id	sid	tid	token	lemma	pos
14-hansen-can	1	1	Chapter	chapter	NN
14-hansen-can	1	2	14	14	CD
14-hansen-can	1	3	Can	Can	MD
14-hansen-can	1	4	a	a	DT
14-hansen-can	1	5	Hammer	Hammer	NNP
14-hansen-can	1	6	Categorize	Categorize	NNP
14-hansen-can	1	7	Highly	highly	RB
14-hansen-can	1	8	Technical	technical	JJ
14-hansen-can	1	9	Articles	article	NNS
14-hansen-can	1	10	?	?	.
14-hansen-can	2	1	Samuel	Samuel	NNP
14-hansen-can	2	2	Hansen	Hansen	NNP
14-hansen-can	2	3	University	University	NNP
14-hansen-can	2	4	of	of	IN
14-hansen-can	2	5	Michigan	Michigan	NNP
14-hansen-can	2	6	When	when	WRB
14-hansen-can	2	7	everything	everything	NN
14-hansen-can	2	8	looks	look	VBZ
14-hansen-can	2	9	like	like	IN
14-hansen-can	2	10	a	a	DT
14-hansen-can	2	11	nail	nail	NN
14-hansen-can	2	12	...	...	.
14-hansen-can	3	1	I	-PRON-	PRP
14-hansen-can	3	2	was	be	VBD
14-hansen-can	3	3	sure	sure	JJ
14-hansen-can	3	4	I	-PRON-	PRP
14-hansen-can	3	5	had	have	VBD
14-hansen-can	3	6	the	the	DT
14-hansen-can	3	7	most	most	RBS
14-hansen-can	3	8	brilliant	brilliant	JJ
14-hansen-can	3	9	research	research	NN
14-hansen-can	3	10	project	project	NN
14-hansen-can	3	11	idea	idea	NN
14-hansen-can	3	12	for	for	IN
14-hansen-can	3	13	my	-PRON-	PRP$
14-hansen-can	3	14	course	course	NN
14-hansen-can	3	15	in	in	IN
14-hansen-can	3	16	Digital	Digital	NNP
14-hansen-can	3	17	Scholarship	Scholarship	NNP
14-hansen-can	3	18	tech-	tech-	NN
14-hansen-can	3	19	niques	nique	NNS
14-hansen-can	3	20	.	.	.
14-hansen-can	4	1	I	-PRON-	PRP
14-hansen-can	4	2	would	would	MD
14-hansen-can	4	3	use	use	VB
14-hansen-can	4	4	the	the	DT
14-hansen-can	4	5	Mathematical	Mathematical	NNP
14-hansen-can	4	6	Subject	Subject	NNP
14-hansen-can	4	7	Classification	Classification	NNP
14-hansen-can	4	8	(	(	-LRB-
14-hansen-can	4	9	MSC	MSC	NNP
14-hansen-can	4	10	)	)	-RRB-
14-hansen-can	4	11	values	value	NNS
14-hansen-can	4	12	assigned	assign	VBN
14-hansen-can	4	13	to	to	IN
14-hansen-can	4	14	the	the	DT
14-hansen-can	4	15	publi-	publi-	NN
14-hansen-can	4	16	cations	cation	NNS
14-hansen-can	4	17	in	in	IN
14-hansen-can	4	18	MathSciNet1	MathSciNet1	NNP
14-hansen-can	4	19	to	to	TO
14-hansen-can	4	20	create	create	VB
14-hansen-can	4	21	a	a	DT
14-hansen-can	4	22	temporal	temporal	JJ
14-hansen-can	4	23	citation	citation	NN
14-hansen-can	4	24	network	network	NN
14-hansen-can	4	25	which	which	WDT
14-hansen-can	4	26	would	would	MD
14-hansen-can	4	27	allow	allow	VB
14-hansen-can	4	28	me	-PRON-	PRP
14-hansen-can	4	29	to	to	TO
14-hansen-can	4	30	visualize	visualize	VB
14-hansen-can	4	31	how	how	WRB
14-hansen-can	4	32	new	new	JJ
14-hansen-can	4	33	mathematical	mathematical	JJ
14-hansen-can	4	34	subfields	subfield	NNS
14-hansen-can	4	35	were	be	VBD
14-hansen-can	4	36	created	create	VBN
14-hansen-can	4	37	and	and	CC
14-hansen-can	4	38	perhaps	perhaps	RB
14-hansen-can	4	39	even	even	RB
14-hansen-can	4	40	predict	predict	VBP
14-hansen-can	4	41	them	-PRON-	PRP
14-hansen-can	4	42	while	while	IN
14-hansen-can	4	43	they	-PRON-	PRP
14-hansen-can	4	44	were	be	VBD
14-hansen-can	4	45	still	still	RB
14-hansen-can	4	46	in	in	IN
14-hansen-can	4	47	their	-PRON-	PRP$
14-hansen-can	4	48	infancy	infancy	NN
14-hansen-can	4	49	.	.	.
14-hansen-can	5	1	I	-PRON-	PRP
14-hansen-can	5	2	thought	think	VBD
14-hansen-can	5	3	it	-PRON-	PRP
14-hansen-can	5	4	would	would	MD
14-hansen-can	5	5	be	be	VB
14-hansen-can	5	6	an	an	DT
14-hansen-can	5	7	easy	easy	JJ
14-hansen-can	5	8	enough	enough	JJ
14-hansen-can	5	9	project	project	NN
14-hansen-can	5	10	.	.	.
14-hansen-can	6	1	I	-PRON-	PRP
14-hansen-can	6	2	already	already	RB
14-hansen-can	6	3	knew	know	VBD
14-hansen-can	6	4	how	how	WRB
14-hansen-can	6	5	to	to	TO
14-hansen-can	6	6	analyze	analyze	VB
14-hansen-can	6	7	network	network	NN
14-hansen-can	6	8	data	datum	NNS
14-hansen-can	6	9	and	and	CC
14-hansen-can	6	10	the	the	DT
14-hansen-can	6	11	data	datum	NNS
14-hansen-can	6	12	I	-PRON-	PRP
14-hansen-can	6	13	needed	need	VBD
14-hansen-can	6	14	already	already	RB
14-hansen-can	6	15	existed	exist	VBD
14-hansen-can	6	16	,	,	,
14-hansen-can	6	17	I	-PRON-	PRP
14-hansen-can	6	18	just	just	RB
14-hansen-can	6	19	had	have	VBD
14-hansen-can	6	20	to	to	TO
14-hansen-can	6	21	get	get	VB
14-hansen-can	6	22	my	-PRON-	PRP$
14-hansen-can	6	23	hands	hand	NNS
14-hansen-can	6	24	on	on	IN
14-hansen-can	6	25	it	-PRON-	PRP
14-hansen-can	6	26	.	.	.
14-hansen-can	7	1	I	-PRON-	PRP
14-hansen-can	7	2	even	even	RB
14-hansen-can	7	3	sold	sell	VBD
14-hansen-can	7	4	a	a	DT
14-hansen-can	7	5	couple	couple	NN
14-hansen-can	7	6	of	of	IN
14-hansen-can	7	7	my	-PRON-	PRP$
14-hansen-can	7	8	fellow	fellow	JJ
14-hansen-can	7	9	coursemates	coursemate	NNS
14-hansen-can	7	10	on	on	IN
14-hansen-can	7	11	the	the	DT
14-hansen-can	7	12	idea	idea	NN
14-hansen-can	7	13	and	and	CC
14-hansen-can	7	14	they	-PRON-	PRP
14-hansen-can	7	15	agreed	agree	VBD
14-hansen-can	7	16	to	to	TO
14-hansen-can	7	17	work	work	VB
14-hansen-can	7	18	with	with	IN
14-hansen-can	7	19	me	-PRON-	PRP
14-hansen-can	7	20	.	.	.
14-hansen-can	8	1	Of	of	RB
14-hansen-can	8	2	course	course	RB
14-hansen-can	8	3	nothing	nothing	NN
14-hansen-can	8	4	is	be	VBZ
14-hansen-can	8	5	as	as	RB
14-hansen-can	8	6	easy	easy	JJ
14-hansen-can	8	7	as	as	IN
14-hansen-can	8	8	that	that	DT
14-hansen-can	8	9	,	,	,
14-hansen-can	8	10	and	and	CC
14-hansen-can	8	11	numerous	numerous	JJ
14-hansen-can	8	12	requests	request	NNS
14-hansen-can	8	13	for	for	IN
14-hansen-can	8	14	data	datum	NNS
14-hansen-can	8	15	went	go	VBD
14-hansen-can	8	16	without	without	IN
14-hansen-can	8	17	response	response	NN
14-hansen-can	8	18	.	.	.
14-hansen-can	9	1	Even	even	RB
14-hansen-can	9	2	after	after	IN
14-hansen-can	9	3	I	-PRON-	PRP
14-hansen-can	9	4	reached	reach	VBD
14-hansen-can	9	5	out	out	RP
14-hansen-can	9	6	to	to	IN
14-hansen-can	9	7	personal	personal	JJ
14-hansen-can	9	8	contacts	contact	NNS
14-hansen-can	9	9	at	at	IN
14-hansen-can	9	10	MathSciNet	MathSciNet	NNP
14-hansen-can	9	11	,	,	,
14-hansen-can	9	12	we	-PRON-	PRP
14-hansen-can	9	13	came	come	VBD
14-hansen-can	9	14	to	to	TO
14-hansen-can	9	15	understand	understand	VB
14-hansen-can	9	16	we	-PRON-	PRP
14-hansen-can	9	17	would	would	MD
14-hansen-can	9	18	not	not	RB
14-hansen-can	9	19	be	be	VB
14-hansen-can	9	20	getting	get	VBG
14-hansen-can	9	21	the	the	DT
14-hansen-can	9	22	MSC	MSC	NNP
14-hansen-can	9	23	data	datum	NNS
14-hansen-can	9	24	the	the	DT
14-hansen-can	9	25	entire	entire	JJ
14-hansen-can	9	26	project	project	NN
14-hansen-can	9	27	relied	rely	VBN
14-hansen-can	9	28	upon	upon	IN
14-hansen-can	9	29	.	.	.
14-hansen-can	10	1	Not	not	RB
14-hansen-can	10	2	that	that	IN
14-hansen-can	10	3	we	-PRON-	PRP
14-hansen-can	10	4	were	be	VBD
14-hansen-can	10	5	going	go	VBG
14-hansen-can	10	6	to	to	TO
14-hansen-can	10	7	let	let	VB
14-hansen-can	10	8	a	a	DT
14-hansen-can	10	9	little	little	JJ
14-hansen-can	10	10	setback	setback	NN
14-hansen-can	10	11	like	like	UH
14-hansen-can	10	12	not	not	RB
14-hansen-can	10	13	having	have	VBG
14-hansen-can	10	14	the	the	DT
14-hansen-can	10	15	necessary	necessary	JJ
14-hansen-can	10	16	data	datum	NNS
14-hansen-can	10	17	stop	stop	VB
14-hansen-can	10	18	us	-PRON-	PRP
14-hansen-can	10	19	.	.	.
14-hansen-can	11	1	After	after	RB
14-hansen-can	11	2	all	all	RB
14-hansen-can	11	3	,	,	,
14-hansen-can	11	4	this	this	DT
14-hansen-can	11	5	was	be	VBD
14-hansen-can	11	6	early	early	JJ
14-hansen-can	11	7	2018	2018	CD
14-hansen-can	11	8	and	and	CC
14-hansen-can	11	9	there	there	EX
14-hansen-can	11	10	had	have	VBD
14-hansen-can	11	11	already	already	RB
14-hansen-can	11	12	been	be	VBN
14-hansen-can	11	13	years	year	NNS
14-hansen-can	11	14	of	of	IN
14-hansen-can	11	15	stories	story	NNS
14-hansen-can	11	16	about	about	IN
14-hansen-can	11	17	how	how	WRB
14-hansen-can	11	18	artificial	artificial	JJ
14-hansen-can	11	19	intelligence	intelligence	NN
14-hansen-can	11	20	,	,	,
14-hansen-can	11	21	machine	machine	NN
14-hansen-can	11	22	learning	learning	NN
14-hansen-can	11	23	in	in	IN
14-hansen-can	11	24	particular	particular	JJ
14-hansen-can	11	25	,	,	,
14-hansen-can	11	26	was	be	VBD
14-hansen-can	11	27	going	go	VBG
14-hansen-can	11	28	to	to	TO
14-hansen-can	11	29	revolutionize	revolutionize	VB
14-hansen-can	11	30	every	every	DT
14-hansen-can	11	31	aspect	aspect	NN
14-hansen-can	11	32	of	of	IN
14-hansen-can	11	33	our	-PRON-	PRP$
14-hansen-can	11	34	world	world	NN
14-hansen-can	11	35	(	(	-LRB-
14-hansen-can	11	36	Kelly	Kelly	NNP
14-hansen-can	11	37	2014	2014	CD
14-hansen-can	11	38	;	;	:
14-hansen-can	11	39	Clark	Clark	NNP
14-hansen-can	11	40	2015	2015	CD
14-hansen-can	11	41	;	;	:
14-hansen-can	11	42	Parloff	Parloff	NNP
14-hansen-can	11	43	2016	2016	CD
14-hansen-can	11	44	;	;	:
14-hansen-can	11	45	Sangwani	Sangwani	NNP
14-hansen-can	11	46	2017	2017	CD
14-hansen-can	11	47	;	;	:
14-hansen-can	11	48	Tank	tank	NN
14-hansen-can	11	49	2017	2017	CD
14-hansen-can	11	50	)	)	-RRB-
14-hansen-can	11	51	.	.	.
14-hansen-can	12	1	All	all	PDT
14-hansen-can	12	2	the	the	DT
14-hansen-can	12	3	coverage	coverage	NN
14-hansen-can	12	4	made	make	VBD
14-hansen-can	12	5	it	-PRON-	PRP
14-hansen-can	12	6	seem	seem	VB
14-hansen-can	12	7	like	like	IN
14-hansen-can	12	8	AI	AI	NNP
14-hansen-can	12	9	was	be	VBD
14-hansen-can	12	10	not	not	RB
14-hansen-can	12	11	only	only	RB
14-hansen-can	12	12	a	a	DT
14-hansen-can	12	13	tool	tool	NN
14-hansen-can	12	14	with	with	IN
14-hansen-can	12	15	as	as	RB
14-hansen-can	12	16	many	many	JJ
14-hansen-can	12	17	applications	application	NNS
14-hansen-can	12	18	as	as	IN
14-hansen-can	12	19	a	a	DT
14-hansen-can	12	20	hammer	hammer	NN
14-hansen-can	12	21	,	,	,
14-hansen-can	12	22	but	but	CC
14-hansen-can	12	23	that	that	IN
14-hansen-can	12	24	it	-PRON-	PRP
14-hansen-can	12	25	also	also	RB
14-hansen-can	12	26	magically	magically	RB
14-hansen-can	12	27	turned	turn	VBD
14-hansen-can	12	28	all	all	DT
14-hansen-can	12	29	problems	problem	NNS
14-hansen-can	12	30	into	into	IN
14-hansen-can	12	31	nails	nail	NNS
14-hansen-can	12	32	.	.	.
14-hansen-can	13	1	While	while	IN
14-hansen-can	13	2	none	none	NN
14-hansen-can	13	3	of	of	IN
14-hansen-can	13	4	us	-PRON-	PRP
14-hansen-can	13	5	were	be	VBD
14-hansen-can	13	6	AI	AI	NNP
14-hansen-can	13	7	experts	expert	NNS
14-hansen-can	13	8	,	,	,
14-hansen-can	13	9	we	-PRON-	PRP
14-hansen-can	13	10	knew	know	VBD
14-hansen-can	13	11	that	that	DT
14-hansen-can	13	12	machine	machine	NN
14-hansen-can	13	13	learning	learning	NN
14-hansen-can	13	14	was	be	VBD
14-hansen-can	13	15	supposed	suppose	VBN
14-hansen-can	13	16	to	to	TO
14-hansen-can	13	17	be	be	VB
14-hansen-can	13	18	good	good	JJ
14-hansen-can	13	19	at	at	IN
14-hansen-can	13	20	classification	classification	NN
14-hansen-can	13	21	and	and	CC
14-hansen-can	13	22	categorization	categorization	NN
14-hansen-can	13	23	.	.	.
14-hansen-can	14	1	The	the	DT
14-hansen-can	14	2	promise	promise	NN
14-hansen-can	14	3	seemed	seem	VBD
14-hansen-can	14	4	to	to	TO
14-hansen-can	14	5	be	be	VB
14-hansen-can	14	6	that	that	IN
14-hansen-can	14	7	if	if	IN
14-hansen-can	14	8	you	-PRON-	PRP
14-hansen-can	14	9	had	have	VBD
14-hansen-can	14	10	stacks	stack	NNS
14-hansen-can	14	11	of	of	IN
14-hansen-can	14	12	data	datum	NNS
14-hansen-can	14	13	,	,	,
14-hansen-can	14	14	a	a	DT
14-hansen-can	14	15	machine	machine	NN
14-hansen-can	14	16	learning	learn	VBG
14-hansen-can	14	17	algorithm	algorithm	NN
14-hansen-can	14	18	could	could	MD
14-hansen-can	14	19	dive	dive	VB
14-hansen-can	14	20	in	in	RP
14-hansen-can	14	21	,	,	,
14-hansen-can	14	22	find	find	VB
14-hansen-can	14	23	the	the	DT
14-hansen-can	14	24	needles	needle	NNS
14-hansen-can	14	25	,	,	,
14-hansen-can	14	26	and	and	CC
14-hansen-can	14	27	arrange	arrange	VB
14-hansen-can	14	28	them	-PRON-	PRP
14-hansen-can	14	29	into	into	IN
14-hansen-can	14	30	neatly	neatly	RB
14-hansen-can	14	31	divided	divide	VBN
14-hansen-can	14	32	piles	pile	NNS
14-hansen-can	14	33	of	of	IN
14-hansen-can	14	34	similar	similar	JJ
14-hansen-can	14	35	sharpness	sharpness	NN
14-hansen-can	14	36	and	and	CC
14-hansen-can	14	37	length	length	NN
14-hansen-can	14	38	.	.	.
14-hansen-can	15	1	Not	not	RB
14-hansen-can	15	2	only	only	RB
14-hansen-can	15	3	that	that	DT
14-hansen-can	15	4	,	,	,
14-hansen-can	15	5	but	but	CC
14-hansen-can	15	6	there	there	EX
14-hansen-can	15	7	were	be	VBD
14-hansen-can	15	8	pre-	pre-	RB
14-hansen-can	15	9	built	build	VBN
14-hansen-can	15	10	tools	tool	NNS
14-hansen-can	15	11	that	that	WDT
14-hansen-can	15	12	made	make	VBD
14-hansen-can	15	13	it	-PRON-	PRP
14-hansen-can	15	14	so	so	RB
14-hansen-can	15	15	almost	almost	RB
14-hansen-can	15	16	anyone	anyone	NN
14-hansen-can	15	17	could	could	MD
14-hansen-can	15	18	do	do	VB
14-hansen-can	15	19	it	-PRON-	PRP
14-hansen-can	15	20	.	.	.
14-hansen-can	16	1	For	for	IN
14-hansen-can	16	2	a	a	DT
14-hansen-can	16	3	group	group	NN
14-hansen-can	16	4	of	of	IN
14-hansen-can	16	5	people	people	NNS
14-hansen-can	16	6	whose	whose	WP$
14-hansen-can	16	7	project	project	NN
14-hansen-can	16	8	was	be	VBD
14-hansen-can	16	9	on	on	IN
14-hansen-can	16	10	1See	1see	CD
14-hansen-can	16	11	?	?	.
14-hansen-can	16	12	iiTb	iitb	UH
14-hansen-can	16	13	,	,	,
14-hansen-can	16	14	ffK	ffK	NNP
14-hansen-can	16	15	�	�	NNP
14-hansen-can	16	16	i?b+BM2iX	i?b+BM2iX	''
14-hansen-can	16	17	�	�	NNP
14-hansen-can	16	18	KbXQ`;f	KbXQ`;f	NNP
14-hansen-can	16	19	.	.	.
14-hansen-can	16	20	159	159	CD
14-hansen-can	16	21	https://mathscinet.ams.org/	https://mathscinet.ams.org/	NN
14-hansen-can	16	22	160	160	CD
14-hansen-can	16	23	Machine	Machine	NNP
14-hansen-can	16	24	Learning	Learning	NNP
14-hansen-can	16	25	,	,	,
14-hansen-can	16	26	Libraries	Libraries	NNPS
14-hansen-can	16	27	,	,	,
14-hansen-can	16	28	and	and	CC
14-hansen-can	16	29	Cross	Cross	NNP
14-hansen-can	16	30	-	-	NNP
14-hansen-can	16	31	Disciplinary	Disciplinary	NNP
14-hansen-can	16	32	ResearchǔChapter	ResearchǔChapter	NNP
14-hansen-can	16	33	14	14	CD
14-hansen-can	16	34	life	life	NN
14-hansen-can	16	35	support	support	NN
14-hansen-can	16	36	because	because	IN
14-hansen-can	16	37	we	-PRON-	PRP
14-hansen-can	16	38	could	could	MD
14-hansen-can	16	39	not	not	RB
14-hansen-can	16	40	get	get	VB
14-hansen-can	16	41	the	the	DT
14-hansen-can	16	42	categorization	categorization	NN
14-hansen-can	16	43	data	datum	NNS
14-hansen-can	16	44	we	-PRON-	PRP
14-hansen-can	16	45	needed	need	VBD
14-hansen-can	16	46	,	,	,
14-hansen-can	16	47	machine	machine	NN
14-hansen-can	16	48	learning	learning	NN
14-hansen-can	16	49	began	begin	VBD
14-hansen-can	16	50	to	to	TO
14-hansen-can	16	51	look	look	VB
14-hansen-can	16	52	like	like	IN
14-hansen-can	16	53	our	-PRON-	PRP$
14-hansen-can	16	54	only	only	JJ
14-hansen-can	16	55	potential	potential	JJ
14-hansen-can	16	56	savior	savior	NN
14-hansen-can	16	57	.	.	.
14-hansen-can	17	1	So	so	RB
14-hansen-can	17	2	,	,	,
14-hansen-can	17	3	machine	machine	NN
14-hansen-can	17	4	learning	learning	NN
14-hansen-can	17	5	is	be	VBZ
14-hansen-can	17	6	what	what	WP
14-hansen-can	17	7	we	-PRON-	PRP
14-hansen-can	17	8	used	use	VBD
14-hansen-can	17	9	.	.	.
14-hansen-can	18	1	I	-PRON-	PRP
14-hansen-can	18	2	will	will	MD
14-hansen-can	18	3	not	not	RB
14-hansen-can	18	4	go	go	VB
14-hansen-can	18	5	too	too	RB
14-hansen-can	18	6	deep	deep	RB
14-hansen-can	18	7	into	into	IN
14-hansen-can	18	8	the	the	DT
14-hansen-can	18	9	actual	actual	JJ
14-hansen-can	18	10	process	process	NN
14-hansen-can	18	11	,	,	,
14-hansen-can	18	12	but	but	CC
14-hansen-can	18	13	I	-PRON-	PRP
14-hansen-can	18	14	will	will	MD
14-hansen-can	18	15	give	give	VB
14-hansen-can	18	16	a	a	DT
14-hansen-can	18	17	brief	brief	JJ
14-hansen-can	18	18	outline	outline	NN
14-hansen-can	18	19	of	of	IN
14-hansen-can	18	20	the	the	DT
14-hansen-can	18	21	techniques	technique	NNS
14-hansen-can	18	22	we	-PRON-	PRP
14-hansen-can	18	23	employed	employ	VBD
14-hansen-can	18	24	.	.	.
14-hansen-can	19	1	Machine	machine	NN
14-hansen-can	19	2	-	-	HYPH
14-hansen-can	19	3	learning	learning	NN
14-hansen-can	19	4	-	-	HYPH
14-hansen-can	19	5	based	base	VBN
14-hansen-can	19	6	categorization	categorization	NN
14-hansen-can	19	7	needs	need	VBZ
14-hansen-can	19	8	data	datum	NNS
14-hansen-can	19	9	to	to	TO
14-hansen-can	19	10	classify	classify	VB
14-hansen-can	19	11	,	,	,
14-hansen-can	19	12	which	which	WDT
14-hansen-can	19	13	in	in	IN
14-hansen-can	19	14	our	-PRON-	PRP$
14-hansen-can	19	15	case	case	NN
14-hansen-can	19	16	were	be	VBD
14-hansen-can	19	17	mathematics	mathematic	NNS
14-hansen-can	19	18	publications	publication	NNS
14-hansen-can	19	19	.	.	.
14-hansen-can	20	1	While	while	IN
14-hansen-can	20	2	this	this	DT
14-hansen-can	20	3	can	can	MD
14-hansen-can	20	4	be	be	VB
14-hansen-can	20	5	done	do	VBN
14-hansen-can	20	6	with	with	IN
14-hansen-can	20	7	titles	title	NNS
14-hansen-can	20	8	and	and	CC
14-hansen-can	20	9	abstracts	abstract	NNS
14-hansen-can	20	10	we	-PRON-	PRP
14-hansen-can	20	11	wanted	want	VBD
14-hansen-can	20	12	to	to	TO
14-hansen-can	20	13	provide	provide	VB
14-hansen-can	20	14	the	the	DT
14-hansen-can	20	15	machine	machine	NN
14-hansen-can	20	16	with	with	IN
14-hansen-can	20	17	as	as	RB
14-hansen-can	20	18	much	much	JJ
14-hansen-can	20	19	data	datum	NNS
14-hansen-can	20	20	as	as	IN
14-hansen-can	20	21	we	-PRON-	PRP
14-hansen-can	20	22	could	could	MD
14-hansen-can	20	23	,	,	,
14-hansen-can	20	24	so	so	RB
14-hansen-can	20	25	we	-PRON-	PRP
14-hansen-can	20	26	decided	decide	VBD
14-hansen-can	20	27	to	to	TO
14-hansen-can	20	28	work	work	VB
14-hansen-can	20	29	with	with	IN
14-hansen-can	20	30	full	full	JJ
14-hansen-can	20	31	-	-	HYPH
14-hansen-can	20	32	text	text	NN
14-hansen-can	20	33	articles	article	NNS
14-hansen-can	20	34	.	.	.
14-hansen-can	21	1	Since	since	IN
14-hansen-can	21	2	we	-PRON-	PRP
14-hansen-can	21	3	were	be	VBD
14-hansen-can	21	4	at	at	IN
14-hansen-can	21	5	the	the	DT
14-hansen-can	21	6	University	University	NNP
14-hansen-can	21	7	of	of	IN
14-hansen-can	21	8	Wisconsin	Wisconsin	NNP
14-hansen-can	21	9	at	at	IN
14-hansen-can	21	10	the	the	DT
14-hansen-can	21	11	time	time	NN
14-hansen-can	21	12	,	,	,
14-hansen-can	21	13	we	-PRON-	PRP
14-hansen-can	21	14	were	be	VBD
14-hansen-can	21	15	able	able	JJ
14-hansen-can	21	16	to	to	TO
14-hansen-can	21	17	connect	connect	VB
14-hansen-can	21	18	with	with	IN
14-hansen-can	21	19	the	the	DT
14-hansen-can	21	20	team	team	NN
14-hansen-can	21	21	behind	behind	IN
14-hansen-can	21	22	GeoDeepDive2	GeoDeepDive2	NNP
14-hansen-can	21	23	who	who	WP
14-hansen-can	21	24	have	have	VBP
14-hansen-can	21	25	agreements	agreement	NNS
14-hansen-can	21	26	with	with	IN
14-hansen-can	21	27	many	many	JJ
14-hansen-can	21	28	publishers	publisher	NNS
14-hansen-can	21	29	to	to	TO
14-hansen-can	21	30	provide	provide	VB
14-hansen-can	21	31	the	the	DT
14-hansen-can	21	32	full	full	JJ
14-hansen-can	21	33	text	text	NN
14-hansen-can	21	34	of	of	IN
14-hansen-can	21	35	ar-	ar-	DT
14-hansen-can	21	36	ticles	ticle	NNS
14-hansen-can	21	37	for	for	IN
14-hansen-can	21	38	text	text	NN
14-hansen-can	21	39	and	and	CC
14-hansen-can	21	40	data	datum	NNS
14-hansen-can	21	41	mining	mining	NN
14-hansen-can	21	42	research	research	NN
14-hansen-can	21	43	(	(	-LRB-
14-hansen-can	21	44	“	"	``
14-hansen-can	21	45	GeoDeepDive	geodeepdive	NN
14-hansen-can	21	46	:	:	:
14-hansen-can	21	47	Project	Project	NNP
14-hansen-can	21	48	Overview	Overview	NNP
14-hansen-can	21	49	”	"	''
14-hansen-can	21	50	n.d	n.d	NNP
14-hansen-can	21	51	.	.	NNP
14-hansen-can	21	52	)	)	-RRB-
14-hansen-can	21	53	.	.	.
14-hansen-can	22	1	GeoDeepDive	geodeepdive	NN
14-hansen-can	22	2	provided	provide	VBD
14-hansen-can	22	3	us	-PRON-	PRP
14-hansen-can	22	4	with	with	IN
14-hansen-can	22	5	the	the	DT
14-hansen-can	22	6	full	full	JJ
14-hansen-can	22	7	text	text	NN
14-hansen-can	22	8	of	of	IN
14-hansen-can	22	9	22,397	22,397	CD
14-hansen-can	22	10	mathematics	mathematic	NNS
14-hansen-can	22	11	articles	article	NNS
14-hansen-can	22	12	which	which	WDT
14-hansen-can	22	13	we	-PRON-	PRP
14-hansen-can	22	14	used	use	VBD
14-hansen-can	22	15	as	as	IN
14-hansen-can	22	16	our	-PRON-	PRP$
14-hansen-can	22	17	corpus	corpus	NN
14-hansen-can	22	18	.	.	.
