PROPN
gc-467	104	17	)	)	PUNCT
gc-467	104	18	means	mean	VERB
gc-467	104	19	the	the	DET
gc-467	104	20	positions	position	NOUN
gc-467	104	21	of	of	ADP
gc-467	104	22	data	datum	NOUN
gc-467	104	23	points	point	NOUN
gc-467	104	24	with	with	ADP
gc-467	104	25	their	their	PRON
gc-467	104	26	original	original	ADJ
gc-467	104	27	coordinates	coordinate	NOUN
gc-467	104	28	in	in	ADP
gc-467	104	29	the	the	DET
gc-467	104	30	map	map	NOUN
gc-467	104	31	.	.	PUNCT
gc-467	105	1	geologia	geologia	PROPN
gc-467	105	2	croatica	croatica	PROPN
gc-467	105	3	64/3geologia	64/3geologia	PROPN
gc-467	105	4	croatica	croatica	PROPN
gc-467	105	5	254	254	NUM
gc-467	105	6	bers	ber	NOUN
gc-467	105	7	of	of	ADP
gc-467	105	8	these	these	DET
gc-467	105	9	reservoirs	reservoir	NOUN
gc-467	105	10	developed	develop	VERB
gc-467	105	11	in	in	ADP
gc-467	105	12	a	a	DET
gc-467	105	13	pannonian	pannonian	ADJ
gc-467	105	14	delta	delta	NOUN
gc-467	105	15	system	system	NOUN
gc-467	105	16	as	as	ADP
gc-467	105	17	the	the	DET
gc-467	105	18	consequences	consequence	NOUN
gc-467	105	19	of	of	ADP
gc-467	105	20	complex	complex	ADJ
gc-467	105	21	lateral	lateral	ADJ
gc-467	105	22	delta	delta	NOUN
gc-467	105	23	-	-	PUNCT
gc-467	105	24	shifting	shift	VERB
gc-467	105	25	and	and	CCONJ
gc-467	105	26	prograding	prograde	VERB
gc-467	105	27	phases	phase	NOUN
gc-467	105	28	.	.	PUNCT
gc-467	106	1	they	they	PRON
gc-467	106	2	can	can	AUX
gc-467	106	3	be	be	AUX
gc-467	106	4	subdivided	subdivide	VERB
gc-467	106	5	into	into	ADP
gc-467	106	6	delta	delta	NOUN
gc-467	106	7	slope	slope	NOUN
gc-467	106	8	and	and	CCONJ
gc-467	106	9	delta	delta	NOUN
gc-467	106	10	plain	plain	ADJ
gc-467	106	11	rock	rock	NOUN
gc-467	106	12	bodies	body	NOUN
gc-467	106	13	.	.	PUNCT
gc-467	107	1	the	the	DET
gc-467	107	2	sills	sill	NOUN
gc-467	107	3	of	of	ADP
gc-467	107	4	the	the	DET
gc-467	107	5	individual	individual	ADJ
gc-467	107	6	reservoirs	reservoir	NOUN
gc-467	107	7	were	be	AUX
gc-467	107	8	formed	form	VERB
gc-467	107	9	during	during	ADP
gc-467	107	10	delta	delta	PROPN
gc-467	107	11	abandonment	abandonment	NOUN
gc-467	107	12	phases	phase	NOUN
gc-467	107	13	.	.	PUNCT
gc-467	108	1	below	below	ADP
gc-467	108	2	this	this	DET
gc-467	108	3	series	series	NOUN
gc-467	108	4	,	,	PUNCT
gc-467	108	5	the	the	DET
gc-467	108	6	lower	low	ADJ
gc-467	108	7	reservoirs	reservoir	NOUN
gc-467	108	8	are	be	AUX
gc-467	108	9	regarded	regard	VERB
gc-467	108	10	as	as	ADP
gc-467	108	11	turbidity	turbidity	NOUN
gc-467	108	12	rock	rock	NOUN
gc-467	108	13	bodies	body	NOUN
gc-467	108	14	of	of	ADP
gc-467	108	15	partly	partly	ADV
gc-467	108	16	pro	pro	ADJ
gc-467	108	17	-	-	ADJ
gc-467	108	18	delta	delta	ADJ
gc-467	108	19	fans	fan	NOUN
gc-467	108	20	and	and	CCONJ
gc-467	108	21	partly	partly	ADV
gc-467	108	22	deep	deep	ADJ
gc-467	108	23	basin	basin	NOUN
gc-467	108	24	origin	origin	NOUN
gc-467	108	25	(	(	PUNCT
gc-467	108	26	révész	révész	PROPN
gc-467	108	27	,	,	PUNCT
gc-467	108	28	1982	1982	NUM
gc-467	108	29	)	)	PUNCT
gc-467	108	30	.	.	PUNCT
gc-467	109	1	the	the	DET
gc-467	109	2	szőreg-1	szőreg-1	NUM
gc-467	109	3	oil	oil	NOUN
gc-467	109	4	reservoir	reservoir	NOUN
gc-467	109	5	,	,	PUNCT
gc-467	109	6	with	with	ADP
gc-467	109	7	a	a	DET
gc-467	109	8	large	large	ADJ
gc-467	109	9	gas	gas	NOUN
gc-467	109	10	cap	cap	NOUN
gc-467	109	11	is	be	AUX
gc-467	109	12	one	one	NUM
gc-467	109	13	of	of	ADP
gc-467	109	14	the	the	DET
gc-467	109	15	largest	large	ADJ
gc-467	109	16	rock	rock	NOUN
gc-467	109	17	bodies	body	NOUN
gc-467	109	18	within	within	ADP
gc-467	109	19	the	the	DET
gc-467	109	20	delta	delta	NOUN
gc-467	109	21	plain	plain	ADJ
gc-467	109	22	record	record	NOUN
gc-467	109	23	(	(	PUNCT
gc-467	109	24	fig	fig	NOUN
gc-467	109	25	.	.	PUNCT
gc-467	109	26	4	4	NUM
gc-467	109	27	)	)	PUNCT
gc-467	109	28	.	.	PUNCT
gc-467	110	1	its	its	PRON
gc-467	110	2	average	average	ADJ
gc-467	110	3	gross	gross	ADJ
gc-467	110	4	thickness	thickness	NOUN
gc-467	110	5	is	be	AUX
gc-467	110	6	about	about	ADV
gc-467	110	7	35	35	NUM
gc-467	110	8	m	m	NOUN
gc-467	110	9	,	,	PUNCT
gc-467	110	10	but	but	CCONJ
gc-467	110	11	locally	locally	ADV
gc-467	110	12	it	it	PRON
gc-467	110	13	can	can	AUX
gc-467	110	14	be	be	AUX
gc-467	110	15	up	up	ADP
gc-467	110	16	to	to	ADP
gc-467	110	17	a	a	DET
gc-467	110	18	maximum	maximum	NOUN
gc-467	110	19	of	of	ADP
gc-467	110	20	50	50	NUM
gc-467	110	21	m	m	NOUN
gc-467	110	22	thick	thick	ADJ
gc-467	110	23	.	.	PUNCT
gc-467	111	1	earlier	early	ADV
gc-467	111	2	works	work	VERB
gc-467	111	3	by	by	ADP
gc-467	111	4	révész	révész	NOUN
gc-467	111	5	(	(	PUNCT
gc-467	111	6	1982	1982	NUM
gc-467	111	7	)	)	PUNCT
gc-467	111	8	,	,	PUNCT
gc-467	111	9	geiger	geiger	PROPN
gc-467	111	10	et	et	PROPN
gc-467	111	11	al	al	PROPN
gc-467	111	12	.	.	PROPN
gc-467	111	13	,	,	PUNCT
gc-467	111	14	(	(	PUNCT
gc-467	111	15	1998	1998	NUM
gc-467	111	16	)	)	PUNCT
gc-467	111	17	and	and	CCONJ
gc-467	111	18	geiger	geiger	PROPN
gc-467	111	19	(	(	PUNCT
gc-467	111	20	2005	2005	NUM
gc-467	111	21	)	)	PUNCT
gc-467	111	22	have	have	AUX
gc-467	111	23	proved	prove	VERB
gc-467	111	24	its	its	PRON
gc-467	111	25	delta	delta	NOUN
gc-467	111	26	plain	plain	ADJ
gc-467	111	27	origin	origin	NOUN
gc-467	111	28	with	with	ADP
gc-467	111	29	a	a	DET
gc-467	111	30	signifi	signifi	NOUN
gc-467	111	31	ca	can	AUX
gc-467	111	32	nt	not	PART
gc-467	111	33	amount	amount	VERB
gc-467	111	34	of	of	ADP
gc-467	111	35	fl	fl	ADP
gc-467	111	36	uvial	uvial	ADJ
gc-467	111	37	channel	channel	NOUN
gc-467	111	38	sedimentation	sedimentation	NOUN
gc-467	111	39	.	.	PUNCT
gc-467	112	1	figure	figure	NOUN
gc-467	112	2	5	5	NUM
gc-467	112	3	shows	show	VERB
gc-467	112	4	the	the	DET
gc-467	112	5	original	original	ADJ
gc-467	112	6	well	well	ADJ
gc-467	112	7	density	density	NOUN
gc-467	112	8	,	,	PUNCT
gc-467	112	9	the	the	DET
gc-467	112	10	dataset	dataset	NOUN
gc-467	112	11	is	be	AUX
gc-467	112	12	from	from	ADP
gc-467	112	13	506	506	NUM
gc-467	112	14	well	well	ADV
gc-467	112	15	on	on	ADP
gc-467	112	16	szőreg-1	szőreg-1	NUM
gc-467	112	17	study	study	NOUN
gc-467	112	18	area	area	NOUN
gc-467	112	19	.	.	PUNCT
gc-467	113	1	4	4	X
gc-467	113	2	.	.	X
gc-467	113	3	data	datum	NOUN
gc-467	113	4	pre	pre	ADJ
gc-467	113	5	-	-	ADJ
gc-467	113	6	processing	processing	NOUN
gc-467	113	7	and	and	CCONJ
gc-467	113	8	analysis	analysis	NOUN
gc-467	113	9	by	by	ADP
gc-467	113	10	som	som	NOUN
gc-467	113	11	the	the	DET
gc-467	113	12	network	network	NOUN
gc-467	113	13	depends	depend	VERB
gc-467	113	14	on	on	ADP
gc-467	113	15	the	the	DET
gc-467	113	16	quality	quality	NOUN
gc-467	113	17	and	and	CCONJ
gc-467	113	18	quantity	quantity	NOUN
gc-467	113	19	of	of	ADP
gc-467	113	20	training	training	NOUN
gc-467	113	21	data	datum	NOUN
gc-467	113	22	,	,	PUNCT
gc-467	113	23	so	so	SCONJ
gc-467	113	24	data	datum	NOUN
gc-467	113	25	pre	pre	ADJ
gc-467	113	26	-	-	ADJ
gc-467	113	27	processing	processing	NOUN
gc-467	113	28	is	be	AUX
gc-467	113	29	very	very	ADV
gc-467	113	30	important	important	ADJ
gc-467	113	31	.	.	PUNCT
gc-467	114	1	this	this	PRON
gc-467	114	2	is	be	AUX
gc-467	114	3	as	as	SCONJ
gc-467	114	4	follows	follow	VERB
gc-467	114	5	:	:	PUNCT
gc-467	114	6	1	1	X
gc-467	114	7	)	)	PUNCT
gc-467	114	8	defi	defi	NOUN
gc-467	114	9	nition	nition	NOUN
gc-467	114	10	of	of	ADP
gc-467	114	11	the	the	DET
gc-467	114	12	data	data	NOUN
gc-467	114	13	type	type	NOUN
gc-467	114	14	(	(	PUNCT
gc-467	114	15	discrete	discrete	ADJ
gc-467	114	16	or	or	CCONJ
gc-467	114	17	constant	constant	ADJ
gc-467	114	18	)	)	PUNCT
gc-467	114	19	,	,	PUNCT
gc-467	114	20	2	2	X
gc-467	114	21	)	)	PUNCT
gc-467	114	22	calculation	calculation	NOUN
gc-467	114	23	of	of	ADP
gc-467	114	24	statistics	statistic	NOUN
gc-467	114	25	:	:	PUNCT
gc-467	114	26	mean	mean	ADJ
gc-467	114	27	,	,	PUNCT
gc-467	114	28	standard	standard	ADJ
gc-467	114	29	deviation	deviation	NOUN
gc-467	114	30	,	,	PUNCT
gc-467	114	31	and	and	CCONJ
gc-467	114	32	3	3	X
gc-467	114	33	)	)	PUNCT
gc-467	114	34	selection	selection	NOUN
gc-467	114	35	of	of	ADP
gc-467	114	36	outlier	outlier	NOUN
gc-467	114	37	data	datum	NOUN
gc-467	114	38	.	.	PUNCT
gc-467	115	1	no	no	DET
gc-467	115	2	1	1	NUM
gc-467	115	3	is	be	AUX
gc-467	115	4	critical	critical	ADJ
gc-467	115	5	because	because	SCONJ
gc-467	115	6	the	the	DET
gc-467	115	7	outlier	outlier	NOUN
gc-467	115	8	data	datum	NOUN
gc-467	115	9	reduces	reduce	VERB
gc-467	115	10	the	the	DET
gc-467	115	11	effi	effi	PROPN
gc-467	115	12	ciency	ciency	NOUN
gc-467	115	13	of	of	ADP
gc-467	115	14	the	the	DET
gc-467	115	15	network.in	network.in	NOUN
gc-467	115	16	the	the	DET
gc-467	115	17	case	case	NOUN
gc-467	115	18	of	of	ADP
gc-467	115	19	category	category	NOUN
gc-467	115	20	data	datum	NOUN
gc-467	115	21	,	,	PUNCT
gc-467	115	22	it	it	PRON
gc-467	115	23	is	be	AUX
gc-467	115	24	necessary	necessary	ADJ
gc-467	115	25	to	to	PART
gc-467	115	26	encode	encode	VERB
gc-467	115	27	or	or	CCONJ
gc-467	115	28	scale	scale	VERB
gc-467	115	29	the	the	DET
gc-467	115	30	data	datum	NOUN
gc-467	115	31	.	.	PUNCT
gc-467	116	1	in	in	ADP
gc-467	116	2	this	this	DET
gc-467	116	3	study	study	NOUN
gc-467	116	4	we	we	PRON
gc-467	116	5	used	use	VERB
gc-467	116	6	continuous	continuous	ADJ
gc-467	116	7	variable	variable	ADJ
gc-467	116	8	data	datum	NOUN
gc-467	116	9	.	.	PUNCT
gc-467	117	1	it	it	PRON
gc-467	117	2	is	be	AUX
gc-467	117	3	imperative	imperative	ADJ
gc-467	117	4	to	to	PART
gc-467	117	5	set	set	VERB
gc-467	117	6	the	the	DET
gc-467	117	7	initial	initial	ADJ
gc-467	117	8	values	value	NOUN
gc-467	117	9	for	for	ADP
gc-467	117	10	the	the	DET
gc-467	117	11	training	training	NOUN
gc-467	117	12	rate	rate	NOUN
gc-467	117	13	and	and	CCONJ
gc-467	117	14	the	the	DET
gc-467	117	15	neighborhood	neighborhood	NOUN
gc-467	117	16	radius	radius	NOUN
gc-467	117	17	.	.	PUNCT
gc-467	118	1	the	the	DET
gc-467	118	2	kohonen	kohonen	PROPN
gc-467	118	3	-	-	PUNCT
gc-467	118	4	learning	learn	VERB
gc-467	118	5	rate	rate	NOUN
gc-467	118	6	is	be	AUX
gc-467	118	7	altered	alter	VERB
gc-467	118	8	linearly	linearly	ADV
gc-467	118	9	from	from	ADP
gc-467	118	10	the	the	DET
gc-467	118	11	fi	fi	NOUN
gc-467	118	12	rst	rst	NOUN
gc-467	118	13	to	to	ADP
gc-467	118	14	the	the	DET
gc-467	118	15	last	last	ADJ
gc-467	118	16	training	training	NOUN
gc-467	118	17	cycle	cycle	NOUN
gc-467	118	18	.	.	PUNCT
gc-467	119	1	we	we	PRON
gc-467	119	2	specifi	specifi	VERB
gc-467	119	3	ed	ed	PROPN
gc-467	119	4	0.3	0.3	NUM
gc-467	119	5	for	for	ADP
gc-467	119	6	the	the	DET
gc-467	119	7	start	start	NOUN
gc-467	119	8	value	value	NOUN
gc-467	119	9	and	and	CCONJ
gc-467	119	10	0.02	0.02	NUM
gc-467	119	11	for	for	ADP
gc-467	119	12	the	the	DET
gc-467	119	13	end	end	NOUN
gc-467	119	14	value	value	NOUN
gc-467	119	15	.	.	PUNCT
gc-467	120	1	the	the	DET
gc-467	120	2	neighborhood	neighborhood	NOUN
gc-467	120	3	radius	radius	NOUN
gc-467	120	4	designates	designate	VERB
gc-467	120	5	the	the	DET
gc-467	120	6	adjacent	adjacent	ADJ
gc-467	120	7	area	area	NOUN
gc-467	120	8	centered	center	VERB
gc-467	120	9	on	on	ADP
gc-467	120	10	the	the	DET
gc-467	120	11	winning	win	VERB
gc-467	120	12	unit	unit	NOUN
gc-467	120	13	;	;	PUNCT
gc-467	120	14	in	in	ADP
gc-467	120	15	this	this	DET
gc-467	120	16	case	case	NOUN
gc-467	120	17	the	the	DET
gc-467	120	18	size	size	NOUN
gc-467	120	19	was	be	AUX
gc-467	120	20	1	1	NUM
gc-467	120	21	and	and	CCONJ
gc-467	120	22	specifi	specifi	PROPN
gc-467	120	23	ed	ed	PROPN
gc-467	120	24	a	a	DET
gc-467	120	25	3x3	3x3	NUM
gc-467	120	26	square	square	NOUN
gc-467	120	27	.	.	PUNCT
gc-467	121	1	normal	normal	ADJ