14-hansen-can	23	1	In	in	IN
14-hansen-can	23	2	or-	or-	JJ
14-hansen-can	23	3	der	der	NN
14-hansen-can	23	4	to	to	TO
14-hansen-can	23	5	classify	classify	VB
14-hansen-can	23	6	these	these	DT
14-hansen-can	23	7	articles	article	NNS
14-hansen-can	23	8	,	,	,
14-hansen-can	23	9	which	which	WDT
14-hansen-can	23	10	were	be	VBD
14-hansen-can	23	11	already	already	RB
14-hansen-can	23	12	pre	pre	VBN
14-hansen-can	23	13	-	-	VBN
14-hansen-can	23	14	processed	process	VBN
14-hansen-can	23	15	by	by	IN
14-hansen-can	23	16	GeoDeepDive	GeoDeepDive	NNP
14-hansen-can	23	17	with	with	IN
14-hansen-can	23	18	CoreNLP,3	corenlp,3	NN
14-hansen-can	23	19	we	-PRON-	PRP
14-hansen-can	23	20	first	first	RB
14-hansen-can	23	21	used	use	VBD
14-hansen-can	23	22	the	the	DT
14-hansen-can	23	23	Python	Python	NNP
14-hansen-can	23	24	package	package	NN
14-hansen-can	23	25	Gensim4	Gensim4	NNP
14-hansen-can	23	26	to	to	TO
14-hansen-can	23	27	process	process	VB
14-hansen-can	23	28	the	the	DT
14-hansen-can	23	29	articles	article	NNS
14-hansen-can	23	30	into	into	IN
14-hansen-can	23	31	a	a	DT
14-hansen-can	23	32	Python	Python	NNP
14-hansen-can	23	33	-	-	HYPH
14-hansen-can	23	34	friendly	friendly	JJ
14-hansen-can	23	35	format	format	NN
14-hansen-can	23	36	and	and	CC
14-hansen-can	23	37	to	to	TO
14-hansen-can	23	38	remove	remove	VB
14-hansen-can	23	39	stopwords	stopword	NNS
14-hansen-can	23	40	.	.	.
14-hansen-can	24	1	Then	then	RB
14-hansen-can	24	2	we	-PRON-	PRP
14-hansen-can	24	3	randomly	randomly	RB
14-hansen-can	24	4	sampled	sample	VBD
14-hansen-can	24	5	1⁄3	1⁄3	CD
14-hansen-can	24	6	of	of	IN
14-hansen-can	24	7	the	the	DT
14-hansen-can	24	8	corpus	corpus	NNP
14-hansen-can	24	9	to	to	TO
14-hansen-can	24	10	create	create	VB
14-hansen-can	24	11	a	a	DT
14-hansen-can	24	12	topic	topic	JJ
14-hansen-can	24	13	model	model	NN
14-hansen-can	24	14	using	use	VBG
14-hansen-can	24	15	the	the	DT
14-hansen-can	24	16	MALLET5	mallet5	NN
14-hansen-can	24	17	topic	topic	NN
14-hansen-can	24	18	modeling	modeling	NN
14-hansen-can	24	19	tool	tool	NN
14-hansen-can	24	20	.	.	.
14-hansen-can	25	1	Finally	finally	RB
14-hansen-can	25	2	,	,	,
14-hansen-can	25	3	we	-PRON-	PRP
14-hansen-can	25	4	applied	apply	VBD
14-hansen-can	25	5	the	the	DT
14-hansen-can	25	6	model	model	NN
14-hansen-can	25	7	to	to	IN
14-hansen-can	25	8	the	the	DT
14-hansen-can	25	9	remaining	remain	VBG
14-hansen-can	25	10	articles	article	NNS
14-hansen-can	25	11	in	in	IN
14-hansen-can	25	12	our	-PRON-	PRP$
14-hansen-can	25	13	corpus	corpus	NN
14-hansen-can	25	14	.	.	.
14-hansen-can	26	1	We	-PRON-	PRP
14-hansen-can	26	2	then	then	RB
14-hansen-can	26	3	coded	code	VBD
14-hansen-can	26	4	the	the	DT
14-hansen-can	26	5	words	word	NNS
14-hansen-can	26	6	within	within	IN
14-hansen-can	26	7	the	the	DT
14-hansen-can	26	8	generated	generate	VBN
14-hansen-can	26	9	topics	topic	NNS
14-hansen-can	26	10	to	to	IN
14-hansen-can	26	11	subfields	subfield	NNS
14-hansen-can	26	12	within	within	IN
14-hansen-can	26	13	mathe-	mathe-	NNP
14-hansen-can	26	14	matics	matic	NNS
14-hansen-can	26	15	and	and	CC
14-hansen-can	26	16	used	use	VBD
14-hansen-can	26	17	those	those	DT
14-hansen-can	26	18	codes	code	NNS
14-hansen-can	26	19	to	to	IN
14-hansen-can	26	20	assign	assign	VB
14-hansen-can	26	21	articles	article	NNS
14-hansen-can	26	22	a	a	DT
14-hansen-can	26	23	subfield	subfield	JJ
14-hansen-can	26	24	category	category	NN
14-hansen-can	26	25	.	.	.
14-hansen-can	27	1	In	in	IN
14-hansen-can	27	2	order	order	NN
14-hansen-can	27	3	to	to	TO
14-hansen-can	27	4	make	make	VB
14-hansen-can	27	5	sure	sure	JJ
14-hansen-can	27	6	our	-PRON-	PRP$
14-hansen-can	27	7	results	result	NNS
14-hansen-can	27	8	were	be	VBD
14-hansen-can	27	9	not	not	RB
14-hansen-can	27	10	just	just	RB
14-hansen-can	27	11	a	a	DT
14-hansen-can	27	12	one	one	CD
14-hansen-can	27	13	-	-	HYPH
14-hansen-can	27	14	off	off	NN
14-hansen-can	27	15	,	,	,
14-hansen-can	27	16	we	-PRON-	PRP
14-hansen-can	27	17	repeated	repeat	VBD
14-hansen-can	27	18	this	this	DT
14-hansen-can	27	19	process	process	NN
14-hansen-can	27	20	multiple	multiple	JJ
14-hansen-can	27	21	times	time	NNS
14-hansen-can	27	22	and	and	CC
14-hansen-can	27	23	checked	check	VBD
14-hansen-can	27	24	for	for	IN
14-hansen-can	27	25	variance	variance	NN
14-hansen-can	27	26	in	in	IN
14-hansen-can	27	27	the	the	DT
14-hansen-can	27	28	results	result	NNS
14-hansen-can	27	29	.	.	.
14-hansen-can	28	1	There	there	EX
14-hansen-can	28	2	was	be	VBD
14-hansen-can	28	3	none	none	NN
14-hansen-can	28	4	,	,	,
14-hansen-can	28	5	the	the	DT
14-hansen-can	28	6	results	result	NNS
14-hansen-can	28	7	were	be	VBD
14-hansen-can	28	8	uniformly	uniformly	RB
14-hansen-can	28	9	poor	poor	JJ
14-hansen-can	28	10	.	.	.
14-hansen-can	29	1	That	that	DT
14-hansen-can	29	2	might	may	MD
14-hansen-can	29	3	not	not	RB
14-hansen-can	29	4	be	be	VB
14-hansen-can	29	5	entirely	entirely	RB
14-hansen-can	29	6	fair	fair	JJ
14-hansen-can	29	7	.	.	.
14-hansen-can	30	1	There	there	EX
14-hansen-can	30	2	were	be	VBD
14-hansen-can	30	3	interesting	interesting	JJ
14-hansen-can	30	4	aspects	aspect	NNS
14-hansen-can	30	5	to	to	IN
14-hansen-can	30	6	the	the	DT
14-hansen-can	30	7	results	result	NNS
14-hansen-can	30	8	of	of	IN
14-hansen-can	30	9	the	the	DT
14-hansen-can	30	10	topic	topic	JJ
14-hansen-can	30	11	mod-	mod-	NN
14-hansen-can	30	12	eling	eling	NN
14-hansen-can	30	13	,	,	,
14-hansen-can	30	14	but	but	CC
14-hansen-can	30	15	when	when	WRB
14-hansen-can	30	16	it	-PRON-	PRP
14-hansen-can	30	17	came	come	VBD
14-hansen-can	30	18	to	to	IN
14-hansen-can	30	19	categorization	categorization	NN
14-hansen-can	30	20	they	-PRON-	PRP
14-hansen-can	30	21	were	be	VBD
14-hansen-can	30	22	useless	useless	JJ
14-hansen-can	30	23	.	.	.
14-hansen-can	31	1	Of	of	IN
14-hansen-can	31	2	the	the	DT
14-hansen-can	31	3	subfield	subfield	NN
14-hansen-can	31	4	codes	code	NNS
14-hansen-can	31	5	assigned	assign	VBN
14-hansen-can	31	6	to	to	IN
14-hansen-can	31	7	arti-	arti-	NNP
14-hansen-can	31	8	cles	cles	NNP
14-hansen-can	31	9	,	,	,
14-hansen-can	31	10	only	only	RB
14-hansen-can	31	11	two	two	CD
14-hansen-can	31	12	were	be	VBD
14-hansen-can	31	13	ever	ever	RB
14-hansen-can	31	14	the	the	DT
14-hansen-can	31	15	dominant	dominant	JJ
14-hansen-can	31	16	result	result	NN
14-hansen-can	31	17	for	for	IN
14-hansen-can	31	18	any	any	DT
14-hansen-can	31	19	given	give	VBN
14-hansen-can	31	20	article	article	NN
14-hansen-can	31	21	:	:	:
14-hansen-can	31	22	Graph	Graph	NNP
14-hansen-can	31	23	Theory	Theory	NNP
14-hansen-can	31	24	and	and	CC
14-hansen-can	31	25	Undefined	Undefined	NNP
14-hansen-can	31	26	,	,	,
14-hansen-can	31	27	which	which	WDT
14-hansen-can	31	28	does	do	VBZ
14-hansen-can	31	29	not	not	RB
14-hansen-can	31	30	really	really	RB
14-hansen-can	31	31	tell	tell	VB
14-hansen-can	31	32	the	the	DT
14-hansen-can	31	33	whole	whole	JJ
14-hansen-can	31	34	story	story	NN
14-hansen-can	31	35	as	as	IN
14-hansen-can	31	36	Undefined	Undefined	NNP
14-hansen-can	31	37	was	be	VBD
14-hansen-can	31	38	the	the	DT
14-hansen-can	31	39	run	run	NN
14-hansen-can	31	40	-	-	HYPH
14-hansen-can	31	41	away	away	RP
14-hansen-can	31	42	winner	winner	NN
14-hansen-can	31	43	in	in	IN
14-hansen-can	31	44	the	the	DT
14-hansen-can	31	45	article	article	NN
14-hansen-can	31	46	classification	classification	NN
14-hansen-can	31	47	race	race	NN
14-hansen-can	31	48	with	with	IN
14-hansen-can	31	49	more	more	JJR
14-hansen-can	31	50	than	than	IN
14-hansen-can	31	51	70	70	CD
14-hansen-can	31	52	%	%	NN
14-hansen-can	31	53	of	of	IN
14-hansen-can	31	54	articles	article	NNS
14-hansen-can	31	55	classified	classify	VBN
14-hansen-can	31	56	as	as	IN
14-hansen-can	31	57	Undefined	undefined	JJ
14-hansen-can	31	58	in	in	IN
14-hansen-can	31	59	each	each	DT
14-hansen-can	31	60	run	run	NN
14-hansen-can	31	61	,	,	,
14-hansen-can	31	62	including	include	VBG
14-hansen-can	31	63	one	one	CD
14-hansen-can	31	64	for	for	IN
14-hansen-can	31	65	which	which	WDT
14-hansen-can	31	66	it	-PRON-	PRP
14-hansen-can	31	67	hit	hit	VBD
14-hansen-can	31	68	95	95	CD
14-hansen-can	31	69	%	%	NN
14-hansen-can	31	70	.	.	.
14-hansen-can	32	1	The	the	DT
14-hansen-can	32	2	topics	topic	NNS
14-hansen-can	32	3	generated	generate	VBN
14-hansen-can	32	4	by	by	IN
14-hansen-can	32	5	MALLET	MALLET	NNP
14-hansen-can	32	6	were	be	VBD
14-hansen-can	32	7	often	often	RB
14-hansen-can	32	8	plagued	plague	VBN
14-hansen-can	32	9	by	by	IN
14-hansen-can	32	10	gibberish	gibberish	NN
14-hansen-can	32	11	caused	cause	VBN
14-hansen-can	32	12	by	by	IN
14-hansen-can	32	13	equations	equation	NNS
14-hansen-can	32	14	in	in	IN
14-hansen-can	32	15	the	the	DT
14-hansen-can	32	16	mathematics	mathematic	NNS
14-hansen-can	32	17	articles	article	NNS
14-hansen-can	32	18	and	and	CC
14-hansen-can	32	19	there	there	EX
14-hansen-can	32	20	was	be	VBD
14-hansen-can	32	21	at	at	RB
14-hansen-can	32	22	least	least	RBS
14-hansen-can	32	23	one	one	CD
14-hansen-can	32	24	topic	topic	NN
14-hansen-can	32	25	in	in	IN
14-hansen-can	32	26	each	each	DT
14-hansen-can	32	27	run	run	NN
14-hansen-can	32	28	that	that	WDT
14-hansen-can	32	29	was	be	VBD
14-hansen-can	32	30	filled	fill	VBN
14-hansen-can	32	31	with	with	IN
14-hansen-can	32	32	the	the	DT
14-hansen-can	32	33	names	name	NNS
14-hansen-can	32	34	of	of	IN
14-hansen-can	32	35	months	month	NNS
14-hansen-can	32	36	and	and	CC
14-hansen-can	32	37	locations	location	NNS
14-hansen-can	32	38	.	.	.
14-hansen-can	33	1	Add	add	VB
14-hansen-can	33	2	how	how	WRB
14-hansen-can	33	3	the	the	DT
14-hansen-can	33	4	technical	technical	JJ
14-hansen-can	33	5	language	language	NN
14-hansen-can	33	6	of	of	IN
14-hansen-can	33	7	math-	math-	NNP
14-hansen-can	33	8	ematics	ematic	NNS
14-hansen-can	33	9	is	be	VBZ
14-hansen-can	33	10	filled	fill	VBN
14-hansen-can	33	11	with	with	IN
14-hansen-can	33	12	words	word	NNS
14-hansen-can	33	13	that	that	WDT
14-hansen-can	33	14	have	have	VBP
14-hansen-can	33	15	non	non	JJ
14-hansen-can	33	16	-	-	JJ
14-hansen-can	33	17	technical	technical	JJ
14-hansen-can	33	18	definitions	definition	NNS
14-hansen-can	33	19	(	(	-LRB-
14-hansen-can	33	20	for	for	IN
14-hansen-can	33	21	example	example	NN
14-hansen-can	33	22	,	,	,
14-hansen-can	33	23	map	map	NN
14-hansen-can	33	24	or	or	CC
14-hansen-can	33	25	space	space	NN
14-hansen-can	33	26	)	)	-RRB-
14-hansen-can	33	27	,	,	,
14-hansen-can	33	28	or	or	CC
14-hansen-can	33	29	words	word	NNS
14-hansen-can	33	30	which	which	WDT
14-hansen-can	33	31	have	have	VBP
14-hansen-can	33	32	their	-PRON-	PRP$
14-hansen-can	33	33	own	own	JJ
14-hansen-can	33	34	subfield	subfield	NN
14-hansen-can	33	35	-	-	HYPH
14-hansen-can	33	36	specific	specific	JJ
14-hansen-can	33	37	meanings	meaning	NNS
14-hansen-can	33	38	(	(	-LRB-
14-hansen-can	33	39	such	such	JJ
14-hansen-can	33	40	as	as	IN
14-hansen-can	33	41	homomorphism	homomorphism	NN
14-hansen-can	33	42	or	or	CC
14-hansen-can	33	43	degree	degree	NN
14-hansen-can	33	44	)	)	-RRB-
14-hansen-can	33	45	,	,	,
14-hansen-can	33	46	both	both	DT
14-hansen-can	33	47	of	of	IN
14-hansen-can	33	48	which	which	WDT
14-hansen-can	33	49	frustrate	frustrate	VBP
14-hansen-can	33	50	attempts	attempt	NNS
14-hansen-can	33	51	to	to	TO
14-hansen-can	33	52	code	code	VB
14-hansen-can	33	53	a	a	DT
14-hansen-can	33	54	subfield	subfield	NN
14-hansen-can	33	55	.	.	.
14-hansen-can	34	1	These	these	DT
14-hansen-can	34	2	issues	issue	NNS
14-hansen-can	34	3	help	help	VBP
14-hansen-can	34	4	make	make	VB
14-hansen-can	34	5	it	-PRON-	PRP
14-hansen-can	34	6	clear	clear	JJ
14-hansen-can	34	7	why	why	WRB
14-hansen-can	34	8	so	so	RB
14-hansen-can	34	9	many	many	JJ
14-hansen-can	34	10	arti-	arti-	JJ
14-hansen-can	34	11	cles	cles	NNP
14-hansen-can	34	12	ended	end	VBD
14-hansen-can	34	13	up	up	RP
14-hansen-can	34	14	as	as	IN
14-hansen-can	34	15	“	"	``
14-hansen-can	34	16	Undefined	undefined	JJ
14-hansen-can	34	17	.	.	.
14-hansen-can	34	18	”	"	''
14-hansen-can	34	19	Even	even	RB
14-hansen-can	34	20	for	for	IN
14-hansen-can	34	21	the	the	DT
14-hansen-can	34	22	one	one	CD
14-hansen-can	34	23	subfield	subfield	NN
14-hansen-can	34	24	which	which	WDT
14-hansen-can	34	25	had	have	VBD
14-hansen-can	34	26	a	a	DT
14-hansen-can	34	27	unique	unique	JJ
14-hansen-can	34	28	enough	enough	JJ
14-hansen-can	34	29	vocabulary	vocabulary	NN
14-hansen-can	34	30	for	for	IN
14-hansen-can	34	31	our	-PRON-	PRP$
14-hansen-can	34	32	topic	topic	JJ
14-hansen-can	34	33	model	model	NN
14-hansen-can	34	34	to	to	TO
14-hansen-can	34	35	partially	partially	RB
14-hansen-can	34	36	be	be	VB
14-hansen-can	34	37	able	able	JJ
14-hansen-can	34	38	to	to	TO
14-hansen-can	34	39	identify	identify	VB
14-hansen-can	34	40	,	,	,
14-hansen-can	34	41	Graph	Graph	NNP
14-hansen-can	34	42	Theory	Theory	NNP
14-hansen-can	34	43	,	,	,
14-hansen-can	34	44	the	the	DT
14-hansen-can	34	45	results	result	NNS
14-hansen-can	34	46	were	be	VBD
14-hansen-can	34	47	marginally	marginally	RB
14-hansen-can	34	48	positive	positive	JJ
14-hansen-can	34	49	at	at	IN
14-hansen-can	34	50	best	good	JJS
14-hansen-can	34	51	.	.	.
14-hansen-can	35	1	We	-PRON-	PRP
14-hansen-can	35	2	were	be	VBD
14-hansen-can	35	3	able	able	JJ
14-hansen-can	35	4	to	to	TO
14-hansen-can	35	5	obtain	obtain	VB
14-hansen-can	35	6	Mathematical	Mathematical	NNP
14-hansen-can	35	7	Subject	Subject	NNP
14-hansen-can	35	8	Classification	Classification	NNP
14-hansen-can	35	9	(	(	-LRB-
14-hansen-can	35	10	MSC	MSC	NNP
14-hansen-can	35	11	)	)	-RRB-
14-hansen-can	35	12	values	value	VBZ
14-hansen-can	35	13	for	for	IN
14-hansen-can	35	14	around	around	IN
14-hansen-can	35	15	10	10	CD
14-hansen-can	35	16	%	%	NN
14-hansen-can	35	17	of	of	IN
14-hansen-can	35	18	our	-PRON-	PRP$
14-hansen-can	35	19	corpus	corpus	NN
14-hansen-can	35	20	.	.	.
14-hansen-can	36	1	When	when	WRB
14-hansen-can	36	2	we	-PRON-	PRP
14-hansen-can	36	3	compared	compare	VBD
14-hansen-can	36	4	the	the	DT
14-hansen-can	36	5	articles	article	NNS
14-hansen-can	36	6	we	-PRON-	PRP
14-hansen-can	36	7	categorized	categorize	VBD
14-hansen-can	36	8	as	as	IN
14-hansen-can	36	9	Graph	Graph	NNP
14-hansen-can	36	10	Theory	Theory	NNP
14-hansen-can	36	11	to	to	IN
14-hansen-can	36	12	the	the	DT
14-hansen-can	36	13	articles	article	NNS
14-hansen-can	36	14	which	which	WDT
14-hansen-can	36	15	had	have	VBD
14-hansen-can	36	16	been	be	VBN
14-hansen-can	36	17	assigned	assign	VBN
14-hansen-can	36	18	the	the	DT
14-hansen-can	36	19	MSC	MSC	NNP
14-hansen-can	36	20	value	value	NN
14-hansen-can	36	21	for	for	IN
14-hansen-can	36	22	Graph	Graph	NNP
14-hansen-can	36	23	Theory	Theory	NNP
14-hansen-can	36	24	(	(	-LRB-
14-hansen-can	36	25	05Cxx	05Cxx	NNP
14-hansen-can	36	26	)	)	-RRB-
14-hansen-can	36	27	,	,	,
14-hansen-can	36	28	we	-PRON-	PRP
14-hansen-can	36	29	found	find	VBD
14-hansen-can	36	30	we	-PRON-	PRP
14-hansen-can	36	31	had	have	VBD
14-hansen-can	36	32	a	a	DT
14-hansen-can	36	33	textbook	textbook	NN
14-hansen-can	36	34	recall	recall	NN
14-hansen-can	36	35	-	-	HYPH
14-hansen-can	36	36	versus	versus	IN
14-hansen-can	36	37	-	-	HYPH
14-hansen-can	36	38	precision	precision	NN
14-hansen-can	36	39	problem	problem	NN
14-hansen-can	36	40	.	.	.
14-hansen-can	37	1	We	-PRON-	PRP
14-hansen-can	37	2	could	could	MD
14-hansen-can	37	3	either	either	RB
14-hansen-can	37	4	correctly	correctly	RB
14-hansen-can	37	5	categorize	categorize	VB
14-hansen-can	37	6	nearly	nearly	RB
14-hansen-can	37	7	all	all	DT
14-hansen-can	37	8	of	of	IN
14-hansen-can	37	9	the	the	DT
14-hansen-can	37	10	Graph	Graph	NNP
14-hansen-can	37	11	Theory	Theory	NNP
14-hansen-can	37	12	articles	article	VBZ
14-hansen-can	37	13	with	with	IN
14-hansen-can	37	14	a	a	DT
14-hansen-can	37	15	very	very	RB
14-hansen-can	37	16	high	high	JJ
14-hansen-can	37	17	rate	rate	NN
14-hansen-can	37	18	of	of	IN
14-hansen-can	37	19	false	false	JJ
14-hansen-can	37	20	positives	positive	NNS
14-hansen-can	37	21	(	(	-LRB-
14-hansen-can	37	22	high	high	JJ
14-hansen-can	37	23	recall	recall	NN
14-hansen-can	37	24	and	and	CC
14-hansen-can	37	25	low	low	JJ
14-hansen-can	37	26	precision	precision	NN
14-hansen-can	37	27	)	)	-RRB-
14-hansen-can	37	28	or	or	CC
14-hansen-can	37	29	we	-PRON-	PRP
14-hansen-can	37	30	could	could	MD
14-hansen-can	37	31	almost	almost	RB
14-hansen-can	37	32	never	never	RB
14-hansen-can	37	33	incorrectly	incorrectly	RB
14-hansen-can	37	34	categorize	categorize	VB
14-hansen-can	37	35	an	an	DT
14-hansen-can	37	36	article	article	NN
14-hansen-can	37	37	as	as	IN
14-hansen-can	37	38	Graph	Graph	NNP
14-hansen-can	37	39	Theory	Theory	NNP
14-hansen-can	37	40	,	,	,
14-hansen-can	37	41	but	but	CC
14-hansen-can	37	42	miss	miss	VB
14-hansen-can	37	43	over	over	IN
14-hansen-can	37	44	30	30	CD
14-hansen-can	37	45	%	%	NN
14-hansen-can	37	46	that	that	IN
14-hansen-can	37	47	we	-PRON-	PRP
14-hansen-can	37	48	should	should	MD
14-hansen-can	37	49	have	have	VB
14-hansen-can	37	50	categorized	categorize	VBN
14-hansen-can	37	51	as	as	IN
14-hansen-can	37	52	Graph	Graph	NNP
14-hansen-can	37	53	Theory	Theory	NNP
14-hansen-can	37	54	(	(	-LRB-
14-hansen-can	37	55	high	high	JJ
14-hansen-can	37	56	precision	precision	NN
14-hansen-can	37	57	and	and	CC
14-hansen-can	37	58	low	low	JJ
14-hansen-can	37	59	recall	recall	NN
14-hansen-can	37	60	)	)	-RRB-
14-hansen-can	37	61	.	.	.
14-hansen-can	38	1	Needless	needless	JJ
14-hansen-can	38	2	to	to	TO
14-hansen-can	38	3	say	say	VB
14-hansen-can	38	4	,	,	,
14-hansen-can	38	5	we	-PRON-	PRP
14-hansen-can	38	6	were	be	VBD
14-hansen-can	38	7	not	not	RB
14-hansen-can	38	8	able	able	JJ
14-hansen-can	38	9	to	to	TO
14-hansen-can	38	10	create	create	VB
14-hansen-can	38	11	the	the	DT
14-hansen-can	38	12	temporal	temporal	JJ
14-hansen-can	38	13	subfield	subfield	NN
14-hansen-can	38	14	network	network	NN
14-hansen-can	38	15	I	-PRON-	PRP
14-hansen-can	38	16	had	have	VBD
14-hansen-can	38	17	imagined	imagine	VBN
14-hansen-can	38	18	.	.	.
14-hansen-can	39	1	While	while	IN
14-hansen-can	39	2	we	-PRON-	PRP
14-hansen-can	39	3	could	could	MD
14-hansen-can	39	4	reasonably	reasonably	RB
14-hansen-can	39	5	claim	claim	VB
14-hansen-can	39	6	that	that	IN
14-hansen-can	39	7	we	-PRON-	PRP
14-hansen-can	39	8	learned	learn	VBD
14-hansen-can	39	9	very	very	RB
14-hansen-can	39	10	interesting	interesting	JJ
14-hansen-can	39	11	things	thing	NNS
14-hansen-can	39	12	about	about	IN
14-hansen-can	39	13	the	the	DT
14-hansen-can	39	14	language	language	NN
14-hansen-can	39	15	of	of	IN
14-hansen-can	39	16	mathematics	mathematic	NNS
14-hansen-can	39	17	and	and	CC
14-hansen-can	39	18	its	-PRON-	PRP$
14-hansen-can	39	19	subfields	subfield	NNS
14-hansen-can	39	20	,	,	,
14-hansen-can	39	21	we	-PRON-	PRP
14-hansen-can	39	22	could	could	MD
14-hansen-can	39	23	not	not	RB
14-hansen-can	39	24	claim	claim	VB
14-hansen-can	39	25	we	-PRON-	PRP
14-hansen-can	39	26	even	even	RB
14-hansen-can	39	27	came	come	VBD
14-hansen-can	39	28	close	close	RB
14-hansen-can	39	29	to	to	IN
14-hansen-can	39	30	automatically	automatically	RB
14-hansen-can	39	31	catego-	catego-	JJ
14-hansen-can	39	32	rizing	rizing	JJ
14-hansen-can	39	33	mathematics	mathematic	NNS
14-hansen-can	39	34	articles	article	NNS
14-hansen-can	39	35	.	.	.
14-hansen-can	40	1	When	when	WRB
14-hansen-can	40	2	we	-PRON-	PRP
14-hansen-can	40	3	had	have	VBD
14-hansen-can	40	4	to	to	TO
14-hansen-can	40	5	report	report	VB
14-hansen-can	40	6	back	back	RP
14-hansen-can	40	7	on	on	IN
14-hansen-can	40	8	our	-PRON-	PRP$
14-hansen-can	40	9	work	work	NN
14-hansen-can	40	10	at	at	IN
14-hansen-can	40	11	the	the	DT
14-hansen-can	40	12	end	end	NN
14-hansen-can	40	13	of	of	IN
14-hansen-can	40	14	the	the	DT
14-hansen-can	40	15	course	course	NN
14-hansen-can	40	16	,	,	,
14-hansen-can	40	17	2See	2see	CD
14-hansen-can	40	18	?	?	.
14-hansen-can	40	19	iiTb	iitb	UH
14-hansen-can	40	20	,	,	,
14-hansen-can	40	21	ff;2Q/22T	ff;2q/22t	JJ
14-hansen-can	40	22	/	/	SYM
14-hansen-can	40	23	Bp2XQ`;f	bp2xq`;f	NN
14-hansen-can	40	24	.	.	.
14-hansen-can	40	25	3See	3see	CD
14-hansen-can	40	26	?	?	.
14-hansen-can	40	27	iiTb	iitb	UH
14-hansen-can	40	28	,	,	,
14-hansen-can	40	29	ffbi	ffbi	NN
14-hansen-can	40	30	�	�	NNP
14-hansen-can	40	31	M7Q`/MHTX;Bi?m#XBQf*Q`2LGSf	M7Q`/MHTX;Bi?m#XBQf*Q`2LGSf	NNP
14-hansen-can	40	32	.	.	.
14-hansen-can	41	1	4See	4see	LS
14-hansen-can	41	2	?	?	.
14-hansen-can	41	3	iiTb	iitb	UH
14-hansen-can	41	4	,	,	,
14-hansen-can	41	5	ff`	ff`	ADD
14-hansen-can	41	6	�	�	NNS
14-hansen-can	41	7	/BK`2?m`2FX+QKf;2MbBKf	/BK`2?m`2FX+QKf;2MbBKf	.
14-hansen-can	41	8	.	.	.
14-hansen-can	42	1	5See	5see	LS
14-hansen-can	42	2	?	?	.
14-hansen-can	42	3	iiT	iit	JJ
14-hansen-can	42	4	,	,	,
14-hansen-can	42	5	ffK	ffK	NNP
14-hansen-can	42	6	�	�	NNP
14-hansen-can	42	7	HH2iX+bXmK	HH2iX+bXmK	VBZ
14-hansen-can	42	8	�	�	NNP
14-hansen-can	42	9	bbX2	bbx2	NN
14-hansen-can	42	10	/	/	SYM
14-hansen-can	42	11	mfiQTB+bXT?T.	mfiqtb+bxt?t.	NN
14-hansen-can	43	1	https://geodeepdive.org/	https://geodeepdive.org/	LS
14-hansen-can	43	2	https://stanfordnlp.github.io/CoreNLP/	https://stanfordnlp.github.io/CoreNLP/	NNPS
14-hansen-can	43	3	https://radimrehurek.com/gensim/	https://radimrehurek.com/gensim/	PRP$
14-hansen-can	43	4	http://mallet.cs.umass.edu/topics.php	http://mallet.cs.umass.edu/topics.php	ADD
14-hansen-can	43	5	Hansen	Hansen	NNP
14-hansen-can	43	6	161	161	CD
14-hansen-can	43	7	our	-PRON-	PRP$
14-hansen-can	43	8	main	main	JJ
14-hansen-can	43	9	result	result	NN
14-hansen-can	43	10	was	be	VBD
14-hansen-can	43	11	that	that	IN
14-hansen-can	43	12	basic	basic	JJ
14-hansen-can	43	13	,	,	,
14-hansen-can	43	14	off	off	IN
14-hansen-can	43	15	-	-	HYPH
14-hansen-can	43	16	the	the	DT
14-hansen-can	43	17	-	-	HYPH
14-hansen-can	43	18	shelf	shelf	NN
14-hansen-can	43	19	topic	topic	NN
14-hansen-can	43	20	modelling	modelling	NN
14-hansen-can	43	21	does	do	VBZ
14-hansen-can	43	22	not	not	RB
14-hansen-can	43	23	work	work	VB
14-hansen-can	43	24	well	well	RB
14-hansen-can	43	25	when	when	WRB
14-hansen-can	43	26	it	-PRON-	PRP
14-hansen-can	43	27	comes	come	VBZ
14-hansen-can	43	28	to	to	IN
14-hansen-can	43	29	highly	highly	RB
14-hansen-can	43	30	technical	technical	JJ
14-hansen-can	43	31	articles	article	NNS
14-hansen-can	43	32	from	from	IN
14-hansen-can	43	33	subjects	subject	NNS
14-hansen-can	43	34	like	like	IN
14-hansen-can	43	35	mathematics	mathematic	NNS
14-hansen-can	43	36	.	.	.
14-hansen-can	44	1	It	-PRON-	PRP
14-hansen-can	44	2	was	be	VBD
14-hansen-can	44	3	also	also	RB
14-hansen-can	44	4	a	a	DT
14-hansen-can	44	5	welcome	welcome	JJ
14-hansen-can	44	6	lesson	lesson	NN
14-hansen-can	44	7	in	in	IN
14-hansen-can	44	8	not	not	RB
14-hansen-can	44	9	believing	believe	VBG
14-hansen-can	44	10	the	the	DT
14-hansen-can	44	11	hype	hype	NN
14-hansen-can	44	12	of	of	IN
14-hansen-can	44	13	machine	machine	NN
14-hansen-can	44	14	learning	learning	NN
14-hansen-can	44	15	,	,	,
14-hansen-can	44	16	even	even	RB
14-hansen-can	44	17	when	when	WRB
14-hansen-can	44	18	a	a	DT
14-hansen-can	44	19	problem	problem	NN
14-hansen-can	44	20	looks	look	VBZ
14-hansen-can	44	21	exactly	exactly	RB
14-hansen-can	44	22	like	like	IN
14-hansen-can	44	23	the	the	DT
14-hansen-can	44	24	kind	kind	JJ
14-hansen-can	44	25	machine	machine	NN
14-hansen-can	44	26	learning	learning	NN
14-hansen-can	44	27	was	be	VBD
14-hansen-can	44	28	supposed	suppose	VBN
14-hansen-can	44	29	to	to	TO
14-hansen-can	44	30	excel	excel	VB
14-hansen-can	44	31	at	at	IN
14-hansen-can	44	32	solving	solve	VBG
14-hansen-can	44	33	.	.	.
14-hansen-can	45	1	While	while	IN
14-hansen-can	45	2	we	-PRON-	PRP
14-hansen-can	45	3	had	have	VBD
14-hansen-can	45	4	a	a	DT
14-hansen-can	45	5	hammer	hammer	NN
14-hansen-can	45	6	and	and	CC
14-hansen-can	45	7	our	-PRON-	PRP$
14-hansen-can	45	8	problem	problem	NN
14-hansen-can	45	9	looked	look	VBD
14-hansen-can	45	10	like	like	IN
14-hansen-can	45	11	a	a	DT
14-hansen-can	45	12	nail	nail	NN
14-hansen-can	45	13	,	,	,
14-hansen-can	45	14	it	-PRON-	PRP
14-hansen-can	45	15	seemed	seem	VBD
14-hansen-can	45	16	that	that	IN
14-hansen-can	45	17	the	the	DT
14-hansen-can	45	18	former	former	JJ
14-hansen-can	45	19	was	be	VBD
14-hansen-can	45	20	a	a	DT
14-hansen-can	45	21	ball	ball	NN
14-hansen-can	45	22	peen	peen	NN
14-hansen-can	45	23	and	and	CC
14-hansen-can	45	24	the	the	DT
14-hansen-can	45	25	latter	latter	JJ
14-hansen-can	45	26	a	a	DT
14-hansen-can	45	27	railroad	railroad	NN
14-hansen-can	45	28	tie	tie	NN
14-hansen-can	45	29	.	.	.
14-hansen-can	46	1	In	in	IN
14-hansen-can	46	2	the	the	DT
14-hansen-can	46	3	end	end	NN
14-hansen-can	46	4	,	,	,
14-hansen-can	46	5	even	even	RB
14-hansen-can	46	6	in	in	IN
14-hansen-can	46	7	the	the	DT
14-hansen-can	46	8	land	land	NN
14-hansen-can	46	9	of	of	IN
14-hansen-can	46	10	hammers	hammer	NNS
14-hansen-can	46	11	and	and	CC
14-hansen-can	46	12	nails	nail	NNS
14-hansen-can	46	13	,	,	,
14-hansen-can	46	14	the	the	DT
14-hansen-can	46	15	tool	tool	NN
14-hansen-can	46	16	has	have	VBZ
14-hansen-can	46	17	to	to	TO
14-hansen-can	46	18	match	match	VB
14-hansen-can	46	19	the	the	DT
14-hansen-can	46	20	task	task	NN
14-hansen-can	46	21	.	.	.
14-hansen-can	47	1	Though	though	IN
14-hansen-can	47	2	we	-PRON-	PRP
14-hansen-can	47	3	failed	fail	VBD
14-hansen-can	47	4	to	to	TO
14-hansen-can	47	5	accomplish	accomplish	VB
14-hansen-can	47	6	automated	automate	VBN
14-hansen-can	47	7	categorization	categorization	NN
14-hansen-can	47	8	of	of	IN
14-hansen-can	47	9	mathematics	mathematic	NNS
14-hansen-can	47	10	,	,	,
14-hansen-can	47	11	we	-PRON-	PRP
14-hansen-can	47	12	were	be	VBD
14-hansen-can	47	13	dilettantes	dilettante	NNS
14-hansen-can	47	14	in	in	IN
14-hansen-can	47	15	the	the	DT
14-hansen-can	47	16	world	world	NN
14-hansen-can	47	17	of	of	IN
14-hansen-can	47	18	machine	machine	NN
14-hansen-can	47	19	learning	learning	NN
14-hansen-can	47	20	.	.	.
14-hansen-can	48	1	I	-PRON-	PRP
14-hansen-can	48	2	believe	believe	VBP
14-hansen-can	48	3	our	-PRON-	PRP$
14-hansen-can	48	4	project	project	NN
14-hansen-can	48	5	is	be	VBZ
14-hansen-can	48	6	a	a	DT
14-hansen-can	48	7	good	good	JJ
14-hansen-can	48	8	example	example	NN
14-hansen-can	48	9	of	of	IN
14-hansen-can	48	10	how	how	WRB
14-hansen-can	48	11	machine	machine	NN
14-hansen-can	48	12	learning	learning	NN
14-hansen-can	48	13	is	be	VBZ
14-hansen-can	48	14	still	still	RB
14-hansen-can	48	15	a	a	DT
14-hansen-can	48	16	long	long	JJ
14-hansen-can	48	17	way	way	NN
14-hansen-can	48	18	from	from	IN
14-hansen-can	48	19	being	be	VBG
14-hansen-can	48	20	the	the	DT
14-hansen-can	48	21	magic	magic	JJ
14-hansen-can	48	22	tool	tool	NN
14-hansen-can	48	23	as	as	IN
14-hansen-can	48	24	some	some	DT
14-hansen-can	48	25	,	,	,
14-hansen-can	48	26	though	though	IN
14-hansen-can	48	27	not	not	RB
14-hansen-can	48	28	all	all	DT
14-hansen-can	48	29	(	(	-LRB-
14-hansen-can	48	30	Rahimi	Rahimi	NNP
14-hansen-can	48	31	and	and	CC
14-hansen-can	48	32	Recht	Recht	NNP
14-hansen-can	48	33	2017	2017	CD
14-hansen-can	48	34	)	)	-RRB-
14-hansen-can	48	35	,	,	,
14-hansen-can	48	36	have	have	VBP
14-hansen-can	48	37	portrayed	portray	VBN
14-hansen-can	48	38	it	-PRON-	PRP
14-hansen-can	48	39	.	.	.
14-hansen-can	49	1	Let	let	VB
14-hansen-can	49	2	us	-PRON-	PRP
14-hansen-can	49	3	look	look	VB
14-hansen-can	49	4	at	at	IN
14-hansen-can	49	5	what	what	WP
14-hansen-can	49	6	happens	happen	VBZ
14-hansen-can	49	7	when	when	WRB
14-hansen-can	49	8	smarter	smart	JJR
14-hansen-can	49	9	and	and	CC
14-hansen-can	49	10	more	more	RBR
14-hansen-can	49	11	capable	capable	JJ
14-hansen-can	49	12	minds	mind	NNS
14-hansen-can	49	13	tackle	tackle	VBP
14-hansen-can	49	14	the	the	DT
14-hansen-can	49	15	problem	problem	NN
14-hansen-can	49	16	of	of	IN
14-hansen-can	49	17	classifying	classify	VBG
14-hansen-can	49	18	mathe-	mathe-	NN
14-hansen-can	49	19	matics	matic	NNS
14-hansen-can	49	20	and	and	CC
14-hansen-can	49	21	other	other	JJ
14-hansen-can	49	22	highly	highly	RB
14-hansen-can	49	23	technical	technical	JJ
14-hansen-can	49	24	subjects	subject	NNS
14-hansen-can	49	25	using	use	VBG
14-hansen-can	49	26	advanced	advanced	JJ
14-hansen-can	49	27	machine	machine	NN
14-hansen-can	49	28	learning	learning	NN
14-hansen-can	49	29	techniques	technique	NNS
14-hansen-can	49	30	.	.	.
14-hansen-can	50	1	Finding	find	VBG
14-hansen-can	50	2	the	the	DT
14-hansen-can	50	3	Right	Right	NNP
14-hansen-can	50	4	Hammer	Hammer	NNP
14-hansen-can	50	5	To	to	TO
14-hansen-can	50	6	illustrate	illustrate	VB
14-hansen-can	50	7	the	the	DT
14-hansen-can	50	8	quest	quest	NN
14-hansen-can	50	9	to	to	TO
14-hansen-can	50	10	find	find	VB
14-hansen-can	50	11	the	the	DT
14-hansen-can	50	12	right	right	JJ
14-hansen-can	50	13	hammer	hammer	NN
14-hansen-can	50	14	I	-PRON-	PRP
14-hansen-can	50	15	am	be	VBP
14-hansen-can	50	16	going	go	VBG
14-hansen-can	50	17	to	to	TO
14-hansen-can	50	18	focus	focus	VB
14-hansen-can	50	19	on	on	IN
14-hansen-can	50	20	three	three	CD
14-hansen-can	50	21	different	different	JJ
14-hansen-can	50	22	projects	project	NNS
14-hansen-can	50	23	that	that	WDT
14-hansen-can	50	24	tackled	tackle	VBD
14-hansen-can	50	25	the	the	DT
14-hansen-can	50	26	automated	automate	VBN
14-hansen-can	50	27	categorization	categorization	NN
14-hansen-can	50	28	of	of	IN
14-hansen-can	50	29	highly	highly	RB
14-hansen-can	50	30	technical	technical	JJ
14-hansen-can	50	31	content	content	NN
14-hansen-can	50	32	,	,	,
14-hansen-can	50	33	two	two	CD
14-hansen-can	50	34	of	of	IN
14-hansen-can	50	35	which	which	WDT
14-hansen-can	50	36	also	also	RB
14-hansen-can	50	37	attempted	attempt	VBD
14-hansen-can	50	38	to	to	TO
14-hansen-can	50	39	categorize	categorize	VB
14-hansen-can	50	40	mathematical	mathematical	JJ
14-hansen-can	50	41	content	content	NN
14-hansen-can	50	42	and	and	CC
14-hansen-can	50	43	one	one	CD
14-hansen-can	50	44	that	that	WDT
14-hansen-can	50	45	looked	look	VBD
14-hansen-can	50	46	to	to	TO
14-hansen-can	50	47	categorize	categorize	VB
14-hansen-can	50	48	scholarly	scholarly	NNP
14-hansen-can	50	49	works	work	NNS
14-hansen-can	50	50	in	in	IN
14-hansen-can	50	51	general	general	JJ
14-hansen-can	50	52	.	.	.
14-hansen-can	51	1	These	these	DT
14-hansen-can	51	2	three	three	CD
14-hansen-can	51	3	projects	project	NNS
14-hansen-can	51	4	provide	provide	VBP
14-hansen-can	51	5	examples	example	NNS
14-hansen-can	51	6	of	of	IN
14-hansen-can	51	7	many	many	JJ
14-hansen-can	51	8	of	of	IN
14-hansen-can	51	9	the	the	DT
14-hansen-can	51	10	approaches	approach	NNS
14-hansen-can	51	11	and	and	CC
14-hansen-can	51	12	practices	practice	NNS
14-hansen-can	51	13	employed	employ	VBN
14-hansen-can	51	14	by	by	IN
14-hansen-can	51	15	ex-	ex-	DT
14-hansen-can	51	16	perts	pert	NNS
14-hansen-can	51	17	in	in	IN
14-hansen-can	51	18	automated	automated	JJ
14-hansen-can	51	19	classification	classification	NN
14-hansen-can	51	20	and	and	CC
14-hansen-can	51	21	demonstrate	demonstrate	VB
14-hansen-can	51	22	the	the	DT
14-hansen-can	51	23	two	two	CD
14-hansen-can	51	24	main	main	JJ
14-hansen-can	51	25	paths	path	NNS
14-hansen-can	51	26	that	that	WDT
14-hansen-can	51	27	these	these	DT
14-hansen-can	51	28	types	type	NNS
14-hansen-can	51	29	of	of	IN
14-hansen-can	51	30	projects	project	NNS
14-hansen-can	51	31	follow	follow	VBP
14-hansen-can	51	32	to	to	TO
14-hansen-can	51	33	accomplish	accomplish	VB
14-hansen-can	51	34	their	-PRON-	PRP$
14-hansen-can	51	35	goals	goal	NNS
14-hansen-can	51	36	.	.	.
14-hansen-can	52	1	Since	since	IN
14-hansen-can	52	2	we	-PRON-	PRP
14-hansen-can	52	3	have	have	VBP
14-hansen-can	52	4	been	be	VBN
14-hansen-can	52	5	discussing	discuss	VBG
14-hansen-can	52	6	mathematics	mathematic	NNS
14-hansen-can	52	7	,	,	,
14-hansen-can	52	8	let	let	VB
14-hansen-can	52	9	us	-PRON-	PRP
14-hansen-can	52	10	start	start	VB
14-hansen-can	52	11	with	with	IN
14-hansen-can	52	12	those	those	DT
14-hansen-can	52	13	two	two	CD
14-hansen-can	52	14	projects	project	NNS
14-hansen-can	52	15	.	.	.
14-hansen-can	53	1	Both	both	DT
14-hansen-can	53	2	projects	project	NNS
14-hansen-can	53	3	began	begin	VBD
14-hansen-can	53	4	because	because	IN
14-hansen-can	53	5	the	the	DT
14-hansen-can	53	6	participants	participant	NNS
14-hansen-can	53	7	were	be	VBD
14-hansen-can	53	8	struggling	struggle	VBG
14-hansen-can	53	9	to	to	TO
14-hansen-can	53	10	categorize	categorize	VB
14-hansen-can	53	11	mathematics	mathematic	NNS
14-hansen-can	53	12	pub-	pub-	JJ
14-hansen-can	53	13	lications	lication	NNS
14-hansen-can	53	14	so	so	IN
14-hansen-can	53	15	they	-PRON-	PRP
14-hansen-can	53	16	would	would	MD
14-hansen-can	53	17	be	be	VB
14-hansen-can	53	18	properly	properly	RB
14-hansen-can	53	19	indexed	index	VBN
14-hansen-can	53	20	and	and	CC
14-hansen-can	53	21	searchable	searchable	JJ
14-hansen-can	53	22	in	in	IN
14-hansen-can	53	23	digital	digital	JJ
14-hansen-can	53	24	mathematics	mathematic	NNS
14-hansen-can	53	25	databases	database	NNS
14-hansen-can	53	26	:	:	:
14-hansen-can	53	27	the	the	DT
14-hansen-can	53	28	Czech	Czech	NNP
14-hansen-can	53	29	Digital	Digital	NNP
14-hansen-can	53	30	Mathematics	Mathematics	NNP
14-hansen-can	53	31	Library	Library	NNP
14-hansen-can	53	32	(	(	-LRB-
14-hansen-can	53	33	DML	DML	NNP
14-hansen-can	53	34	-	-	HYPH
14-hansen-can	53	35	CZ)6	CZ)6	NNP
14-hansen-can	53	36	and	and	CC
14-hansen-can	53	37	NUMDAM7	numdam7	NN
14-hansen-can	53	38	in	in	IN
14-hansen-can	53	39	the	the	DT
14-hansen-can	53	40	case	case	NN
14-hansen-can	53	41	of	of	IN
14-hansen-can	53	42	Radim	Radim	NNP
14-hansen-can	53	43	Ře-	Ře-	NNP
14-hansen-can	53	44	hůřek	hůřek	UH
14-hansen-can	53	45	and	and	CC
14-hansen-can	53	46	Petr	Petr	VBN
14-hansen-can	53	47	Sojka	sojka	RB
14-hansen-can	53	48	(	(	-LRB-
14-hansen-can	53	49	Řehůřek	Řehůřek	NNP
14-hansen-can	53	50	and	and	CC
14-hansen-can	53	51	Sojka	sojka	RB
14-hansen-can	53	52	2008	2008	CD
14-hansen-can	53	53	)	)	-RRB-
14-hansen-can	53	54	,	,	,
14-hansen-can	53	55	and	and	CC
14-hansen-can	53	56	Zentralblatt	Zentralblatt	NNP
14-hansen-can	53	57	MATH	MATH	NNP
14-hansen-can	53	58	(	(	-LRB-
14-hansen-can	53	59	zbMath)8	zbMath)8	NNP
14-hansen-can	53	60	in	in	IN
14-hansen-can	53	61	the	the	DT
14-hansen-can	53	62	case	case	NN
14-hansen-can	53	63	of	of	IN
14-hansen-can	53	64	Simon	Simon	NNP
14-hansen-can	53	65	Barthel	Barthel	NNP
14-hansen-can	53	66	,	,	,
14-hansen-can	53	67	Sascha	Sascha	NNP
14-hansen-can	53	68	Tönnies	tönnie	NNS
14-hansen-can	53	69	,	,	,
14-hansen-can	53	70	and	and	CC
14-hansen-can	53	71	Wolf	Wolf	NNP
14-hansen-can	53	72	-	-	HYPH
14-hansen-can	53	73	Tilo	Tilo	NNP
14-hansen-can	53	74	Balke	Balke	NNP
14-hansen-can	53	75	(	(	-LRB-
14-hansen-can	53	76	Barthel	Barthel	NNP
14-hansen-can	53	77	,	,	,
14-hansen-can	53	78	Tönnies	Tönnies	NNP
14-hansen-can	53	79	,	,	,
14-hansen-can	53	80	and	and	CC
14-hansen-can	53	81	Balke	Balke	NNP
14-hansen-can	53	82	2013	2013	CD
14-hansen-can	53	83	)	)	-RRB-
14-hansen-can	53	84	.	.	.
14-hansen-can	54	1	All	all	DT
14-hansen-can	54	2	of	of	IN
14-hansen-can	54	3	these	these	DT
14-hansen-can	54	4	databases	database	NNS
14-hansen-can	54	5	rely	rely	VBP
14-hansen-can	54	6	on	on	IN
14-hansen-can	54	7	the	the	DT
14-hansen-can	54	8	aforementioned	aforementioned	JJ
14-hansen-can	54	9	MSC9	MSC9	NNP
14-hansen-can	54	10	to	to	TO
14-hansen-can	54	11	aid	aid	VB
14-hansen-can	54	12	in	in	IN
14-hansen-can	54	13	indexing	indexing	NN
14-hansen-can	54	14	and	and	CC
14-hansen-can	54	15	retrieval	retrieval	NN
14-hansen-can	54	16	,	,	,
14-hansen-can	54	17	and	and	CC
14-hansen-can	54	18	so	so	RB
14-hansen-can	54	19	their	-PRON-	PRP$
14-hansen-can	54	20	goal	goal	NN
14-hansen-can	54	21	was	be	VBD
14-hansen-can	54	22	to	to	TO
14-hansen-can	54	23	automate	automate	VB
14-hansen-can	54	24	the	the	DT
14-hansen-can	54	25	assignment	assignment	NN
14-hansen-can	54	26	of	of	IN
14-hansen-can	54	27	MSC	MSC	NNP
14-hansen-can	54	28	values	value	NNS
14-hansen-can	54	29	to	to	TO
14-hansen-can	54	30	lower	lower	VB
14-hansen-can	54	31	the	the	DT
14-hansen-can	54	32	time	time	NN
14-hansen-can	54	33	and	and	CC
14-hansen-can	54	34	labor	labor	NN
14-hansen-can	54	35	cost	cost	NN
14-hansen-can	54	36	of	of	IN
14-hansen-can	54	37	requir-	requir-	NNS
14-hansen-can	54	38	ing	ing	NNP
14-hansen-can	54	39	humans	human	NNS
14-hansen-can	54	40	to	to	TO
14-hansen-can	54	41	do	do	VB
14-hansen-can	54	42	this	this	DT
14-hansen-can	54	43	task	task	NN
14-hansen-can	54	44	.	.	.
14-hansen-can	55	1	The	the	DT
14-hansen-can	55	2	main	main	JJ
14-hansen-can	55	3	differences	difference	NNS
14-hansen-can	55	4	between	between	IN
14-hansen-can	55	5	their	-PRON-	PRP$
14-hansen-can	55	6	tasks	task	NNS
14-hansen-can	55	7	related	relate	VBN
14-hansen-can	55	8	to	to	IN
14-hansen-can	55	9	the	the	DT
14-hansen-can	55	10	number	number	NN
14-hansen-can	55	11	of	of	IN
14-hansen-can	55	12	documents	document	NNS
14-hansen-can	55	13	they	-PRON-	PRP
14-hansen-can	55	14	were	be	VBD
14-hansen-can	55	15	working	work	VBG
14-hansen-can	55	16	with	with	IN
14-hansen-can	55	17	(	(	-LRB-
14-hansen-can	55	18	thousands	thousand	NNS
14-hansen-can	55	19	for	for	IN
14-hansen-can	55	20	Řehůřek	Řehůřek	NNP
14-hansen-can	55	21	and	and	CC
14-hansen-can	55	22	Sojka	sojka	JJ
14-hansen-can	55	23	and	and	CC
14-hansen-can	55	24	millions	million	NNS
14-hansen-can	55	25	for	for	IN
14-hansen-can	55	26	Barthel	Barthel	NNP
14-hansen-can	55	27	,	,	,
14-hansen-can	55	28	Tönnies	Tönnies	NNP
14-hansen-can	55	29	,	,	,
14-hansen-can	55	30	and	and	CC
14-hansen-can	55	31	Balke	Balke	NNP
14-hansen-can	55	32	)	)	-RRB-
14-hansen-can	55	33	,	,	,
14-hansen-can	55	34	the	the	DT
14-hansen-can	55	35	amount	amount	NN
14-hansen-can	55	36	of	of	IN
14-hansen-can	55	37	the	the	DT
14-hansen-can	55	38	works	work	NNS
14-hansen-can	55	39	available	available	JJ
14-hansen-can	55	40	(	(	-LRB-
14-hansen-can	55	41	full	full	JJ
14-hansen-can	55	42	text	text	NN
14-hansen-can	55	43	for	for	IN
14-hansen-can	55	44	Řehůřek	Řehůřek	NNP
14-hansen-can	55	45	and	and	CC
14-hansen-can	55	46	Sojka	sojka	RB
14-hansen-can	55	47	,	,	,
14-hansen-can	55	48	and	and	CC
14-hansen-can	55	49	titles	title	NNS
14-hansen-can	55	50	,	,	,
14-hansen-can	55	51	authors	author	NNS
14-hansen-can	55	52	,	,	,
14-hansen-can	55	53	and	and	CC
14-hansen-can	55	54	abstracts	abstract	NNS
14-hansen-can	55	55	for	for	IN
14-hansen-can	55	56	Barthel	Barthel	NNP
14-hansen-can	55	57	,	,	,
14-hansen-can	55	58	Tönnies	Tönnies	NNP
14-hansen-can	55	59	,	,	,
14-hansen-can	55	60	and	and	CC
14-hansen-can	55	61	Balke	Balke	NNP
14-hansen-can	55	62	)	)	-RRB-
14-hansen-can	55	63	,	,	,
14-hansen-can	55	64	and	and	CC
14-hansen-can	55	65	the	the	DT
14-hansen-can	55	66	quality	quality	NN
14-hansen-can	55	67	of	of	IN
14-hansen-can	55	68	the	the	DT
14-hansen-can	55	69	data	datum	NNS
14-hansen-can	55	70	(	(	-LRB-
14-hansen-can	55	71	mostly	mostly	RB
14-hansen-can	55	72	OCR	ocr	NN
14-hansen-can	55	73	scans	scan	NNS
14-hansen-can	55	74	for	for	IN
14-hansen-can	55	75	Řehůřek	Řehůřek	NNP
14-hansen-can	55	76	and	and	CC
14-hansen-can	55	77	Sojka	sojka	RB
14-hansen-can	55	78	and	and	CC
14-hansen-can	55	79	mostly	mostly	RB
14-hansen-can	55	80	TeX	TeX	VBD
14-hansen-can	55	81	for	for	IN
14-hansen-can	55	82	Barthel	Barthel	NNP
14-hansen-can	55	83	,	,	,
14-hansen-can	55	84	Tönnies	Tönnies	NNP
14-hansen-can	55	85	,	,	,
14-hansen-can	55	86	and	and	CC
14-hansen-can	55	87	Balke	Balke	NNP
14-hansen-can	55	88	)	)	-RRB-
14-hansen-can	55	89	.	.	.