gc-467	121	2	randomization	randomization	NOUN
gc-467	121	3	of	of	ADP
gc-467	121	4	weights	weight	NOUN
gc-467	121	5	was	be	AUX
gc-467	121	6	used	use	VERB
gc-467	121	7	for	for	ADP
gc-467	121	8	the	the	DET
gc-467	121	9	training	training	NOUN
gc-467	121	10	;	;	PUNCT
gc-467	121	11	the	the	DET
gc-467	121	12	mean	mean	NOUN
gc-467	121	13	and	and	CCONJ
gc-467	121	14	variance	variance	NOUN
gc-467	121	15	are	be	AUX
gc-467	121	16	specifi	specifi	PROPN
gc-467	121	17	ed	ed	NOUN
gc-467	121	18	,	,	PUNCT
gc-467	121	19	and	and	CCONJ
gc-467	121	20	are	be	AUX
gc-467	121	21	used	use	VERB
gc-467	121	22	to	to	PART
gc-467	121	23	draw	draw	VERB
gc-467	121	24	the	the	DET
gc-467	121	25	initial	initial	ADJ
gc-467	121	26	weight	weight	NOUN
gc-467	121	27	values	value	NOUN
gc-467	121	28	.	.	PUNCT
gc-467	122	1	the	the	DET
gc-467	122	2	second	second	ADJ
gc-467	122	3	important	important	ADJ
gc-467	122	4	step	step	NOUN
gc-467	122	5	is	be	AUX
gc-467	122	6	to	to	PART
gc-467	122	7	defi	defi	VERB
gc-467	122	8	ne	ne	PROPN
gc-467	122	9	the	the	DET
gc-467	122	10	training	training	NOUN
gc-467	122	11	,	,	PUNCT
gc-467	122	12	test	test	NOUN
gc-467	122	13	and	and	CCONJ
gc-467	122	14	validation	validation	NOUN
gc-467	122	15	sets	set	NOUN
gc-467	122	16	for	for	ADP
gc-467	122	17	training	training	NOUN
gc-467	122	18	of	of	ADP
gc-467	122	19	som	som	NOUN
gc-467	122	20	.	.	PUNCT
gc-467	123	1	the	the	DET
gc-467	123	2	original	original	ADJ
gc-467	123	3	database	database	NOUN
gc-467	123	4	comprises	comprise	VERB
gc-467	123	5	7500	7500	NUM
gc-467	123	6	points	point	NOUN
gc-467	123	7	(	(	PUNCT
gc-467	123	8	grid	grid	NOUN
gc-467	123	9	points	point	NOUN
gc-467	123	10	)	)	PUNCT
gc-467	123	11	.	.	PUNCT
gc-467	124	1	this	this	DET
gc-467	124	2	dataset	dataset	NOUN
gc-467	124	3	is	be	AUX
gc-467	124	4	deconstructed	deconstruct	VERB
gc-467	124	5	into	into	ADP
gc-467	124	6	three	three	NUM
gc-467	124	7	sub	sub	NOUN
gc-467	124	8	-	-	NOUN
gc-467	124	9	sets	set	NOUN
gc-467	124	10	(	(	PUNCT
gc-467	124	11	training-	training-	X
gc-467	124	12	,	,	PUNCT
gc-467	124	13	testand	testand	NOUN
gc-467	124	14	validation	validation	NOUN
gc-467	124	15	set	set	NOUN
gc-467	124	16	)	)	PUNCT
gc-467	124	17	using	use	VERB
gc-467	124	18	a	a	DET
gc-467	124	19	random	random	ADJ
gc-467	124	20	number	number	NOUN
gc-467	124	21	generator	generator	NOUN
gc-467	124	22	to	to	PART
gc-467	124	23	avoid	avoid	VERB
gc-467	124	24	bias	bias	NOUN
gc-467	124	25	.	.	PUNCT
gc-467	125	1	60	60	NUM
gc-467	125	2	%	%	NOUN
gc-467	125	3	of	of	ADP
gc-467	125	4	this	this	DET
gc-467	125	5	database	database	NOUN
gc-467	125	6	is	be	AUX
gc-467	125	7	used	use	VERB
gc-467	125	8	for	for	ADP
gc-467	125	9	building	build	VERB
gc-467	125	10	a	a	DET
gc-467	125	11	neural	neural	ADJ
gc-467	125	12	network	network	NOUN
gc-467	125	13	by	by	ADP
gc-467	125	14	som	som	NOUN
gc-467	125	15	as	as	ADP
gc-467	125	16	a	a	DET
gc-467	125	17	training	training	NOUN
gc-467	125	18	set	set	NOUN
gc-467	125	19	,	,	PUNCT
gc-467	125	20	20	20	NUM
gc-467	125	21	%	%	NOUN
gc-467	125	22	as	as	ADP
gc-467	125	23	a	a	DET
gc-467	125	24	test	test	NOUN
gc-467	125	25	,	,	PUNCT
gc-467	125	26	and	and	CCONJ
gc-467	125	27	20	20	NUM
gc-467	125	28	%	%	NOUN
gc-467	125	29	as	as	ADP
gc-467	125	30	a	a	DET
gc-467	125	31	validation	validation	NOUN
gc-467	125	32	set	set	NOUN
gc-467	125	33	.	.	PUNCT
gc-467	126	1	training	training	NOUN
gc-467	126	2	set	set	NOUN
gc-467	126	3	:	:	PUNCT
gc-467	126	4	this	this	DET
gc-467	126	5	set	set	NOUN
gc-467	126	6	is	be	AUX
gc-467	126	7	important	important	ADJ
gc-467	126	8	to	to	PART
gc-467	126	9	learn	learn	VERB
gc-467	126	10	to	to	ADP
gc-467	126	11	fi	fi	NOUN
gc-467	126	12	t	t	PROPN
gc-467	126	13	the	the	DET
gc-467	126	14	parameters	parameter	NOUN
gc-467	126	15	of	of	ADP
gc-467	126	16	the	the	DET
gc-467	126	17	clusters	cluster	NOUN
gc-467	126	18	(	(	PUNCT
gc-467	126	19	in	in	ADP
gc-467	126	20	this	this	DET
gc-467	126	21	case	case	NOUN
gc-467	126	22	clusters	cluster	NOUN
gc-467	126	23	are	be	AUX
gc-467	126	24	the	the	DET
gc-467	126	25	neurons	neuron	NOUN
gc-467	126	26	that	that	PRON
gc-467	126	27	characterized	characterize	VERB
gc-467	126	28	the	the	DET
gc-467	126	29	clusters	cluster	NOUN
gc-467	126	30	)	)	PUNCT
gc-467	126	31	.	.	PUNCT
gc-467	127	1	som	som	NOUN
gc-467	127	2	is	be	AUX
gc-467	127	3	applied	apply	VERB
gc-467	127	4	to	to	ADP
gc-467	127	5	fi	fi	NOUN
gc-467	127	6	nd	nd	ADP
gc-467	127	7	the	the	DET
gc-467	127	8	optimal	optimal	ADJ
gc-467	127	9	weights	weight	NOUN
gc-467	127	10	to	to	PART
gc-467	127	11	update	update	VERB
gc-467	127	12	the	the	DET
gc-467	127	13	kohonen	kohonen	PROPN
gc-467	127	14	’s	’s	PART
gc-467	127	15	layer	layer	NOUN
gc-467	127	16	and	and	CCONJ
gc-467	127	17	to	to	PART
gc-467	127	18	position	position	VERB
gc-467	127	19	the	the	DET
gc-467	127	20	neurons	neuron	NOUN
gc-467	127	21	of	of	ADP
gc-467	127	22	clusters	cluster	NOUN
gc-467	127	23	.	.	PUNCT
gc-467	128	1	validation	validation	NOUN
gc-467	128	2	set	set	PROPN
gc-467	128	3	:	:	PUNCT
gc-467	128	4	this	this	DET
gc-467	128	5	set	set	NOUN
gc-467	128	6	is	be	AUX
gc-467	128	7	applied	apply	VERB
gc-467	128	8	to	to	PART
gc-467	128	9	tune	tune	VERB
gc-467	128	10	the	the	DET
gc-467	128	11	parameters	parameter	NOUN
gc-467	128	12	of	of	ADP
gc-467	128	13	a	a	DET
gc-467	128	14	classifi	classifi	NOUN
gc-467	128	15	er	er	INTJ
gc-467	128	16	,	,	PUNCT
gc-467	128	17	and	and	CCONJ
gc-467	128	18	determine	determine	VERB
gc-467	128	19	the	the	DET
gc-467	128	20	stopping	stopping	NOUN
gc-467	128	21	point	point	NOUN
gc-467	128	22	of	of	ADP
gc-467	128	23	learning	learn	VERB
gc-467	128	24	process	process	NOUN
gc-467	128	25	.	.	PUNCT
gc-467	129	1	test	test	NOUN
gc-467	129	2	set	set	NOUN
gc-467	129	3	:	:	PUNCT
gc-467	129	4	this	this	DET
gc-467	129	5	set	set	NOUN
gc-467	129	6	lends	lend	VERB
gc-467	129	7	itself	itself	PRON
gc-467	129	8	to	to	PART
gc-467	129	9	assess	assess	VERB
gc-467	129	10	the	the	DET
gc-467	129	11	performance	performance	NOUN
gc-467	129	12	of	of	ADP
gc-467	129	13	the	the	DET
gc-467	129	14	trained	train	VERB
gc-467	129	15	clusters	cluster	NOUN
gc-467	129	16	.	.	PUNCT
gc-467	130	1	after	after	ADP
gc-467	130	2	pre	pre	ADJ
gc-467	130	3	-	-	ADJ
gc-467	130	4	processing	processing	NOUN
gc-467	130	5	,	,	PUNCT
gc-467	130	6	the	the	DET
gc-467	130	7	fi	fi	NOUN
gc-467	130	8	rst	rst	ADJ
gc-467	130	9	step	step	NOUN
gc-467	130	10	only	only	ADV
gc-467	130	11	sampled	sample	VERB
gc-467	130	12	distributary	distributary	ADJ
gc-467	130	13	mouth	mouth	NOUN
gc-467	130	14	bars	bar	NOUN
gc-467	130	15	developed	develop	VERB
gc-467	130	16	in	in	ADP
gc-467	130	17	szőreg-1	szőreg-1	NUM
gc-467	130	18	to	to	PART
gc-467	130	19	analyze	analyze	VERB
gc-467	130	20	how	how	SCONJ
gc-467	130	21	the	the	DET
gc-467	130	22	som	som	NOUN
gc-467	130	23	method	method	NOUN
gc-467	130	24	can	can	AUX
gc-467	130	25	recognize	recognize	VERB
gc-467	130	26	the	the	DET
gc-467	130	27	pattern	pattern	NOUN
gc-467	130	28	for	for	ADP
gc-467	130	29	this	this	DET
gc-467	130	30	part	part	NOUN
gc-467	130	31	.	.	PUNCT
gc-467	131	1	the	the	DET
gc-467	131	2	pattern	pattern	NOUN
gc-467	131	3	of	of	ADP
gc-467	131	4	distributary	distributary	ADJ
gc-467	131	5	mouth	mouth	NOUN
gc-467	131	6	bars	bar	NOUN
gc-467	131	7	was	be	AUX
gc-467	131	8	given	give	VERB
gc-467	131	9	by	by	ADP
gc-467	131	10	sand	sand	NOUN
gc-467	131	11	contours	contours	NOUN
gc-467	131	12	that	that	PRON
gc-467	131	13	can	can	AUX
gc-467	131	14	refl	refl	VERB
gc-467	131	15	ect	ect	VERB
gc-467	131	16	the	the	DET
gc-467	131	17	geometry	geometry	NOUN
gc-467	131	18	(	(	PUNCT
gc-467	131	19	figs	fig	NOUN
gc-467	131	20	.	.	PUNCT
gc-467	132	1	6a	6a	NOUN
gc-467	132	2	,	,	PUNCT
gc-467	132	3	b	b	NOUN
gc-467	132	4	)	)	PUNCT
gc-467	132	5	.	.	PUNCT
gc-467	133	1	it	it	PRON
gc-467	133	2	was	be	AUX
gc-467	133	3	an	an	DET
gc-467	133	4	imporfigure	imporfigure	NOUN
gc-467	133	5	4	4	NUM
gc-467	133	6	:	:	PUNCT
gc-467	133	7	macro	macro	ADJ
gc-467	133	8	-	-	ADJ
gc-467	133	9	sedimentological	sedimentological	ADJ
gc-467	133	10	model	model	NOUN
gc-467	133	11	of	of	ADP
gc-467	133	12	the	the	DET
gc-467	133	13	pannonian	pannonian	ADJ
gc-467	133	14	series	series	NOUN
gc-467	133	15	of	of	ADP
gc-467	133	16	algyő	algyő	PROPN
gc-467	133	17	(	(	PUNCT
gc-467	133	18	after	after	ADP
gc-467	133	19	bérczi	bérczi	PROPN
gc-467	133	20	,	,	PUNCT
gc-467	133	21	1988	1988	NUM
gc-467	133	22	)	)	PUNCT
gc-467	133	23	.	.	PUNCT
gc-467	134	1	figure	figure	VERB
gc-467	134	2	5	5	NUM
gc-467	134	3	:	:	PUNCT
gc-467	134	4	well	well	ADJ
gc-467	134	5	density	density	NOUN
gc-467	134	6	of	of	ADP
gc-467	134	7	the	the	DET
gc-467	134	8	study	study	NOUN
gc-467	134	9	area	area	NOUN
gc-467	134	10	(	(	PUNCT
gc-467	134	11	szőreg-1	szőreg-1	NUM
gc-467	134	12	reservoir	reservoir	NOUN
gc-467	134	13	)	)	PUNCT
gc-467	134	14	.	.	PUNCT
gc-467	135	1	janina	janina	PROPN
gc-467	135	2	horváth	horváth	PROPN
gc-467	135	3	:	:	PUNCT
gc-467	135	4	defi	defi	PROPN
gc-467	135	5	ning	ning	ADJ
gc-467	135	6	depositional	depositional	ADJ
gc-467	135	7	environments	environment	NOUN
gc-467	135	8	by	by	ADP
gc-467	135	9	using	use	VERB
gc-467	135	10	neural	neural	ADJ
gc-467	135	11	networks	network	NOUN
gc-467	135	12	geologia	geologia	VERB
gc-467	135	13	croatica	croatica	PROPN
gc-467	135	14	255	255	NUM
gc-467	135	15	tant	tant	ADJ
gc-467	135	16	step	step	NOUN
gc-467	135	17	since	since	SCONJ
gc-467	135	18	it	it	PRON
gc-467	135	19	can	can	AUX
gc-467	135	20	show	show	VERB
gc-467	135	21	how	how	SCONJ
gc-467	135	22	well	well	ADV
gc-467	135	23	the	the	DET
gc-467	135	24	som	som	NOUN
gc-467	135	25	-	-	PUNCT
gc-467	135	26	method	method	NOUN
gc-467	135	27	refl	refl	NOUN
gc-467	135	28	ects	ect	VERB
gc-467	135	29	patterns	pattern	NOUN
gc-467	135	30	jointly	jointly	ADV
gc-467	135	31	through	through	ADP
gc-467	135	32	three	three	NUM
gc-467	135	33	other	other	ADJ
gc-467	135	34	variables	variable	NOUN
gc-467	135	35	.	.	PUNCT
gc-467	136	1	these	these	DET
gc-467	136	2	variables	variable	NOUN
gc-467	136	3	were	be	AUX
gc-467	136	4	porosity	porosity	NOUN
gc-467	136	5	,	,	PUNCT
gc-467	136	6	net	net	ADJ
gc-467	136	7	pore	pore	ADJ
gc-467	136	8	volume	volume	NOUN
gc-467	136	9	and	and	CCONJ
gc-467	136	10	hydraulic	hydraulic	ADJ
gc-467	136	11	conductivity	conductivity	NOUN
gc-467	136	12	data	datum	NOUN
gc-467	136	13	(	(	PUNCT
gc-467	136	14	figs	fig	NOUN
gc-467	136	15	.	.	PUNCT
gc-467	137	1	7a	7a	NUM
gc-467	137	2	,	,	PUNCT
gc-467	137	3	b	b	NOUN
gc-467	137	4	)	)	PUNCT
gc-467	137	5	.	.	PUNCT
gc-467	138	1	the	the	DET
gc-467	138	2	input	input	NOUN
gc-467	138	3	data	datum	NOUN
gc-467	138	4	set	set	NOUN
gc-467	138	5	comprises	comprise	VERB
gc-467	138	6	2200	2200	NUM
gc-467	138	7	grid	grid	NOUN
gc-467	138	8	points	point	NOUN
gc-467	138	9	(	(	PUNCT
gc-467	138	10	with	with	ADP
gc-467	138	11	100x100	100x100	PROPN
gc-467	138	12	m	m	NUM
gc-467	138	13	dissolution	dissolution	NOUN
gc-467	138	14	)	)	PUNCT
gc-467	138	15	,	,	PUNCT
gc-467	138	16	randomly	randomly	ADV
gc-467	138	17	divided	divide	VERB
gc-467	138	18	into	into	ADP
gc-467	138	19	three	three	NUM
gc-467	138	20	(	(	PUNCT
gc-467	138	21	training	training	NOUN
gc-467	138	22	,	,	PUNCT
gc-467	138	23	test	test	NOUN
gc-467	138	24	and	and	CCONJ
gc-467	138	25	validation	validation	NOUN
gc-467	138	26	)	)	PUNCT
gc-467	138	27	subsets	subset	NOUN
gc-467	138	28	.	.	PUNCT
gc-467	139	1	the	the	DET
gc-467	139	2	predefi	predefi	NOUN
gc-467	139	3	ned	ned	ADJ
gc-467	139	4	number	number	NOUN
gc-467	139	5	of	of	ADP
gc-467	139	6	clusters	cluster	NOUN
gc-467	139	7	was	be	AUX