14-hansen-can	56	1	Even	even	RB
14-hansen-can	56	2	with	with	IN
14-hansen-can	56	3	these	these	DT
14-hansen-can	56	4	differences	difference	NNS
14-hansen-can	56	5	,	,	,
14-hansen-can	56	6	both	both	DT
14-hansen-can	56	7	projects	project	NNS
14-hansen-can	56	8	took	take	VBD
14-hansen-can	56	9	a	a	DT
14-hansen-can	56	10	similar	similar	JJ
14-hansen-can	56	11	approach	approach	NN
14-hansen-can	56	12	,	,	,
14-hansen-can	56	13	and	and	CC
14-hansen-can	56	14	it	-PRON-	PRP
14-hansen-can	56	15	is	be	VBZ
14-hansen-can	56	16	the	the	DT
14-hansen-can	56	17	first	first	JJ
14-hansen-can	56	18	of	of	IN
14-hansen-can	56	19	the	the	DT
14-hansen-can	56	20	two	two	CD
14-hansen-can	56	21	main	main	JJ
14-hansen-can	56	22	pathways	pathway	NNS
14-hansen-can	56	23	to-	to-	XX
14-hansen-can	56	24	ward	ward	NNP
14-hansen-can	56	25	classification	classification	NN
14-hansen-can	56	26	I	-PRON-	PRP
14-hansen-can	56	27	spoke	speak	VBD
14-hansen-can	56	28	of	of	IN
14-hansen-can	56	29	earlier	early	RBR
14-hansen-can	56	30	:	:	:
14-hansen-can	56	31	using	use	VBG
14-hansen-can	56	32	a	a	DT
14-hansen-can	56	33	predetermined	predetermined	JJ
14-hansen-can	56	34	taxonomy	taxonomy	NN
14-hansen-can	56	35	and	and	CC
14-hansen-can	56	36	a	a	DT
14-hansen-can	56	37	set	set	NN
14-hansen-can	56	38	of	of	IN
14-hansen-can	56	39	pre	pre	JJ
14-hansen-can	56	40	-	-	JJ
14-hansen-can	56	41	categorized	categorized	JJ
14-hansen-can	56	42	data	datum	NNS
14-hansen-can	56	43	to	to	TO
14-hansen-can	56	44	build	build	VB
14-hansen-can	56	45	a	a	DT
14-hansen-can	56	46	machine	machine	NN
14-hansen-can	56	47	learning	learn	VBG
14-hansen-can	56	48	categorizer	categorizer	NN
14-hansen-can	56	49	.	.	.
14-hansen-can	57	1	In	in	IN
14-hansen-can	57	2	the	the	DT
14-hansen-can	57	3	end	end	NN
14-hansen-can	57	4	,	,	,
14-hansen-can	57	5	while	while	IN
14-hansen-can	57	6	both	both	DT
14-hansen-can	57	7	projects	project	NNS
14-hansen-can	57	8	determined	determine	VBD
14-hansen-can	57	9	that	that	IN
14-hansen-can	57	10	the	the	DT
14-hansen-can	57	11	use	use	NN
14-hansen-can	57	12	of	of	IN
14-hansen-can	57	13	Support	Support	NNP
14-hansen-can	57	14	Vector	Vector	NNP
14-hansen-can	57	15	Machines	Machines	NNPS
14-hansen-can	57	16	(	(	-LRB-
14-hansen-can	57	17	Gandhi	Gandhi	NNP
14-hansen-can	57	18	2018)10	2018)10	NNP
14-hansen-can	57	19	provided	provide	VBD
14-hansen-can	57	20	the	the	DT
14-hansen-can	57	21	best	good	JJS
14-hansen-can	57	22	categorization	categorization	NN
14-hansen-can	57	23	results	result	NNS
14-hansen-can	57	24	,	,	,
14-hansen-can	57	25	their	-PRON-	PRP$
14-hansen-can	57	26	implementations	implementation	NNS
14-hansen-can	57	27	were	be	VBD
14-hansen-can	57	28	different	different	JJ
14-hansen-can	57	29	.	.	.
14-hansen-can	58	1	The	the	DT
14-hansen-can	58	2	Ře-	Ře-	NNP
14-hansen-can	58	3	6See	6see	NN
14-hansen-can	58	4	?	?	.
14-hansen-can	58	5	iiTb	iitb	UH
14-hansen-can	58	6	,	,	,
14-hansen-can	58	7	ff	ff	NNP
14-hansen-can	58	8	/	/	SYM
14-hansen-can	58	9	KHX+xf	KHX+xf	NNP
14-hansen-can	58	10	.	.	.
14-hansen-can	59	1	7See	7See	``
14-hansen-can	59	2	?	?	.
14-hansen-can	59	3	iiT	iit	JJ
14-hansen-can	59	4	,	,	,
14-hansen-can	59	5	ffrrrXMmK/	ffrrrxmmk/	CD
14-hansen-can	59	6	�	�	NNP
14-hansen-can	59	7	KXQ`;f	kxq`;f	NN
14-hansen-can	59	8	.	.	.
14-hansen-can	59	9	8See	8see	LS
14-hansen-can	59	10	?	?	.
14-hansen-can	59	11	iiTb	iitb	UH
14-hansen-can	59	12	,	,	,
14-hansen-can	59	13	ffx#K	ffx#K	NNP
14-hansen-can	59	14	�	�	NNP
14-hansen-can	59	15	i?XQ`;f	i?XQ`;f	NNP
14-hansen-can	59	16	.	.	.
14-hansen-can	59	17	9Mathematical	9Mathematical	NNP
14-hansen-can	59	18	Subject	Subject	NNP
14-hansen-can	59	19	Classification	Classification	NNP
14-hansen-can	59	20	(	(	-LRB-
14-hansen-can	59	21	MSC	MSC	NNP
14-hansen-can	59	22	)	)	-RRB-
14-hansen-can	59	23	values	value	NNS
14-hansen-can	59	24	in	in	IN
14-hansen-can	59	25	MathSciNet	MathSciNet	NNP
14-hansen-can	59	26	and	and	CC
14-hansen-can	59	27	zbMath	zbMath	NNP
14-hansen-can	59	28	are	be	VBP
14-hansen-can	59	29	a	a	DT
14-hansen-can	59	30	particularly	particularly	RB
14-hansen-can	59	31	interesting	interesting	JJ
14-hansen-can	59	32	catego-	catego-	NN
14-hansen-can	59	33	rization	rization	NN
14-hansen-can	59	34	set	set	VBN
14-hansen-can	59	35	to	to	TO
14-hansen-can	59	36	work	work	VB
14-hansen-can	59	37	with	with	IN
14-hansen-can	59	38	as	as	IN
14-hansen-can	59	39	they	-PRON-	PRP
14-hansen-can	59	40	are	be	VBP
14-hansen-can	59	41	assigned	assign	VBN
14-hansen-can	59	42	and	and	CC
14-hansen-can	59	43	reviewed	review	VBN
14-hansen-can	59	44	by	by	IN
14-hansen-can	59	45	a	a	DT
14-hansen-can	59	46	subject	subject	JJ
14-hansen-can	59	47	area	area	NN
14-hansen-can	59	48	expert	expert	NN
14-hansen-can	59	49	editor	editor	NN
14-hansen-can	59	50	and	and	CC
14-hansen-can	59	51	an	an	DT
14-hansen-can	59	52	active	active	JJ
14-hansen-can	59	53	researcher	researcher	NN
14-hansen-can	59	54	in	in	IN
14-hansen-can	59	55	the	the	DT
14-hansen-can	59	56	same	same	JJ
14-hansen-can	59	57	,	,	,
14-hansen-can	59	58	or	or	CC
14-hansen-can	59	59	closely	closely	RB
14-hansen-can	59	60	related	relate	VBN
14-hansen-can	59	61	,	,	,
14-hansen-can	59	62	subfield	subfield	NNP
14-hansen-can	59	63	as	as	IN
14-hansen-can	59	64	the	the	DT
14-hansen-can	59	65	article㸪s	article㸪s	NNP
14-hansen-can	59	66	content	content	NN
14-hansen-can	59	67	before	before	IN
14-hansen-can	59	68	they	-PRON-	PRP
14-hansen-can	59	69	are	be	VBP
14-hansen-can	59	70	published	publish	VBN
14-hansen-can	59	71	.	.	.
14-hansen-can	60	1	This	this	DT
14-hansen-can	60	2	multi	multi	JJ
14-hansen-can	60	3	-	-	JJ
14-hansen-can	60	4	step	step	JJ
14-hansen-can	60	5	process	process	NN
14-hansen-can	60	6	of	of	IN
14-hansen-can	60	7	review	review	NN
14-hansen-can	60	8	yields	yield	NNS
14-hansen-can	60	9	a	a	DT
14-hansen-can	60	10	built	build	VBN
14-hansen-can	60	11	-	-	HYPH
14-hansen-can	60	12	in	in	RP
14-hansen-can	60	13	accuracy	accuracy	NN
14-hansen-can	60	14	check	check	NN
14-hansen-can	60	15	for	for	IN
14-hansen-can	60	16	the	the	DT
14-hansen-can	60	17	categorization	categorization	NN
14-hansen-can	60	18	.	.	.
14-hansen-can	61	1	10Support	10Support	NNP
14-hansen-can	61	2	Vector	Vector	NNP
14-hansen-can	61	3	Machines	machine	NNS
14-hansen-can	61	4	(	(	-LRB-
14-hansen-can	61	5	SVMs	svm	NNS
14-hansen-can	61	6	)	)	-RRB-
14-hansen-can	61	7	are	be	VBP
14-hansen-can	61	8	machine	machine	NN
14-hansen-can	61	9	learning	learning	NN
14-hansen-can	61	10	models	model	NNS
14-hansen-can	61	11	which	which	WDT
14-hansen-can	61	12	are	be	VBP
14-hansen-can	61	13	trained	train	VBN
14-hansen-can	61	14	using	use	VBG
14-hansen-can	61	15	a	a	DT
14-hansen-can	61	16	pre	pre	JJ
14-hansen-can	61	17	-	-	JJ
14-hansen-can	61	18	classified	classified	JJ
14-hansen-can	61	19	corpus	corpus	NN
14-hansen-can	61	20	to	to	TO
14-hansen-can	61	21	split	split	VB
14-hansen-can	61	22	a	a	DT
14-hansen-can	61	23	vector	vector	NN
14-hansen-can	61	24	space	space	NN
14-hansen-can	61	25	into	into	IN
14-hansen-can	61	26	a	a	DT
14-hansen-can	61	27	set	set	NN
14-hansen-can	61	28	of	of	IN
14-hansen-can	61	29	differentiated	differentiate	VBN
14-hansen-can	61	30	areas	area	NNS
14-hansen-can	61	31	(	(	-LRB-
14-hansen-can	61	32	or	or	CC
14-hansen-can	61	33	categories	category	NNS
14-hansen-can	61	34	)	)	-RRB-
14-hansen-can	61	35	and	and	CC
14-hansen-can	61	36	then	then	RB
14-hansen-can	61	37	attempt	attempt	VB
14-hansen-can	61	38	to	to	TO
14-hansen-can	61	39	classify	classify	VB
14-hansen-can	61	40	new	new	JJ
14-hansen-can	61	41	items	item	NNS
14-hansen-can	61	42	by	by	IN
14-hansen-can	61	43	where	where	WRB
14-hansen-can	61	44	in	in	IN
14-hansen-can	61	45	the	the	DT
14-hansen-can	61	46	https://dml.cz/	https://dml.cz/	NNP
14-hansen-can	61	47	http://www.numdam.org/	http://www.numdam.org/	NN
14-hansen-can	61	48	https://zbmath.org/	https://zbmath.org/	CD
14-hansen-can	61	49	162	162	CD
14-hansen-can	61	50	Machine	Machine	NNP
14-hansen-can	61	51	Learning	Learning	NNP
14-hansen-can	61	52	,	,	,
14-hansen-can	61	53	Libraries	Libraries	NNPS
14-hansen-can	61	54	,	,	,
14-hansen-can	61	55	and	and	CC
14-hansen-can	61	56	Cross	Cross	NNP
14-hansen-can	61	57	-	-	NNP
14-hansen-can	61	58	Disciplinary	Disciplinary	NNP
14-hansen-can	61	59	ResearchǔChapter	ResearchǔChapter	NNP
14-hansen-can	61	60	14	14	CD
14-hansen-can	61	61	hůřek	hůřek	DT
14-hansen-can	61	62	and	and	CC
14-hansen-can	61	63	Sojka	sojka	RB
14-hansen-can	61	64	SVMs	svm	NNS
14-hansen-can	61	65	were	be	VBD
14-hansen-can	61	66	trained	train	VBN
14-hansen-can	61	67	with	with	IN
14-hansen-can	61	68	terms	term	NNS
14-hansen-can	61	69	weighted	weight	VBN
14-hansen-can	61	70	using	use	VBG
14-hansen-can	61	71	augmented	augment	VBN
14-hansen-can	61	72	term	term	NN
14-hansen-can	61	73	frequency11	frequency11	VBP
14-hansen-can	61	74	and	and	CC
14-hansen-can	61	75	dynamic	dynamic	JJ
14-hansen-can	61	76	decision	decision	NN
14-hansen-can	61	77	threshold12	threshold12	NN
14-hansen-can	61	78	selection	selection	NN
14-hansen-can	61	79	using	use	VBG
14-hansen-can	61	80	s	s	NNPS
14-hansen-can	61	81	-	-	HYPH
14-hansen-can	61	82	cut13	cut13	NNP
14-hansen-can	61	83	(	(	-LRB-
14-hansen-can	61	84	Řehůřek	Řehůřek	NNP
14-hansen-can	61	85	and	and	CC
14-hansen-can	61	86	Sojka	sojka	RB
14-hansen-can	61	87	2008	2008	CD
14-hansen-can	61	88	,	,	,
14-hansen-can	61	89	549	549	CD
14-hansen-can	61	90	)	)	-RRB-
14-hansen-can	61	91	and	and	CC
14-hansen-can	61	92	Barthel	Barthel	NNP
14-hansen-can	61	93	,	,	,
14-hansen-can	61	94	Tönnies	Tönnies	NNP
14-hansen-can	61	95	,	,	,
14-hansen-can	61	96	and	and	CC
14-hansen-can	61	97	Balke	Balke	NNP
14-hansen-can	61	98	’s	’	VBZ
14-hansen-can	61	99	with	with	IN
14-hansen-can	61	100	term	term	NN
14-hansen-can	61	101	weighting	weight	VBG
14-hansen-can	61	102	using	use	VBG
14-hansen-can	61	103	term	term	NN
14-hansen-can	61	104	frequency	frequency	NN
14-hansen-can	61	105	–	–	:
14-hansen-can	61	106	inverse	inverse	NN
14-hansen-can	61	107	document	document	NN
14-hansen-can	61	108	frequency14	frequency14	NN
14-hansen-can	61	109	and	and	CC
14-hansen-can	61	110	Euclidean	euclidean	JJ
14-hansen-can	61	111	normalization15	normalization15	NFP
14-hansen-can	61	112	(	(	-LRB-
14-hansen-can	61	113	Barthel	Barthel	NNP
14-hansen-can	61	114	,	,	,
14-hansen-can	61	115	Tönnies	Tönnies	NNP
14-hansen-can	61	116	,	,	,
14-hansen-can	61	117	and	and	CC
14-hansen-can	61	118	Balke	Balke	NNP
14-hansen-can	61	119	2013	2013	CD
14-hansen-can	61	120	,	,	,
14-hansen-can	61	121	88	88	CD
14-hansen-can	61	122	)	)	-RRB-
14-hansen-can	61	123	,	,	,
14-hansen-can	61	124	but	but	CC
14-hansen-can	61	125	the	the	DT
14-hansen-can	61	126	main	main	JJ
14-hansen-can	61	127	difference	difference	NN
14-hansen-can	61	128	was	be	VBD
14-hansen-can	61	129	how	how	WRB
14-hansen-can	61	130	they	-PRON-	PRP
14-hansen-can	61	131	handled	handle	VBD
14-hansen-can	61	132	formulae	formulae	NNP
14-hansen-can	61	133	.	.	.
14-hansen-can	62	1	In	in	IN
14-hansen-can	62	2	particular	particular	JJ
14-hansen-can	62	3	the	the	DT
14-hansen-can	62	4	Barthel	Barthel	NNP
14-hansen-can	62	5	,	,	,
14-hansen-can	62	6	Tönnies	Tönnies	NNP
14-hansen-can	62	7	,	,	,
14-hansen-can	62	8	and	and	CC
14-hansen-can	62	9	Balke	Balke	NNP
14-hansen-can	62	10	group	group	NN
14-hansen-can	62	11	split	split	VBD
14-hansen-can	62	12	their	-PRON-	PRP$
14-hansen-can	62	13	corpus	corpus	NN
14-hansen-can	62	14	into	into	IN
14-hansen-can	62	15	words	word	NNS
14-hansen-can	62	16	and	and	CC
14-hansen-can	62	17	formulae	formula	NNS
14-hansen-can	62	18	and	and	CC
14-hansen-can	62	19	mapped	map	VBD
14-hansen-can	62	20	them	-PRON-	PRP
14-hansen-can	62	21	to	to	TO
14-hansen-can	62	22	separate	separate	JJ
14-hansen-can	62	23	vectors	vector	NNS
14-hansen-can	62	24	which	which	WDT
14-hansen-can	62	25	were	be	VBD
14-hansen-can	62	26	then	then	RB
14-hansen-can	62	27	merged	merge	VBN
14-hansen-can	62	28	together	together	RB
14-hansen-can	62	29	for	for	IN
14-hansen-can	62	30	a	a	DT
14-hansen-can	62	31	combined	combine	VBN
14-hansen-can	62	32	vector	vector	NN
14-hansen-can	62	33	used	use	VBN
14-hansen-can	62	34	for	for	IN
14-hansen-can	62	35	categorization	categorization	NN
14-hansen-can	62	36	.	.	.
14-hansen-can	63	1	Řehůřek	Řehůřek	NNP
14-hansen-can	63	2	and	and	CC
14-hansen-can	63	3	Sojka	Sojka	NNP
14-hansen-can	63	4	did	do	VBD
14-hansen-can	63	5	not	not	RB
14-hansen-can	63	6	differenti-	differenti-	VB
14-hansen-can	63	7	ate	eat	VBN
14-hansen-can	63	8	between	between	IN
14-hansen-can	63	9	words	word	NNS
14-hansen-can	63	10	and	and	CC
14-hansen-can	63	11	formulae	formula	NNS
14-hansen-can	63	12	in	in	IN
14-hansen-can	63	13	their	-PRON-	PRP$
14-hansen-can	63	14	corpus	corpus	NN
14-hansen-can	63	15	,	,	,
14-hansen-can	63	16	and	and	CC
14-hansen-can	63	17	they	-PRON-	PRP
14-hansen-can	63	18	did	do	VBD
14-hansen-can	63	19	note	note	VB
14-hansen-can	63	20	that	that	IN
14-hansen-can	63	21	their	-PRON-	PRP$
14-hansen-can	63	22	OCR	ocr	NN
14-hansen-can	63	23	scans	scan	NNS
14-hansen-can	63	24	’	’	POS
14-hansen-can	63	25	poor	poor	JJ
14-hansen-can	63	26	handling	handling	NN
14-hansen-can	63	27	of	of	IN
14-hansen-can	63	28	formulae	formula	NNS
14-hansen-can	63	29	could	could	MD
14-hansen-can	63	30	have	have	VB
14-hansen-can	63	31	hindered	hinder	VBN
14-hansen-can	63	32	their	-PRON-	PRP$
14-hansen-can	63	33	results	result	NNS
14-hansen-can	63	34	(	(	-LRB-
14-hansen-can	63	35	Řehůřek	Řehůřek	NNP
14-hansen-can	63	36	and	and	CC
14-hansen-can	63	37	Sojka	sojka	RB
14-hansen-can	63	38	2008	2008	CD
14-hansen-can	63	39	,	,	,
14-hansen-can	63	40	555	555	CD
14-hansen-can	63	41	)	)	-RRB-
14-hansen-can	63	42	.	.	.
14-hansen-can	64	1	In	in	IN
14-hansen-can	64	2	the	the	DT
14-hansen-can	64	3	end	end	NN
14-hansen-can	64	4	,	,	,
14-hansen-can	64	5	not	not	RB
14-hansen-can	64	6	having	have	VBG
14-hansen-can	64	7	the	the	DT
14-hansen-can	64	8	ability	ability	NN
14-hansen-can	64	9	to	to	TO
14-hansen-can	64	10	handle	handle	VB
14-hansen-can	64	11	formulae	formulae	NNP
14-hansen-can	64	12	separately	separately	RB
14-hansen-can	64	13	did	do	VBD
14-hansen-can	64	14	not	not	RB
14-hansen-can	64	15	seem	seem	VB
14-hansen-can	64	16	to	to	TO
14-hansen-can	64	17	matter	matter	VB
14-hansen-can	64	18	as	as	IN
14-hansen-can	64	19	Řehůřek	Řehůřek	NNP
14-hansen-can	64	20	and	and	CC
14-hansen-can	64	21	Sojka	Sojka	NNP
14-hansen-can	64	22	claimed	claim	VBD
14-hansen-can	64	23	microaveraged	microaverage	VBD
14-hansen-can	64	24	F1	F1	NNP
14-hansen-can	64	25	scores	score	NNS
14-hansen-can	64	26	of	of	IN
14-hansen-can	64	27	89.03	89.03	CD
14-hansen-can	64	28	%	%	NN
14-hansen-can	64	29	(	(	-LRB-
14-hansen-can	64	30	Řehůřek	Řehůřek	NNP
14-hansen-can	64	31	and	and	CC
14-hansen-can	64	32	Sojka	sojka	RB
14-hansen-can	64	33	2008	2008	CD
14-hansen-can	64	34	,	,	,
14-hansen-can	64	35	549	549	CD
14-hansen-can	64	36	)	)	-RRB-
14-hansen-can	64	37	when	when	WRB
14-hansen-can	64	38	classify-	classify-	NNP
14-hansen-can	64	39	ing	e	VBG
14-hansen-can	64	40	the	the	DT
14-hansen-can	64	41	top	top	JJ
14-hansen-can	64	42	level	level	NN
14-hansen-can	64	43	MSC	MSC	NNP
14-hansen-can	64	44	category	category	NN
14-hansen-can	64	45	with	with	IN
14-hansen-can	64	46	their	-PRON-	PRP$
14-hansen-can	64	47	best	good	JJS
14-hansen-can	64	48	performing	perform	VBG
14-hansen-can	64	49	SVM	SVM	NNP
14-hansen-can	64	50	.	.	.
14-hansen-can	65	1	When	when	WRB
14-hansen-can	65	2	this	this	DT
14-hansen-can	65	3	is	be	VBZ
14-hansen-can	65	4	compared	compare	VBN
14-hansen-can	65	5	to	to	IN
14-hansen-can	65	6	the	the	DT
14-hansen-can	65	7	microaveraged	microaverage	VBN
14-hansen-can	65	8	F1	F1	NNP
14-hansen-can	65	9	of	of	IN
14-hansen-can	65	10	67.3	67.3	CD
14-hansen-can	65	11	%	%	NN
14-hansen-can	65	12	obtained	obtain	VBN
14-hansen-can	65	13	by	by	IN
14-hansen-can	65	14	Barthel	Barthel	NNP
14-hansen-can	65	15	,	,	,
14-hansen-can	65	16	Tönnies	Tönnies	NNP
14-hansen-can	65	17	,	,	,
14-hansen-can	65	18	and	and	CC
14-hansen-can	65	19	Balke	Balke	NNP
14-hansen-can	65	20	(	(	-LRB-
14-hansen-can	65	21	Barthel	Barthel	NNP
14-hansen-can	65	22	,	,	,
14-hansen-can	65	23	Tönnies	Tönnies	NNP
14-hansen-can	65	24	,	,	,
14-hansen-can	65	25	and	and	CC
14-hansen-can	65	26	Balke	Balke	NNP
14-hansen-can	65	27	2013	2013	CD
14-hansen-can	65	28	,	,	,
14-hansen-can	65	29	88	88	CD
14-hansen-can	65	30	)	)	-RRB-
14-hansen-can	65	31	,	,	,
14-hansen-can	65	32	it	-PRON-	PRP
14-hansen-can	65	33	would	would	MD
14-hansen-can	65	34	seem	seem	VB
14-hansen-can	65	35	that	that	IN
14-hansen-can	65	36	either	either	CC
14-hansen-can	65	37	Řehůřek	Řehůřek	NNP
14-hansen-can	65	38	’s	’s	,
14-hansen-can	65	39	and	and	CC
14-hansen-can	65	40	Sojka	sojka	RB
14-hansen-can	65	41	’s	’	VBZ
14-hansen-can	65	42	implementation	implementation	NN
14-hansen-can	65	43	of	of	IN
14-hansen-can	65	44	SVMs	svm	NNS
14-hansen-can	65	45	or	or	CC
14-hansen-can	65	46	their	-PRON-	PRP$
14-hansen-can	65	47	ac-	ac-	RB
14-hansen-can	65	48	cess	cess	NN
14-hansen-can	65	49	to	to	IN
14-hansen-can	65	50	full	full	JJ
14-hansen-can	65	51	-	-	HYPH
14-hansen-can	65	52	text	text	NN
14-hansen-can	65	53	led	lead	VBD
14-hansen-can	65	54	to	to	IN
14-hansen-can	65	55	a	a	DT
14-hansen-can	65	56	clear	clear	JJ
14-hansen-can	65	57	advantage	advantage	NN
14-hansen-can	65	58	.	.	.
14-hansen-can	66	1	This	this	DT
14-hansen-can	66	2	advantage	advantage	NN
14-hansen-can	66	3	becomes	become	VBZ
14-hansen-can	66	4	less	less	RBR
14-hansen-can	66	5	clear	clear	JJ
14-hansen-can	66	6	when	when	WRB
14-hansen-can	66	7	one	one	PRP
14-hansen-can	66	8	takes	take	VBZ
14-hansen-can	66	9	into	into	IN
14-hansen-can	66	10	account	account	NN
14-hansen-can	66	11	that	that	IN
14-hansen-can	66	12	Řehůřek	Řehůřek	NNP
14-hansen-can	66	13	and	and	CC
14-hansen-can	66	14	Sojka	Sojka	NNP
14-hansen-can	66	15	were	be	VBD
14-hansen-can	66	16	only	only	RB
14-hansen-can	66	17	working	work	VBG
14-hansen-can	66	18	with	with	IN
14-hansen-can	66	19	top	top	JJ
14-hansen-can	66	20	level	level	NN
14-hansen-can	66	21	MSCs	msc	NNS
14-hansen-can	66	22	where	where	WRB
14-hansen-can	66	23	they	-PRON-	PRP
14-hansen-can	66	24	had	have	VBD
14-hansen-can	66	25	at	at	RB
14-hansen-can	66	26	least	least	RBS
14-hansen-can	66	27	30	30	CD
14-hansen-can	66	28	(	(	-LRB-
14-hansen-can	66	29	60	60	CD
14-hansen-can	66	30	in	in	IN
14-hansen-can	66	31	the	the	DT
14-hansen-can	66	32	case	case	NN
14-hansen-can	66	33	of	of	IN
14-hansen-can	66	34	their	-PRON-	PRP$
14-hansen-can	66	35	best	good	JJS
14-hansen-can	66	36	result	result	NN
14-hansen-can	66	37	)	)	-RRB-
14-hansen-can	66	38	articles	article	NNS
14-hansen-can	66	39	,	,	,
14-hansen-can	66	40	and	and	CC
14-hansen-can	66	41	their	-PRON-	PRP$
14-hansen-can	66	42	limited	limited	JJ
14-hansen-can	66	43	corpus	corpus	NN
14-hansen-can	66	44	meant	mean	VBD
14-hansen-can	66	45	that	that	IN
14-hansen-can	66	46	many	many	JJ
14-hansen-can	66	47	top	top	JJ
14-hansen-can	66	48	-	-	HYPH
14-hansen-can	66	49	level	level	NN
14-hansen-can	66	50	MSC	MSC	NNP
14-hansen-can	66	51	categories	category	NNS
14-hansen-can	66	52	would	would	MD
14-hansen-can	66	53	not	not	RB
14-hansen-can	66	54	have	have	VB
14-hansen-can	66	55	been	be	VBN
14-hansen-can	66	56	included	include	VBN
14-hansen-can	66	57	.	.	.
14-hansen-can	67	1	Looking	look	VBG
14-hansen-can	67	2	at	at	IN
14-hansen-can	67	3	the	the	DT
14-hansen-can	67	4	work	work	NN
14-hansen-can	67	5	done	do	VBN
14-hansen-can	67	6	by	by	IN
14-hansen-can	67	7	Barthel	Barthel	NNP
14-hansen-can	67	8	,	,	,
14-hansen-can	67	9	Tönnies	Tönnies	NNP
14-hansen-can	67	10	,	,	,
14-hansen-can	67	11	and	and	CC
14-hansen-can	67	12	Balke	Balke	NNP
14-hansen-can	67	13	makes	make	VBZ
14-hansen-can	67	14	it	-PRON-	PRP
14-hansen-can	67	15	clear	clear	JJ
14-hansen-can	67	16	that	that	IN
14-hansen-can	67	17	these	these	DT
14-hansen-can	67	18	less	less	RBR
14-hansen-can	67	19	common	common	JJ
14-hansen-can	67	20	MSC	MSC	NNP
14-hansen-can	67	21	categories	category	NNS
14-hansen-can	67	22	such	such	JJ
14-hansen-can	67	23	as	as	IN
14-hansen-can	67	24	K	K	NNP
14-hansen-can	67	25	-	-	HYPH
14-hansen-can	67	26	Theory	Theory	NNP
14-hansen-can	67	27	or	or	CC
14-hansen-can	67	28	Potential	Potential	NNP
14-hansen-can	67	29	Theory	Theory	NNP
14-hansen-can	67	30	,	,	,
14-hansen-can	67	31	for	for	IN
14-hansen-can	67	32	which	which	WDT
14-hansen-can	67	33	Barthel	Barthel	NNP
14-hansen-can	67	34	,	,	,
14-hansen-can	67	35	Tönnies	Tönnies	NNP
14-hansen-can	67	36	,	,	,
14-hansen-can	67	37	and	and	CC
14-hansen-can	67	38	Balke	Balke	NNP
14-hansen-can	67	39	achieved	achieve	VBD
14-hansen-can	67	40	microaveraged	microaverage	VBD
14-hansen-can	67	41	F1	F1	NNP
14-hansen-can	67	42	measures	measure	NNS
14-hansen-can	67	43	of	of	IN
14-hansen-can	67	44	18.2	18.2	CD
14-hansen-can	67	45	%	%	NN
14-hansen-can	67	46	and	and	CC
14-hansen-can	67	47	24	24	CD
14-hansen-can	67	48	%	%	NN
14-hansen-can	67	49	respectively	respectively	RB
14-hansen-can	67	50	,	,	,
14-hansen-can	67	51	have	have	VBP
14-hansen-can	67	52	a	a	DT
14-hansen-can	67	53	large	large	JJ
14-hansen-can	67	54	impact	impact	NN
14-hansen-can	67	55	on	on	IN
14-hansen-can	67	56	the	the	DT
14-hansen-can	67	57	overall	overall	JJ
14-hansen-can	67	58	effectiveness	effectiveness	NN
14-hansen-can	67	59	of	of	IN
14-hansen-can	67	60	the	the	DT
14-hansen-can	67	61	automated	automated	JJ
14-hansen-can	67	62	categorization	categorization	NN
14-hansen-can	67	63	.	.	.