gc-467	139	8	tuned	tune	VERB
gc-467	139	9	into	into	ADP
gc-467	139	10	3	3	NUM
gc-467	139	11	,	,	PUNCT
gc-467	139	12	4	4	NUM
gc-467	139	13	and	and	CCONJ
gc-467	139	14	higher	high	ADJ
gc-467	139	15	.	.	PUNCT
gc-467	140	1	in	in	ADP
gc-467	140	2	the	the	DET
gc-467	140	3	case	case	NOUN
gc-467	140	4	of	of	ADP
gc-467	140	5	more	more	ADJ
gc-467	140	6	than	than	ADP
gc-467	140	7	4	4	NUM
gc-467	140	8	clusters	cluster	NOUN
gc-467	140	9	,	,	PUNCT
gc-467	140	10	the	the	DET
gc-467	140	11	algorithm	algorithm	NOUN
gc-467	140	12	became	become	VERB
gc-467	140	13	too	too	ADV
gc-467	140	14	confused	confused	ADJ
gc-467	140	15	for	for	ADP
gc-467	140	16	interpretation	interpretation	NOUN
gc-467	140	17	.	.	PUNCT
gc-467	141	1	even	even	ADV
gc-467	141	2	,	,	PUNCT
gc-467	141	3	after	after	ADP
gc-467	141	4	mapping	map	VERB
gc-467	141	5	these	these	DET
gc-467	141	6	results	result	NOUN
gc-467	141	7	it	it	PRON
gc-467	141	8	did	do	AUX
gc-467	141	9	not	not	PART
gc-467	141	10	constitute	constitute	VERB
gc-467	141	11	disjunctive	disjunctive	ADJ
gc-467	141	12	clusters	cluster	NOUN
gc-467	141	13	.	.	PUNCT
gc-467	142	1	in	in	ADP
gc-467	142	2	the	the	DET
gc-467	142	3	fi	fi	NOUN
gc-467	142	4	rst	rst	NOUN
gc-467	142	5	run	run	NOUN
gc-467	142	6	,	,	PUNCT
gc-467	142	7	the	the	DET
gc-467	142	8	minimum	minimum	ADJ
gc-467	142	9	number	number	NOUN
gc-467	142	10	of	of	ADP
gc-467	142	11	clusters	cluster	NOUN
gc-467	142	12	is	be	AUX
gc-467	142	13	easier	easy	ADJ
gc-467	142	14	to	to	PART
gc-467	142	15	tune	tune	VERB
gc-467	142	16	in	in	ADP
gc-467	142	17	3	3	NUM
gc-467	142	18	because	because	SCONJ
gc-467	142	19	distributary	distributary	ADJ
gc-467	142	20	mouth	mouth	NOUN
gc-467	142	21	bars	bar	NOUN
gc-467	142	22	can	can	AUX
gc-467	142	23	be	be	AUX
gc-467	142	24	divided	divide	VERB
gc-467	142	25	into	into	ADP
gc-467	142	26	three	three	NUM
gc-467	142	27	sub	sub	NOUN
gc-467	142	28	-	-	NOUN
gc-467	142	29	environments	environment	NOUN
gc-467	142	30	as	as	ADP
gc-467	142	31	channel	channel	NOUN
gc-467	142	32	,	,	PUNCT
gc-467	142	33	outer	outer	ADJ
gc-467	142	34	bar	bar	NOUN
gc-467	142	35	,	,	PUNCT
gc-467	142	36	and	and	CCONJ
gc-467	142	37	bar	bar	NOUN
gc-467	142	38	crest	crest	NOUN
gc-467	142	39	.	.	PUNCT
gc-467	143	1	after	after	ADP
gc-467	143	2	the	the	DET
gc-467	143	3	clustering	clustering	NOUN
gc-467	143	4	,	,	PUNCT
gc-467	143	5	we	we	PRON
gc-467	143	6	mapped	map	VERB
gc-467	143	7	the	the	DET
gc-467	143	8	patterns	pattern	NOUN
gc-467	143	9	.	.	PUNCT
gc-467	144	1	in	in	ADP
gc-467	144	2	the	the	DET
gc-467	144	3	maps	map	NOUN
gc-467	144	4	these	these	DET
gc-467	144	5	patterns	pattern	NOUN
gc-467	144	6	are	be	AUX
gc-467	144	7	the	the	DET
gc-467	144	8	separated	separate	VERB
gc-467	144	9	clusters	cluster	NOUN
gc-467	144	10	of	of	ADP
gc-467	144	11	the	the	DET
gc-467	144	12	analyzed	analyze	VERB
gc-467	144	13	area	area	NOUN
gc-467	144	14	(	(	PUNCT
gc-467	144	15	distributary	distributary	ADJ
gc-467	144	16	mouth	mouth	NOUN
gc-467	144	17	bars	bar	NOUN
gc-467	144	18	)	)	PUNCT
gc-467	144	19	and	and	CCONJ
gc-467	144	20	this	this	DET
gc-467	144	21	patterns	pattern	NOUN
gc-467	144	22	mean	mean	VERB
gc-467	144	23	the	the	DET
gc-467	144	24	blocks	block	NOUN
gc-467	144	25	of	of	ADP
gc-467	144	26	similar	similar	ADJ
gc-467	144	27	properties	property	NOUN
gc-467	144	28	.	.	PUNCT
gc-467	145	1	figure	figure	VERB
gc-467	145	2	8a	8a	NUM
gc-467	145	3	,	,	PUNCT
gc-467	145	4	b	b	PROPN
gc-467	145	5	represents	represent	VERB
gc-467	145	6	the	the	DET
gc-467	145	7	mapped	map	VERB
gc-467	145	8	result	result	NOUN
gc-467	145	9	of	of	ADP
gc-467	145	10	the	the	DET
gc-467	145	11	fi	fi	NOUN
gc-467	145	12	rst	rst	PROPN
gc-467	145	13	run	run	NOUN
gc-467	145	14	of	of	ADP
gc-467	145	15	som	som	NOUN
gc-467	145	16	.	.	PUNCT
gc-467	146	1	the	the	DET
gc-467	146	2	pattern	pattern	NOUN
gc-467	146	3	within	within	ADP
gc-467	146	4	this	this	DET
gc-467	146	5	depositional	depositional	ADJ
gc-467	146	6	environment	environment	NOUN
gc-467	146	7	can	can	AUX
gc-467	146	8	affect	affect	VERB
gc-467	146	9	the	the	DET
gc-467	146	10	spatial	spatial	ADJ
gc-467	146	11	arrangement	arrangement	NOUN
gc-467	146	12	of	of	ADP
gc-467	146	13	reservoir	reservoir	NOUN
gc-467	146	14	properties	property	NOUN
gc-467	146	15	.	.	PUNCT
gc-467	147	1	usually	usually	ADV
gc-467	147	2	the	the	DET
gc-467	147	3	sand	sand	NOUN
gc-467	147	4	contour	contour	NOUN
gc-467	147	5	used	use	VERB
gc-467	147	6	to	to	PART
gc-467	147	7	refl	refl	VERB
gc-467	147	8	ect	ect	ADP
gc-467	147	9	the	the	DET
gc-467	147	10	spatial	spatial	ADJ
gc-467	147	11	patterns	pattern	NOUN
gc-467	147	12	but	but	CCONJ
gc-467	147	13	in	in	ADP
gc-467	147	14	the	the	DET
gc-467	147	15	case	case	NOUN
gc-467	147	16	of	of	ADP
gc-467	147	17	the	the	DET
gc-467	147	18	clustering	clustering	ADJ
gc-467	147	19	method	method	NOUN
gc-467	147	20	and	and	CCONJ
gc-467	147	21	after	after	ADP
gc-467	147	22	that	that	PRON
gc-467	147	23	the	the	DET
gc-467	147	24	mapping	mapping	NOUN
gc-467	147	25	of	of	ADP
gc-467	147	26	clusters	cluster	NOUN
gc-467	147	27	,	,	PUNCT
gc-467	147	28	similar	similar	ADJ
gc-467	147	29	patterns	pattern	NOUN
gc-467	147	30	are	be	AUX
gc-467	147	31	discernible	discernible	ADJ
gc-467	147	32	like	like	ADP
gc-467	147	33	the	the	DET
gc-467	147	34	maps	map	NOUN
gc-467	147	35	of	of	ADP
gc-467	147	36	three	three	NUM
gc-467	147	37	original	original	ADJ
gc-467	147	38	properties	property	NOUN
gc-467	147	39	(	(	PUNCT
gc-467	147	40	figs	fig	NOUN
gc-467	147	41	.	.	PUNCT
gc-467	148	1	7a	7a	NUM
gc-467	148	2	,	,	PUNCT
gc-467	148	3	c	c	NOUN
gc-467	148	4	)	)	PUNCT
gc-467	148	5	or	or	CCONJ
gc-467	148	6	map	map	VERB
gc-467	148	7	of	of	ADP
gc-467	148	8	sand	sand	NOUN
gc-467	148	9	contour	contour	NOUN
gc-467	148	10	(	(	PUNCT
gc-467	148	11	fig	fig	NOUN
gc-467	148	12	.	.	PUNCT
gc-467	148	13	6b	6b	NUM
gc-467	148	14	)	)	PUNCT
gc-467	148	15	.	.	PUNCT
gc-467	149	1	in	in	ADP
gc-467	149	2	this	this	DET
gc-467	149	3	case	case	NOUN
gc-467	149	4	the	the	DET
gc-467	149	5	resultmaps	resultmap	NOUN
gc-467	149	6	can	can	AUX
gc-467	149	7	demonstrate	demonstrate	VERB
gc-467	149	8	that	that	SCONJ
gc-467	149	9	it	it	PRON
gc-467	149	10	is	be	AUX
gc-467	149	11	also	also	ADV
gc-467	149	12	possible	possible	ADJ
gc-467	149	13	to	to	PART
gc-467	149	14	apply	apply	VERB
gc-467	149	15	clustering	clustering	ADJ
gc-467	149	16	methods	method	NOUN
gc-467	149	17	for	for	ADP
gc-467	149	18	outline	outline	NOUN
gc-467	149	19	the	the	DET
gc-467	149	20	depositional	depositional	ADJ
gc-467	149	21	geometry	geometry	NOUN
gc-467	149	22	which	which	PRON
gc-467	149	23	are	be	AUX
gc-467	149	24	based	base	VERB
gc-467	149	25	on	on	ADP
gc-467	149	26	other	other	ADJ
gc-467	149	27	three	three	NUM
gc-467	149	28	petrophysical	petrophysical	ADJ
gc-467	149	29	parameters	parameter	NOUN
gc-467	149	30	jointly	jointly	ADV
gc-467	149	31	.	.	PUNCT
gc-467	150	1	figure	figure	VERB
gc-467	150	2	6	6	NUM
gc-467	150	3	:	:	PUNCT
gc-467	150	4	a	a	X
gc-467	150	5	)	)	PUNCT
gc-467	150	6	gross	gross	ADJ
gc-467	150	7	thickness	thickness	NOUN
gc-467	150	8	map	map	NOUN
gc-467	150	9	of	of	ADP
gc-467	150	10	the	the	DET
gc-467	150	11	szőreg-1	szőreg-1	NUM
gc-467	150	12	reservoir	reservoir	NOUN
gc-467	150	13	(	(	PUNCT
gc-467	150	14	entire	entire	ADJ
gc-467	150	15	area	area	NOUN
gc-467	150	16	)	)	PUNCT
gc-467	150	17	,	,	PUNCT
gc-467	150	18	b	b	X
gc-467	150	19	)	)	PUNCT
gc-467	150	20	gross	gross	ADJ
gc-467	150	21	thickness	thickness	NOUN
gc-467	150	22	map	map	NOUN
gc-467	150	23	of	of	ADP
gc-467	150	24	the	the	DET
gc-467	150	25	area	area	NOUN
gc-467	150	26	of	of	ADP
gc-467	150	27	the	the	DET
gc-467	150	28	distributary	distributary	ADJ
gc-467	150	29	mouth	mouth	NOUN
gc-467	150	30	bars	bar	NOUN
gc-467	150	31	in	in	ADP
gc-467	150	32	the	the	DET
gc-467	150	33	szőreg-1	szőreg-1	NUM
gc-467	150	34	reservoir	reservoir	NOUN
gc-467	150	35	.	.	PUNCT
gc-467	151	1	figure	figure	VERB
gc-467	151	2	7	7	NUM
gc-467	151	3	:	:	PUNCT
gc-467	151	4	a	a	X
gc-467	151	5	)	)	PUNCT
gc-467	151	6	porosity	porosity	NOUN
gc-467	151	7	map	map	NOUN
gc-467	151	8	of	of	ADP
gc-467	151	9	distributary	distributary	ADJ
gc-467	151	10	mouth	mouth	NOUN
gc-467	151	11	bars	bar	NOUN
gc-467	151	12	in	in	ADP
gc-467	151	13	the	the	DET
gc-467	151	14	szőreg-1	szőreg-1	NUM
gc-467	151	15	reservoir	reservoir	NOUN
gc-467	151	16	,	,	PUNCT
gc-467	151	17	b	b	NOUN
gc-467	151	18	)	)	PUNCT
gc-467	151	19	hfi	hfi	NOUN
gc-467	151	20	map	map	NOUN
gc-467	151	21	of	of	ADP
gc-467	151	22	distributary	distributary	ADJ
gc-467	151	23	mouth	mouth	NOUN
gc-467	151	24	bars	bar	NOUN
gc-467	151	25	in	in	ADP
gc-467	151	26	the	the	DET
gc-467	151	27	szőreg-1	szőreg-1	NUM
gc-467	151	28	reservoir	reservoir	NOUN
gc-467	151	29	,	,	PUNCT
gc-467	151	30	c	c	X
gc-467	151	31	)	)	PUNCT
gc-467	151	32	hk	hk	PROPN
gc-467	151	33	map	map	NOUN
gc-467	151	34	of	of	ADP
gc-467	151	35	distributary	distributary	ADJ
gc-467	151	36	mouth	mouth	NOUN
gc-467	151	37	bars	bar	NOUN
gc-467	151	38	in	in	ADP
gc-467	151	39	the	the	DET
gc-467	151	40	szőreg-1	szőreg-1	NUM
gc-467	151	41	reservoir	reservoir	NOUN
gc-467	151	42	.	.	PUNCT
gc-467	152	1	a	a	DET
gc-467	152	2	)	)	PUNCT
gc-467	152	3	b	b	NOUN
gc-467	152	4	)	)	PUNCT
gc-467	152	5	a	a	PRON
gc-467	152	6	)	)	PUNCT
gc-467	152	7	b	b	NOUN
gc-467	152	8	)	)	PUNCT
gc-467	152	9	c	c	NOUN
gc-467	152	10	)	)	PUNCT
gc-467	152	11	geologia	geologia	NOUN
gc-467	152	12	croatica	croatica	PROPN
gc-467	152	13	64/3geologia	64/3geologia	PROPN
gc-467	152	14	croatica	croatica	PROPN
gc-467	152	15	256	256	NUM
gc-467	152	16	in	in	ADP
gc-467	152	17	the	the	DET
gc-467	152	18	second	second	ADJ
gc-467	152	19	run	run	NOUN
gc-467	152	20	,	,	PUNCT
gc-467	152	21	we	we	PRON
gc-467	152	22	have	have	AUX
gc-467	152	23	involved	involve	VERB
gc-467	152	24	each	each	PRON
gc-467	152	25	of	of	ADP
gc-467	152	26	the	the	DET
gc-467	152	27	available	available	ADJ
gc-467	152	28	7500	7500	NUM
gc-467	152	29	grid	grid	NOUN
gc-467	152	30	points	point	NOUN
gc-467	152	31	of	of	ADP
gc-467	152	32	the	the	DET
gc-467	152	33	‘	'	PUNCT
gc-467	152	34	basic	basic	ADJ
gc-467	152	35	’	'	PUNCT
gc-467	152	36	grid	grid	NOUN
gc-467	152	37	system	system	NOUN
gc-467	152	38	(	(	PUNCT
gc-467	152	39	with	with	ADP
gc-467	152	40	100x100	100x100	PROPN
gc-467	152	41	m	m	NOUN
gc-467	152	42	resolution	resolution	NOUN
gc-467	152	43	,	,	PUNCT
gc-467	152	44	derived	derive	VERB
gc-467	152	45	from	from	ADP
gc-467	152	46	well	well	ADV
gc-467	152	47	506	506	NUM
gc-467	152	48	,	,	PUNCT
gc-467	152	49	fig	fig	NOUN
gc-467	152	50	.	.	PUNCT
gc-467	153	1	5	5	NUM
gc-467	153	2	)	)	PUNCT
gc-467	153	3	.	.	PUNCT
gc-467	154	1	in	in	ADP
gc-467	154	2	addition	addition	NOUN
gc-467	154	3	to	to	ADP
gc-467	154	4	recognizing	recognize	VERB
gc-467	154	5	the	the	DET
gc-467	154	6	patterns	pattern	NOUN
gc-467	154	7	again	again	ADV
gc-467	154	8	,	,	PUNCT
gc-467	154	9	the	the	DET
gc-467	154	10	goal	goal	NOUN
gc-467	154	11	was	be	AUX
gc-467	154	12	also	also	ADV
gc-467	154	13	to	to	PART
gc-467	154	14	identify	identify	VERB
gc-467	154	15	the	the	DET
gc-467	154	16	contours	contours	NOUN
gc-467	154	17	of	of	ADP
gc-467	154	18	the	the	DET
gc-467	154	19	distributary	distributary	ADJ
gc-467	154	20	bars	bar	NOUN
gc-467	154	21	.	.	PUNCT
gc-467	155	1	in	in	ADP
gc-467	155	2	this	this	DET
gc-467	155	3	case	case	NOUN
gc-467	155	4	,	,	PUNCT
gc-467	155	5	the	the	DET
gc-467	155	6	number	number	NOUN
gc-467	155	7	of	of	ADP
gc-467	155	8	clusters	cluster	NOUN
gc-467	155	9	was	be	AUX
gc-467	155	10	tuned	tune	VERB
gc-467	155	11	in	in	ADP