14-hansen-can	68	1	Remember	remember	VB
14-hansen-can	68	2	,	,	,
14-hansen-can	68	3	this	this	DT
14-hansen-can	68	4	is	be	VBZ
14-hansen-can	68	5	only	only	RB
14-hansen-can	68	6	for	for	IN
14-hansen-can	68	7	the	the	DT
14-hansen-can	68	8	top	top	JJ
14-hansen-can	68	9	level	level	NN
14-hansen-can	68	10	of	of	IN
14-hansen-can	68	11	MSC	MSC	NNP
14-hansen-can	68	12	codes	code	NNS
14-hansen-can	68	13	,	,	,
14-hansen-can	68	14	and	and	CC
14-hansen-can	68	15	the	the	DT
14-hansen-can	68	16	work	work	NN
14-hansen-can	68	17	of	of	IN
14-hansen-can	68	18	Barthel	Barthel	NNP
14-hansen-can	68	19	,	,	,
14-hansen-can	68	20	Tönnies	Tönnies	NNP
14-hansen-can	68	21	,	,	,
14-hansen-can	68	22	and	and	CC
14-hansen-can	68	23	Balke	Balke	NNP
14-hansen-can	68	24	suggests	suggest	VBZ
14-hansen-can	68	25	it	-PRON-	PRP
14-hansen-can	68	26	would	would	MD
14-hansen-can	68	27	get	get	VB
14-hansen-can	68	28	worse	bad	JJR
14-hansen-can	68	29	when	when	WRB
14-hansen-can	68	30	trying	try	VBG
14-hansen-can	68	31	to	to	TO
14-hansen-can	68	32	apply	apply	VB
14-hansen-can	68	33	the	the	DT
14-hansen-can	68	34	second	second	JJ
14-hansen-can	68	35	and	and	CC
14-hansen-can	68	36	third	third	JJ
14-hansen-can	68	37	level	level	NN
14-hansen-can	68	38	for	for	IN
14-hansen-can	68	39	full	full	JJ
14-hansen-can	68	40	MSC	MSC	NNP
14-hansen-can	68	41	categorization	categorization	NN
14-hansen-can	68	42	to	to	IN
14-hansen-can	68	43	these	these	DT
14-hansen-can	68	44	less	less	RBR
14-hansen-can	68	45	-	-	HYPH
14-hansen-can	68	46	common	common	JJ
14-hansen-can	68	47	categories	category	NNS
14-hansen-can	68	48	.	.	.
14-hansen-can	69	1	This	this	DT
14-hansen-can	69	2	leads	lead	VBZ
14-hansen-can	69	3	me	-PRON-	PRP
14-hansen-can	69	4	to	to	TO
14-hansen-can	69	5	believe	believe	VB
14-hansen-can	69	6	that	that	IN
14-hansen-can	69	7	in	in	IN
14-hansen-can	69	8	the	the	DT
14-hansen-can	69	9	case	case	NN
14-hansen-can	69	10	of	of	IN
14-hansen-can	69	11	cat-	cat-	NN
14-hansen-can	69	12	egorizing	egorize	VBG
14-hansen-can	69	13	highly	highly	RB
14-hansen-can	69	14	technical	technical	JJ
14-hansen-can	69	15	mathematical	mathematical	JJ
14-hansen-can	69	16	works	work	NNS
14-hansen-can	69	17	to	to	IN
14-hansen-can	69	18	an	an	DT
14-hansen-can	69	19	existing	exist	VBG
14-hansen-can	69	20	taxonomy	taxonomy	NN
14-hansen-can	69	21	,	,	,
14-hansen-can	69	22	people	people	NNS
14-hansen-can	69	23	have	have	VBP
14-hansen-can	69	24	come	come	VBN
14-hansen-can	69	25	close	close	RB
14-hansen-can	69	26	to	to	IN
14-hansen-can	69	27	identifying	identify	VBG
14-hansen-can	69	28	the	the	DT
14-hansen-can	69	29	overall	overall	JJ
14-hansen-can	69	30	size	size	NN
14-hansen-can	69	31	of	of	IN
14-hansen-can	69	32	the	the	DT
14-hansen-can	69	33	machine	machine	NN
14-hansen-can	69	34	learning	learning	NN
14-hansen-can	69	35	hammer	hammer	NNP
14-hansen-can	69	36	,	,	,
14-hansen-can	69	37	but	but	CC
14-hansen-can	69	38	are	be	VBP
14-hansen-can	69	39	still	still	RB
14-hansen-can	69	40	a	a	DT
14-hansen-can	69	41	long	long	JJ
14-hansen-can	69	42	way	way	NN
14-hansen-can	69	43	away	away	RB
14-hansen-can	69	44	from	from	IN
14-hansen-can	69	45	finding	find	VBG
14-hansen-can	69	46	the	the	DT
14-hansen-can	69	47	right	right	JJ
14-hansen-can	69	48	match	match	NN
14-hansen-can	69	49	for	for	IN
14-hansen-can	69	50	the	the	DT
14-hansen-can	69	51	categorization	categorization	NN
14-hansen-can	69	52	nail	nail	NN
14-hansen-can	69	53	.	.	.
14-hansen-can	70	1	Now	now	RB
14-hansen-can	70	2	let	let	VB
14-hansen-can	70	3	us	-PRON-	PRP
14-hansen-can	70	4	shift	shift	VB
14-hansen-can	70	5	from	from	IN
14-hansen-can	70	6	mathematics	mathematics	NN
14-hansen-can	70	7	-	-	HYPH
14-hansen-can	70	8	specific	specific	JJ
14-hansen-can	70	9	categorization	categorization	NN
14-hansen-can	70	10	to	to	TO
14-hansen-can	70	11	subject	subject	JJ
14-hansen-can	70	12	categorization	categorization	NN
14-hansen-can	70	13	in	in	IN
14-hansen-can	70	14	gen-	gen-	NN
14-hansen-can	70	15	eral	eral	NNP
14-hansen-can	70	16	and	and	CC
14-hansen-can	70	17	look	look	VB
14-hansen-can	70	18	at	at	IN
14-hansen-can	70	19	the	the	DT
14-hansen-can	70	20	work	work	NN
14-hansen-can	70	21	Microsoft	Microsoft	NNP
14-hansen-can	70	22	has	have	VBZ
14-hansen-can	70	23	done	do	VBN
14-hansen-can	70	24	assigning	assigning	NN
14-hansen-can	70	25	Fields	Fields	NNP
14-hansen-can	70	26	of	of	IN
14-hansen-can	70	27	Study	Study	NNP
14-hansen-can	70	28	(	(	-LRB-
14-hansen-can	70	29	FoS	FoS	NNP
14-hansen-can	70	30	)	)	-RRB-
14-hansen-can	70	31	in	in	IN
14-hansen-can	70	32	the	the	DT
14-hansen-can	70	33	Microsoft	Microsoft	NNP
14-hansen-can	70	34	Academic	Academic	NNP
14-hansen-can	70	35	Graph	Graph	NNP
14-hansen-can	70	36	(	(	-LRB-
14-hansen-can	70	37	MAG	MAG	NNP
14-hansen-can	70	38	)	)	-RRB-
14-hansen-can	70	39	which	which	WDT
14-hansen-can	70	40	is	be	VBZ
14-hansen-can	70	41	used	use	VBN
14-hansen-can	70	42	to	to	TO
14-hansen-can	70	43	create	create	VB
14-hansen-can	70	44	their	-PRON-	PRP$
14-hansen-can	70	45	Microsoft	Microsoft	NNP
14-hansen-can	70	46	Academic	Academic	NNP
14-hansen-can	70	47	article	article	NN
14-hansen-can	70	48	search	search	NN
14-hansen-can	70	49	prod-	prod-	XX
14-hansen-can	70	50	uct.16	uct.16	JJ
14-hansen-can	70	51	While	while	IN
14-hansen-can	70	52	the	the	DT
14-hansen-can	70	53	MAG	MAG	NNP
14-hansen-can	70	54	FoS	fos	NN
14-hansen-can	70	55	project	project	NN
14-hansen-can	70	56	is	be	VBZ
14-hansen-can	70	57	also	also	RB
14-hansen-can	70	58	attempting	attempt	VBG
14-hansen-can	70	59	to	to	TO
14-hansen-can	70	60	categorize	categorize	VB
14-hansen-can	70	61	articles	article	NNS
14-hansen-can	70	62	for	for	IN
14-hansen-can	70	63	proper	proper	JJ
14-hansen-can	70	64	indexing	indexing	NN
14-hansen-can	70	65	and	and	CC
14-hansen-can	70	66	search	search	NN
14-hansen-can	70	67	,	,	,
14-hansen-can	70	68	it	-PRON-	PRP
14-hansen-can	70	69	represents	represent	VBZ
14-hansen-can	70	70	the	the	DT
14-hansen-can	70	71	second	second	JJ
14-hansen-can	70	72	path	path	NN
14-hansen-can	70	73	which	which	WDT
14-hansen-can	70	74	is	be	VBZ
14-hansen-can	70	75	taken	take	VBN
14-hansen-can	70	76	by	by	IN
14-hansen-can	70	77	automated	automate	VBN
14-hansen-can	70	78	categorization	categorization	NN
14-hansen-can	70	79	projects	project	NNS
14-hansen-can	70	80	:	:	:
14-hansen-can	70	81	using	use	VBG
14-hansen-can	70	82	machine	machine	NN
14-hansen-can	70	83	learning	learning	NN
14-hansen-can	70	84	techniques	technique	NNS
14-hansen-can	70	85	to	to	TO
14-hansen-can	70	86	both	both	DT
14-hansen-can	70	87	create	create	VB
14-hansen-can	70	88	the	the	DT
14-hansen-can	70	89	taxonomy	taxonomy	NN
14-hansen-can	70	90	and	and	CC
14-hansen-can	70	91	to	to	TO
14-hansen-can	70	92	classify	classify	VB
14-hansen-can	70	93	.	.	.
14-hansen-can	71	1	Microsoft	Microsoft	NNP
14-hansen-can	71	2	took	take	VBD
14-hansen-can	71	3	a	a	DT
14-hansen-can	71	4	unique	unique	JJ
14-hansen-can	71	5	approach	approach	NN
14-hansen-can	71	6	in	in	IN
14-hansen-can	71	7	the	the	DT
14-hansen-can	71	8	development	development	NN
14-hansen-can	71	9	of	of	IN
14-hansen-can	71	10	their	-PRON-	PRP$
14-hansen-can	71	11	taxonomy	taxonomy	NN
14-hansen-can	71	12	.	.	.
14-hansen-can	72	1	Instead	instead	RB
14-hansen-can	72	2	of	of	IN
14-hansen-can	72	3	rely-	rely-	JJ
14-hansen-can	72	4	vector	vector	NN
14-hansen-can	72	5	space	space	NN
14-hansen-can	72	6	the	the	DT
14-hansen-can	72	7	trained	train	VBN
14-hansen-can	72	8	model	model	NN
14-hansen-can	72	9	places	place	VBZ
14-hansen-can	72	10	them	-PRON-	PRP
14-hansen-can	72	11	.	.	.
14-hansen-can	73	1	For	for	IN
14-hansen-can	73	2	a	a	DT
14-hansen-can	73	3	more	more	JJR
14-hansen-can	73	4	in	in	IN
14-hansen-can	73	5	-	-	HYPH
14-hansen-can	73	6	depth	depth	NN
14-hansen-can	73	7	,	,	,
14-hansen-can	73	8	technical	technical	JJ
14-hansen-can	73	9	explanation	explanation	NN
14-hansen-can	73	10	,	,	,
14-hansen-can	73	11	see	see	VB
14-hansen-can	73	12	:	:	:
14-hansen-can	73	13	?	?	.
14-hansen-can	73	14	iiTb	iitb	UH
14-hansen-can	73	15	,	,	,
14-hansen-can	73	16	ffiQr	ffiqr	ADD
14-hansen-can	73	17	�	�	ADD
14-hansen-can	73	18	`/b/	`/b/	NNP
14-hansen-can	73	19	�	�	NNP
14-hansen-can	73	20	i	i	PRP
14-hansen-can	73	21	�	�	VBP
14-hansen-can	73	22	b	b	NN
14-hansen-can	73	23	+	+	CC
14-hansen-can	73	24	B2M+2X+QKfbmTTQ`i@p2+iQ`@K	B2M+2X+QKfbmTTQ`i@p2+iQ`@K	NNP
14-hansen-can	73	25	�	�	NNP
14-hansen-can	73	26	+?BM2@BMi`Q	+?BM2@BMi`Q	NNP
14-hansen-can	73	27	/	/	SYM
14-hansen-can	73	28	m+iBQM@iQ@K	m+iBQM@iQ@K	NNP
14-hansen-can	73	29	�	�	,
14-hansen-can	73	30	+?BM2@H2	+?BM2@H2	NNP
14-hansen-can	73	31	�	�	NNP
14-hansen-can	73	32	`MBM;@	`mbm;@	NN
14-hansen-can	73	33	�	�	.
14-hansen-can	73	34	H;Q`Bi?Kb@Nj9	h;q`bi?kb@nj9	NN
14-hansen-can	73	35	�	�	NNP
14-hansen-can	73	36	99	99	CD
14-hansen-can	73	37	97+	97+	CD
14-hansen-can	73	38	�	�	NNS
14-hansen-can	73	39	9d	9d	NN
14-hansen-can	73	40	.	.	.
14-hansen-can	74	1	11Augmented	11augmented	JJ
14-hansen-can	74	2	term	term	NN
14-hansen-can	74	3	frequency	frequency	NN
14-hansen-can	74	4	refers	refer	VBZ
14-hansen-can	74	5	to	to	IN
14-hansen-can	74	6	the	the	DT
14-hansen-can	74	7	number	number	NN
14-hansen-can	74	8	of	of	IN
14-hansen-can	74	9	times	time	NNS
14-hansen-can	74	10	a	a	DT
14-hansen-can	74	11	term	term	NN
14-hansen-can	74	12	occurs	occur	VBZ
14-hansen-can	74	13	in	in	IN
14-hansen-can	74	14	the	the	DT
14-hansen-can	74	15	document	document	NN
14-hansen-can	74	16	divided	divide	VBN
14-hansen-can	74	17	by	by	IN
14-hansen-can	74	18	the	the	DT
14-hansen-can	74	19	number	number	NN
14-hansen-can	74	20	of	of	IN
14-hansen-can	74	21	times	time	NNS
14-hansen-can	74	22	the	the	DT
14-hansen-can	74	23	most	most	RBS
14-hansen-can	74	24	frequent	frequent	JJ
14-hansen-can	74	25	occurring	occurring	NN
14-hansen-can	74	26	term	term	NN
14-hansen-can	74	27	appears	appear	VBZ
14-hansen-can	74	28	in	in	IN
14-hansen-can	74	29	the	the	DT
14-hansen-can	74	30	document	document	NN
14-hansen-can	74	31	.	.	.
14-hansen-can	75	1	12The	12the	CD
14-hansen-can	75	2	decision	decision	NN
14-hansen-can	75	3	threshold	threshold	NN
14-hansen-can	75	4	is	be	VBZ
14-hansen-can	75	5	the	the	DT
14-hansen-can	75	6	cut	cut	NN
14-hansen-can	75	7	-	-	HYPH
14-hansen-can	75	8	off	off	RP
14-hansen-can	75	9	for	for	IN
14-hansen-can	75	10	how	how	WRB
14-hansen-can	75	11	close	close	RB
14-hansen-can	75	12	to	to	IN
14-hansen-can	75	13	a	a	DT
14-hansen-can	75	14	category	category	NN
14-hansen-can	75	15	the	the	DT
14-hansen-can	75	16	SVM	SVM	NNP
14-hansen-can	75	17	must	must	MD
14-hansen-can	75	18	determine	determine	VB
14-hansen-can	75	19	an	an	DT
14-hansen-can	75	20	item	item	NN
14-hansen-can	75	21	to	to	TO
14-hansen-can	75	22	be	be	VB
14-hansen-can	75	23	in	in	IN
14-hansen-can	75	24	order	order	NN
14-hansen-can	75	25	for	for	IN
14-hansen-can	75	26	it	-PRON-	PRP
14-hansen-can	75	27	to	to	TO
14-hansen-can	75	28	be	be	VB
14-hansen-can	75	29	assigned	assign	VBN
14-hansen-can	75	30	that	that	DT
14-hansen-can	75	31	category	category	NN
14-hansen-can	75	32	.	.	.
14-hansen-can	76	1	Řehůřek	Řehůřek	NNP
14-hansen-can	76	2	and	and	CC
14-hansen-can	76	3	Sojka㸪s	Sojka㸪s	NNP
14-hansen-can	76	4	work	work	NN
14-hansen-can	76	5	varied	vary	VBD
14-hansen-can	76	6	this	this	DT
14-hansen-can	76	7	threshold	threshold	NN
14-hansen-can	76	8	dynamically	dynamically	RB
14-hansen-can	76	9	.	.	.
14-hansen-can	77	1	13Score	13score	CD
14-hansen-can	77	2	-	-	HYPH
14-hansen-can	77	3	based	base	VBN
14-hansen-can	77	4	local	local	JJ
14-hansen-can	77	5	optimization	optimization	NN
14-hansen-can	77	6	,	,	,
14-hansen-can	77	7	or	or	CC
14-hansen-can	77	8	s	s	NN
14-hansen-can	77	9	-	-	HYPH
14-hansen-can	77	10	cut	cut	VBN
14-hansen-can	77	11	,	,	,
14-hansen-can	77	12	allows	allow	VBZ
14-hansen-can	77	13	a	a	DT
14-hansen-can	77	14	machine	machine	NN
14-hansen-can	77	15	-	-	HYPH
14-hansen-can	77	16	learning	learn	VBG
14-hansen-can	77	17	model	model	NN
14-hansen-can	77	18	to	to	TO
14-hansen-can	77	19	set	set	VB
14-hansen-can	77	20	different	different	JJ
14-hansen-can	77	21	thresholds	threshold	NNS
14-hansen-can	77	22	for	for	IN
14-hansen-can	77	23	each	each	DT
14-hansen-can	77	24	category	category	NN
14-hansen-can	77	25	with	with	IN
14-hansen-can	77	26	an	an	DT
14-hansen-can	77	27	emphasis	emphasis	NN
14-hansen-can	77	28	on	on	IN
14-hansen-can	77	29	local	local	JJ
14-hansen-can	77	30	,	,	,
14-hansen-can	77	31	or	or	CC
14-hansen-can	77	32	category	category	NN
14-hansen-can	77	33	,	,	,
14-hansen-can	77	34	instead	instead	RB
14-hansen-can	77	35	of	of	IN
14-hansen-can	77	36	global	global	JJ
14-hansen-can	77	37	performance	performance	NN
14-hansen-can	77	38	.	.	.
14-hansen-can	78	1	14Term	14term	CD
14-hansen-can	78	2	frequency	frequency	NN
14-hansen-can	78	3	–	–	:
14-hansen-can	78	4	inverse	inverse	NN
14-hansen-can	78	5	document	document	NN
14-hansen-can	78	6	frequency	frequency	NN
14-hansen-can	78	7	provides	provide	VBZ
14-hansen-can	78	8	a	a	DT
14-hansen-can	78	9	weight	weight	NN
14-hansen-can	78	10	for	for	IN
14-hansen-can	78	11	terms	term	NNS
14-hansen-can	78	12	depending	depend	VBG
14-hansen-can	78	13	on	on	IN
14-hansen-can	78	14	how	how	WRB
14-hansen-can	78	15	frequently	frequently	RB
14-hansen-can	78	16	it	-PRON-	PRP
14-hansen-can	78	17	occurs	occur	VBZ
14-hansen-can	78	18	across	across	IN
14-hansen-can	78	19	the	the	DT
14-hansen-can	78	20	corpus	corpus	NN
14-hansen-can	78	21	.	.	.
14-hansen-can	79	1	A	a	DT
14-hansen-can	79	2	term	term	NN
14-hansen-can	79	3	which	which	WDT
14-hansen-can	79	4	occurs	occur	VBZ
14-hansen-can	79	5	rarely	rarely	RB
14-hansen-can	79	6	across	across	IN
14-hansen-can	79	7	the	the	DT
14-hansen-can	79	8	corpus	corpus	NN
14-hansen-can	79	9	but	but	CC
14-hansen-can	79	10	with	with	IN
14-hansen-can	79	11	a	a	DT
14-hansen-can	79	12	high	high	JJ
14-hansen-can	79	13	frequency	frequency	NN
14-hansen-can	79	14	within	within	IN
14-hansen-can	79	15	a	a	DT
14-hansen-can	79	16	single	single	JJ
14-hansen-can	79	17	document	document	NN
14-hansen-can	79	18	will	will	MD
14-hansen-can	79	19	have	have	VB
14-hansen-can	79	20	a	a	DT
14-hansen-can	79	21	higher	high	JJR
14-hansen-can	79	22	weight	weight	NN
14-hansen-can	79	23	when	when	WRB
14-hansen-can	79	24	classifying	classify	VBG
14-hansen-can	79	25	the	the	DT
14-hansen-can	79	26	document	document	NN
14-hansen-can	79	27	in	in	IN
14-hansen-can	79	28	question	question	NN
14-hansen-can	79	29	.	.	.
14-hansen-can	80	1	15A	15a	CD
14-hansen-can	80	2	Euclidean	euclidean	JJ
14-hansen-can	80	3	norm	norm	NN
14-hansen-can	80	4	provides	provide	VBZ
14-hansen-can	80	5	the	the	DT
14-hansen-can	80	6	distance	distance	NN
14-hansen-can	80	7	from	from	IN
14-hansen-can	80	8	the	the	DT
14-hansen-can	80	9	origin	origin	NN
14-hansen-can	80	10	to	to	IN
14-hansen-can	80	11	a	a	DT
14-hansen-can	80	12	point	point	NN
14-hansen-can	80	13	in	in	IN
14-hansen-can	80	14	an	an	DT
14-hansen-can	80	15	n	n	JJ
14-hansen-can	80	16	-	-	HYPH
14-hansen-can	80	17	dimensional	dimensional	JJ
14-hansen-can	80	18	space	space	NN
14-hansen-can	80	19	.	.	.
14-hansen-can	81	1	It	-PRON-	PRP
14-hansen-can	81	2	is	be	VBZ
14-hansen-can	81	3	calculated	calculate	VBN
14-hansen-can	81	4	by	by	IN
14-hansen-can	81	5	taking	take	VBG
14-hansen-can	81	6	the	the	DT
14-hansen-can	81	7	square	square	JJ
14-hansen-can	81	8	root	root	NN
14-hansen-can	81	9	of	of	IN
14-hansen-can	81	10	the	the	DT
14-hansen-can	81	11	sum	sum	NN
14-hansen-can	81	12	of	of	IN
14-hansen-can	81	13	the	the	DT
14-hansen-can	81	14	squares	square	NNS
14-hansen-can	81	15	of	of	IN
14-hansen-can	81	16	all	all	DT
14-hansen-can	81	17	coordinate	coordinate	JJ
14-hansen-can	81	18	values	value	NNS
14-hansen-can	81	19	.	.	.
14-hansen-can	82	1	16See	16see	LS
14-hansen-can	82	2	?	?	.
14-hansen-can	82	3	iiTb	iitb	UH
14-hansen-can	82	4	,	,	,
14-hansen-can	82	5	ff	ff	NNP
14-hansen-can	82	6	�	�	NNP
14-hansen-can	82	7	+	+	SYM
14-hansen-can	82	8	�	�	NNP
14-hansen-can	82	9	/2KB+XKB+`QbQ7iX+QKf	/2KB+XKB+`QbQ7iX+QKf	.
14-hansen-can	82	10	.	.	.
14-hansen-can	83	1	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	NNP
14-hansen-can	83	2	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	FW
14-hansen-can	83	3	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	NNP
14-hansen-can	83	4	https://academic.microsoft.com/	https://academic.microsoft.com/	ADD
14-hansen-can	83	5	Hansen	Hansen	NNP
14-hansen-can	83	6	163	163	CD
14-hansen-can	83	7	ing	ing	NNP
14-hansen-can	83	8	on	on	IN
14-hansen-can	83	9	the	the	DT
14-hansen-can	83	10	corpus	corpus	NN
14-hansen-can	83	11	of	of	IN
14-hansen-can	83	12	articles	article	NNS
14-hansen-can	83	13	in	in	IN
14-hansen-can	83	14	the	the	DT
14-hansen-can	83	15	MAG	MAG	NNP
14-hansen-can	83	16	to	to	TO
14-hansen-can	83	17	develop	develop	VB
14-hansen-can	83	18	it	-PRON-	PRP
14-hansen-can	83	19	,	,	,
14-hansen-can	83	20	they	-PRON-	PRP
14-hansen-can	83	21	relied	rely	VBD
14-hansen-can	83	22	primarily	primarily	RB
14-hansen-can	83	23	on	on	IN
14-hansen-can	83	24	Wikipedia	Wikipedia	NNP
14-hansen-can	83	25	for	for	IN
14-hansen-can	83	26	its	-PRON-	PRP$
14-hansen-can	83	27	creation	creation	NN
14-hansen-can	83	28	.	.	.
14-hansen-can	84	1	They	-PRON-	PRP
14-hansen-can	84	2	generated	generate	VBD
14-hansen-can	84	3	an	an	DT
14-hansen-can	84	4	initial	initial	JJ
14-hansen-can	84	5	seed	seed	NN
14-hansen-can	84	6	by	by	IN
14-hansen-can	84	7	referencing	reference	VBG
14-hansen-can	84	8	the	the	DT
14-hansen-can	84	9	Science	Science	NNP
14-hansen-can	84	10	Metrix	Metrix	NNP
14-hansen-can	84	11	classification	classification	NN
14-hansen-can	84	12	scheme17	scheme17	NN
14-hansen-can	84	13	and	and	CC
14-hansen-can	84	14	a	a	DT
14-hansen-can	84	15	couple	couple	NN
14-hansen-can	84	16	thousand	thousand	CD
14-hansen-can	84	17	FoS	FoS	NNP
14-hansen-can	84	18	Wikipedia	Wikipedia	NNP
14-hansen-can	84	19	articles	article	NNS
14-hansen-can	84	20	they	-PRON-	PRP
14-hansen-can	84	21	identified	identify	VBD
14-hansen-can	84	22	internally	internally	RB
14-hansen-can	84	23	.	.	.
14-hansen-can	85	1	They	-PRON-	PRP
14-hansen-can	85	2	then	then	RB
14-hansen-can	85	3	used	use	VBD
14-hansen-can	85	4	an	an	DT
14-hansen-can	85	5	iter-	iter-	JJ
14-hansen-can	85	6	ative	ative	JJ
14-hansen-can	85	7	process	process	NN
14-hansen-can	85	8	to	to	TO
14-hansen-can	85	9	identify	identify	VB
14-hansen-can	85	10	more	more	JJR
14-hansen-can	85	11	FoS	fos	NN
14-hansen-can	85	12	in	in	IN
14-hansen-can	85	13	Wikipedia	Wikipedia	NNP
14-hansen-can	85	14	based	base	VBN
14-hansen-can	85	15	on	on	IN
14-hansen-can	85	16	whether	whether	IN
14-hansen-can	85	17	they	-PRON-	PRP
14-hansen-can	85	18	were	be	VBD
14-hansen-can	85	19	linked	link	VBN
14-hansen-can	85	20	to	to	IN
14-hansen-can	85	21	Wikipedia	Wikipedia	NNP
14-hansen-can	85	22	articles	article	NNS
14-hansen-can	85	23	that	that	WDT
14-hansen-can	85	24	were	be	VBD
14-hansen-can	85	25	already	already	RB
14-hansen-can	85	26	identified	identify	VBN
14-hansen-can	85	27	as	as	IN
14-hansen-can	85	28	FoS	fos	NN
14-hansen-can	85	29	and	and	CC
14-hansen-can	85	30	whether	whether	IN
14-hansen-can	85	31	the	the	DT
14-hansen-can	85	32	new	new	JJ
14-hansen-can	85	33	articles	article	NNS
14-hansen-can	85	34	represented	represent	VBD
14-hansen-can	85	35	valid	valid	JJ
14-hansen-can	85	36	entity	entity	NN
14-hansen-can	85	37	types	type	NNS
14-hansen-can	85	38	—	—	:
14-hansen-can	85	39	e.g	e.g	NNP
14-hansen-can	85	40	.	.	.