gc-467	155	12	4	4	NUM
gc-467	155	13	and	and	CCONJ
gc-467	155	14	6	6	NUM
gc-467	155	15	,	,	PUNCT
gc-467	155	16	because	because	SCONJ
gc-467	155	17	we	we	PRON
gc-467	155	18	assumed	assume	VERB
gc-467	155	19	at	at	ADP
gc-467	155	20	least	least	ADV
gc-467	155	21	one	one	NUM
gc-467	155	22	,	,	PUNCT
gc-467	155	23	but	but	CCONJ
gc-467	155	24	possibly	possibly	ADV
gc-467	155	25	two	two	NUM
gc-467	155	26	additional	additional	ADJ
gc-467	155	27	groups	group	NOUN
gc-467	155	28	compared	compare	VERB
gc-467	155	29	to	to	ADP
gc-467	155	30	the	the	DET
gc-467	155	31	fi	fi	NOUN
gc-467	155	32	rst	rst	NOUN
gc-467	155	33	run	run	NOUN
gc-467	155	34	.	.	PUNCT
gc-467	156	1	figures	figure	NOUN
gc-467	156	2	9	9	NUM
gc-467	156	3	a	a	PRON
gc-467	156	4	,	,	PUNCT
gc-467	156	5	b	b	PROPN
gc-467	156	6	represents	represent	VERB
gc-467	156	7	the	the	DET
gc-467	156	8	mapped	map	VERB
gc-467	156	9	result	result	NOUN
gc-467	156	10	of	of	ADP
gc-467	156	11	the	the	DET
gc-467	156	12	second	second	ADJ
gc-467	156	13	run	run	NOUN
gc-467	156	14	of	of	ADP
gc-467	156	15	som	som	NOUN
gc-467	156	16	.	.	PUNCT
gc-467	157	1	it	it	PRON
gc-467	157	2	expresses	express	VERB
gc-467	157	3	again	again	ADV
gc-467	157	4	,	,	PUNCT
gc-467	157	5	that	that	SCONJ
gc-467	157	6	the	the	DET
gc-467	157	7	boundary	boundary	NOUN
gc-467	157	8	of	of	ADP
gc-467	157	9	this	this	DET
gc-467	157	10	depositional	depositional	ADJ
gc-467	157	11	environment	environment	NOUN
gc-467	157	12	can	can	AUX
gc-467	157	13	also	also	ADV
gc-467	157	14	affect	affect	VERB
gc-467	157	15	the	the	DET
gc-467	157	16	spatial	spatial	ADJ
gc-467	157	17	arrangement	arrangement	NOUN
gc-467	157	18	of	of	ADP
gc-467	157	19	reservoir	reservoir	NOUN
gc-467	157	20	properties	property	NOUN
gc-467	157	21	.	.	PUNCT
gc-467	158	1	however	however	ADV
gc-467	158	2	,	,	PUNCT
gc-467	158	3	if	if	SCONJ
gc-467	158	4	we	we	PRON
gc-467	158	5	compare	compare	VERB
gc-467	158	6	the	the	DET
gc-467	158	7	mapped	map	VERB
gc-467	158	8	clusters	cluster	NOUN
gc-467	158	9	to	to	ADP
gc-467	158	10	the	the	DET
gc-467	158	11	original	original	ADJ
gc-467	158	12	contours	contours	NOUN
gc-467	158	13	of	of	ADP
gc-467	158	14	the	the	DET
gc-467	158	15	distributary	distributary	ADJ
gc-467	158	16	mouth	mouth	NOUN
gc-467	158	17	bars	bar	NOUN
gc-467	158	18	,	,	PUNCT
gc-467	158	19	figure	figure	NOUN
gc-467	158	20	10	10	NUM
gc-467	158	21	shows	show	VERB
gc-467	158	22	the	the	DET
gc-467	158	23	similarities	similarity	NOUN
gc-467	158	24	and	and	CCONJ
gc-467	158	25	differences	difference	NOUN
gc-467	158	26	.	.	PUNCT
gc-467	159	1	it	it	PRON
gc-467	159	2	can	can	AUX
gc-467	159	3	be	be	AUX
gc-467	159	4	seen	see	VERB
gc-467	159	5	that	that	SCONJ
gc-467	159	6	joint	joint	ADJ
gc-467	159	7	use	use	NOUN
gc-467	159	8	of	of	ADP
gc-467	159	9	three	three	NUM
gc-467	159	10	variables	variable	NOUN
gc-467	159	11	in	in	ADP
gc-467	159	12	the	the	DET
gc-467	159	13	som	som	NOUN
gc-467	159	14	method	method	NOUN
gc-467	159	15	produces	produce	VERB
gc-467	159	16	a	a	DET
gc-467	159	17	similar	similar	ADJ
gc-467	159	18	pattern	pattern	NOUN
gc-467	159	19	within	within	ADP
gc-467	159	20	the	the	DET
gc-467	159	21	distributary	distributary	ADJ
gc-467	159	22	mouth	mouth	NOUN
gc-467	159	23	bars	bar	NOUN
gc-467	159	24	as	as	ADP
gc-467	159	25	using	use	VERB
gc-467	159	26	one	one	NUM
gc-467	159	27	variable	variable	NOUN
gc-467	159	28	(	(	PUNCT
gc-467	159	29	i.e.	i.e.	X
gc-467	159	30	sand	sand	NOUN
gc-467	159	31	content	content	NOUN
gc-467	159	32	)	)	PUNCT
gc-467	159	33	,	,	PUNCT
gc-467	159	34	but	but	CCONJ
gc-467	159	35	the	the	DET
gc-467	159	36	contours	contours	NOUN
gc-467	159	37	of	of	ADP
gc-467	159	38	the	the	DET
gc-467	159	39	shapes	shape	NOUN
gc-467	159	40	are	be	AUX
gc-467	159	41	different	different	ADJ
gc-467	159	42	.	.	PUNCT
gc-467	160	1	so	so	ADV
gc-467	160	2	,	,	PUNCT
gc-467	160	3	the	the	DET
gc-467	160	4	mapped	map	VERB
gc-467	160	5	results	result	NOUN
gc-467	160	6	show	show	VERB
gc-467	160	7	the	the	DET
gc-467	160	8	clusters	cluster	NOUN
gc-467	160	9	which	which	PRON
gc-467	160	10	contain	contain	VERB
gc-467	160	11	the	the	DET
gc-467	160	12	points	point	NOUN
gc-467	160	13	with	with	ADP
gc-467	160	14	similar	similar	ADJ
gc-467	160	15	properties	property	NOUN
gc-467	160	16	in	in	ADP
gc-467	160	17	the	the	DET
gc-467	160	18	present	present	ADJ
gc-467	160	19	stage	stage	NOUN
gc-467	160	20	of	of	ADP
gc-467	160	21	diagenesis	diagenesis	NOUN
gc-467	160	22	.	.	PUNCT
gc-467	161	1	in	in	ADP
gc-467	161	2	both	both	DET
gc-467	161	3	cases	case	NOUN
gc-467	161	4	,	,	PUNCT
gc-467	161	5	the	the	DET
gc-467	161	6	run	run	ADJ
gc-467	161	7	time	time	NOUN
gc-467	161	8	of	of	ADP
gc-467	161	9	the	the	DET
gc-467	161	10	training	training	NOUN
gc-467	161	11	algorithm	algorithm	NOUN
gc-467	161	12	depends	depend	VERB
gc-467	161	13	primarily	primarily	ADV
gc-467	161	14	on	on	ADP
gc-467	161	15	the	the	DET
gc-467	161	16	size	size	NOUN
gc-467	161	17	of	of	ADP
gc-467	161	18	the	the	DET
gc-467	161	19	network	network	NOUN
gc-467	161	20	and	and	CCONJ
gc-467	161	21	only	only	ADV
gc-467	161	22	secondarily	secondarily	ADV
gc-467	161	23	on	on	ADP
gc-467	161	24	the	the	DET
gc-467	161	25	number	number	NOUN
gc-467	161	26	of	of	ADP
gc-467	161	27	training	training	NOUN
gc-467	161	28	steps	step	NOUN
gc-467	161	29	.	.	PUNCT
gc-467	162	1	the	the	DET
gc-467	162	2	presented	present	VERB
gc-467	162	3	mapped	map	VERB
gc-467	162	4	results	result	NOUN
gc-467	162	5	(	(	PUNCT
gc-467	162	6	figs	fig	NOUN
gc-467	162	7	.	.	PUNCT
gc-467	162	8	8,9	8,9	NUM
gc-467	162	9	)	)	PUNCT
gc-467	162	10	are	be	AUX
gc-467	162	11	composed	compose	VERB
gc-467	162	12	by	by	ADP
gc-467	162	13	setting	set	VERB
gc-467	162	14	1000	1000	NUM
gc-467	162	15	learning	learning	NOUN
gc-467	162	16	steps	step	NOUN
gc-467	162	17	in	in	ADP
gc-467	162	18	the	the	DET
gc-467	162	19	som	som	NOUN
gc-467	162	20	process	process	NOUN
gc-467	162	21	.	.	PUNCT
gc-467	163	1	for	for	ADP
gc-467	163	2	this	this	DET
gc-467	163	3	setting	setting	NOUN
gc-467	163	4	,	,	PUNCT
gc-467	163	5	(	(	PUNCT
gc-467	163	6	above	above	ADP
gc-467	163	7	mentioned	mention	VERB
gc-467	163	8	numbers	number	NOUN
gc-467	163	9	of	of	ADP
gc-467	163	10	clusters	cluster	NOUN
gc-467	163	11	and	and	CCONJ
gc-467	163	12	number	number	NOUN
gc-467	163	13	of	of	ADP
gc-467	163	14	learning	learn	VERB
gc-467	163	15	steps	step	NOUN
gc-467	163	16	)	)	PUNCT
gc-467	163	17	the	the	DET
gc-467	163	18	run	run	NOUN
gc-467	163	19	of	of	ADP
gc-467	163	20	som	som	NOUN
gc-467	163	21	gives	give	VERB
gc-467	163	22	similar	similar	ADJ
gc-467	163	23	values	value	NOUN
gc-467	163	24	for	for	ADP
gc-467	163	25	the	the	DET
gc-467	163	26	error	error	NOUN
gc-467	163	27	rates	rate	NOUN
gc-467	163	28	.	.	PUNCT
gc-467	164	1	table	table	NOUN
gc-467	164	2	1	1	NUM
gc-467	164	3	shows	show	VERB
gc-467	164	4	the	the	DET
gc-467	164	5	rate	rate	NOUN
gc-467	164	6	of	of	ADP
gc-467	164	7	errors	error	NOUN
gc-467	164	8	for	for	ADP
gc-467	164	9	each	each	DET
gc-467	164	10	set	set	NOUN
gc-467	164	11	.	.	PUNCT
gc-467	165	1	figure	figure	VERB
gc-467	165	2	9	9	NUM
gc-467	165	3	:	:	PUNCT
gc-467	165	4	a	a	DET
gc-467	165	5	)	)	PUNCT
gc-467	165	6	mapped	mapped	ADJ
gc-467	165	7	result	result	NOUN
gc-467	165	8	for	for	ADP
gc-467	165	9	4	4	NUM
gc-467	165	10	clusters	cluster	NOUN
gc-467	165	11	,	,	PUNCT
gc-467	165	12	where	where	SCONJ
gc-467	165	13	clusters	cluster	NOUN
gc-467	165	14	contain	contain	VERB
gc-467	165	15	points	point	NOUN
gc-467	165	16	with	with	ADP
gc-467	165	17	similar	similar	ADJ
gc-467	165	18	properties	property	NOUN
gc-467	165	19	in	in	ADP
gc-467	165	20	the	the	DET
gc-467	165	21	present	present	ADJ
gc-467	165	22	stage	stage	NOUN
gc-467	165	23	of	of	ADP
gc-467	165	24	diagenesis	diagenesis	NOUN
gc-467	165	25	,	,	PUNCT
gc-467	165	26	b	b	X
gc-467	165	27	)	)	PUNCT
gc-467	165	28	mapped	map	VERB
gc-467	165	29	result	result	NOUN
gc-467	165	30	for	for	ADP
gc-467	165	31	6	6	NUM
gc-467	165	32	clusters	cluster	NOUN
gc-467	165	33	,	,	PUNCT
gc-467	165	34	where	where	SCONJ
gc-467	165	35	clusters	cluster	NOUN
gc-467	165	36	contain	contain	VERB
gc-467	165	37	points	point	NOUN
gc-467	165	38	with	with	ADP
gc-467	165	39	similar	similar	ADJ
gc-467	165	40	properties	property	NOUN
gc-467	165	41	in	in	ADP
gc-467	165	42	the	the	DET
gc-467	165	43	present	present	ADJ
gc-467	165	44	stage	stage	NOUN
gc-467	165	45	of	of	ADP
gc-467	165	46	diagenesis	diagenesis	NOUN
gc-467	165	47	.	.	PUNCT
gc-467	166	1	figure	figure	NOUN
gc-467	166	2	8	8	NUM
gc-467	166	3	:	:	PUNCT
gc-467	166	4	mapped	map	VERB
gc-467	166	5	result	result	NOUN
gc-467	166	6	for	for	ADP
gc-467	166	7	3	3	NUM
gc-467	166	8	clusters	cluster	NOUN
gc-467	166	9	,	,	PUNCT
gc-467	166	10	where	where	SCONJ
gc-467	166	11	clusters	cluster	NOUN
gc-467	166	12	contain	contain	VERB
gc-467	166	13	points	point	NOUN
gc-467	166	14	with	with	ADP
gc-467	166	15	similar	similar	ADJ
gc-467	166	16	properties	property	NOUN
gc-467	166	17	in	in	ADP
gc-467	166	18	the	the	DET
gc-467	166	19	present	present	ADJ
gc-467	166	20	stage	stage	NOUN
gc-467	166	21	of	of	ADP
gc-467	166	22	diagenesis	diagenesis	NOUN
gc-467	166	23	,	,	PUNCT
gc-467	166	24	b	b	X
gc-467	166	25	)	)	PUNCT
gc-467	166	26	mapped	map	VERB
gc-467	166	27	result	result	NOUN
gc-467	166	28	for	for	ADP
gc-467	166	29	4	4	NUM
gc-467	166	30	clusters	cluster	NOUN
gc-467	166	31	,	,	PUNCT
gc-467	166	32	where	where	SCONJ
gc-467	166	33	clusters	cluster	NOUN
gc-467	166	34	contain	contain	VERB
gc-467	166	35	points	point	NOUN
gc-467	166	36	with	with	ADP
gc-467	166	37	similar	similar	ADJ
gc-467	166	38	properties	property	NOUN
gc-467	166	39	in	in	ADP
gc-467	166	40	the	the	DET
gc-467	166	41	present	present	ADJ
gc-467	166	42	stage	stage	NOUN
gc-467	166	43	of	of	ADP
gc-467	166	44	diagenesis	diagenesis	NOUN
gc-467	166	45	.	.	PUNCT
gc-467	167	1	a	a	DET
gc-467	167	2	)	)	PUNCT
gc-467	167	3	b	b	NOUN
gc-467	167	4	)	)	PUNCT
gc-467	167	5	a	a	PRON
gc-467	167	6	)	)	PUNCT
gc-467	167	7	b	b	NOUN
gc-467	167	8	)	)	PUNCT
gc-467	167	9	a	a	DET
gc-467	167	10	)	)	PUNCT
gc-467	167	11	b	b	NOUN
gc-467	167	12	)	)	PUNCT
gc-467	167	13	janina	janina	PROPN
gc-467	167	14	horváth	horváth	PROPN
gc-467	167	15	:	:	PUNCT
gc-467	167	16	defi	defi	PROPN
gc-467	167	17	ning	ning	ADJ
gc-467	167	18	depositional	depositional	ADJ
gc-467	167	19	environments	environment	NOUN
gc-467	167	20	by	by	ADP
gc-467	167	21	using	use	VERB
gc-467	167	22	neural	neural	ADJ
gc-467	167	23	networks	network	NOUN
gc-467	167	24	geologia	geologia	VERB
gc-467	167	25	croatica	croatica	PROPN
gc-467	167	26	257	257	NUM
gc-467	167	27	besides	besides	SCONJ
gc-467	167	28	the	the	DET
gc-467	167	29	error	error	NOUN
gc-467	167	30	rates	rate	NOUN
gc-467	167	31	of	of	ADP
gc-467	167	32	sets	set	NOUN
gc-467	167	33	,	,	PUNCT
gc-467	167	34	we	we	PRON
gc-467	167	35	can	can	AUX
gc-467	167	36	determine	determine	VERB
gc-467	167	37	the	the	DET
gc-467	167	38	goodness	goodness	NOUN
gc-467	167	39	of	of	ADP
gc-467	167	40	clustering	clustering	NOUN
gc-467	167	41	of	of	ADP
gc-467	167	42	som	som	NOUN
gc-467	167	43	.	.	PUNCT
gc-467	168	1	discriminant	discriminant	ADJ
gc-467	168	2	analysis	analysis	NOUN
gc-467	168	3	can	can	AUX
gc-467	168	4	show	show	VERB
gc-467	168	5	how	how	SCONJ
gc-467	168	6	well	well	ADV
gc-467	168	7	the	the	DET
gc-467	168	8	group	group	NOUN
gc-467	168	9	a	a	DET
gc-467	168	10	particular	particular	ADJ
gc-467	168	11	case	case	NOUN
gc-467	168	12	belongs	belong	VERB
gc-467	168	13	to	to	PART
gc-467	168	14	can	can	AUX
gc-467	168	15	be	be	AUX