14-hansen-can	86	1	an	an	DT
14-hansen-can	86	2	entity	entity	NN
14-hansen-can	86	3	type	type	NN
14-hansen-can	86	4	of	of	IN
14-hansen-can	86	5	protein	protein	NN
14-hansen-can	86	6	would	would	MD
14-hansen-can	86	7	be	be	VB
14-hansen-can	86	8	added	add	VBN
14-hansen-can	86	9	and	and	CC
14-hansen-can	86	10	an	an	DT
14-hansen-can	86	11	entity	entity	NN
14-hansen-can	86	12	type	type	NN
14-hansen-can	86	13	of	of	IN
14-hansen-can	86	14	person	person	NN
14-hansen-can	86	15	would	would	MD
14-hansen-can	86	16	be	be	VB
14-hansen-can	86	17	ex-	ex-	RB
14-hansen-can	86	18	cluded	clude	VBN
14-hansen-can	86	19	(	(	-LRB-
14-hansen-can	86	20	Shen	Shen	NNP
14-hansen-can	86	21	,	,	,
14-hansen-can	86	22	Ma	Ma	NNP
14-hansen-can	86	23	,	,	,
14-hansen-can	86	24	and	and	CC
14-hansen-can	86	25	Wang	Wang	NNP
14-hansen-can	86	26	2018	2018	CD
14-hansen-can	86	27	,	,	,
14-hansen-can	86	28	3	3	CD
14-hansen-can	86	29	)	)	-RRB-
14-hansen-can	86	30	.	.	.
14-hansen-can	87	1	This	this	DT
14-hansen-can	87	2	work	work	NN
14-hansen-can	87	3	allowed	allow	VBD
14-hansen-can	87	4	Microsoft	Microsoft	NNP
14-hansen-can	87	5	to	to	TO
14-hansen-can	87	6	develop	develop	VB
14-hansen-can	87	7	a	a	DT
14-hansen-can	87	8	list	list	NN
14-hansen-can	87	9	of	of	IN
14-hansen-can	87	10	more	more	JJR
14-hansen-can	87	11	than	than	IN
14-hansen-can	87	12	200,000	200,000	CD
14-hansen-can	87	13	Fields	field	NNS
14-hansen-can	87	14	of	of	IN
14-hansen-can	87	15	Study	Study	NNP
14-hansen-can	87	16	for	for	IN
14-hansen-can	87	17	use	use	NN
14-hansen-can	87	18	as	as	IN
14-hansen-can	87	19	categories	category	NNS
14-hansen-can	87	20	in	in	IN
14-hansen-can	87	21	the	the	DT
14-hansen-can	87	22	MAG	MAG	NNP
14-hansen-can	87	23	.	.	.
14-hansen-can	88	1	Microsoft	Microsoft	NNP
14-hansen-can	88	2	then	then	RB
14-hansen-can	88	3	used	use	VBD
14-hansen-can	88	4	machine	machine	NN
14-hansen-can	88	5	learning	learning	NN
14-hansen-can	88	6	techniques	technique	NNS
14-hansen-can	88	7	to	to	TO
14-hansen-can	88	8	apply	apply	VB
14-hansen-can	88	9	these	these	DT
14-hansen-can	88	10	FoS	fos	NN
14-hansen-can	88	11	to	to	IN
14-hansen-can	88	12	their	-PRON-	PRP$
14-hansen-can	88	13	corpus	corpus	NN
14-hansen-can	88	14	of	of	IN
14-hansen-can	88	15	over	over	IN
14-hansen-can	88	16	140	140	CD
14-hansen-can	88	17	million	million	CD
14-hansen-can	88	18	academic	academic	JJ
14-hansen-can	88	19	articles	article	NNS
14-hansen-can	88	20	.	.	.
14-hansen-can	89	1	The	the	DT
14-hansen-can	89	2	specific	specific	JJ
14-hansen-can	89	3	techniques	technique	NNS
14-hansen-can	89	4	are	be	VBP
14-hansen-can	89	5	not	not	RB
14-hansen-can	89	6	as	as	RB
14-hansen-can	89	7	clear	clear	JJ
14-hansen-can	89	8	as	as	IN
14-hansen-can	89	9	they	-PRON-	PRP
14-hansen-can	89	10	were	be	VBD
14-hansen-can	89	11	with	with	IN
14-hansen-can	89	12	the	the	DT
14-hansen-can	89	13	previ-	previ-	JJ
14-hansen-can	89	14	ous	ous	JJ
14-hansen-can	89	15	examples	example	NNS
14-hansen-can	89	16	,	,	,
14-hansen-can	89	17	likely	likely	RB
14-hansen-can	89	18	due	due	IN
14-hansen-can	89	19	to	to	IN
14-hansen-can	89	20	Microsoft	Microsoft	NNP
14-hansen-can	89	21	protecting	protect	VBG
14-hansen-can	89	22	their	-PRON-	PRP$
14-hansen-can	89	23	specific	specific	JJ
14-hansen-can	89	24	methods	method	NNS
14-hansen-can	89	25	from	from	IN
14-hansen-can	89	26	competitors	competitor	NNS
14-hansen-can	89	27	,	,	,
14-hansen-can	89	28	but	but	CC
14-hansen-can	89	29	the	the	DT
14-hansen-can	89	30	article	article	NN
14-hansen-can	89	31	published	publish	VBN
14-hansen-can	89	32	to	to	IN
14-hansen-can	89	33	the	the	DT
14-hansen-can	89	34	arXiv	arXiv	NNP
14-hansen-can	89	35	by	by	IN
14-hansen-can	89	36	their	-PRON-	PRP$
14-hansen-can	89	37	researchers	researcher	NNS
14-hansen-can	89	38	(	(	-LRB-
14-hansen-can	89	39	Shen	Shen	NNP
14-hansen-can	89	40	,	,	,
14-hansen-can	89	41	Ma	Ma	NNP
14-hansen-can	89	42	,	,	,
14-hansen-can	89	43	and	and	CC
14-hansen-can	89	44	Wang	Wang	NNP
14-hansen-can	89	45	2018	2018	CD
14-hansen-can	89	46	)	)	-RRB-
14-hansen-can	89	47	and	and	CC
14-hansen-can	89	48	the	the	DT
14-hansen-can	89	49	write	write	NN
14-hansen-can	89	50	up	up	RP
14-hansen-can	89	51	on	on	IN
14-hansen-can	89	52	the	the	DT
14-hansen-can	89	53	MAG	MAG	NNP
14-hansen-can	89	54	website	website	NN
14-hansen-can	89	55	does	do	VBZ
14-hansen-can	89	56	make	make	VB
14-hansen-can	89	57	it	-PRON-	PRP
14-hansen-can	89	58	clear	clear	JJ
14-hansen-can	89	59	they	-PRON-	PRP
14-hansen-can	89	60	used	use	VBD
14-hansen-can	89	61	vector	vector	NN
14-hansen-can	89	62	based	base	VBN
14-hansen-can	89	63	convolutional	convolutional	JJ
14-hansen-can	89	64	neural	neural	JJ
14-hansen-can	89	65	networks	network	NNS
14-hansen-can	89	66	which	which	WDT
14-hansen-can	89	67	relied	rely	VBD
14-hansen-can	89	68	on	on	IN
14-hansen-can	89	69	Skip	Skip	NNP
14-hansen-can	89	70	-	-	HYPH
14-hansen-can	89	71	gram	gram	NNP
14-hansen-can	89	72	(	(	-LRB-
14-hansen-can	89	73	Mikolov	Mikolov	NNP
14-hansen-can	89	74	et	et	FW
14-hansen-can	89	75	al	al	NNP
14-hansen-can	89	76	.	.	.
14-hansen-can	90	1	2013	2013	LS
14-hansen-can	90	2	)	)	-RRB-
14-hansen-can	90	3	embeddings	embedding	NNS
14-hansen-can	90	4	and	and	CC
14-hansen-can	90	5	bag	bag	NN
14-hansen-can	90	6	-	-	HYPH
14-hansen-can	90	7	of	of	IN
14-hansen-can	90	8	-	-	HYPH
14-hansen-can	90	9	words	word	NNS
14-hansen-can	90	10	/	/	SYM
14-hansen-can	90	11	entities	entity	NNS
14-hansen-can	90	12	features	feature	VBZ
14-hansen-can	90	13	to	to	TO
14-hansen-can	90	14	cre-	cre-	VB
14-hansen-can	90	15	ate	eat	VBD
14-hansen-can	90	16	their	-PRON-	PRP$
14-hansen-can	90	17	vectors	vector	NNS
14-hansen-can	90	18	(	(	-LRB-
14-hansen-can	90	19	“	"	``
14-hansen-can	90	20	Microsoft	Microsoft	NNP
14-hansen-can	90	21	Academic	Academic	NNP
14-hansen-can	90	22	Increases	Increases	NNPS
14-hansen-can	90	23	Power	Power	NNP
14-hansen-can	90	24	of	of	IN
14-hansen-can	90	25	Semantic	Semantic	NNP
14-hansen-can	90	26	Search	Search	NNP
14-hansen-can	90	27	by	by	IN
14-hansen-can	90	28	Adding	add	VBG
14-hansen-can	90	29	More	More	JJR
14-hansen-can	90	30	Fields	field	NNS
14-hansen-can	90	31	of	of	IN
14-hansen-can	90	32	Study	Study	NNP
14-hansen-can	90	33	—	—	:
14-hansen-can	90	34	Microsoft	Microsoft	NNP
14-hansen-can	90	35	Research	Research	NNP
14-hansen-can	90	36	”	"	''
14-hansen-can	90	37	2018	2018	CD
14-hansen-can	90	38	)	)	-RRB-
14-hansen-can	90	39	.	.	.
14-hansen-can	91	1	One	one	CD
14-hansen-can	91	2	really	really	RB
14-hansen-can	91	3	interesting	interesting	JJ
14-hansen-can	91	4	part	part	NN
14-hansen-can	91	5	of	of	IN
14-hansen-can	91	6	the	the	DT
14-hansen-can	91	7	machine	machine	NN
14-hansen-can	91	8	learn-	learn-	NNP
14-hansen-can	91	9	ing	ing	NNP
14-hansen-can	91	10	method	method	NN
14-hansen-can	91	11	used	use	VBN
14-hansen-can	91	12	by	by	IN
14-hansen-can	91	13	Microsoft	Microsoft	NNP
14-hansen-can	91	14	was	be	VBD
14-hansen-can	91	15	that	that	IN
14-hansen-can	91	16	it	-PRON-	PRP
14-hansen-can	91	17	did	do	VBD
14-hansen-can	91	18	not	not	RB
14-hansen-can	91	19	rely	rely	VB
14-hansen-can	91	20	only	only	RB
14-hansen-can	91	21	on	on	IN
14-hansen-can	91	22	information	information	NN
14-hansen-can	91	23	from	from	IN
14-hansen-can	91	24	the	the	DT
14-hansen-can	91	25	article	article	NN
14-hansen-can	91	26	being	be	VBG
14-hansen-can	91	27	categorized	categorize	VBN
14-hansen-can	91	28	.	.	.
14-hansen-can	92	1	It	-PRON-	PRP
14-hansen-can	92	2	also	also	RB
14-hansen-can	92	3	utilized	utilize	VBD
14-hansen-can	92	4	the	the	DT
14-hansen-can	92	5	citations	citation	NNS
14-hansen-can	92	6	to	to	IN
14-hansen-can	92	7	and	and	CC
14-hansen-can	92	8	references	reference	NNS
14-hansen-can	92	9	from	from	IN
14-hansen-can	92	10	information	information	NN
14-hansen-can	92	11	about	about	IN
14-hansen-can	92	12	the	the	DT
14-hansen-can	92	13	article	article	NN
14-hansen-can	92	14	in	in	IN
14-hansen-can	92	15	the	the	DT
14-hansen-can	92	16	MAG	MAG	NNP
14-hansen-can	92	17	,	,	,
14-hansen-can	92	18	and	and	CC
14-hansen-can	92	19	used	use	VBD
14-hansen-can	92	20	the	the	DT
14-hansen-can	92	21	FoS	fos	NN
14-hansen-can	92	22	the	the	DT
14-hansen-can	92	23	citations	citation	NNS
14-hansen-can	92	24	and	and	CC
14-hansen-can	92	25	references	reference	NNS
14-hansen-can	92	26	were	be	VBD
14-hansen-can	92	27	assigned	assign	VBN
14-hansen-can	92	28	in	in	IN
14-hansen-can	92	29	order	order	NN
14-hansen-can	92	30	to	to	TO
14-hansen-can	92	31	influence	influence	VB
14-hansen-can	92	32	the	the	DT
14-hansen-can	92	33	FoS	fos	NN
14-hansen-can	92	34	of	of	IN
14-hansen-can	92	35	the	the	DT
14-hansen-can	92	36	original	original	JJ
14-hansen-can	92	37	article	article	NN
14-hansen-can	92	38	.	.	.
14-hansen-can	93	1	The	the	DT
14-hansen-can	93	2	identification	identification	NN
14-hansen-can	93	3	of	of	IN
14-hansen-can	93	4	potential	potential	JJ
14-hansen-can	93	5	FoS	fos	NN
14-hansen-can	93	6	and	and	CC
14-hansen-can	93	7	their	-PRON-	PRP$
14-hansen-can	93	8	assignment	assignment	NN
14-hansen-can	93	9	to	to	IN
14-hansen-can	93	10	articles	article	NNS
14-hansen-can	93	11	was	be	VBD
14-hansen-can	93	12	only	only	RB
14-hansen-can	93	13	a	a	DT
14-hansen-can	93	14	part	part	NN
14-hansen-can	93	15	of	of	IN
14-hansen-can	93	16	Mi-	Mi-	NNP
14-hansen-can	93	17	crosoft	crosoft	NN
14-hansen-can	93	18	’s	’s	POS
14-hansen-can	93	19	purpose	purpose	NN
14-hansen-can	93	20	.	.	.
14-hansen-can	94	1	In	in	IN
14-hansen-can	94	2	order	order	NN
14-hansen-can	94	3	to	to	TO
14-hansen-can	94	4	fully	fully	RB
14-hansen-can	94	5	index	index	VB
14-hansen-can	94	6	the	the	DT
14-hansen-can	94	7	MAG	MAG	NNP
14-hansen-can	94	8	and	and	CC
14-hansen-can	94	9	make	make	VB
14-hansen-can	94	10	it	-PRON-	PRP
14-hansen-can	94	11	searchable	searchable	JJ
14-hansen-can	94	12	they	-PRON-	PRP
14-hansen-can	94	13	also	also	RB
14-hansen-can	94	14	wished	wish	VBD
14-hansen-can	94	15	to	to	TO
14-hansen-can	94	16	determine	determine	VB
14-hansen-can	94	17	the	the	DT
14-hansen-can	94	18	relationships	relationship	NNS
14-hansen-can	94	19	between	between	IN
14-hansen-can	94	20	the	the	DT
14-hansen-can	94	21	FoS	fos	NN
14-hansen-can	94	22	;	;	:
14-hansen-can	94	23	in	in	IN
14-hansen-can	94	24	other	other	JJ
14-hansen-can	94	25	words	word	NNS
14-hansen-can	94	26	they	-PRON-	PRP
14-hansen-can	94	27	wanted	want	VBD
14-hansen-can	94	28	to	to	TO
14-hansen-can	94	29	build	build	VB
14-hansen-can	94	30	a	a	DT
14-hansen-can	94	31	hierarchical	hierarchical	JJ
14-hansen-can	94	32	taxonomy	taxonomy	NN
14-hansen-can	94	33	.	.	.
14-hansen-can	95	1	To	to	TO
14-hansen-can	95	2	achieve	achieve	VB
14-hansen-can	95	3	this	this	DT
14-hansen-can	95	4	they	-PRON-	PRP
14-hansen-can	95	5	used	use	VBD
14-hansen-can	95	6	the	the	DT
14-hansen-can	95	7	article	article	NN
14-hansen-can	95	8	categorizations	categorization	NNS
14-hansen-can	95	9	and	and	CC
14-hansen-can	95	10	defined	define	VBD
14-hansen-can	95	11	a	a	DT
14-hansen-can	95	12	Field	Field	NNP
14-hansen-can	95	13	of	of	IN
14-hansen-can	95	14	Study	Study	NNP
14-hansen-can	95	15	A	A	NNP
14-hansen-can	95	16	as	as	IN
14-hansen-can	95	17	the	the	DT
14-hansen-can	95	18	parent	parent	NN
14-hansen-can	95	19	of	of	IN
14-hansen-can	95	20	B	b	NN
14-hansen-can	95	21	if	if	IN
14-hansen-can	95	22	the	the	DT
14-hansen-can	95	23	articles	article	NNS
14-hansen-can	95	24	categorized	categorize	VBN
14-hansen-can	95	25	as	as	IN
14-hansen-can	95	26	B	B	NNP
14-hansen-can	95	27	were	be	VBD
14-hansen-can	95	28	close	close	JJ
14-hansen-can	95	29	to	to	IN
14-hansen-can	95	30	a	a	DT
14-hansen-can	95	31	subset	subset	NN
14-hansen-can	95	32	of	of	IN
14-hansen-can	95	33	the	the	DT
14-hansen-can	95	34	articles	article	NNS
14-hansen-can	95	35	categorized	categorize	VBN
14-hansen-can	95	36	as	as	IN
14-hansen-can	95	37	A	a	DT
14-hansen-can	95	38	(	(	-LRB-
14-hansen-can	95	39	a	a	DT
14-hansen-can	95	40	more	more	RBR
14-hansen-can	95	41	formal	formal	JJ
14-hansen-can	95	42	definition	definition	NN
14-hansen-can	95	43	can	can	MD
14-hansen-can	95	44	be	be	VB
14-hansen-can	95	45	found	find	VBN
14-hansen-can	95	46	in	in	IN
14-hansen-can	95	47	(	(	-LRB-
14-hansen-can	95	48	Shen	Shen	NNP
14-hansen-can	95	49	,	,	,
14-hansen-can	95	50	Ma	Ma	NNP
14-hansen-can	95	51	,	,	,
14-hansen-can	95	52	and	and	CC
14-hansen-can	95	53	Wang	Wang	NNP
14-hansen-can	95	54	2018	2018	CD
14-hansen-can	95	55	,	,	,
14-hansen-can	95	56	4	4	CD
14-hansen-can	95	57	)	)	-RRB-
14-hansen-can	95	58	.	.	.
14-hansen-can	96	1	This	this	DT
14-hansen-can	96	2	work	work	NN
14-hansen-can	96	3	,	,	,
14-hansen-can	96	4	which	which	WDT
14-hansen-can	96	5	cre-	cre-	NN
14-hansen-can	96	6	ated	ate	VBD
14-hansen-can	96	7	a	a	DT
14-hansen-can	96	8	six	six	CD
14-hansen-can	96	9	-	-	HYPH
14-hansen-can	96	10	level	level	NN
14-hansen-can	96	11	hierarchy	hierarchy	NN
14-hansen-can	96	12	,	,	,
14-hansen-can	96	13	was	be	VBD
14-hansen-can	96	14	mostly	mostly	RB
14-hansen-can	96	15	automated	automate	VBN
14-hansen-can	96	16	,	,	,
14-hansen-can	96	17	but	but	CC
14-hansen-can	96	18	Microsoft	Microsoft	NNP
14-hansen-can	96	19	did	do	VBD
14-hansen-can	96	20	inspect	inspect	VB
14-hansen-can	96	21	and	and	CC
14-hansen-can	96	22	manually	manually	RB
14-hansen-can	96	23	adjust	adjust	VB
14-hansen-can	96	24	the	the	DT
14-hansen-can	96	25	relationships	relationship	NNS
14-hansen-can	96	26	between	between	IN
14-hansen-can	96	27	FoS	FoS	NNP
14-hansen-can	96	28	on	on	IN
14-hansen-can	96	29	the	the	DT
14-hansen-can	96	30	highest	high	JJS
14-hansen-can	96	31	two	two	CD
14-hansen-can	96	32	levels	level	NNS
14-hansen-can	96	33	.	.	.
14-hansen-can	97	1	To	to	TO
14-hansen-can	97	2	evaluate	evaluate	VB
14-hansen-can	97	3	the	the	DT
14-hansen-can	97	4	quality	quality	NN
14-hansen-can	97	5	of	of	IN
14-hansen-can	97	6	their	-PRON-	PRP$
14-hansen-can	97	7	FoS	FoS	NNP
14-hansen-can	97	8	taxonomy	taxonomy	NN
14-hansen-can	97	9	and	and	CC
14-hansen-can	97	10	categorization	categorization	NN
14-hansen-can	97	11	work	work	NN
14-hansen-can	97	12	,	,	,
14-hansen-can	97	13	Microsoft	Microsoft	NNP
14-hansen-can	97	14	randomly	randomly	RB
14-hansen-can	97	15	sampled	sample	VBD
14-hansen-can	97	16	data	datum	NNS
14-hansen-can	97	17	at	at	IN
14-hansen-can	97	18	each	each	DT
14-hansen-can	97	19	of	of	IN
14-hansen-can	97	20	the	the	DT
14-hansen-can	97	21	three	three	CD
14-hansen-can	97	22	steps	step	NNS
14-hansen-can	97	23	of	of	IN
14-hansen-can	97	24	the	the	DT
14-hansen-can	97	25	project	project	NN
14-hansen-can	97	26	and	and	CC
14-hansen-can	97	27	used	use	VBD
14-hansen-can	97	28	human	human	JJ
14-hansen-can	97	29	judges	judge	NNS
14-hansen-can	97	30	to	to	TO
14-hansen-can	97	31	assess	assess	VB
14-hansen-can	97	32	their	-PRON-	PRP$
14-hansen-can	97	33	ac-	ac-	JJ
14-hansen-can	97	34	curacy	curacy	NN
14-hansen-can	97	35	.	.	.
14-hansen-can	98	1	The	the	DT
14-hansen-can	98	2	accuracy	accuracy	NN
14-hansen-can	98	3	assessments	assessment	NNS
14-hansen-can	98	4	of	of	IN
14-hansen-can	98	5	the	the	DT
14-hansen-can	98	6	three	three	CD
14-hansen-can	98	7	steps	step	NNS
14-hansen-can	98	8	were	be	VBD
14-hansen-can	98	9	not	not	RB
14-hansen-can	98	10	as	as	RB
14-hansen-can	98	11	complete	complete	JJ
14-hansen-can	98	12	as	as	IN
14-hansen-can	98	13	they	-PRON-	PRP
14-hansen-can	98	14	would	would	MD
14-hansen-can	98	15	be	be	VB
14-hansen-can	98	16	with	with	IN
14-hansen-can	98	17	the	the	DT
14-hansen-can	98	18	mathematics	mathematic	NNS
14-hansen-can	98	19	categorization	categorization	NN
14-hansen-can	98	20	,	,	,
14-hansen-can	98	21	as	as	IN
14-hansen-can	98	22	that	that	DT
14-hansen-can	98	23	approach	approach	NN
14-hansen-can	98	24	would	would	MD
14-hansen-can	98	25	evaluate	evaluate	VB
14-hansen-can	98	26	terms	term	NNS
14-hansen-can	98	27	across	across	IN
14-hansen-can	98	28	the	the	DT
14-hansen-can	98	29	whole	whole	NN
14-hansen-can	98	30	of	of	IN
14-hansen-can	98	31	their	-PRON-	PRP$
14-hansen-can	98	32	data	data	NN
14-hansen-can	98	33	sets	set	NNS
14-hansen-can	98	34	,	,	,
14-hansen-can	98	35	but	but	CC
14-hansen-can	98	36	the	the	DT
14-hansen-can	98	37	projects	project	NNS
14-hansen-can	98	38	are	be	VBP
14-hansen-can	98	39	of	of	IN
14-hansen-can	98	40	very	very	RB
14-hansen-can	98	41	different	different	JJ
14-hansen-can	98	42	scales	scale	NNS
14-hansen-can	98	43	so	so	RB
14-hansen-can	98	44	different	different	JJ
14-hansen-can	98	45	methods	method	NNS
14-hansen-can	98	46	are	be	VBP
14-hansen-can	98	47	appropriate	appropriate	JJ
14-hansen-can	98	48	.	.	.
14-hansen-can	99	1	In	in	IN
14-hansen-can	99	2	the	the	DT
14-hansen-can	99	3	end	end	NN
14-hansen-can	99	4	Microsoft	Microsoft	NNP
14-hansen-can	99	5	estimates	estimate	VBZ
14-hansen-can	99	6	the	the	DT
14-hansen-can	99	7	accuracy	accuracy	NN
14-hansen-can	99	8	of	of	IN
14-hansen-can	99	9	the	the	DT
14-hansen-can	99	10	FoS	fos	NN
14-hansen-can	99	11	at	at	IN
14-hansen-can	99	12	94.75	94.75	CD
14-hansen-can	99	13	%	%	NN
14-hansen-can	99	14	,	,	,
14-hansen-can	99	15	the	the	DT
14-hansen-can	99	16	article	article	NN
14-hansen-can	99	17	categorization	categorization	NN
14-hansen-can	99	18	at	at	IN
14-hansen-can	99	19	81.2	81.2	CD
14-hansen-can	99	20	%	%	NN
14-hansen-can	99	21	,	,	,
14-hansen-can	99	22	and	and	CC
14-hansen-can	99	23	the	the	DT
14-hansen-can	99	24	hierarchy	hierarchy	NN
14-hansen-can	99	25	at	at	IN
14-hansen-can	99	26	78	78	CD
14-hansen-can	99	27	%	%	NN
14-hansen-can	99	28	(	(	-LRB-
14-hansen-can	99	29	Shen	Shen	NNP
14-hansen-can	99	30	,	,	,
14-hansen-can	99	31	Ma	Ma	NNP
14-hansen-can	99	32	,	,	,
14-hansen-can	99	33	and	and	CC
14-hansen-can	99	34	Wang	Wang	NNP
14-hansen-can	99	35	2018	2018	CD
14-hansen-can	99	36	,	,	,
14-hansen-can	99	37	5	5	CD
14-hansen-can	99	38	)	)	-RRB-
14-hansen-can	99	39	.	.	.
14-hansen-can	100	1	Since	since	IN
14-hansen-can	100	2	MSC	MSC	NNP
14-hansen-can	100	3	was	be	VBD
14-hansen-can	100	4	created	create	VBN
14-hansen-can	100	5	by	by	IN
14-hansen-can	100	6	humans	human	NNS
14-hansen-can	100	7	there	there	EX
14-hansen-can	100	8	is	be	VBZ
14-hansen-can	100	9	no	no	DT
14-hansen-can	100	10	meaningful	meaningful	JJ
14-hansen-can	100	11	way	way	NN
14-hansen-can	100	12	to	to	TO
14-hansen-can	100	13	compare	compare	VB
14-hansen-can	100	14	the	the	DT
14-hansen-can	100	15	FoS	FoS	NNP
14-hansen-can	100	16	accuracy	accuracy	NN
14-hansen-can	100	17	measurements	measurement	NNS
14-hansen-can	100	18	,	,	,
14-hansen-can	100	19	but	but	CC
14-hansen-can	100	20	the	the	DT
14-hansen-can	100	21	categorization	categorization	NN
14-hansen-can	100	22	accuracy	accuracy	NN
14-hansen-can	100	23	falls	fall	VBZ
14-hansen-can	100	24	somewhere	somewhere	RB
14-hansen-can	100	25	between	between	IN
14-hansen-can	100	26	that	that	DT
14-hansen-can	100	27	of	of	IN
14-hansen-can	100	28	the	the	DT
14-hansen-can	100	29	two	two	CD
14-hansen-can	100	30	mathematics	mathematic	NNS
14-hansen-can	100	31	projects	project	NNS
14-hansen-can	100	32	.	.	.
14-hansen-can	101	1	This	this	DT
14-hansen-can	101	2	is	be	VBZ
14-hansen-can	101	3	a	a	DT
14-hansen-can	101	4	very	very	RB
14-hansen-can	101	5	impres-	impres-	JJ
14-hansen-can	101	6	sive	sive	JJ
14-hansen-can	101	7	result	result	NN
14-hansen-can	101	8	,	,	,
14-hansen-can	101	9	especially	especially	RB
14-hansen-can	101	10	when	when	WRB
14-hansen-can	101	11	the	the	DT
14-hansen-can	101	12	aforementioned	aforementioned	JJ
14-hansen-can	101	13	scale	scale	NN
14-hansen-can	101	14	is	be	VBZ
14-hansen-can	101	15	taken	take	VBN
14-hansen-can	101	16	into	into	IN
14-hansen-can	101	17	account	account	NN
14-hansen-can	101	18	.	.	.
14-hansen-can	102	1	Instead	instead	RB
14-hansen-can	102	2	of	of	IN
14-hansen-can	102	3	trying	try	VBG
14-hansen-can	102	4	to	to	TO
14-hansen-can	102	5	replace	replace	VB
14-hansen-can	102	6	the	the	DT
14-hansen-can	102	7	work	work	NN
14-hansen-can	102	8	of	of	IN
14-hansen-can	102	9	humans	human	NNS
14-hansen-can	102	10	categorizing	categorize	VBG
14-hansen-can	102	11	mathematics	mathematic	NNS
14-hansen-can	102	12	articles	article	NNS
14-hansen-can	102	13	indexed	index	VBN
14-hansen-can	102	14	in	in	IN
14-hansen-can	102	15	a	a	DT
14-hansen-can	102	16	database	database	NN
14-hansen-can	102	17	,	,	,
14-hansen-can	102	18	which	which	WDT
14-hansen-can	102	19	for	for	IN
14-hansen-can	102	20	2018	2018	CD
14-hansen-can	102	21	was	be	VBD
14-hansen-can	102	22	120,324	120,324	CD
14-hansen-can	102	23	items	item	NNS
14-hansen-can	102	24	in	in	IN
14-hansen-can	102	25	MathSciNet18	MathSciNet18	NNP
14-hansen-can	102	26	and	and	CC
14-hansen-can	102	27	97,819	97,819	CD
14-hansen-can	102	28	in	in	IN
14-hansen-can	102	29	zbMath,19	zbmath,19	PRP
14-hansen-can	102	30	the	the	DT
14-hansen-can	102	31	FoS	FoS	NNP
14-hansen-can	102	32	project	project	NN
14-hansen-can	102	33	is	be	VBZ
14-hansen-can	102	34	trying	try	VBG
14-hansen-can	102	35	to	to	TO
14-hansen-can	102	36	replace	replace	VB
14-hansen-can	102	37	the	the	DT
14-hansen-can	102	38	human	human	JJ
14-hansen-can	102	39	categorization	categorization	NN
14-hansen-can	102	40	of	of	IN
14-hansen-can	102	41	all	all	DT
14-hansen-can	102	42	items	item	NNS
14-hansen-can	102	43	indexed	index	VBN
14-hansen-can	102	44	in	in	IN
14-hansen-can	102	45	MAG	MAG	NNP
14-hansen-can	102	46	,	,	,
14-hansen-can	102	47	which	which	WDT
14-hansen-can	102	48	was	be	VBD
14-hansen-can	102	49	10,616,601	10,616,601	CD
14-hansen-can	102	50	in	in	IN
14-hansen-can	102	51	2018.20	2018.20	CD
14-hansen-can	102	52	17See	17see	CD
14-hansen-can	102	53	?	?	.