gc-467	168	16	predicted	predict	VERB
gc-467	168	17	(	(	PUNCT
gc-467	168	18	see	see	VERB
gc-467	168	19	table	table	NOUN
gc-467	168	20	2	2	NUM
gc-467	168	21	a	a	NOUN
gc-467	168	22	-	-	PUNCT
gc-467	168	23	d	d	NOUN
gc-467	168	24	)	)	PUNCT
gc-467	168	25	.	.	PUNCT
gc-467	169	1	since	since	SCONJ
gc-467	169	2	the	the	DET
gc-467	169	3	size	size	NOUN
gc-467	169	4	of	of	ADP
gc-467	169	5	each	each	DET
gc-467	169	6	cluster	cluster	NOUN
gc-467	169	7	is	be	AUX
gc-467	169	8	not	not	PART
gc-467	169	9	the	the	DET
gc-467	169	10	same	same	ADJ
gc-467	169	11	(	(	PUNCT
gc-467	169	12	the	the	DET
gc-467	169	13	clusters	cluster	NOUN
gc-467	169	14	contain	contain	VERB
gc-467	169	15	different	different	ADJ
gc-467	169	16	amounts	amount	NOUN
gc-467	169	17	of	of	ADP
gc-467	169	18	points	point	NOUN
gc-467	169	19	)	)	PUNCT
gc-467	169	20	,	,	PUNCT
gc-467	169	21	the	the	DET
gc-467	169	22	priori	priori	ADJ
gc-467	169	23	probabilities	probability	NOUN
gc-467	169	24	(	(	PUNCT
gc-467	169	25	p	p	NOUN
gc-467	169	26	)	)	PUNCT
gc-467	169	27	are	be	AUX
gc-467	169	28	not	not	PART
gc-467	169	29	equal	equal	ADJ
gc-467	169	30	to	to	ADP
gc-467	169	31	1/3	1/3	NUM
gc-467	169	32	for	for	ADP
gc-467	169	33	each	each	DET
gc-467	169	34	subset	subset	NOUN
gc-467	169	35	.	.	PUNCT
gc-467	170	1	the	the	DET
gc-467	170	2	fi	fi	NOUN
gc-467	170	3	rst	rst	ADJ
gc-467	170	4	column	column	NOUN
gc-467	170	5	of	of	ADP
gc-467	170	6	the	the	DET
gc-467	170	7	spreadsheet	spreadsheet	NOUN
gc-467	170	8	indicates	indicate	VERB
gc-467	170	9	the	the	DET
gc-467	170	10	percentage	percentage	NOUN
gc-467	170	11	of	of	ADP
gc-467	170	12	cases	case	NOUN
gc-467	170	13	that	that	PRON
gc-467	170	14	are	be	AUX
gc-467	170	15	correctly	correctly	ADV
gc-467	170	16	classifi	classifi	ADJ
gc-467	170	17	ed	ed	NOUN
gc-467	170	18	in	in	ADP
gc-467	170	19	each	each	DET
gc-467	170	20	cluster	cluster	NOUN
gc-467	170	21	.	.	PUNCT
gc-467	171	1	other	other	ADJ
gc-467	171	2	columns	column	NOUN
gc-467	171	3	show	show	VERB
gc-467	171	4	the	the	DET
gc-467	171	5	number	number	NOUN
gc-467	171	6	of	of	ADP
gc-467	171	7	misclassifi	misclassifi	PROPN
gc-467	171	8	cations	cation	NOUN
gc-467	171	9	.	.	PUNCT
gc-467	172	1	according	accord	VERB
gc-467	172	2	to	to	ADP
gc-467	172	3	discriminant	discriminant	ADJ
gc-467	172	4	analysis	analysis	NOUN
gc-467	172	5	,	,	PUNCT
gc-467	172	6	the	the	DET
gc-467	172	7	results	result	NOUN
gc-467	172	8	of	of	ADP
gc-467	172	9	som	som	NOUN
gc-467	172	10	are	be	AUX
gc-467	172	11	95	95	NUM
gc-467	172	12	%	%	NOUN
gc-467	172	13	adequate	adequate	ADJ
gc-467	172	14	on	on	ADP
gc-467	172	15	average	average	ADJ
gc-467	172	16	.	.	PUNCT
gc-467	173	1	figure	figure	NOUN
gc-467	173	2	10	10	NUM
gc-467	173	3	:	:	PUNCT
gc-467	173	4	mapped	map	VERB
gc-467	173	5	result	result	NOUN
gc-467	173	6	for	for	ADP
gc-467	173	7	6	6	NUM
gc-467	173	8	clusters	cluster	NOUN
gc-467	173	9	with	with	ADP
gc-467	173	10	the	the	DET
gc-467	173	11	original	original	ADJ
gc-467	173	12	geometry	geometry	NOUN
gc-467	173	13	of	of	ADP
gc-467	173	14	distributary	distributary	ADJ
gc-467	173	15	mouth	mouth	NOUN
gc-467	173	16	bars	bar	NOUN
gc-467	173	17	by	by	ADP
gc-467	173	18	sand	sand	NOUN
gc-467	173	19	content	content	NOUN
gc-467	173	20	,	,	PUNCT
gc-467	173	21	(	(	PUNCT
gc-467	173	22	where	where	SCONJ
gc-467	173	23	clusters	cluster	NOUN
gc-467	173	24	contain	contain	VERB
gc-467	173	25	points	point	NOUN
gc-467	173	26	with	with	ADP
gc-467	173	27	similar	similar	ADJ
gc-467	173	28	properties	property	NOUN
gc-467	173	29	in	in	ADP
gc-467	173	30	the	the	DET
gc-467	173	31	present	present	ADJ
gc-467	173	32	stage	stage	NOUN
gc-467	173	33	of	of	ADP
gc-467	173	34	diagenesis	diagenesis	NOUN
gc-467	173	35	)	)	PUNCT
gc-467	173	36	.	.	PUNCT
gc-467	174	1	table	table	NOUN
gc-467	174	2	1	1	NUM
gc-467	174	3	:	:	PUNCT
gc-467	174	4	error	error	NOUN
gc-467	174	5	rates	rate	NOUN
gc-467	174	6	of	of	ADP
gc-467	174	7	running	run	VERB
gc-467	174	8	sets	set	NOUN
gc-467	174	9	in	in	ADP
gc-467	174	10	case	case	NOUN
gc-467	174	11	of	of	ADP
gc-467	174	12	running	run	VERB
gc-467	174	13	a	a	DET
gc-467	174	14	-	-	PUNCT
gc-467	174	15	b	b	NOUN
gc-467	174	16	-	-	PUNCT
gc-467	174	17	c	c	NOUN
gc-467	174	18	-	-	PUNCT
gc-467	174	19	d.	d.	NOUN
gc-467	174	20	errors	error	NOUN
gc-467	174	21	rate	rate	NOUN
gc-467	174	22	of	of	ADP
gc-467	174	23	sets	set	NOUN
gc-467	174	24	case	case	NOUN
gc-467	174	25	a	a	DET
gc-467	174	26	)	)	PUNCT
gc-467	174	27	case	case	NOUN
gc-467	174	28	b	b	NOUN
gc-467	174	29	)	)	PUNCT
gc-467	174	30	case	case	NOUN
gc-467	174	31	c	c	NOUN
gc-467	174	32	)	)	PUNCT
gc-467	174	33	case	case	NOUN
gc-467	174	34	d	d	X
gc-467	174	35	)	)	PUNCT
gc-467	174	36	training	training	NOUN
gc-467	174	37	set	set	VERB
gc-467	174	38	0.02786	0.02786	NUM
gc-467	175	1	0.028644	0.028644	NUM
gc-467	175	2	0.01515	0.01515	NUM
gc-467	175	3	0.01515	0.01515	NUM
gc-467	175	4	test	test	NOUN
gc-467	175	5	set	set	VERB
gc-467	175	6	0.020765	0.020765	NUM
gc-467	175	7	0.028264	0.028264	NUM
gc-467	175	8	0.031158	0.031158	NUM
gc-467	175	9	0.031158	0.031158	NUM
gc-467	175	10	validation	validation	NOUN
gc-467	175	11	set	set	VERB
gc-467	175	12	0.019769	0.019769	NUM
gc-467	175	13	0.028178	0.028178	NUM
gc-467	175	14	0.0319757	0.0319757	NUM
gc-467	175	15	0.031957	0.031957	NUM
gc-467	175	16	table	table	NOUN
gc-467	175	17	2a	2a	NUM
gc-467	175	18	:	:	PUNCT
gc-467	175	19	classifi	classifi	PROPN
gc-467	175	20	cation	cation	NOUN
gc-467	175	21	matrix	matrix	NOUN
gc-467	175	22	(	(	PUNCT
gc-467	175	23	distributary	distributary	ADJ
gc-467	175	24	mouth	mouth	NOUN
gc-467	175	25	bars	bar	NOUN
gc-467	175	26	–	–	PUNCT
gc-467	175	27	4	4	NUM
gc-467	175	28	clusters	cluster	NOUN
gc-467	175	29	)	)	PUNCT
gc-467	175	30	c_i	c_i	PUNCT
gc-467	175	31	ith	ith	NOUN
gc-467	175	32	cluster	cluster	NOUN
gc-467	175	33	percent	percent	NOUN
gc-467	175	34	corrects	correct	VERB
gc-467	175	35	c_1	c_1	PROPN
gc-467	175	36	p=0.16789	p=0.16789	VERB
gc-467	175	37	c_2	c_2	NOUN
gc-467	175	38	p=0.39853	p=0.39853	NOUN
gc-467	175	39	c_3	c_3	PROPN
gc-467	175	40	p=0.18582	p=0.18582	PROPN
gc-467	175	41	c_4	c_4	PROPN
gc-467	175	42	p=0.24830	p=0.24830	PROPN
gc-467	175	43	c_1	c_1	PROPN
gc-467	175	44	88.02589	88.02589	NUM
gc-467	175	45	544	544	NUM
gc-467	175	46	56	56	NUM
gc-467	175	47	0	0	NUM
gc-467	175	48	18	18	NUM
gc-467	175	49	c_2	c_2	NOUN
gc-467	175	50	99.38651	99.38651	NUM
gc-467	175	51	0	0	NUM
gc-467	175	52	1458	1458	NUM
gc-467	175	53	9	9	NUM
gc-467	175	54	0	0	NUM
gc-467	175	55	c_3	c_3	VERB
gc-467	175	56	84.31085	84.31085	NUM
gc-467	175	57	0	0	NUM
gc-467	175	58	107	107	NUM
gc-467	175	59	575	575	NUM
gc-467	175	60	0	0	NUM
gc-467	176	1	c_4	c_4	NOUN
gc-467	176	2	92.88840	92.88840	NUM
gc-467	176	3	42	42	NUM
gc-467	176	4	23	23	NUM
gc-467	176	5	0	0	NUM
gc-467	176	6	849	849	NUM
gc-467	176	7	total	total	NOUN
gc-467	176	8	93.07253	93.07253	NUM
gc-467	176	9	586	586	NUM
gc-467	176	10	1644	1644	NUM
gc-467	176	11	584	584	NUM
gc-467	176	12	867	867	NUM
gc-467	176	13	table	table	NOUN
gc-467	176	14	2b	2b	NOUN
gc-467	176	15	:	:	PUNCT
gc-467	176	16	classifi	classifi	PROPN
gc-467	176	17	cation	cation	NOUN
gc-467	176	18	matrix	matrix	NOUN
gc-467	176	19	(	(	PUNCT
gc-467	176	20	distributary	distributary	ADJ
gc-467	176	21	mouth	mouth	NOUN
gc-467	176	22	bars	bar	NOUN
gc-467	176	23	–	–	PUNCT
gc-467	176	24	3	3	NUM
gc-467	176	25	clusters	cluster	NOUN
gc-467	176	26	)	)	PUNCT
gc-467	176	27	c_i	c_i	PUNCT
gc-467	177	1	ith	ith	NOUN
gc-467	177	2	cluster	cluster	NOUN
gc-467	177	3	percent	percent	NOUN
gc-467	177	4	correct	correct	ADJ
gc-467	177	5	c_1	c_1	PROPN
gc-467	177	6	p=0.45314	p=0.45314	PROPN
gc-467	177	7	c_2	c_2	PROPN
gc-467	177	8	p=0.31459	p=0.31459	PROPN
gc-467	177	9	c_3	c_3	VERB
gc-467	177	10	p=0.23227	p=0.23227	PROPN
gc-467	177	11	c_1	c_1	PROPN
gc-467	177	12	98.32134	98.32134	NUM
gc-467	177	13	1640	1640	NUM
gc-467	177	14	28	28	NUM
gc-467	177	15	0	0	NUM
gc-467	177	16	c_2	c_2	VERB
gc-467	177	17	96.80483	96.80483	NUM
gc-467	177	18	30	30	NUM
gc-467	177	19	1121	1121	NUM
gc-467	177	20	7	7	NUM
gc-467	177	21	c_3	c_3	NOUN
gc-467	177	22	96.49123	96.49123	NUM
gc-467	177	23	0	0	NUM
gc-467	177	24	30	30	NUM
gc-467	177	25	825	825	NUM
gc-467	177	26	total	total	NOUN
gc-467	177	27	97.41918	97.41918	NUM
gc-467	177	28	1670	1670	NUM
gc-467	177	29	1179	1179	NUM
gc-467	177	30	832	832	NUM
gc-467	177	31	table	table	NOUN
gc-467	177	32	2c	2c	NOUN
gc-467	177	33	:	:	PUNCT
gc-467	177	34	classifi	classifi	PROPN
gc-467	177	35	cation	cation	NOUN
gc-467	177	36	matrix	matrix	NOUN
gc-467	177	37	(	(	PUNCT
gc-467	177	38	entire	entire	ADJ
gc-467	177	39	dataset	dataset	NOUN
gc-467	177	40	–	–	PUNCT
gc-467	177	41	6	6	NUM
gc-467	177	42	clusters	cluster	NOUN
gc-467	177	43	)	)	PUNCT
gc-467	177	44	c_i	c_i	PUNCT
gc-467	177	45	ith	ith	NOUN
gc-467	177	46	cluster	cluster	NOUN
gc-467	177	47	percent	percent	NOUN
gc-467	177	48	corrects	correct	NOUN
gc-467	177	49	c_1	c_1	PROPN
gc-467	177	50	p=0.23560	p=0.23560	PROPN
gc-467	177	51	c_2	c_2	NOUN
gc-467	177	52	=	=	NOUN
gc-467	177	53	0.14747	0.14747	NUM
gc-467	177	54	c_3	c_3	VERB
gc-467	177	55	p=0.25400	p=0.25400	NOUN
gc-467	177	56	c_4	c_4	PROPN
gc-467	177	57	p=0.13680	p=0.13680	AUX
gc-467	177	58	c_5	c_5	PROPN
gc-467	177	59	p=0.11200	p=0.11200	PROPN
gc-467	177	60	c_6	c_6	VERB
gc-467	177	61	p=0.11413	p=0.11413	PROPN
gc-467	177	62	c_1	c_1	PROPN
gc-467	177	63	94.68025	94.68025	NUM
gc-467	177	64	1673	1673	NUM
gc-467	177	65	0	0	NUM
gc-467	177	66	72	72	NUM
gc-467	177	67	4	4	NUM
gc-467	177	68	18	18	NUM
gc-467	177	69	0	0	NUM
gc-467	177	70	c_2	c_2	NOUN
gc-467	177	71	99.18626	99.18626	NUM
gc-467	177	72	0	0	NUM
gc-467	177	73	1097	1097	NUM
gc-467	177	74	0	0	NUM
gc-467	177	75	9	9	NUM
gc-467	177	76	0	0	NUM
gc-467	177	77	0	0	NUM
gc-467	178	1	c_3	c_3	PROPN
gc-467	179	1	97.42782	97.42782	NUM
gc-467	180	1	43	43	NUM
gc-467	180	2	0	0	NUM
gc-467	180	3	1856	1856	NUM
gc-467	180	4	6	6	NUM
gc-467	180	5	0	0	SYM
gc-467	180	6	0	0	NUM
gc-467	180	7	c_4	c_4	NOUN
gc-467	180	8	94.15205	94.15205	NUM
gc-467	180	9	34	34	NUM
gc-467	180	10	0	0	NUM
gc-467	180	11	0	0	NUM
gc-467	181	1	966	966	NUM
gc-467	181	2	0	0	NUM
gc-467	181	3	26	26	NUM
gc-467	181	4	c_5	c_5	VERB
gc-467	181	5	88.33334	88.33334	NUM
gc-467	181	6	26	26	NUM
gc-467	181	7	0	0	NUM
gc-467	181	8	0	0	NUM
gc-467	181	9	15	15	NUM
gc-467	181	10	742	742	NUM
gc-467	181	11	57	57	NUM
gc-467	181	12	c_6	c_6	VERB
gc-467	181	13	92.87383	92.87383	NUM
gc-467	181	14	0	0	NUM
gc-467	181	15	18	18	NUM
gc-467	181	16	0	0	NUM
gc-467	181	17	0	0	NUM
gc-467	181	18	43	43	NUM
gc-467	181	19	795	795	NUM
gc-467	181	20	total	total	NOUN
gc-467	181	21	95.05334	95.05334	NUM
gc-467	181	22	1776	1776	NUM
gc-467	181	23	1115	1115	NUM
gc-467	181	24	1928	1928	NUM
gc-467	181	25	1000	1000	NUM
gc-467	181	26	803	803	NUM
gc-467	181	27	878	878	NUM
gc-467	181	28	table	table	NOUN
gc-467	181	29	2d	2d	NOUN
gc-467	181	30	:	:	PUNCT
gc-467	181	31	classifi	classifi	NOUN
gc-467	181	32	cation	cation	NOUN
gc-467	181	33	matrix	matrix	NOUN
gc-467	181	34	(	(	PUNCT
gc-467	181	35	entire	entire	ADJ
gc-467	181	36	dataset	dataset	NOUN
gc-467	181	37	–	–	PUNCT
gc-467	181	38	4	4	NUM
gc-467	181	39	clusters	cluster	NOUN
gc-467	181	40	)	)	PUNCT
gc-467	181	41	c_i	c_i	PUNCT
gc-467	181	42	ith	ith	NOUN
gc-467	181	43	cluster	cluster	NOUN
gc-467	181	44	percent	percent	NOUN
gc-467	181	45	correct	correct	ADJ
gc-467	181	46	c_1	c_1	PROPN
gc-467	181	47	p=0.35520	p=0.35520	PROPN
gc-467	181	48	c_2	c_2	PROPN
gc-467	181	49	p=0.15800	p=0.15800	PROPN
gc-467	181	50	c_3	c_3	VERB
gc-467	181	51	p=0.32853	p=0.32853	ADP
gc-467	181	52	c_4	c_4	NOUN
gc-467	181	53	p=0.15827	p=0.15827	PROPN
gc-467	181	54	c_1	c_1	PROPN
gc-467	181	55	94.68025	94.68025	NUM
gc-467	181	56	1673	1673	NUM
gc-467	181	57	0	0	NUM
gc-467	181	58	72	72	NUM
gc-467	181	59	4	4	NUM
gc-467	181	60	c_2	c_2	VERB
gc-467	181	61	99.18626	99.18626	NUM
gc-467	181	62	0	0	NUM
gc-467	181	63	1097	1097	NUM
gc-467	181	64	0	0	NUM
gc-467	181	65	9	9	NUM
gc-467	181	66	c_3	c_3	NOUN
gc-467	181	67	97.42782	97.42782	NUM
gc-467	182	1	43	43	NUM
gc-467	182	2	0	0	NUM
gc-467	182	3	1856	1856	NUM
gc-467	182	4	6	6	NUM
gc-467	182	5	c_4	c_4	NOUN
gc-467	182	6	94.15205	94.15205	NUM
gc-467	182	7	34	34	NUM
gc-467	182	8	0	0	NUM
gc-467	182	9	0	0	NUM
gc-467	182	10	966	966	NUM
gc-467	182	11	total	total	ADJ
gc-467	182	12	95.05334	95.05334	NUM
gc-467	182	13	1776	1776	NUM
gc-467	182	14	1115	1115	NUM
gc-467	182	15	1928	1928	NUM
gc-467	182	16	1000	1000	NUM
gc-467	182	17	geologia	geologia	PROPN
gc-467	182	18	croatica	croatica	PROPN
gc-467	182	19	64/3geologia	64/3geologia	PROPN
gc-467	182	20	croatica	croatica	PROPN
gc-467	182	21	258	258	NUM
gc-467	182	22	5	5	NUM
gc-467	182	23	.	.	PUNCT
gc-467	182	24	conclusions	conclusion	NOUN
gc-467	182	25	usually	usually	ADV
gc-467	182	26	kohonen	kohonen	PROPN
gc-467	182	27	’s	’s	PART
gc-467	182	28	network	network	NOUN
gc-467	182	29	is	be	AUX
gc-467	182	30	applied	apply	VERB
gc-467	182	31	to	to	PART
gc-467	182	32	solve	solve	VERB
gc-467	182	33	classical	classical	ADJ
gc-467	182	34	pattern	pattern	NOUN
gc-467	182	35	recognition	recognition	NOUN
gc-467	182	36	problems	problem	NOUN
gc-467	182	37	such	such	ADJ
gc-467	182	38	as	as	ADP
gc-467	182	39	the	the	DET
gc-467	182	40	recognition	recognition	NOUN
gc-467	182	41	of	of	ADP
gc-467	182	42	a	a	DET
gc-467	182	43	writing	writing	NOUN
gc-467	182	44	character	character	NOUN
gc-467	182	45	or	or	CCONJ
gc-467	182	46	pictures	picture	NOUN
gc-467	182	47	.	.	PUNCT
gc-467	183	1	frequently	frequently	ADV
gc-467	183	2	nonetheless	nonetheless	ADV
gc-467	183	3	,	,	PUNCT
gc-467	183	4	it	it	PRON
gc-467	183	5	can	can	AUX
gc-467	183	6	be	be	AUX
gc-467	183	7	applied	apply	VERB
gc-467	183	8	to	to	ADP
gc-467	183	9	identifying	identify	VERB
gc-467	183	10	a	a	DET
gc-467	183	11	pattern	pattern	NOUN
gc-467	183	12	as	as	ADP
gc-467	183	13	a	a	DET
gc-467	183	14	classifi	classifi	ADJ
gc-467	183	15	cation	cation	NOUN
gc-467	183	16	problem	problem	NOUN
gc-467	183	17	,	,	PUNCT
gc-467	183	18	since	since	SCONJ
gc-467	183	19	in	in	ADP
gc-467	183	20	the	the	DET
gc-467	183	21	background	background	NOUN
gc-467	183	22	of	of	ADP
gc-467	183	23	pattern	pattern	NOUN
gc-467	183	24	recognition	recognition	NOUN
gc-467	183	25	there	there	PRON
gc-467	183	26	are	be	VERB
gc-467	183	27	clustering	cluster	VERB
gc-467	183	28	problems	problem	NOUN
gc-467	183	29	.	.	PUNCT
gc-467	184	1	this	this	DET
gc-467	184	2	paper	paper	NOUN
gc-467	184	3	demonstrated	demonstrate	VERB
gc-467	184	4	the	the	DET
gc-467	184	5	approach	approach	NOUN
gc-467	184	6	of	of	ADP
gc-467	184	7	using	use	VERB
gc-467	184	8	an	an	DET
gc-467	184	9	unsupervised	unsupervised	ADJ
gc-467	184	10	neural	neural	ADJ
gc-467	184	11	network	network	NOUN
gc-467	184	12	to	to	PART
gc-467	184	13	distinguish	distinguish	VERB
gc-467	184	14	parts	part	NOUN
gc-467	184	15	of	of	ADP
gc-467	184	16	the	the	DET
gc-467	184	17	depositional	depositional	ADJ
gc-467	184	18	sub	sub	NOUN
gc-467	184	19	-	-	NOUN
gc-467	184	20	environment	environment	NOUN
gc-467	184	21	as	as	ADP
gc-467	184	22	clusters	cluster	NOUN
gc-467	184	23	which	which	PRON
gc-467	184	24	contain	contain	VERB
gc-467	184	25	points	point	NOUN
gc-467	184	26	with	with	ADP
gc-467	184	27	similar	similar	ADJ
gc-467	184	28	properties	property	NOUN
gc-467	184	29	in	in	ADP
gc-467	184	30	the	the	DET
gc-467	184	31	present	present	ADJ
gc-467	184	32	stage	stage	NOUN
gc-467	184	33	of	of	ADP
gc-467	184	34	diagenesis	diagenesis	NOUN
gc-467	184	35	.	.	PUNCT
gc-467	185	1	thus	thus	ADV
gc-467	185	2	the	the	DET
gc-467	185	3	som	som	NOUN
gc-467	185	4	is	be	AUX
gc-467	185	5	an	an	DET
gc-467	185	6	adequate	adequate	ADJ
gc-467	185	7	tool	tool	NOUN
gc-467	185	8	to	to	PART
gc-467	185	9	help	help	AUX
gc-467	185	10	identify	identify	VERB
gc-467	185	11	genetic	genetic	ADJ
gc-467	185	12	geological	geological	ADJ
gc-467	185	13	environments	environment	NOUN
gc-467	185	14	,	,	PUNCT
gc-467	185	15	sub	sub	NOUN
gc-467	185	16	-	-	ADJ
gc-467	185	17	environments	environment	NOUN
gc-467	185	18	supplemented	supplement	VERB
gc-467	185	19	with	with	ADP
gc-467	185	20	the	the	DET
gc-467	185	21	mapping	mapping	NOUN
gc-467	185	22	process	process	NOUN
gc-467	185	23	.	.	PUNCT
gc-467	186	1	the	the	DET
gc-467	186	2	fi	fi	NOUN
gc-467	186	3	rst	rst	NOUN
gc-467	186	4	test	test	NOUN
gc-467	186	5	using	use	VERB
gc-467	186	6	the	the	DET
gc-467	186	7	som	som	NOUN
gc-467	186	8	-	-	PUNCT
gc-467	186	9	method	method	NOUN
gc-467	186	10	refl	refl	NOUN
gc-467	186	11	ected	ecte	VERB
gc-467	186	12	considerably	considerably	ADV
gc-467	186	13	well	well	INTJ
gc-467	186	14	the	the	DET
gc-467	186	15	patterns	pattern	NOUN
gc-467	186	16	of	of	ADP
gc-467	186	17	the	the	DET
gc-467	186	18	distributary	distributary	ADJ
gc-467	186	19	mouth	mouth	NOUN
gc-467	186	20	bars	bar	NOUN
gc-467	186	21	using	use	VERB
gc-467	186	22	three	three	NUM
gc-467	186	23	variables	variable	NOUN
gc-467	186	24	(	(	PUNCT
gc-467	186	25	figs	fig	NOUN
gc-467	186	26	.	.	PUNCT
gc-467	187	1	7	7	NUM
gc-467	187	2	a	a	DET
gc-467	187	3	,	,	PUNCT
gc-467	187	4	b	b	NOUN
gc-467	187	5	)	)	PUNCT
gc-467	187	6	.	.	PUNCT
gc-467	188	1	in	in	ADP
gc-467	188	2	the	the	DET
gc-467	188	3	case	case	NOUN
gc-467	188	4	of	of	ADP
gc-467	188	5	the	the	DET
gc-467	188	6	second	second	ADJ
gc-467	188	7	run	run	NOUN
gc-467	188	8	of	of	ADP
gc-467	188	9	som	som	NOUN
gc-467	188	10	,	,	PUNCT
gc-467	188	11	the	the	DET
gc-467	188	12	mapped	map	VERB
gc-467	188	13	results	result	NOUN
gc-467	188	14	cluster	cluster	NOUN
gc-467	188	15	does	do	AUX
gc-467	188	16	not	not	PART
gc-467	188	17	show	show	VERB
gc-467	188	18	exactly	exactly	ADV
gc-467	188	19	the	the	DET
gc-467	188	20	same	same	ADJ
gc-467	188	21	boundaries	boundary	NOUN
gc-467	188	22	of	of	ADP
gc-467	188	23	the	the	DET
gc-467	188	24	distributary	distributary	ADJ
gc-467	188	25	mouth	mouth	NOUN
gc-467	188	26	bars	bar	NOUN
gc-467	188	27	,	,	PUNCT
gc-467	188	28	but	but	CCONJ
gc-467	188	29	a	a	DET
gc-467	188	30	similar	similar	ADJ
gc-467	188	31	pattern	pattern	NOUN
gc-467	188	32	within	within	ADP
gc-467	188	33	the	the	DET
gc-467	188	34	area	area	NOUN
gc-467	188	35	can	can	AUX
gc-467	188	36	be	be	AUX
gc-467	188	37	recognized	recognize	VERB
gc-467	188	38	.	.	PUNCT
gc-467	189	1	this	this	DET
gc-467	189	2	paper	paper	NOUN
gc-467	189	3	focused	focus	VERB
gc-467	189	4	on	on	ADP
gc-467	189	5	joint	joint	ADJ
gc-467	189	6	handling	handling	NOUN
gc-467	189	7	of	of	ADP
gc-467	189	8	more	more	ADJ
gc-467	189	9	property	property	NOUN
gc-467	189	10	to	to	PART
gc-467	189	11	characterize	characterize	VERB
gc-467	189	12	parts	part	NOUN
gc-467	189	13	of	of	ADP
gc-467	189	14	the	the	DET
gc-467	189	15	sub	sub	NOUN
gc-467	189	16	-	-	NOUN
gc-467	189	17	environment	environment	NOUN
gc-467	189	18	;	;	PUNCT
gc-467	189	19	and	and	CCONJ
gc-467	189	20	then	then	ADV
gc-467	189	21	mapping	map	VERB
gc-467	189	22	these	these	PRON
gc-467	189	23	as	as	ADP
gc-467	189	24	arranged	arrange	VERB
gc-467	189	25	points	point	NOUN
gc-467	189	26	in	in	ADP
gc-467	189	27	space	space	NOUN
gc-467	189	28	using	use	VERB
gc-467	189	29	some	some	DET
gc-467	189	30	defi	defi	NOUN
gc-467	189	31	ned	ned	NOUN
gc-467	189	32	rules	rule	NOUN
gc-467	189	33	for	for	ADP
gc-467	189	34	geometry	geometry	NOUN
gc-467	189	35	.	.	PUNCT
gc-467	190	1	in	in	ADP
gc-467	190	2	fact	fact	NOUN
gc-467	190	3	,	,	PUNCT
gc-467	190	4	the	the	DET
gc-467	190	5	neural	neural	ADJ
gc-467	190	6	network	network	NOUN
gc-467	190	7	answers	answer	NOUN
gc-467	190	8	do	do	AUX
gc-467	190	9	not	not	PART
gc-467	190	10	differ	differ	VERB
gc-467	190	11	significantly	significantly	ADV
gc-467	190	12	from	from	ADP
gc-467	190	13	the	the	DET
gc-467	190	14	original	original	ADJ
gc-467	190	15	geological	geological	ADJ
gc-467	190	16	model	model	NOUN
gc-467	190	17	obtained	obtain	VERB
gc-467	190	18	.	.	PUNCT
gc-467	191	1	however	however	ADV
gc-467	191	2	,	,	PUNCT
gc-467	191	3	differences	difference	NOUN
gc-467	191	4	are	be	AUX
gc-467	191	5	visible	visible	ADJ
gc-467	191	6	,	,	PUNCT
gc-467	191	7	especially	especially	ADV
gc-467	191	8	at	at	ADP
gc-467	191	9	the	the	DET
gc-467	191	10	contour	contour	NOUN
gc-467	191	11	of	of	ADP
gc-467	191	12	distributary	distributary	ADJ
gc-467	191	13	mouth	mouth	NOUN
gc-467	191	14	bars	bar	NOUN
gc-467	191	15	.	.	PUNCT
gc-467	192	1	this	this	PRON
gc-467	192	2	raises	raise	VERB
gc-467	192	3	the	the	DET
gc-467	192	4	question	question	NOUN
gc-467	192	5	of	of	ADP
gc-467	192	6	whether	whether	SCONJ
gc-467	192	7	the	the	DET
gc-467	192	8	differences	difference	NOUN
gc-467	192	9	show	show	VERB
gc-467	192	10	greater	great	ADJ
gc-467	192	11	accuracy	accuracy	NOUN
gc-467	192	12	or	or	CCONJ
gc-467	192	13	greater	great	ADJ
gc-467	192	14	uncertainty	uncertainty	NOUN
gc-467	192	15	.	.	PUNCT
gc-467	193	1	nevertheless	nevertheless	ADV
gc-467	193	2	the	the	DET
gc-467	193	3	discriminant	discriminant	NOUN
gc-467	193	4	analyses	analysis	NOUN
gc-467	193	5	show	show	VERB
gc-467	193	6	that	that	SCONJ
gc-467	193	7	the	the	DET
gc-467	193	8	clusters	cluster	NOUN
gc-467	193	9	are	be	AUX
gc-467	193	10	well	well	ADV
gc-467	193	11	-	-	PUNCT
gc-467	193	12	defi	defi	NOUN
gc-467	193	13	ned	ned	NOUN
gc-467	193	14	at	at	ADV
gc-467	193	15	least	least	ADJ
gc-467	193	16	on	on	ADP
gc-467	193	17	average	average	ADJ
gc-467	193	18	for	for	ADP
gc-467	193	19	95	95	NUM
gc-467	193	20	%	%	NOUN
gc-467	193	21	of	of	ADP
gc-467	193	22	the	the	DET
gc-467	193	23	time	time	NOUN
gc-467	193	24	.	.	PUNCT
gc-467	194	1	references	reference	NOUN
gc-467	194	2	ahmed	ahmed	PROPN
gc-467	194	3	,	,	PUNCT
gc-467	194	4	t.	t.	PROPN
gc-467	194	5	,	,	PUNCT
gc-467	194	6	link	link	PROPN
gc-467	194	7	,	,	PUNCT
gc-467	194	8	c.a	c.a	PROPN
gc-467	194	9	.	.	PROPN
gc-467	194	10	,	,	PUNCT
gc-467	194	11	porter	porter	PROPN
gc-467	194	12	,	,	PUNCT
gc-467	194	13	k.w	k.w	PROPN
gc-467	194	14	.	.	PROPN
gc-467	194	15	,	,	PUNCT
gc-467	194	16	wideman	wideman	PROPN
gc-467	194	17	,	,	PUNCT
gc-467	194	18	c.j	c.j	PROPN
gc-467	194	19	.	.	PROPN
gc-467	194	20	,	,	PUNCT
gc-467	194	21	himmer	himmer	PROPN
gc-467	194	22	,	,	PUNCT
gc-467	194	23	p.	p.	NOUN
gc-467	194	24	&	&	CCONJ
gc-467	194	25	braun	braun	PROPN
gc-467	194	26	,	,	PUNCT
gc-467	194	27	j.	j.	PROPN
gc-467	194	28	(	(	PUNCT
gc-467	194	29	1997	1997	NUM
gc-467	194	30	):	):	PUNCT
gc-467	194	31	application	application	NOUN
gc-467	194	32	of	of	ADP
gc-467	194	33	neural	neural	ADJ
gc-467	194	34	network	network	NOUN
gc-467	194	35	parameter	parameter	NOUN
gc-467	194	36	prediction	prediction	NOUN
gc-467	194	37	in	in	ADP
gc-467	194	38	reservoir	reservoir	NOUN
gc-467	194	39	characterization	characterization	NOUN
gc-467	194	40	and	and	CCONJ
gc-467	194	41	simulation	simulation	NOUN
gc-467	194	42	–	–	PUNCT
gc-467	194	43	a	a	DET
gc-467	194	44	case	case	NOUN
gc-467	194	45	history	history	NOUN
gc-467	194	46	:	:	PUNCT
gc-467	194	47	the	the	DET
gc-467	194	48	rabbit	rabbit	NOUN
gc-467	194	49	hills	hill	NOUN
gc-467	194	50	field	field	NOUN
gc-467	194	51	–	–	PUNCT
gc-467	194	52	paper	paper	NOUN
gc-467	194	53	spe	spe	X
gc-467	194	54	38985	38985	NUM
gc-467	194	55	presented	present	VERB