14-hansen-can	102	54	iiT	iit	CD
14-hansen-can	102	55	,	,	,
14-hansen-can	102	56	ffb+B2M+2@K2i`BtX+QKf?[42Mf+H	ffb+B2M+2@K2i`BtX+QKf?[42Mf+H	NNP
14-hansen-can	102	57	�	�	NNP
14-hansen-can	102	58	bbB7B+	bbB7B+	NNP
14-hansen-can	102	59	�	�	NNP
14-hansen-can	102	60	iBQM	ibqm	NN
14-hansen-can	102	61	.	.	.
14-hansen-can	103	1	18See	18see	LS
14-hansen-can	103	2	?	?	.
14-hansen-can	103	3	iiTb	iitb	UH
14-hansen-can	103	4	,	,	,
14-hansen-can	103	5	ffK	ffK	NNP
14-hansen-can	103	6	�	�	NNP
14-hansen-can	103	7	i?b+BM2iX	i?b+BM2iX	''
14-hansen-can	103	8	�	�	NNP
14-hansen-can	103	9	KbXQ`;fK	KbXQ`;fK	NNP
14-hansen-can	103	10	�	�	NNP
14-hansen-can	103	11	i?b+BM2ifb2	i?b+bm2ifb2	JJ
14-hansen-can	103	12	�	�	JJ
14-hansen-can	103	13	`+?fTm#HB+	`+?ftm#hb+	CD
14-hansen-can	103	14	�	�	,
14-hansen-can	103	15	iBQMbX?iKH?/`4Tm#v2	ibqmbx?ikh?/`4tm#v2	PRP$
14-hansen-can	103	16	�	�	NN
14-hansen-can	103	17	`	`	''
14-hansen-can	103	18	�	�	JJ
14-hansen-can	103	19	v`QT4	v`qt4	NN
14-hansen-can	103	20	2[	2[	NNS
14-hansen-can	103	21	�	�	NNS
14-hansen-can	103	22	�	�	ADD
14-hansen-can	103	23	`;j4kyR3	`;j4kyr3	ADD
14-hansen-can	103	24	.	.	.
14-hansen-can	104	1	19See	19see	CD
14-hansen-can	104	2	?	?	.
14-hansen-can	104	3	iiTb	iitb	UH
14-hansen-can	104	4	,	,	,
14-hansen-can	104	5	ffx#K	ffx#K	NNP
14-hansen-can	104	6	�	�	NNP
14-hansen-can	104	7	i?XQ`;f?[4TvWj	i?XQ`;f?[4TvWj	.
14-hansen-can	104	8	�	�	NNP
14-hansen-can	104	9	kyR3	kyR3	NNP
14-hansen-can	104	10	.	.	.
14-hansen-can	105	1	20See	20see	CD
14-hansen-can	105	2	?	?	.
14-hansen-can	105	3	iiTb	iitb	UH
14-hansen-can	105	4	,	,	,
14-hansen-can	105	5	ff	ff	NNP
14-hansen-can	105	6	�	�	NNP
14-hansen-can	105	7	+	+	SYM
14-hansen-can	105	8	�	�	NNP
14-hansen-can	105	9	/2KB+XKB+`QbQ7iX+QKfTm#HB+	/2kb+xkb+`qbq7ix+qkftm#hb+	NN
14-hansen-can	105	10	�	�	NNP
14-hansen-can	105	11	iBQMbfjjNkj89d	iBQMbfjjNkj89d	NNP
14-hansen-can	105	12	.	.	.
14-hansen-can	106	1	http://science-metrix.com/?q=en/classification	http://science-metrix.com/?q=en/classification	NNP
14-hansen-can	106	2	https://mathscinet.ams.org/mathscinet/search/publications.html?dr=pubyear&yrop=eq&arg3=2018	https://mathscinet.ams.org/mathscinet/search/publications.html?dr=pubyear&yrop=eq&arg3=2018	NNP
14-hansen-can	106	3	https://mathscinet.ams.org/mathscinet/search/publications.html?dr=pubyear&yrop=eq&arg3=2018	https://mathscinet.ams.org/mathscinet/search/publications.html?dr=pubyear&yrop=eq&arg3=2018	NNP
14-hansen-can	106	4	https://zbmath.org/?q=py%3A2018	https://zbmath.org/?q=py%3A2018	VBD
14-hansen-can	106	5	https://academic.microsoft.com/publications/33923547	https://academic.microsoft.com/publications/33923547	NN
14-hansen-can	106	6	164	164	CD
14-hansen-can	106	7	Machine	Machine	NNP
14-hansen-can	106	8	Learning	Learning	NNP
14-hansen-can	106	9	,	,	,
14-hansen-can	106	10	Libraries	Libraries	NNPS
14-hansen-can	106	11	,	,	,
14-hansen-can	106	12	and	and	CC
14-hansen-can	106	13	Cross	Cross	NNP
14-hansen-can	106	14	-	-	NNP
14-hansen-can	106	15	Disciplinary	Disciplinary	NNP
14-hansen-can	106	16	ResearchǔChapter	ResearchǔChapter	NNP
14-hansen-can	106	17	14	14	CD
14-hansen-can	106	18	Both	both	CC
14-hansen-can	106	19	zbMath	zbMath	NNP
14-hansen-can	106	20	and	and	CC
14-hansen-can	106	21	MathSciNet	MathSciNet	NNP
14-hansen-can	106	22	were	be	VBD
14-hansen-can	106	23	capable	capable	JJ
14-hansen-can	106	24	of	of	IN
14-hansen-can	106	25	providing	provide	VBG
14-hansen-can	106	26	the	the	DT
14-hansen-can	106	27	human	human	JJ
14-hansen-can	106	28	labor	labor	NN
14-hansen-can	106	29	to	to	TO
14-hansen-can	106	30	do	do	VB
14-hansen-can	106	31	the	the	DT
14-hansen-can	106	32	work	work	NN
14-hansen-can	106	33	of	of	IN
14-hansen-can	106	34	assigning	assign	VBG
14-hansen-can	106	35	MSC	MSC	NNP
14-hansen-can	106	36	values	value	NNS
14-hansen-can	106	37	to	to	IN
14-hansen-can	106	38	the	the	DT
14-hansen-can	106	39	mathematics	mathematic	NNS
14-hansen-can	106	40	articles	article	NNS
14-hansen-can	106	41	they	-PRON-	PRP
14-hansen-can	106	42	indexed	index	VBD
14-hansen-can	106	43	in	in	IN
14-hansen-can	106	44	2018.21	2018.21	CD
14-hansen-can	106	45	Therefore	therefore	RB
14-hansen-can	106	46	using	use	VBG
14-hansen-can	106	47	an	an	DT
14-hansen-can	106	48	automated	automate	VBN
14-hansen-can	106	49	categorization	categorization	NN
14-hansen-can	106	50	,	,	,
14-hansen-can	106	51	which	which	WDT
14-hansen-can	106	52	at	at	IN
14-hansen-can	106	53	best	good	JJS
14-hansen-can	106	54	could	could	MD
14-hansen-can	106	55	only	only	RB
14-hansen-can	106	56	get	get	VB
14-hansen-can	106	57	the	the	DT
14-hansen-can	106	58	top	top	JJ
14-hansen-can	106	59	level	level	NN
14-hansen-can	106	60	right	right	RB
14-hansen-can	106	61	with	with	IN
14-hansen-can	106	62	90	90	CD
14-hansen-can	106	63	%	%	NN
14-hansen-can	106	64	accuracy	accuracy	NN
14-hansen-can	106	65	,	,	,
14-hansen-can	106	66	was	be	VBD
14-hansen-can	106	67	not	not	RB
14-hansen-can	106	68	the	the	DT
14-hansen-can	106	69	right	right	JJ
14-hansen-can	106	70	approach	approach	NN
14-hansen-can	106	71	.	.	.
14-hansen-can	107	1	On	on	IN
14-hansen-can	107	2	the	the	DT
14-hansen-can	107	3	other	other	JJ
14-hansen-can	107	4	hand	hand	NN
14-hansen-can	107	5	,	,	,
14-hansen-can	107	6	it	-PRON-	PRP
14-hansen-can	107	7	seems	seem	VBZ
14-hansen-can	107	8	clear	clear	JJ
14-hansen-can	107	9	that	that	IN
14-hansen-can	107	10	no	no	DT
14-hansen-can	107	11	one	one	PRP
14-hansen-can	107	12	could	could	MD
14-hansen-can	107	13	feasibly	feasibly	RB
14-hansen-can	107	14	provide	provide	VB
14-hansen-can	107	15	the	the	DT
14-hansen-can	107	16	human	human	JJ
14-hansen-can	107	17	labor	labor	NN
14-hansen-can	107	18	to	to	TO
14-hansen-can	107	19	categorize	categorize	VB
14-hansen-can	107	20	all	all	DT
14-hansen-can	107	21	articles	article	NNS
14-hansen-can	107	22	indexed	index	VBN
14-hansen-can	107	23	by	by	IN
14-hansen-can	107	24	MAG	MAG	NNP
14-hansen-can	107	25	in	in	IN
14-hansen-can	107	26	2018	2018	CD
14-hansen-can	107	27	so	so	IN
14-hansen-can	107	28	an	an	DT
14-hansen-can	107	29	80	80	CD
14-hansen-can	107	30	%	%	NN
14-hansen-can	107	31	accurate	accurate	JJ
14-hansen-can	107	32	categorization	categorization	NN
14-hansen-can	107	33	is	be	VBZ
14-hansen-can	107	34	a	a	DT
14-hansen-can	107	35	significant	significant	JJ
14-hansen-can	107	36	accomplishment	accomplishment	NN
14-hansen-can	107	37	.	.	.
14-hansen-can	108	1	To	to	TO
14-hansen-can	108	2	go	go	VB
14-hansen-can	108	3	back	back	RB
14-hansen-can	108	4	to	to	IN
14-hansen-can	108	5	the	the	DT
14-hansen-can	108	6	nail	nail	NN
14-hansen-can	108	7	and	and	CC
14-hansen-can	108	8	hammer	hammer	NN
14-hansen-can	108	9	analogy	analogy	NN
14-hansen-can	108	10	,	,	,
14-hansen-can	108	11	Microsoft	Microsoft	NNP
14-hansen-can	108	12	may	may	MD
14-hansen-can	108	13	have	have	VB
14-hansen-can	108	14	used	use	VBN
14-hansen-can	108	15	a	a	DT
14-hansen-can	108	16	sledgehammer	sledgehammer	NN
14-hansen-can	108	17	but	but	CC
14-hansen-can	108	18	they	-PRON-	PRP
14-hansen-can	108	19	were	be	VBD
14-hansen-can	108	20	hammering	hammer	VBG
14-hansen-can	108	21	a	a	DT
14-hansen-can	108	22	rather	rather	RB
14-hansen-can	108	23	giant	giant	JJ
14-hansen-can	108	24	nail	nail	NN
14-hansen-can	108	25	.	.	.
14-hansen-can	109	1	Are	be	VBP
14-hansen-can	109	2	You	-PRON-	PRP
14-hansen-can	109	3	Sure	sure	JJ
14-hansen-can	109	4	it	-PRON-	PRP
14-hansen-can	109	5	’s	’	VBZ
14-hansen-can	109	6	a	a	DT
14-hansen-can	109	7	Nail	nail	NN
14-hansen-can	109	8	?	?	.
14-hansen-can	110	1	I	-PRON-	PRP
14-hansen-can	110	2	started	start	VBD
14-hansen-can	110	3	this	this	DT
14-hansen-can	110	4	chapter	chapter	NN
14-hansen-can	110	5	talking	talk	VBG
14-hansen-can	110	6	about	about	IN
14-hansen-can	110	7	how	how	WRB
14-hansen-can	110	8	we	-PRON-	PRP
14-hansen-can	110	9	have	have	VBP
14-hansen-can	110	10	all	all	DT
14-hansen-can	110	11	been	be	VBN
14-hansen-can	110	12	told	tell	VBN
14-hansen-can	110	13	that	that	IN
14-hansen-can	110	14	AI	AI	NNP
14-hansen-can	110	15	and	and	CC
14-hansen-can	110	16	machine	machine	NN
14-hansen-can	110	17	learning	learning	NN
14-hansen-can	110	18	were	be	VBD
14-hansen-can	110	19	going	go	VBG
14-hansen-can	110	20	to	to	TO
14-hansen-can	110	21	revolutionize	revolutionize	VB
14-hansen-can	110	22	everything	everything	NN
14-hansen-can	110	23	in	in	IN
14-hansen-can	110	24	the	the	DT
14-hansen-can	110	25	world	world	NN
14-hansen-can	110	26	.	.	.
14-hansen-can	111	1	That	that	IN
14-hansen-can	111	2	they	-PRON-	PRP
14-hansen-can	111	3	were	be	VBD
14-hansen-can	111	4	the	the	DT
14-hansen-can	111	5	hammers	hammer	NNS
14-hansen-can	111	6	and	and	CC
14-hansen-can	111	7	all	all	PDT
14-hansen-can	111	8	the	the	DT
14-hansen-can	111	9	world	world	NN
14-hansen-can	111	10	’s	’s	POS
14-hansen-can	111	11	problems	problem	NNS
14-hansen-can	111	12	were	be	VBD
14-hansen-can	111	13	nails	nail	NNS
14-hansen-can	111	14	.	.	.
14-hansen-can	112	1	I	-PRON-	PRP
14-hansen-can	112	2	found	find	VBD
14-hansen-can	112	3	that	that	IN
14-hansen-can	112	4	this	this	DT
14-hansen-can	112	5	was	be	VBD
14-hansen-can	112	6	not	not	RB
14-hansen-can	112	7	the	the	DT
14-hansen-can	112	8	case	case	NN
14-hansen-can	112	9	when	when	WRB
14-hansen-can	112	10	we	-PRON-	PRP
14-hansen-can	112	11	tried	try	VBD
14-hansen-can	112	12	to	to	TO
14-hansen-can	112	13	employ	employ	VB
14-hansen-can	112	14	it	-PRON-	PRP
14-hansen-can	112	15	,	,	,
14-hansen-can	112	16	in	in	IN
14-hansen-can	112	17	an	an	DT
14-hansen-can	112	18	ad-	ad-	XX
14-hansen-can	112	19	mittedly	mittedly	RB
14-hansen-can	112	20	rather	rather	RB
14-hansen-can	112	21	naive	naive	JJ
14-hansen-can	112	22	fashion	fashion	NN
14-hansen-can	112	23	,	,	,
14-hansen-can	112	24	to	to	TO
14-hansen-can	112	25	automatically	automatically	RB
14-hansen-can	112	26	categorize	categorize	VB
14-hansen-can	112	27	mathematical	mathematical	JJ
14-hansen-can	112	28	articles	article	NNS
14-hansen-can	112	29	.	.	.
14-hansen-can	113	1	From	from	IN
14-hansen-can	113	2	the	the	DT
14-hansen-can	113	3	other	other	JJ
14-hansen-can	113	4	examples	example	NNS
14-hansen-can	113	5	I	-PRON-	PRP
14-hansen-can	113	6	included	include	VBD
14-hansen-can	113	7	,	,	,
14-hansen-can	113	8	it	-PRON-	PRP
14-hansen-can	113	9	is	be	VBZ
14-hansen-can	113	10	also	also	RB
14-hansen-can	113	11	clear	clear	JJ
14-hansen-can	113	12	computational	computational	JJ
14-hansen-can	113	13	experts	expert	NNS
14-hansen-can	113	14	find	find	VBP
14-hansen-can	113	15	the	the	DT
14-hansen-can	113	16	automatic	automatic	JJ
14-hansen-can	113	17	categorization	categorization	NN
14-hansen-can	113	18	of	of	IN
14-hansen-can	113	19	highly	highly	RB
14-hansen-can	113	20	technical	technical	JJ
14-hansen-can	113	21	content	content	NN
14-hansen-can	113	22	a	a	DT
14-hansen-can	113	23	hard	hard	JJ
14-hansen-can	113	24	problem	problem	NN
14-hansen-can	113	25	to	to	TO
14-hansen-can	113	26	tackle	tackle	VB
14-hansen-can	113	27	,	,	,
14-hansen-can	113	28	one	one	CD
14-hansen-can	113	29	where	where	WRB
14-hansen-can	113	30	success	success	NN
14-hansen-can	113	31	is	be	VBZ
14-hansen-can	113	32	very	very	RB
14-hansen-can	113	33	much	much	RB
14-hansen-can	113	34	dependent	dependent	JJ
14-hansen-can	113	35	on	on	IN
14-hansen-can	113	36	what	what	WP
14-hansen-can	113	37	it	-PRON-	PRP
14-hansen-can	113	38	is	be	VBZ
14-hansen-can	113	39	being	be	VBG
14-hansen-can	113	40	measured	measure	VBN
14-hansen-can	113	41	against	against	IN
14-hansen-can	113	42	.	.	.
14-hansen-can	114	1	In	in	IN
14-hansen-can	114	2	the	the	DT
14-hansen-can	114	3	case	case	NN
14-hansen-can	114	4	of	of	IN
14-hansen-can	114	5	classifying	classify	VBG
14-hansen-can	114	6	mathematics	mathematic	NNS
14-hansen-can	114	7	,	,	,
14-hansen-can	114	8	machine	machine	NN
14-hansen-can	114	9	learning	learning	NN
14-hansen-can	114	10	can	can	MD
14-hansen-can	114	11	do	do	VB
14-hansen-can	114	12	a	a	DT
14-hansen-can	114	13	decent	decent	JJ
14-hansen-can	114	14	job	job	NN
14-hansen-can	114	15	but	but	CC
14-hansen-can	114	16	not	not	RB
14-hansen-can	114	17	enough	enough	JJ
14-hansen-can	114	18	to	to	TO
14-hansen-can	114	19	compete	compete	VB
14-hansen-can	114	20	with	with	IN
14-hansen-can	114	21	humans	human	NNS
14-hansen-can	114	22	.	.	.
14-hansen-can	115	1	In	in	IN
14-hansen-can	115	2	the	the	DT
14-hansen-can	115	3	case	case	NN
14-hansen-can	115	4	of	of	IN
14-hansen-can	115	5	classifying	classify	VBG
14-hansen-can	115	6	everything	everything	NN
14-hansen-can	115	7	,	,	,
14-hansen-can	115	8	scale	scale	NN
14-hansen-can	115	9	gives	give	VBZ
14-hansen-can	115	10	machines	machine	NNS
14-hansen-can	115	11	an	an	DT
14-hansen-can	115	12	edge	edge	NN
14-hansen-can	115	13	,	,	,
14-hansen-can	115	14	as	as	RB
14-hansen-can	115	15	long	long	RB
14-hansen-can	115	16	as	as	IN
14-hansen-can	115	17	you	-PRON-	PRP
14-hansen-can	115	18	have	have	VBP
14-hansen-can	115	19	the	the	DT
14-hansen-can	115	20	computational	computational	JJ
14-hansen-can	115	21	power	power	NN
14-hansen-can	115	22	and	and	CC
14-hansen-can	115	23	knowledge	knowledge	NN
14-hansen-can	115	24	wielded	wield	VBN
14-hansen-can	115	25	by	by	IN
14-hansen-can	115	26	a	a	DT
14-hansen-can	115	27	company	company	NN
14-hansen-can	115	28	like	like	IN
14-hansen-can	115	29	Microsoft	Microsoft	NNP
14-hansen-can	115	30	.	.	.
14-hansen-can	116	1	This	this	DT
14-hansen-can	116	2	collection	collection	NN
14-hansen-can	116	3	is	be	VBZ
14-hansen-can	116	4	about	about	IN
14-hansen-can	116	5	the	the	DT
14-hansen-can	116	6	intersection	intersection	NN
14-hansen-can	116	7	of	of	IN
14-hansen-can	116	8	AI	AI	NNP
14-hansen-can	116	9	,	,	,
14-hansen-can	116	10	machine	machine	NN
14-hansen-can	116	11	learning	learning	NN
14-hansen-can	116	12	,	,	,
14-hansen-can	116	13	deep	deep	JJ
14-hansen-can	116	14	learning	learning	NN
14-hansen-can	116	15	,	,	,
14-hansen-can	116	16	and	and	CC
14-hansen-can	116	17	libraries	library	NNS
14-hansen-can	116	18	.	.	.
14-hansen-can	117	1	While	while	IN
14-hansen-can	117	2	there	there	EX
14-hansen-can	117	3	are	be	VBP
14-hansen-can	117	4	definitely	definitely	RB
14-hansen-can	117	5	problems	problem	NNS
14-hansen-can	117	6	in	in	IN
14-hansen-can	117	7	libraries	library	NNS
14-hansen-can	117	8	where	where	WRB
14-hansen-can	117	9	these	these	DT
14-hansen-can	117	10	techniques	technique	NNS
14-hansen-can	117	11	will	will	MD
14-hansen-can	117	12	be	be	VB
14-hansen-can	117	13	the	the	DT
14-hansen-can	117	14	answer	answer	NN
14-hansen-can	117	15	,	,	,
14-hansen-can	117	16	I	-PRON-	PRP
14-hansen-can	117	17	think	think	VBP
14-hansen-can	117	18	it	-PRON-	PRP
14-hansen-can	117	19	is	be	VBZ
14-hansen-can	117	20	important	important	JJ
14-hansen-can	117	21	to	to	TO
14-hansen-can	117	22	pause	pause	VB
14-hansen-can	117	23	and	and	CC
14-hansen-can	117	24	consider	consider	VB
14-hansen-can	117	25	if	if	IN
14-hansen-can	117	26	artificial	artificial	JJ
14-hansen-can	117	27	intelligence	intelligence	NN
14-hansen-can	117	28	techniques	technique	NNS
14-hansen-can	117	29	are	be	VBP
14-hansen-can	117	30	the	the	DT
14-hansen-can	117	31	best	good	JJS
14-hansen-can	117	32	approach	approach	NN
14-hansen-can	117	33	before	before	IN
14-hansen-can	117	34	trying	try	VBG
14-hansen-can	117	35	to	to	TO
14-hansen-can	117	36	use	use	VB
14-hansen-can	117	37	them	-PRON-	PRP
14-hansen-can	117	38	.	.	.
14-hansen-can	118	1	Libraries	library	NNS
14-hansen-can	118	2	,	,	,
14-hansen-can	118	3	even	even	RB
14-hansen-can	118	4	those	those	DT
14-hansen-can	118	5	like	like	IN
14-hansen-can	118	6	the	the	DT
14-hansen-can	118	7	one	one	NN
14-hansen-can	118	8	I	-PRON-	PRP
14-hansen-can	118	9	work	work	VBP
14-hansen-can	118	10	in	in	RP
14-hansen-can	118	11	,	,	,
14-hansen-can	118	12	which	which	WDT
14-hansen-can	118	13	are	be	VBP
14-hansen-can	118	14	lucky	lucky	JJ
14-hansen-can	118	15	enough	enough	RB
14-hansen-can	118	16	to	to	TO
14-hansen-can	118	17	boast	boast	VB
14-hansen-can	118	18	of	of	IN
14-hansen-can	118	19	incredibly	incredibly	RB
14-hansen-can	118	20	talented	talented	JJ
14-hansen-can	118	21	IT	IT	NNP
14-hansen-can	118	22	departments	department	NNS
14-hansen-can	118	23	,	,	,
14-hansen-can	118	24	do	do	VB
14-hansen-can	118	25	not	not	RB
14-hansen-can	118	26	tend	tend	VB
14-hansen-can	118	27	to	to	TO
14-hansen-can	118	28	have	have	VB
14-hansen-can	118	29	access	access	NN
14-hansen-can	118	30	to	to	IN
14-hansen-can	118	31	a	a	DT
14-hansen-can	118	32	large	large	JJ
14-hansen-can	118	33	amount	amount	NN
14-hansen-can	118	34	of	of	IN
14-hansen-can	118	35	unused	unused	JJ
14-hansen-can	118	36	computational	computational	JJ
14-hansen-can	118	37	power	power	NN
14-hansen-can	118	38	or	or	CC
14-hansen-can	118	39	numerous	numerous	JJ
14-hansen-can	118	40	experts	expert	NNS
14-hansen-can	118	41	in	in	IN
14-hansen-can	118	42	bleeding	bleed	VBG
14-hansen-can	118	43	-	-	HYPH
14-hansen-can	118	44	edge	edge	NN
14-hansen-can	118	45	AI	ai	NN
14-hansen-can	118	46	.	.	.
14-hansen-can	119	1	They	-PRON-	PRP
14-hansen-can	119	2	are	be	VBP
14-hansen-can	119	3	also	also	RB
14-hansen-can	119	4	rather	rather	RB
14-hansen-can	119	5	no-	no-	RB
14-hansen-can	119	6	toriously	toriously	RB
14-hansen-can	119	7	limited	limited	JJ
14-hansen-can	119	8	budget	budget	NN
14-hansen-can	119	9	-	-	HYPH
14-hansen-can	119	10	wise	wise	JJ
14-hansen-can	119	11	and	and	CC
14-hansen-can	119	12	would	would	MD
14-hansen-can	119	13	likely	likely	RB
14-hansen-can	119	14	have	have	VB
14-hansen-can	119	15	to	to	TO
14-hansen-can	119	16	decide	decide	VB
14-hansen-can	119	17	between	between	IN
14-hansen-can	119	18	existing	exist	VBG
14-hansen-can	119	19	budget	budget	NN
14-hansen-can	119	20	items	item	NNS
14-hansen-can	119	21	and	and	CC
14-hansen-can	119	22	developing	develop	VBG
14-hansen-can	119	23	an	an	DT
14-hansen-can	119	24	in	in	IN
14-hansen-can	119	25	-	-	HYPH
14-hansen-can	119	26	house	house	NN
14-hansen-can	119	27	machine	machine	NN
14-hansen-can	119	28	learning	learning	NN
14-hansen-can	119	29	program	program	NN
14-hansen-can	119	30	.	.	.
14-hansen-can	120	1	Those	those	DT
14-hansen-can	120	2	realities	reality	NNS
14-hansen-can	120	3	combined	combine	VBN
14-hansen-can	120	4	with	with	IN
14-hansen-can	120	5	the	the	DT
14-hansen-can	120	6	legitimate	legitimate	JJ
14-hansen-can	120	7	questions	question	NNS
14-hansen-can	120	8	which	which	WDT
14-hansen-can	120	9	can	can	MD
14-hansen-can	120	10	be	be	VB
14-hansen-can	120	11	raised	raise	VBN
14-hansen-can	120	12	about	about	IN
14-hansen-can	120	13	the	the	DT
14-hansen-can	120	14	efficacy	efficacy	NN
14-hansen-can	120	15	of	of	IN
14-hansen-can	120	16	machine	machine	NN
14-hansen-can	120	17	learning	learning	NN
14-hansen-can	120	18	and	and	CC
14-hansen-can	120	19	AI	AI	NNP
14-hansen-can	120	20	with	with	IN
14-hansen-can	120	21	respect	respect	NN
14-hansen-can	120	22	to	to	IN
14-hansen-can	120	23	the	the	DT
14-hansen-can	120	24	types	type	NNS
14-hansen-can	120	25	of	of	IN
14-hansen-can	120	26	problems	problem	NNS
14-hansen-can	120	27	a	a	DT
14-hansen-can	120	28	library	library	NN
14-hansen-can	120	29	may	may	MD
14-hansen-can	120	30	encounter	encounter	VB
14-hansen-can	120	31	,	,	,
14-hansen-can	120	32	such	such	JJ
14-hansen-can	120	33	as	as	IN
14-hansen-can	120	34	categorizing	categorize	VBG
14-hansen-can	120	35	the	the	DT
14-hansen-can	120	36	contents	content	NNS
14-hansen-can	120	37	of	of	IN
14-hansen-can	120	38	highly	highly	RB
14-hansen-can	120	39	technical	technical	JJ
14-hansen-can	120	40	articles	article	NNS
14-hansen-can	120	41	,	,	,
14-hansen-can	120	42	make	make	VB
14-hansen-can	120	43	me	-PRON-	PRP
14-hansen-can	120	44	worry	worry	VB
14-hansen-can	120	45	.	.	.