gc-467	194	56	at	at	ADP
gc-467	194	57	the	the	DET
gc-467	194	58	1997	1997	NUM
gc-467	194	59	spe	spe	PROPN
gc-467	194	60	latin	latin	ADJ
gc-467	194	61	american	american	ADJ
gc-467	194	62	and	and	CCONJ
gc-467	194	63	caribbean	caribbean	ADJ
gc-467	194	64	petroleum	petroleum	NOUN
gc-467	194	65	engineering	engineering	NOUN
gc-467	194	66	conference	conference	NOUN
gc-467	194	67	and	and	CCONJ
gc-467	194	68	exhibition	exhibition	NOUN
gc-467	194	69	held	hold	VERB
gc-467	194	70	in	in	ADP
gc-467	194	71	rio	rio	PROPN
gc-467	194	72	de	de	PROPN
gc-467	194	73	janeiro	janeiro	PROPN
gc-467	194	74	,	,	PUNCT
gc-467	194	75	bra	bra	NOUN
gc-467	194	76	zil	zil	NOUN
gc-467	194	77	,	,	PUNCT
gc-467	194	78	30	30	NUM
gc-467	194	79	august–3	august–3	NUM
gc-467	194	80	september	september	PROPN
gc-467	194	81	1997	1997	NUM
gc-467	194	82	.	.	PUNCT
gc-467	195	1	doi	doi	NOUN
gc-467	195	2	:	:	PUNCT
gc-467	195	3	10.2118/38985	10.2118/38985	NUM
gc-467	195	4	-	-	PUNCT
gc-467	195	5	ms	ms	ADJ
gc-467	195	6	akinyokun	akinyokun	PROPN
gc-467	195	7	,	,	PUNCT
gc-467	195	8	o.c	o.c	PROPN
gc-467	195	9	.	.	PROPN
gc-467	195	10	,	,	PUNCT
gc-467	195	11	enikanselu	enikanselu	PROPN
gc-467	195	12	,	,	PUNCT
gc-467	195	13	p.a	p.a	PROPN
gc-467	195	14	.	.	PROPN
gc-467	195	15	,	,	PUNCT
gc-467	195	16	adeyemo	adeyemo	ADJ
gc-467	195	17	,	,	PUNCT
gc-467	195	18	a.b	a.b	PROPN
gc-467	195	19	.	.	PROPN
gc-467	195	20	&	&	CCONJ
gc-467	195	21	adesida	adesida	PROPN
gc-467	195	22	,	,	PUNCT
gc-467	195	23	a.	a.	NOUN
gc-467	195	24	(	(	PUNCT
gc-467	195	25	2009	2009	NUM
gc-467	195	26	):	):	PUNCT
gc-467	195	27	well	well	ADV
gc-467	195	28	log	log	VERB
gc-467	195	29	interpretation	interpretation	NOUN
gc-467	195	30	model	model	NOUN
gc-467	195	31	for	for	ADP
gc-467	195	32	the	the	DET
gc-467	195	33	determination	determination	NOUN
gc-467	195	34	of	of	ADP
gc-467	195	35	lithology	lithology	NOUN
gc-467	195	36	and	and	CCONJ
gc-467	195	37	fl	fl	ADP
gc-467	195	38	uid	uid	ADJ
gc-467	195	39	contents	content	NOUN
gc-467	195	40	.	.	PUNCT
gc-467	196	1	–	–	PUNCT
gc-467	196	2	the	the	DET
gc-467	196	3	pacifi	pacifi	NOUN
gc-467	196	4	c	c	PROPN
gc-467	196	5	journal	journal	PROPN
gc-467	196	6	of	of	ADP
gc-467	196	7	science	science	NOUN
gc-467	196	8	and	and	CCONJ
gc-467	196	9	technology	technology	NOUN
gc-467	196	10	,	,	PUNCT
gc-467	196	11	springer	springer	NOUN
gc-467	196	12	.	.	PUNCT
gc-467	197	1	bérczi	bérczi	PROPN
gc-467	197	2	,	,	PUNCT
gc-467	197	3	i.	i.	PROPN
gc-467	197	4	(	(	PUNCT
gc-467	197	5	1988	1988	NUM
gc-467	197	6	):	):	PUNCT
gc-467	197	7	preliminary	preliminary	ADJ
gc-467	197	8	sedimentological	sedimentological	ADJ
gc-467	197	9	investigations	investigation	NOUN
gc-467	197	10	of	of	ADP
gc-467	197	11	a	a	DET
gc-467	197	12	neogene	neogene	ADJ
gc-467	197	13	depression	depression	NOUN
gc-467	197	14	in	in	ADP
gc-467	197	15	the	the	DET
gc-467	197	16	great	great	ADJ
gc-467	197	17	hungarian	hungarian	ADJ
gc-467	197	18	plain	plain	NOUN
gc-467	197	19	.	.	PUNCT
gc-467	197	20	–	–	PUNCT
gc-467	197	21	in	in	ADP
gc-467	197	22	:	:	PUNCT
gc-467	197	23	royden	royden	PROPN
gc-467	197	24	&	&	CCONJ
gc-467	197	25	horváth	horváth	PROPN
gc-467	197	26	(	(	PUNCT
gc-467	197	27	ed	ed	NOUN
gc-467	197	28	.	.	PROPN
gc-467	197	29	):	):	PUNCT
gc-467	197	30	the	the	DET
gc-467	197	31	pannonian	pannonian	ADJ
gc-467	197	32	basin	basin	NOUN
gc-467	197	33	–	–	PUNCT
gc-467	197	34	a	a	DET
gc-467	197	35	study	study	NOUN
gc-467	197	36	in	in	ADP
gc-467	197	37	basin	basin	NOUN
gc-467	197	38	evolution	evolution	NOUN
gc-467	197	39	.	.	PUNCT
gc-467	197	40	–	–	PUNCT
gc-467	197	41	aapg	aapg	ADJ
gc-467	197	42	memoir	memoir	NOUN
gc-467	197	43	,	,	PUNCT
gc-467	197	44	45	45	NUM
gc-467	197	45	,	,	PUNCT
gc-467	197	46	107–116	107–116	NUM
gc-467	197	47	.	.	PUNCT
gc-467	198	1	chang	chang	PROPN
gc-467	198	2	,	,	PUNCT
gc-467	198	3	h.-c	h.-c	PROPN
gc-467	198	4	.	.	PUNCT
gc-467	198	5	,	,	PUNCT
gc-467	198	6	kopaska	kopaska	PROPN
gc-467	198	7	-	-	PUNCT
gc-467	198	8	merkel	merkel	PROPN
gc-467	198	9	,	,	PUNCT
gc-467	198	10	d.c	d.c	PROPN
gc-467	198	11	.	.	PROPN
gc-467	198	12	&	&	CCONJ
gc-467	198	13	chen	chen	PROPN
gc-467	198	14	,	,	PUNCT
gc-467	198	15	h.-c	h.-c	PROPN
gc-467	198	16	.	.	PUNCT
gc-467	199	1	(	(	PUNCT
gc-467	199	2	2002	2002	NUM
gc-467	199	3	):	):	PUNCT
gc-467	199	4	identifi	identifi	PROPN
gc-467	199	5	cation	cation	NOUN
gc-467	199	6	of	of	ADP
gc-467	199	7	lithofacies	lithofacie	NOUN
gc-467	199	8	using	use	VERB
gc-467	199	9	kohonen	kohonen	PROPN
gc-467	199	10	self	self	NOUN
gc-467	199	11	-	-	PUNCT
gc-467	199	12	organizing	organize	VERB
gc-467	199	13	maps	map	NOUN
gc-467	199	14	.	.	PUNCT
gc-467	199	15	–	–	PUNCT
gc-467	199	16	computers	computer	NOUN
gc-467	199	17	&	&	CCONJ
gc-467	199	18	geosciences	geoscience	NOUN
gc-467	199	19	,	,	PUNCT
gc-467	199	20	28	28	NUM
gc-467	199	21	,	,	PUNCT
gc-467	199	22	223–229	223–229	NUM
gc-467	199	23	.	.	PUNCT
gc-467	200	1	doi	doi	NOUN
gc-467	200	2	:	:	PUNCT
gc-467	200	3	10.1016	10.1016	NUM
gc-467	200	4	/	/	SYM
gc-467	200	5	s0098	s0098	PROPN
gc-467	200	6	-	-	PUNCT
gc-467	200	7	3004(01)00067	3004(01)00067	NUM
gc-467	200	8	-	-	PUNCT
gc-467	200	9	x	x	SYM
gc-467	200	10	fausett	fausett	NOUN
gc-467	200	11	,	,	PUNCT
gc-467	200	12	l.	l.	PROPN
gc-467	200	13	(	(	PUNCT
gc-467	200	14	1994	1994	NUM
gc-467	200	15	):	):	PUNCT
gc-467	200	16	fundamentals	fundamental	NOUN
gc-467	200	17	of	of	ADP
gc-467	200	18	neural	neural	ADJ
gc-467	200	19	networks	network	NOUN
gc-467	200	20	–	–	PUNCT
gc-467	200	21	architectures	architecture	NOUN
gc-467	200	22	,	,	PUNCT
gc-467	200	23	algorithms	algorithm	NOUN
gc-467	200	24	and	and	CCONJ
gc-467	200	25	applications	application	NOUN
gc-467	200	26	,	,	PUNCT
gc-467	200	27	prentice	prentice	NOUN
gc-467	200	28	hall	hall	PROPN
gc-467	200	29	,	,	PUNCT
gc-467	200	30	englewood	englewood	PROPN
gc-467	200	31	cliffs	cliffs	PROPN
gc-467	200	32	,	,	PUNCT
gc-467	200	33	nj	nj	PROPN
gc-467	200	34	.	.	PUNCT
gc-467	201	1	geiger	geiger	PROPN
gc-467	201	2	,	,	PUNCT
gc-467	201	3	j.	j.	PROPN
gc-467	201	4	(	(	PUNCT
gc-467	201	5	2005	2005	NUM
gc-467	201	6	):	):	PUNCT
gc-467	201	7	sedimentological	sedimentological	ADJ
gc-467	201	8	study	study	NOUN
gc-467	201	9	of	of	ADP
gc-467	201	10	szőreg-1	szőreg-1	NUM
gc-467	201	11	reservoir	reservoir	NOUN
gc-467	201	12	(	(	PUNCT
gc-467	201	13	algyő	algyő	NOUN
gc-467	201	14	field	field	NOUN
gc-467	201	15	):	):	PUNCT
gc-467	201	16	a	a	DET
gc-467	201	17	kind	kind	NOUN
gc-467	201	18	of	of	ADP
gc-467	201	19	combination	combination	NOUN
gc-467	201	20	of	of	ADP
gc-467	201	21	traditional	traditional	ADJ
gc-467	201	22	and	and	CCONJ
gc-467	201	23	3d	3d	NUM
gc-467	201	24	sedimentological	sedimentological	ADJ
gc-467	201	25	approaches	approach	NOUN
gc-467	201	26	.	.	PUNCT
gc-467	201	27	–	–	PUNCT
gc-467	201	28	in	in	ADP
gc-467	201	29	:	:	PUNCT
gc-467	201	30	hum	hum	ADJ
gc-467	201	31	,	,	PUNCT
gc-467	201	32	l.	l.	PROPN
gc-467	201	33	et	et	PROPN
gc-467	201	34	al	al	PROPN
gc-467	201	35	.	.	PROPN
gc-467	201	36	(	(	PUNCT
gc-467	201	37	eds	ed	NOUN
gc-467	201	38	.	.	PROPN
gc-467	201	39	):	):	PUNCT
gc-467	201	40	environmental	environmental	ADJ
gc-467	201	41	historical	historical	ADJ
gc-467	201	42	studies	study	NOUN
gc-467	201	43	from	from	ADP
gc-467	201	44	the	the	DET
gc-467	201	45	late	late	ADJ
gc-467	201	46	tertiary	tertiary	ADJ
gc-467	201	47	and	and	CCONJ
gc-467	201	48	quarternary	quarternary	ADJ
gc-467	201	49	of	of	ADP
gc-467	201	50	hungary	hungary	PROPN
gc-467	201	51	.	.	PUNCT
gc-467	202	1	department	department	PROPN
gc-467	202	2	of	of	ADP
gc-467	202	3	geology	geology	NOUN
gc-467	202	4	and	and	CCONJ
gc-467	202	5	paleontology	paleontology	NOUN
gc-467	202	6	,	,	PUNCT
gc-467	202	7	university	university	PROPN
gc-467	202	8	of	of	ADP
gc-467	202	9	szeged	szeged	PROPN
gc-467	202	10	,	,	PUNCT
gc-467	202	11	25–45	25–45	NUM
gc-467	202	12	.	.	PUNCT
gc-467	203	1	geiger	geiger	PROPN
gc-467	203	2	,	,	PUNCT
gc-467	203	3	j.	j.	PROPN
gc-467	203	4	,	,	PUNCT
gc-467	203	5	kissné	kissné	PROPN
gc-467	203	6	,	,	PUNCT
gc-467	203	7	v.k	v.k	PROPN
gc-467	203	8	.	.	PROPN
gc-467	203	9	,	,	PUNCT
gc-467	203	10	veres	veres	PROPN
gc-467	203	11	,	,	PUNCT
gc-467	203	12	k.	k.	PROPN
gc-467	203	13	&	&	CCONJ
gc-467	203	14	komlós	komlós	PROPN
gc-467	203	15	,	,	PUNCT
gc-467	203	16	j.	j.	PROPN
gc-467	203	17	(	(	PUNCT
gc-467	203	18	1998	1998	NUM
gc-467	203	19	):	):	PUNCT
gc-467	203	20	a	a	DET
gc-467	203	21	szőreg-1	szőreg-1	NUM
gc-467	203	22	telep	telep	PROPN
gc-467	203	23	3d	3d	PROPN
gc-467	203	24	rezervoár	rezervoár	PROPN
gc-467	203	25	geológiai	geológiai	PROPN
gc-467	203	26	modellje	modellje	PROPN
gc-467	203	27	.	.	PUNCT
gc-467	204	1	(	(	PUNCT
gc-467	204	2	3d	3d	NOUN
gc-467	204	3	sedimentological	sedimentological	NOUN
gc-467	204	4	modelling	modelling	NOUN
gc-467	204	5	of	of	ADP
gc-467	204	6	szőreg-1	szőreg-1	NUM
gc-467	204	7	reservoir	reservoir	NOUN
gc-467	204	8	)	)	PUNCT
gc-467	204	9	,	,	PUNCT
gc-467	204	10	kummi	kummi	PROPN
gc-467	204	11	jelentés	jelentés	PROPN
gc-467	204	12	.	.	PUNCT
gc-467	205	1	p.	p.	NOUN
gc-467	205	2	216	216	NUM
gc-467	205	3	.	.	PUNCT
gc-467	206	1	tsz	tsz	PROPN
gc-467	206	2	.	.	PROPN
gc-467	207	1	156–5636	156–5636	NUM
gc-467	207	2	.	.	PROPN
gc-467	207	3	,	,	PUNCT
gc-467	207	4	szeged	szeged	PROPN
gc-467	207	5	.	.	PUNCT
gc-467	208	1	haykin	haykin	PROPN
gc-467	208	2	,	,	PUNCT
gc-467	208	3	s.	s.	PROPN
gc-467	208	4	(	(	PUNCT
gc-467	208	5	1999	1999	NUM
gc-467	208	6	):	):	PUNCT
gc-467	208	7	neural	neural	ADJ
gc-467	208	8	networks	network	NOUN
gc-467	208	9	:	:	PUNCT
gc-467	208	10	a	a	DET
gc-467	208	11	comprehensive	comprehensive	ADJ
gc-467	208	12	foundation	foundation	NOUN
gc-467	208	13	.	.	PUNCT
gc-467	209	1	macmillan	macmillan	PROPN
gc-467	209	2	.	.	PROPN
gc-467	209	3	–	–	PUNCT
gc-467	209	4	the	the	DET
gc-467	209	5	knowledge	knowledge	NOUN
gc-467	209	6	engineering	engineering	PROPN
gc-467	209	7	review	review	PROPN
gc-467	209	8	,	,	PUNCT
gc-467	209	9	new	new	PROPN
gc-467	209	10	york	york	PROPN
gc-467	209	11	,	,	PUNCT
gc-467	209	12	13/4	13/4	NUM
gc-467	209	13	,	,	PUNCT
gc-467	209	14	409–412	409–412	NUM
gc-467	209	15	.	.	PUNCT
gc-467	210	1	doi	doi	NOUN
gc-467	210	2	:	:	PUNCT
gc-467	210	3	10.1017	10.1017	NUM
gc-467	210	4	/	/	SYM
gc-467	210	5	s0269888998214044	s0269888998214044	PROPN
gc-467	210	6	johansson	johansson	PROPN
gc-467	210	7	,	,	PUNCT
gc-467	210	8	j.	j.	PROPN
gc-467	210	9	,	,	PUNCT
gc-467	210	10	jern	jern	PROPN
gc-467	210	11	,	,	PUNCT
gc-467	210	12	m.	m.	NOUN
gc-467	210	13	,	,	PUNCT
gc-467	210	14	treloar	treloar	PROPN
gc-467	210	15	,	,	PUNCT
gc-467	210	16	r.	r.	PROPN
gc-467	210	17	,	,	PUNCT
gc-467	210	18	jansson	jansson	PROPN
gc-467	210	19	m.	m.	PROPN
gc-467	210	20	(	(	PUNCT
gc-467	210	21	2003	2003	NUM
gc-467	210	22	):	):	PUNCT
gc-467	210	23	“	"	PUNCT
gc-467	210	24	visual	visual	ADJ
gc-467	210	25	analysis	analysis	NOUN
gc-467	210	26	based	base	VERB
gc-467	210	27	on	on	ADP
gc-467	210	28	algorithmic	algorithmic	ADJ
gc-467	210	29	classifi	classifi	PROPN
gc-467	210	30	cation	cation	NOUN
gc-467	210	31	”	"	PUNCT
gc-467	210	32	iv	iv	NUM
gc-467	210	33	,	,	PUNCT
gc-467	210	34	seventh	seventh	ADJ
gc-467	210	35	international	international	ADJ
gc-467	210	36	conference	conference	NOUN
gc-467	210	37	on	on	ADP
gc-467	210	38	information	information	NOUN
gc-467	210	39	visualization	visualization	NOUN
gc-467	210	40	,	,	PUNCT
gc-467	210	41	p.	p.	NOUN
gc-467	210	42	86	86	NUM
gc-467	210	43	.	.	PUNCT
gc-467	211	1	kohonen	kohonen	PROPN
gc-467	211	2	,	,	PUNCT
gc-467	211	3	t.	t.	PROPN
gc-467	211	4	(	(	PUNCT
gc-467	211	5	1982	1982	NUM
gc-467	211	6	):	):	PUNCT
gc-467	211	7	self	self	NOUN
gc-467	211	8	-	-	PUNCT
gc-467	211	9	organized	organize	VERB
gc-467	211	10	formation	formation	NOUN
gc-467	211	11	of	of	ADP
gc-467	211	12	topologically	topologically	ADV
gc-467	211	13	correct	correct	ADJ
gc-467	211	14	feature	feature	NOUN
gc-467	211	15	maps	map	NOUN
gc-467	211	16	.	.	PUNCT
gc-467	211	17	–	–	PUNCT
gc-467	211	18	biological	biological	ADJ
gc-467	211	19	cybernetics	cybernetic	NOUN
gc-467	211	20	,	,	PUNCT
gc-467	211	21	43	43	NUM
gc-467	211	22	,	,	PUNCT
gc-467	211	23	59–69	59–69	NUM
gc-467	211	24	.	.	PUNCT
gc-467	212	1	doi	doi	NOUN
gc-467	212	2	:	:	PUNCT
gc-467	212	3	10.1007/	10.1007/	NUM
gc-467	212	4	bf00337288	bf00337288	PROPN
gc-467	212	5	kohonen	kohonen	PROPN
gc-467	212	6	,	,	PUNCT
gc-467	212	7	t.	t.	PROPN
gc-467	212	8	(	(	PUNCT
gc-467	212	9	2001	2001	NUM
gc-467	212	10	):	):	PUNCT
gc-467	212	11	self	self	NOUN
gc-467	212	12	organized	organize	VERB
gc-467	212	13	maps	map	NOUN
gc-467	212	14	–	–	PUNCT
gc-467	212	15	springer	springer	NOUN
gc-467	212	16	,	,	PUNCT
gc-467	212	17	berlin	berlin	PROPN
gc-467	212	18	,	,	PUNCT
gc-467	212	19	germany	germany	PROPN
gc-467	212	20	.	.	PUNCT
gc-467	213	1	lampinen	lampinen	PROPN
gc-467	213	2	,	,	PUNCT
gc-467	213	3	t.	t.	PROPN
gc-467	213	4	,	,	PUNCT
gc-467	213	5	laurikkala	laurikkala	PROPN
gc-467	213	6	,	,	PUNCT
gc-467	213	7	m.	m.	NOUN
gc-467	213	8	,	,	PUNCT
gc-467	213	9	koivisto	koivisto	PROPN
gc-467	213	10	,	,	PUNCT
gc-467	213	11	h.	h.	PROPN
gc-467	213	12	&	&	CCONJ
gc-467	213	13	honkanen	honkanen	PROPN
gc-467	213	14	,	,	PUNCT
gc-467	213	15	t.	t.	PROPN
gc-467	213	16	(	(	PUNCT
gc-467	213	17	2005	2005	NUM
gc-467	213	18	):	):	PUNCT
gc-467	213	19	profi	profi	PROPN
gc-467	213	20	ling	ling	PROPN
gc-467	213	21	network	network	NOUN
gc-467	213	22	applications	application	NOUN
gc-467	213	23	with	with	ADP
gc-467	213	24	fuzzy	fuzzy	ADJ
gc-467	213	25	c	c	NOUN
gc-467	213	26	-	-	PUNCT
gc-467	213	27	means	mean	NOUN
gc-467	213	28	and	and	CCONJ
gc-467	213	29	self	self	NOUN
gc-467	213	30	-	-	PUNCT
gc-467	213	31	organizing	organize	VERB
gc-467	213	32	maps	map	NOUN
gc-467	213	33	studies	study	NOUN
gc-467	213	34	in	in	ADP
gc-467	213	35	computational	computational	ADJ
gc-467	213	36	intelligence	intelligence	NOUN
gc-467	213	37	,	,	PUNCT
gc-467	213	38	volume	volume	NOUN
gc-467	213	39	4/2005	4/2005	NUM
gc-467	213	40	classifi	classifi	PROPN
gc-467	213	41	cation	cation	NOUN
gc-467	213	42	and	and	CCONJ
gc-467	213	43	clustering	cluster	VERB
gc-467	213	44	for	for	ADP
gc-467	213	45	knowledge	knowledge	NOUN
gc-467	213	46	discovery	discovery	NOUN
gc-467	213	47	,	,	PUNCT
gc-467	213	48	springer	springer	NOUN
gc-467	213	49	berlin	berlin	PROPN
gc-467	213	50	/	/	SYM
gc-467	213	51	heidelberg	heidelberg	PROPN
gc-467	213	52	.	.	PUNCT
gc-467	214	1	mahalanobis	mahalanobis	PROPN
gc-467	214	2	,	,	PUNCT
gc-467	214	3	p.c	p.c	PROPN
gc-467	214	4	.	.	PROPN
gc-467	214	5	(	(	PUNCT
gc-467	214	6	1936	1936	NUM
gc-467	214	7	):	):	PUNCT
gc-467	214	8	“	"	PUNCT
gc-467	214	9	on	on	ADP
gc-467	214	10	the	the	DET
gc-467	214	11	generalized	generalized	ADJ
gc-467	214	12	distance	distance	NOUN
gc-467	214	13	in	in	ADP
gc-467	214	14	statistics	statistic	NOUN
gc-467	214	15	”	"	PUNCT
gc-467	214	16	.	.	PUNCT
gc-467	215	1	proceedings	proceeding	NOUN
gc-467	215	2	of	of	ADP
gc-467	215	3	the	the	DET
gc-467	215	4	national	national	PROPN
gc-467	215	5	institute	institute	PROPN
gc-467	215	6	of	of	ADP
gc-467	215	7	sciences	sciences	PROPN
gc-467	215	8	of	of	ADP
gc-467	215	9	india	india	PROPN
gc-467	215	10	2/1	2/1	NUM
gc-467	215	11	:	:	PUNCT
gc-467	215	12	49–55	49–55	NUM
gc-467	215	13	.	.	PUNCT
gc-467	216	1	patterson	patterson	PROPN
gc-467	216	2	,	,	PUNCT
gc-467	216	3	d.	d.	PROPN
gc-467	216	4	(	(	PUNCT
gc-467	216	5	1996	1996	NUM
gc-467	216	6	)	)	PUNCT
gc-467	216	7	artifi	artifi	ADP
gc-467	216	8	cial	cial	ADJ
gc-467	216	9	neural	neural	ADJ
gc-467	216	10	networks	network	NOUN
gc-467	216	11	,	,	PUNCT
gc-467	216	12	prentice	prentice	NOUN
gc-467	216	13	hall	hall	PROPN
gc-467	216	14	,	,	PUNCT
gc-467	216	15	singapore	singapore	PROPN
gc-467	216	16	,	,	PUNCT
gc-467	216	17	xy	xy	PROPN
gc-467	216	18	p.	p.	NOUN
gc-467	216	19	pettijohn	pettijohn	NOUN
gc-467	216	20	,	,	PUNCT
gc-467	216	21	f.j	f.j	PROPN
gc-467	216	22	.	.	PROPN
gc-467	216	23	&	&	CCONJ
gc-467	216	24	potter	potter	PROPN
gc-467	216	25	,	,	PUNCT
gc-467	216	26	p.e	p.e	PROPN
gc-467	216	27	.	.	PROPN
gc-467	216	28	(	(	PUNCT
gc-467	216	29	1972	1972	NUM
gc-467	216	30	):	):	PUNCT
gc-467	216	31	sand	sand	NOUN
gc-467	216	32	and	and	CCONJ
gc-467	216	33	sandstone	sandstone	NOUN
gc-467	216	34	.	.	PUNCT
gc-467	216	35	–	–	PUNCT
gc-467	216	36	sprin	sprin	NOUN
gc-467	216	37	ger	ger	PROPN
gc-467	216	38	verlag	verlag	PROPN
gc-467	216	39	berlin	berlin	PROPN
gc-467	216	40	–	–	PUNCT
gc-467	216	41	heidelberg	heidelberg	PROPN
gc-467	216	42	–	–	PUNCT
gc-467	216	43	new	new	PROPN
gc-467	216	44	york	york	PROPN
gc-467	216	45	,	,	PUNCT
gc-467	216	46	618	618	NUM
gc-467	216	47	p.	p.	NOUN
gc-467	216	48	révész	révész	PROPN
gc-467	216	49	,	,	PUNCT
gc-467	216	50	i.	i.	PROPN
gc-467	216	51	(	(	PUNCT
gc-467	216	52	1982	1982	NUM
gc-467	216	53	):	):	PUNCT
gc-467	216	54	az	az	PROPN
gc-467	216	55	algyői	algyői	PROPN
gc-467	216	56	maros	maro	NOUN
gc-467	216	57	-	-	PUNCT
gc-467	216	58	szőreg	szőreg	VERB
gc-467	216	59	szénhidrogéntelepek	szénhidrogéntelepek	NOUN
gc-467	216	60	üledékföldtani	üledékföldtani	NOUN
gc-467	216	61	modellje	modellje	PROPN
gc-467	216	62	–	–	PUNCT
gc-467	216	63	egy	egy	PROPN
gc-467	216	64	fosszilis	fosszilis	PROPN
gc-467	216	65	delta	delta	PROPN
gc-467	216	66	fejlődéstörténete	fejlődéstörténete	ADV
gc-467	216	67	.	.	PUNCT
gc-467	217	1	(	(	PUNCT
gc-467	217	2	modelling	modelling	NOUN
gc-467	217	3	of	of	ADP
gc-467	217	4	maros	maro	NOUN
gc-467	217	5	-	-	PUNCT
gc-467	217	6	szőreg	szőreg	ADJ
gc-467	217	7	hydrocarbon	hydrocarbon	NOUN
gc-467	217	8	reservoir	reservoir	NOUN
gc-467	217	9	(	(	PUNCT
gc-467	217	10	algyő	algyő	NOUN
gc-467	217	11	field	field	NOUN
gc-467	217	12	)	)	PUNCT
gc-467	217	13	–	–	PUNCT
gc-467	217	14	a	a	DET
gc-467	217	15	develop	develop	VERB
gc-467	217	16	history	history	NOUN
gc-467	217	17	of	of	ADP
gc-467	217	18	the	the	DET
gc-467	217	19	pannonian	pannonian	ADJ
gc-467	217	20	fossil	fossil	PROPN
gc-467	217	21	delta	delta	NOUN
gc-467	217	22	.	.	PUNCT
gc-467	217	23	)	)	PUNCT
gc-467	217	24	.	.	PUNCT
gc-467	218	1	–	–	PUNCT
gc-467	218	2	kőolaj	kőolaj	NOUN
gc-467	218	3	és	és	PROPN
gc-467	218	4	földgáz	földgáz	PROPN
gc-467	218	5	,	,	PUNCT
gc-467	218	6	115	115	NUM
gc-467	218	7	,	,	PUNCT
gc-467	218	8	176–177	176–177	NUM
gc-467	218	9	.	.	PUNCT
gc-467	219	1	rogers	rogers	PROPN
gc-467	219	2	,	,	PUNCT
gc-467	219	3	s.j	s.j	PROPN
gc-467	219	4	.	.	PROPN
gc-467	219	5	,	,	PUNCT
gc-467	219	6	chen	chen	PROPN
gc-467	219	7	,	,	PUNCT
gc-467	219	8	h.c	h.c	PROPN
gc-467	219	9	.	.	PROPN
gc-467	219	10	,	,	PUNCT
gc-467	219	11	kopaska	kopaska	PROPN
gc-467	219	12	-	-	PUNCT
gc-467	219	13	merkel	merkel	PROPN
gc-467	219	14	,	,	PUNCT
gc-467	219	15	d.c	d.c	PROPN
gc-467	219	16	.	.	PROPN
gc-467	219	17	&	&	CCONJ
gc-467	219	18	fang	fang	PROPN
gc-467	219	19	,	,	PUNCT
gc-467	219	20	j.h	j.h	PROPN
gc-467	219	21	.	.	PROPN
gc-467	219	22	(	(	PUNCT
gc-467	219	23	1995	1995	NUM
gc-467	219	24	):	):	PUNCT
gc-467	219	25	predicting	predict	VERB
gc-467	219	26	permeability	permeability	NOUN
gc-467	219	27	from	from	ADP
gc-467	219	28	porosity	porosity	NOUN
gc-467	219	29	using	use	VERB
gc-467	219	30	artifi	artifi	PRON
gc-467	219	31	cial	cial	ADJ
gc-467	219	32	neural	neural	ADJ
gc-467	219	33	networks	network	NOUN
gc-467	219	34	.	.	PUNCT
gc-467	220	1	–	–	PUNCT
gc-467	220	2	aapg	aapg	VERB
gc-467	220	3	bulletin	bulletin	NOUN
gc-467	220	4	,	,	PUNCT
gc-467	220	5	79/12	79/12	NUM
gc-467	220	6	,	,	PUNCT
gc-467	220	7	1786–1797	1786–1797	NUM
gc-467	220	8	.	.	PUNCT
gc-467	221	1	ultsch	ultsch	PROPN
gc-467	221	2	,	,	PUNCT
gc-467	221	3	a.	a.	NOUN
gc-467	221	4	(	(	PUNCT
gc-467	221	5	1995	1995	NUM
gc-467	221	6	):	):	PUNCT
gc-467	221	7	self	self	NOUN
gc-467	221	8	organizing	organize	VERB
gc-467	221	9	neural	neural	ADJ
gc-467	221	10	networks	network	NOUN
gc-467	221	11	perform	perform	VERB
gc-467	221	12	different	different	ADJ
gc-467	221	13	from	from	ADP
gc-467	221	14	statistical	statistical	ADJ
gc-467	221	15	k	k	ADJ
gc-467	221	16	-	-	PUNCT
gc-467	221	17	means	means	NOUN
gc-467	221	18	clustering	clustering	NOUN
gc-467	221	19	.	.	PUNCT
gc-467	221	20	–	–	PUNCT
gc-467	221	21	in	in	ADP
gc-467	221	22	:	:	PUNCT
gc-467	221	23	proc	proc	NOUN
gc-467	221	24	.	.	PUNCT
gc-467	222	1	gfkl	gfkl	PROPN
gc-467	222	2	,	,	PUNCT
gc-467	222	3	basel	basel	PROPN
gc-467	222	4	,	,	PUNCT
gc-467	222	5	swiss	swiss	PROPN
gc-467	222	6	.	.	PUNCT
gc-467	223	1	ultsch	ultsch	PROPN
gc-467	223	2	,	,	PUNCT
gc-467	223	3	a.	a.	PROPN
gc-467	223	4	,	,	PUNCT
gc-467	223	5	korus	korus	PROPN
gc-467	223	6	,	,	PUNCT
gc-467	223	7	d.	d.	PROPN
gc-467	223	8	&	&	CCONJ
gc-467	223	9	wehrmann	wehrmann	PROPN
gc-467	223	10	,	,	PUNCT
gc-467	223	11	a.	a.	PROPN
gc-467	223	12	(	(	PUNCT
gc-467	223	13	1995	1995	NUM
gc-467	223	14	):	):	PUNCT
gc-467	223	15	neural	neural	ADJ
gc-467	223	16	networks	network	NOUN
gc-467	223	17	and	and	CCONJ
gc-467	223	18	their	their	PRON
gc-467	223	19	rules	rule	NOUN
gc-467	223	20	for	for	ADP
gc-467	223	21	classifi	classifi	PROPN
gc-467	223	22	cation	cation	NOUN
gc-467	223	23	in	in	ADP
gc-467	223	24	marine	marine	ADJ
gc-467	223	25	geology	geology	NOUN
gc-467	223	26	,	,	PUNCT
gc-467	223	27	raum	raum	PROPN
gc-467	223	28	und	und	VERB
gc-467	223	29	zeit	zeit	PROPN
gc-467	223	30	in	in	ADP
gc-467	223	31	umweltinformations	umweltinformation	NOUN
gc-467	223	32	-	-	PUNCT
gc-467	223	33	systemen	systemen	NOUN
gc-467	223	34	,	,	PUNCT
gc-467	223	35	9th	9th	ADJ
gc-467	223	36	intl	intl	PROPN
gc-467	223	37	.	.	PUNCT
gc-467	224	1	symposium	symposium	NOUN
gc-467	224	2	on	on	ADP
gc-467	224	3	computer	computer	NOUN
gc-467	224	4	science	science	NOUN
gc-467	224	5	for	for	ADP
gc-467	224	6	environmental	environmental	ADJ
gc-467	224	7	protection	protection	PROPN
gc-467	224	8	csep	csep	PROPN
gc-467	224	9	´	´	PROPN
gc-467	224	10	95	95	NUM
gc-467	224	11	,	,	PUNCT
gc-467	224	12	vol	vol	NOUN
gc-467	224	13	.	.	PUNCT
gc-467	225	1	i	i	PRON
gc-467	225	2	,	,	PUNCT
gc-467	225	3	ed	ed	PROPN
gc-467	225	4	.	.	PROPN
gc-467	225	5	gifachausschuß	gifachausschuß	VERB
gc-467	225	6	4.6	4.6	NUM
gc-467	225	7	“	"	PUNCT
gc-467	225	8	informatik	informatik	PROPN
gc-467	225	9	i	i	NOUN
gc-467	225	10	m	m	VERB
gc-467	225	11	umweltschutz	umweltschutz	ADJ
gc-467	225	12	”	"	PUNCT
gc-467	225	13	vol	vol	NOUN
gc-467	225	14	.	.	PROPN
gc-467	225	15	7	7	NUM
gc-467	225	16	,	,	PUNCT
gc-467	225	17	metropolis	metropolis	NOUN
gc-467	225	18	-	-	PUNCT
gc-467	225	19	verlag	verlag	PROPN
gc-467	225	20	,	,	PUNCT
gc-467	225	21	marburg	marburg	PROPN
gc-467	225	22	,	,	PUNCT
gc-467	225	23	676–693	676–693	NUM
gc-467	225	24	.	.	PUNCT
gc-467	226	1	manuscript	manuscript	NOUN
gc-467	226	2	received	receive	VERB
gc-467	226	3	december	december	PROPN
gc-467	226	4	03	03	NUM
gc-467	226	5	,	,	PUNCT
gc-467	226	6	2010	2010	NUM
gc-467	226	7	revised	revise	VERB
gc-467	226	8	manuscript	manuscript	NOUN
gc-467	226	9	accepted	accept	VERB
gc-467	226	10	july	july	PROPN
gc-467	226	11	11	11	NUM
gc-467	226	12	,	,	PUNCT
gc-467	226	13	2011	2011	NUM
gc-467	226	14	available	available	ADJ
gc-467	226	15	online	online	ADJ
gc-467	226	16	october	october	PROPN
gc-467	226	17	26	26	NUM
gc-467	226	18	,	,	PUNCT
gc-467	226	19	2011	2011	NUM