14-hansen-can	121	1	While	while	IN
14-hansen-can	121	2	there	there	EX
14-hansen-can	121	3	will	will	MD
14-hansen-can	121	4	be	be	VB
14-hansen-can	121	5	many	many	JJ
14-hansen-can	121	6	cases	case	NNS
14-hansen-can	121	7	where	where	WRB
14-hansen-can	121	8	using	use	VBG
14-hansen-can	121	9	AI	AI	NNP
14-hansen-can	121	10	makes	make	VBZ
14-hansen-can	121	11	sense	sense	NN
14-hansen-can	121	12	,	,	,
14-hansen-can	121	13	I	-PRON-	PRP
14-hansen-can	121	14	want	want	VBP
14-hansen-can	121	15	to	to	TO
14-hansen-can	121	16	be	be	VB
14-hansen-can	121	17	sure	sure	JJ
14-hansen-can	121	18	libraries	library	NNS
14-hansen-can	121	19	are	be	VBP
14-hansen-can	121	20	asking	ask	VBG
14-hansen-can	121	21	themselves	-PRON-	PRP
14-hansen-can	121	22	a	a	DT
14-hansen-can	121	23	lot	lot	NN
14-hansen-can	121	24	of	of	IN
14-hansen-can	121	25	questions	question	NNS
14-hansen-can	121	26	before	before	IN
14-hansen-can	121	27	starting	start	VBG
14-hansen-can	121	28	to	to	TO
14-hansen-can	121	29	use	use	VB
14-hansen-can	121	30	it	-PRON-	PRP
14-hansen-can	121	31	.	.	.
14-hansen-can	122	1	Questions	question	NNS
14-hansen-can	122	2	like	like	IN
14-hansen-can	122	3	:	:	:
14-hansen-can	122	4	is	be	VBZ
14-hansen-can	122	5	this	this	DT
14-hansen-can	122	6	problem	problem	NN
14-hansen-can	122	7	large	large	JJ
14-hansen-can	122	8	enough	enough	RB
14-hansen-can	122	9	in	in	IN
14-hansen-can	122	10	scale	scale	NN
14-hansen-can	122	11	to	to	IN
14-hansen-can	122	12	substitute	substitute	NN
14-hansen-can	122	13	machines	machine	NNS
14-hansen-can	122	14	for	for	IN
14-hansen-can	122	15	human	human	JJ
14-hansen-can	122	16	labor	labor	NN
14-hansen-can	122	17	given	give	VBN
14-hansen-can	122	18	that	that	IN
14-hansen-can	122	19	machines	machine	NNS
14-hansen-can	122	20	will	will	MD
14-hansen-can	122	21	likely	likely	RB
14-hansen-can	122	22	be	be	VB
14-hansen-can	122	23	less	less	RBR
14-hansen-can	122	24	accurate	accurate	JJ
14-hansen-can	122	25	?	?	.
14-hansen-can	123	1	Or	or	CC
14-hansen-can	123	2	:	:	:
14-hansen-can	123	3	will	will	MD
14-hansen-can	123	4	using	use	VBG
14-hansen-can	123	5	machines	machine	NNS
14-hansen-can	123	6	to	to	TO
14-hansen-can	123	7	solve	solve	VB
14-hansen-can	123	8	this	this	DT
14-hansen-can	123	9	problem	problem	NN
14-hansen-can	123	10	cost	cost	VB
14-hansen-can	123	11	us	-PRON-	PRP
14-hansen-can	123	12	more	more	RBR
14-hansen-can	123	13	in	in	IN
14-hansen-can	123	14	equip-	equip-	JJ
14-hansen-can	123	15	ment	ment	JJ
14-hansen-can	123	16	and	and	CC
14-hansen-can	123	17	highly	highly	RB
14-hansen-can	123	18	technical	technical	JJ
14-hansen-can	123	19	staff	staff	NN
14-hansen-can	123	20	than	than	IN
14-hansen-can	123	21	our	-PRON-	PRP$
14-hansen-can	123	22	current	current	JJ
14-hansen-can	123	23	solution	solution	NN
14-hansen-can	123	24	,	,	,
14-hansen-can	123	25	and	and	CC
14-hansen-can	123	26	has	have	VBZ
14-hansen-can	123	27	that	that	DT
14-hansen-can	123	28	factored	factor	VBN
14-hansen-can	123	29	in	in	IN
14-hansen-can	123	30	the	the	DT
14-hansen-can	123	31	people	people	NNS
14-hansen-can	123	32	and	and	CC
14-hansen-can	123	33	services	service	NNS
14-hansen-can	123	34	a	a	DT
14-hansen-can	123	35	library	library	NN
14-hansen-can	123	36	may	may	MD
14-hansen-can	123	37	need	need	VB
14-hansen-can	123	38	to	to	TO
14-hansen-can	123	39	cut	cut	VB
14-hansen-can	123	40	to	to	TO
14-hansen-can	123	41	afford	afford	VB
14-hansen-can	123	42	them	-PRON-	PRP
14-hansen-can	123	43	?	?	.
14-hansen-can	124	1	Or	or	CC
14-hansen-can	124	2	:	:	:
14-hansen-can	124	3	does	do	VBZ
14-hansen-can	124	4	the	the	DT
14-hansen-can	124	5	data	datum	NNS
14-hansen-can	124	6	we	-PRON-	PRP
14-hansen-can	124	7	have	have	VBP
14-hansen-can	124	8	to	to	TO
14-hansen-can	124	9	train	train	VB
14-hansen-can	124	10	a	a	DT
14-hansen-can	124	11	machine	machine	NN
14-hansen-can	124	12	contain	contain	NN
14-hansen-can	124	13	bias	bias	NN
14-hansen-can	124	14	and	and	CC
14-hansen-can	124	15	therefore	therefore	RB
14-hansen-can	124	16	will	will	MD
14-hansen-can	124	17	produce	produce	VB
14-hansen-can	124	18	a	a	DT
14-hansen-can	124	19	biased	biased	JJ
14-hansen-can	124	20	model	model	NN
14-hansen-can	124	21	which	which	WDT
14-hansen-can	124	22	will	will	MD
14-hansen-can	124	23	only	only	RB
14-hansen-can	124	24	serve	serve	VB
14-hansen-can	124	25	to	to	TO
14-hansen-can	124	26	perpetuate	perpetuate	VB
14-hansen-can	124	27	exist-	exist-	NNP
14-hansen-can	124	28	ing	ing	NNP
14-hansen-can	124	29	inequities	inequity	NNS
14-hansen-can	124	30	and	and	CC
14-hansen-can	124	31	systemic	systemic	JJ
14-hansen-can	124	32	oppression	oppression	NN
14-hansen-can	124	33	?	?	.
14-hansen-can	125	1	Not	not	RB
14-hansen-can	125	2	to	to	TO
14-hansen-can	125	3	mention	mention	VB
14-hansen-can	125	4	:	:	:
14-hansen-can	125	5	is	be	VBZ
14-hansen-can	125	6	this	this	DT
14-hansen-can	125	7	really	really	RB
14-hansen-can	125	8	a	a	DT
14-hansen-can	125	9	problem	problem	NN
14-hansen-can	125	10	or	or	CC
14-hansen-can	125	11	are	be	VBP
14-hansen-can	125	12	we	-PRON-	PRP
14-hansen-can	125	13	just	just	RB
14-hansen-can	125	14	looking	look	VBG
14-hansen-can	125	15	for	for	IN
14-hansen-can	125	16	a	a	DT
14-hansen-can	125	17	way	way	NN
14-hansen-can	125	18	to	to	TO
14-hansen-can	125	19	employ	employ	VB
14-hansen-can	125	20	machine	machine	NN
14-hansen-can	125	21	learning	learn	VBG
14-hansen-can	125	22	to	to	TO
14-hansen-can	125	23	say	say	VB
14-hansen-can	125	24	that	that	IN
14-hansen-can	125	25	we	-PRON-	PRP
14-hansen-can	125	26	did	do	VBD
14-hansen-can	125	27	?	?	.
14-hansen-can	126	1	In	in	IN
14-hansen-can	126	2	the	the	DT
14-hansen-can	126	3	cases	case	NNS
14-hansen-can	126	4	where	where	WRB
14-hansen-can	126	5	the	the	DT
14-hansen-can	126	6	answers	answer	NNS
14-hansen-can	126	7	to	to	IN
14-hansen-can	126	8	these	these	DT
14-hansen-can	126	9	questions	question	NNS
14-hansen-can	126	10	are	be	VBP
14-hansen-can	126	11	yes	yes	UH
14-hansen-can	126	12	,	,	,
14-hansen-can	126	13	it	-PRON-	PRP
14-hansen-can	126	14	will	will	MD
14-hansen-can	126	15	make	make	VB
14-hansen-can	126	16	sense	sense	NN
14-hansen-can	126	17	for	for	IN
14-hansen-can	126	18	libraries	library	NNS
14-hansen-can	126	19	to	to	TO
14-hansen-can	126	20	employ	employ	VB
14-hansen-can	126	21	machine	machine	NN
14-hansen-can	126	22	learning	learning	NN
14-hansen-can	126	23	.	.	.
14-hansen-can	127	1	I	-PRON-	PRP
14-hansen-can	127	2	just	just	RB
14-hansen-can	127	3	want	want	VBP
14-hansen-can	127	4	libraries	library	NNS
14-hansen-can	127	5	to	to	TO
14-hansen-can	127	6	look	look	VB
14-hansen-can	127	7	really	really	RB
14-hansen-can	127	8	carefully	carefully	RB
14-hansen-can	127	9	at	at	IN
14-hansen-can	127	10	how	how	WRB
14-hansen-can	127	11	they	-PRON-	PRP
14-hansen-can	127	12	approach	approach	VBP
14-hansen-can	127	13	problems	problem	NNS
14-hansen-can	127	14	and	and	CC
14-hansen-can	127	15	solutions	solution	NNS
14-hansen-can	127	16	,	,	,
14-hansen-can	127	17	to	to	TO
14-hansen-can	127	18	make	make	VB
14-hansen-can	127	19	sure	sure	JJ
14-hansen-can	127	20	that	that	IN
14-hansen-can	127	21	21When	21when	CD
14-hansen-can	127	22	an	an	DT
14-hansen-can	127	23	article	article	NN
14-hansen-can	127	24	is	be	VBZ
14-hansen-can	127	25	indexed	index	VBN
14-hansen-can	127	26	by	by	IN
14-hansen-can	127	27	MathSciNet	MathSciNet	NNP
14-hansen-can	127	28	it	-PRON-	PRP
14-hansen-can	127	29	receives	receive	VBZ
14-hansen-can	127	30	initial	initial	JJ
14-hansen-can	127	31	MSC	MSC	NNP
14-hansen-can	127	32	values	value	NNS
14-hansen-can	127	33	from	from	IN
14-hansen-can	127	34	a	a	DT
14-hansen-can	127	35	subject	subject	JJ
14-hansen-can	127	36	area	area	NN
14-hansen-can	127	37	editor	editor	NN
14-hansen-can	127	38	who	who	WP
14-hansen-can	127	39	then	then	RB
14-hansen-can	127	40	passes	pass	VBZ
14-hansen-can	127	41	the	the	DT
14-hansen-can	127	42	article	article	NN
14-hansen-can	127	43	along	along	IN
14-hansen-can	127	44	to	to	IN
14-hansen-can	127	45	an	an	DT
14-hansen-can	127	46	external	external	JJ
14-hansen-can	127	47	expert	expert	NN
14-hansen-can	127	48	reviewer	reviewer	NN
14-hansen-can	127	49	who	who	WP
14-hansen-can	127	50	suggests	suggest	VBZ
14-hansen-can	127	51	new	new	JJ
14-hansen-can	127	52	MSC	MSC	NNP
14-hansen-can	127	53	values	value	NNS
14-hansen-can	127	54	,	,	,
14-hansen-can	127	55	completes	complete	VBZ
14-hansen-can	127	56	partial	partial	JJ
14-hansen-can	127	57	values	value	NNS
14-hansen-can	127	58	,	,	,
14-hansen-can	127	59	and	and	CC
14-hansen-can	127	60	provides	provide	VBZ
14-hansen-can	127	61	potential	potential	JJ
14-hansen-can	127	62	corrections	correction	NNS
14-hansen-can	127	63	to	to	IN
14-hansen-can	127	64	the	the	DT
14-hansen-can	127	65	MSC	MSC	NNP
14-hansen-can	127	66	values	value	NNS
14-hansen-can	127	67	assigned	assign	VBN
14-hansen-can	127	68	by	by	IN
14-hansen-can	127	69	the	the	DT
14-hansen-can	127	70	editors	editor	NNS
14-hansen-can	127	71	(	(	-LRB-
14-hansen-can	127	72	㸫Mathematical	㸫Mathematical	NNP
14-hansen-can	127	73	Reviews	Reviews	NNP
14-hansen-can	127	74	Guide	Guide	NNP
14-hansen-can	127	75	For	for	IN
14-hansen-can	127	76	Reviewers㸬2020	Reviewers㸬2020	NNP
14-hansen-can	127	77	)	)	-RRB-
14-hansen-can	127	78	and	and	CC
14-hansen-can	127	79	then	then	RB
14-hansen-can	127	80	the	the	DT
14-hansen-can	127	81	subject	subject	JJ
14-hansen-can	127	82	area	area	NN
14-hansen-can	127	83	editors	editor	NNS
14-hansen-can	127	84	will	will	MD
14-hansen-can	127	85	make	make	VB
14-hansen-can	127	86	the	the	DT
14-hansen-can	127	87	final	final	JJ
14-hansen-can	127	88	determination	determination	NN
14-hansen-can	127	89	in	in	IN
14-hansen-can	127	90	order	order	NN
14-hansen-can	127	91	to	to	TO
14-hansen-can	127	92	make	make	VB
14-hansen-can	127	93	sure	sure	JJ
14-hansen-can	127	94	internal	internal	JJ
14-hansen-can	127	95	styles	style	NNS
14-hansen-can	127	96	are	be	VBP
14-hansen-can	127	97	followed	follow	VBN
14-hansen-can	127	98	.	.	.
14-hansen-can	128	1	zbMath	zbMath	NNP
14-hansen-can	128	2	follows	follow	VBZ
14-hansen-can	128	3	a	a	DT
14-hansen-can	128	4	similar	similar	JJ
14-hansen-can	128	5	procedure	procedure	NN
14-hansen-can	128	6	.	.	.
14-hansen-can	129	1	Hansen	Hansen	NNP
14-hansen-can	129	2	165	165	CD
14-hansen-can	129	3	their	-PRON-	PRP$
14-hansen-can	129	4	problem	problem	NN
14-hansen-can	129	5	is	be	VBZ
14-hansen-can	129	6	,	,	,
14-hansen-can	129	7	in	in	IN
14-hansen-can	129	8	fact	fact	NN
14-hansen-can	129	9	,	,	,
14-hansen-can	129	10	a	a	DT
14-hansen-can	129	11	nail	nail	NN
14-hansen-can	129	12	,	,	,
14-hansen-can	129	13	and	and	CC
14-hansen-can	129	14	then	then	RB
14-hansen-can	129	15	to	to	TO
14-hansen-can	129	16	look	look	VB
14-hansen-can	129	17	even	even	RB
14-hansen-can	129	18	closer	close	RBR
14-hansen-can	129	19	and	and	CC
14-hansen-can	129	20	make	make	VB
14-hansen-can	129	21	sure	sure	JJ
14-hansen-can	129	22	it	-PRON-	PRP
14-hansen-can	129	23	is	be	VBZ
14-hansen-can	129	24	the	the	DT
14-hansen-can	129	25	type	type	NN
14-hansen-can	129	26	of	of	IN
14-hansen-can	129	27	nail	nail	NN
14-hansen-can	129	28	a	a	DT
14-hansen-can	129	29	machine	machine	NN
14-hansen-can	129	30	-	-	HYPH
14-hansen-can	129	31	learning	learn	VBG
14-hansen-can	129	32	hammer	hammer	NN
14-hansen-can	129	33	can	can	MD
14-hansen-can	129	34	hit	hit	VB
14-hansen-can	129	35	.	.	.
14-hansen-can	130	1	References	References	NNPS
14-hansen-can	130	2	Barthel	Barthel	NNP
14-hansen-can	130	3	,	,	,
14-hansen-can	130	4	Simon	Simon	NNP
14-hansen-can	130	5	,	,	,
14-hansen-can	130	6	Sascha	Sascha	NNP
14-hansen-can	130	7	Tönnies	Tönnies	NNP
14-hansen-can	130	8	,	,	,
14-hansen-can	130	9	and	and	CC
14-hansen-can	130	10	Wolf	Wolf	NNP
14-hansen-can	130	11	-	-	HYPH
14-hansen-can	130	12	Tilo	Tilo	NNP
14-hansen-can	130	13	Balke	Balke	NNP
14-hansen-can	130	14	.	.	.
14-hansen-can	131	1	2013	2013	CD
14-hansen-can	131	2	.	.	.
14-hansen-can	132	1	“	"	``
14-hansen-can	132	2	Large	large	JJ
14-hansen-can	132	3	-	-	HYPH
14-hansen-can	132	4	Scale	scale	NN
14-hansen-can	132	5	Experiments	experiment	NNS
14-hansen-can	132	6	for	for	IN
14-hansen-can	132	7	Math-	Math-	NNP
14-hansen-can	132	8	ematical	ematical	JJ
14-hansen-can	132	9	Document	Document	NNP
14-hansen-can	132	10	Classification	Classification	NNP
14-hansen-can	132	11	.	.	.
14-hansen-can	132	12	”	"	''
14-hansen-can	132	13	In	in	IN
14-hansen-can	132	14	Digital	Digital	NNP
14-hansen-can	132	15	Libraries	Libraries	NNPS
14-hansen-can	132	16	:	:	:
14-hansen-can	132	17	Social	Social	NNP
14-hansen-can	132	18	Media	Media	NNPS
14-hansen-can	132	19	and	and	CC
14-hansen-can	132	20	Community	Community	NNP
14-hansen-can	132	21	Networks	Networks	NNP
14-hansen-can	132	22	,	,	,
14-hansen-can	132	23	edited	edit	VBN
14-hansen-can	132	24	by	by	IN
14-hansen-can	132	25	Shalini	Shalini	NNP
14-hansen-can	132	26	R.	R.	NNP
14-hansen-can	132	27	Urs	Urs	NNP
14-hansen-can	132	28	,	,	,
14-hansen-can	132	29	Jin	Jin	NNP
14-hansen-can	132	30	-	-	HYPH
14-hansen-can	132	31	Cheon	Cheon	NNP
14-hansen-can	132	32	Na	Na	NNP
14-hansen-can	132	33	,	,	,
14-hansen-can	132	34	and	and	CC
14-hansen-can	132	35	George	George	NNP
14-hansen-can	132	36	Buchanan	Buchanan	NNP
14-hansen-can	132	37	,	,	,
14-hansen-can	132	38	83–92	83–92	NN
14-hansen-can	132	39	.	.	.
14-hansen-can	133	1	Cham	Cham	NNP
14-hansen-can	133	2	:	:	:
14-hansen-can	133	3	Springer	Springer	NNP
14-hansen-can	133	4	International	International	NNP
14-hansen-can	133	5	Publishing	Publishing	NNP
14-hansen-can	133	6	.	.	.
14-hansen-can	134	1	Clark	Clark	NNP
14-hansen-can	134	2	,	,	,
14-hansen-can	134	3	Jack	Jack	NNP
14-hansen-can	134	4	.	.	.
14-hansen-can	135	1	2015	2015	CD
14-hansen-can	135	2	.	.	.
14-hansen-can	136	1	“	"	``
14-hansen-can	136	2	Why	why	WRB
14-hansen-can	136	3	2015	2015	CD
14-hansen-can	136	4	Was	be	VBD
14-hansen-can	136	5	a	a	DT
14-hansen-can	136	6	Breakthrough	Breakthrough	NNP
14-hansen-can	136	7	Year	Year	NNP
14-hansen-can	136	8	in	in	IN
14-hansen-can	136	9	Artificial	Artificial	NNP
14-hansen-can	136	10	Intelligence	Intelligence	NNP
14-hansen-can	136	11	.	.	.
14-hansen-can	136	12	”	"	''
14-hansen-can	136	13	Bloomberg	Bloomberg	NNP
14-hansen-can	136	14	,	,	,
14-hansen-can	136	15	December	December	NNP
14-hansen-can	136	16	8	8	CD
14-hansen-can	136	17	,	,	,
14-hansen-can	136	18	2015	2015	CD
14-hansen-can	136	19	.	.	.
14-hansen-can	137	1	?	?	.
14-hansen-can	137	2	iiTb	iitb	UH
14-hansen-can	137	3	,	,	,
14-hansen-can	137	4	ffrrrX#HQQK#2`;X+QKfM2rbf	ffrrrx#hqqk#2`;x+qkfm2rbf	ADD
14-hansen-can	137	5	�	�	NNP
14-hansen-can	137	6	`iB+H2bfkyR8@Rk@y3	`ib+h2bfkyr8@rk@y3	JJ
14-hansen-can	137	7	fr?v@kyR8@r	fr?v@kyr8@r	PRP
14-hansen-can	137	8	�	�	JJ
14-hansen-can	137	9	b@	b@	NNPS
14-hansen-can	137	10	�	�	NNP
14-hansen-can	137	11	@#`2	@#`2	.
14-hansen-can	137	12	�	�	NNP
14-hansen-can	137	13	Fi?`Qm;?@v2	Fi?`Qm;?@v2	NNP
14-hansen-can	137	14	�	�	NNS
14-hansen-can	137	15	`@BM@	`@bm@	IN
14-hansen-can	137	16	�	�	NNP
14-hansen-can	137	17	`iB7B+B	`iB7B+B	NNP
14-hansen-can	137	18	�	�	JJ
14-hansen-can	137	19	H@BMi2HHB;2M+2	h@bmi2hhb;2m+2	NN
14-hansen-can	137	20	.	.	.
14-hansen-can	138	1	Gandhi	Gandhi	NNP
14-hansen-can	138	2	,	,	,
14-hansen-can	138	3	Rohith	Rohith	NNP
14-hansen-can	138	4	.	.	.
14-hansen-can	139	1	2018	2018	CD
14-hansen-can	139	2	.	.	.
14-hansen-can	140	1	“	"	``
14-hansen-can	140	2	Support	Support	NNP
14-hansen-can	140	3	Vector	Vector	NNP
14-hansen-can	140	4	Machine	Machine	NNP
14-hansen-can	140	5	—	—	:
14-hansen-can	140	6	Introduction	introduction	NN
14-hansen-can	140	7	to	to	IN
14-hansen-can	140	8	Machine	Machine	NNP
14-hansen-can	140	9	Learning	Learning	NNP
14-hansen-can	140	10	Algo-	Algo-	NNP
14-hansen-can	140	11	rithms	rithms	NNP
14-hansen-can	140	12	.	.	.
14-hansen-can	140	13	”	"	''
14-hansen-can	140	14	Medium	medium	NN
14-hansen-can	140	15	.	.	.
14-hansen-can	141	1	July	July	NNP
14-hansen-can	141	2	5	5	CD
14-hansen-can	141	3	,	,	,
14-hansen-can	141	4	2018	2018	CD
14-hansen-can	141	5	.	.	.
14-hansen-can	142	1	?	?	.
14-hansen-can	142	2	iiTb	iitb	UH
14-hansen-can	142	3	,	,	,
14-hansen-can	142	4	ffiQr	ffiqr	ADD
14-hansen-can	142	5	�	�	ADD
14-hansen-can	142	6	`/b/	`/b/	NNP
14-hansen-can	142	7	�	�	NNP
14-hansen-can	142	8	i	i	PRP
14-hansen-can	142	9	�	�	:
14-hansen-can	142	10	b+B2M+2X+QKfbmTTQ`i@p2	b+b2m+2x+qkfbmttq`i@p2	NN
14-hansen-can	142	11	+	+	SYM
14-hansen-can	142	12	iQ`@K	iq`@k	NN
14-hansen-can	142	13	�	�	NNP
14-hansen-can	142	14	+?BM2@BMi`Q	+?BM2@BMi`Q	NNP
14-hansen-can	142	15	/	/	SYM
14-hansen-can	142	16	m+iBQM@iQ@K	m+iBQM@iQ@K	NNP
14-hansen-can	142	17	�	�	,
14-hansen-can	142	18	+?BM2@H2	+?BM2@H2	NNP
14-hansen-can	142	19	�	�	NNP
14-hansen-can	142	20	`MBM;@	`mbm;@	NN
14-hansen-can	142	21	�	�	.
14-hansen-can	142	22	H;Q`Bi?Kb@Nj9	h;q`bi?kb@nj9	NN
14-hansen-can	142	23	�	�	NNP
14-hansen-can	142	24	9997	9997	CD
14-hansen-can	142	25	+	+	SYM
14-hansen-can	142	26	�	�	NNP
14-hansen-can	142	27	9d	9d	NNP
14-hansen-can	142	28	.	.	.
14-hansen-can	143	1	“	"	``
14-hansen-can	143	2	GeoDeepDive	geodeepdive	NN
14-hansen-can	143	3	:	:	:
14-hansen-can	143	4	Project	Project	NNP
14-hansen-can	143	5	Overview	Overview	NNP
14-hansen-can	143	6	.	.	.
14-hansen-can	143	7	’	'	''
14-hansen-can	143	8	n.d	n.d	NNP
14-hansen-can	143	9	.	.	NNP
14-hansen-can	143	10	Accessed	Accessed	NNP
14-hansen-can	143	11	May	May	NNP
14-hansen-can	143	12	7	7	CD
14-hansen-can	143	13	,	,	,
14-hansen-can	143	14	2018	2018	CD
14-hansen-can	143	15	.	.	.
14-hansen-can	144	1	?	?	.
14-hansen-can	144	2	iiTb	iitb	UH
14-hansen-can	144	3	,	,	,
14-hansen-can	144	4	ff;2Q/22T	ff;2q/22t	JJ
14-hansen-can	144	5	/	/	SYM
14-hansen-can	144	6	Bp2XQ	bp2xq	IN
14-hansen-can	144	7	`	`	''
14-hansen-can	144	8	;	;	:
14-hansen-can	144	9	f	f	NNP
14-hansen-can	144	10	�	�	NNP
14-hansen-can	144	11	#QmiX?iKH	#QmiX?iKH	NNP
14-hansen-can	144	12	.	.	.
14-hansen-can	145	1	Kelly	Kelly	NNP
14-hansen-can	145	2	,	,	,
14-hansen-can	145	3	Kevin	Kevin	NNP
14-hansen-can	145	4	.	.	.
14-hansen-can	146	1	2014	2014	CD
14-hansen-can	146	2	.	.	.
14-hansen-can	147	1	“	"	``
14-hansen-can	147	2	The	the	DT
14-hansen-can	147	3	Three	three	CD
14-hansen-can	147	4	Breakthroughs	Breakthroughs	NNPS
14-hansen-can	147	5	That	that	WDT
14-hansen-can	147	6	Have	have	VBP
14-hansen-can	147	7	Finally	finally	RB
14-hansen-can	147	8	Unleashed	unleash	VBN
14-hansen-can	147	9	AI	AI	NNP
14-hansen-can	147	10	on	on	IN
14-hansen-can	147	11	the	the	DT
14-hansen-can	147	12	World	World	NNP
14-hansen-can	147	13	.	.	.
14-hansen-can	147	14	”	"	''
14-hansen-can	147	15	Wired	wire	VBN
14-hansen-can	147	16	,	,	,
14-hansen-can	147	17	October	October	NNP
14-hansen-can	147	18	27	27	CD
14-hansen-can	147	19	,	,	,
14-hansen-can	147	20	2014	2014	CD
14-hansen-can	147	21	.	.	.
14-hansen-can	148	1	?	?	.
14-hansen-can	148	2	iiTb	iitb	UH
14-hansen-can	148	3	,	,	,
14-hansen-can	148	4	ffrrrXrB`2	ffrrrXrB`2	NNP
14-hansen-can	148	5	/	/	SYM
14-hansen-can	148	6	X+QKfkyR9fRyf7mim`2@Q7@	X+QKfkyR9fRyf7mim`2@Q7@	NNP
14-hansen-can	148	7	�	�	NNP
14-hansen-can	148	8	`iB7B	`ib7b	CD
14-hansen-can	148	9	+	+	CC
14-hansen-can	148	10	B	B	NNP
14-hansen-can	148	11	�	�	NNP
14-hansen-can	148	12	H@BMi2HHB;2M+2f	H@BMi2HHB;2M+2f	NNP
14-hansen-can	148	13	.	.	.
14-hansen-can	149	1	“	"	``
14-hansen-can	149	2	Mathematical	Mathematical	NNP
14-hansen-can	149	3	Reviews	Reviews	NNPS
14-hansen-can	149	4	Guide	Guide	NNP
14-hansen-can	149	5	For	for	IN
14-hansen-can	149	6	Reviewers	Reviewers	NNPS
14-hansen-can	149	7	.	.	.
14-hansen-can	149	8	”	"	''
14-hansen-can	149	9	2015	2015	CD
14-hansen-can	149	10	.	.	.
14-hansen-can	150	1	AmericanMathematicalSociety	AmericanMathematicalSociety	:
14-hansen-can	150	2	.	.	.
14-hansen-can	151	1	February	February	NNP
14-hansen-can	151	2	2015	2015	CD
14-hansen-can	151	3	.	.	.
14-hansen-can	152	1	?	?	.
14-hansen-can	152	2	iiTb	iitb	UH
14-hansen-can	152	3	,	,	,
14-hansen-can	152	4	ffK	ffK	NNP
14-hansen-can	152	5	�	�	NNP
14-hansen-can	152	6	i?b+BM2iX	i?b+BM2iX	VBZ
14-hansen-can	152	7	�	�	NNP
14-hansen-can	152	8	KbXQ`;fK`2bm#bf;mB/2@`2pB2r2`bX?iKH	KbXQ`;fK`2bm#bf;mB/2@`2pB2r2`bX?iKH	NNP
14-hansen-can	152	9	.	.	.
14-hansen-can	153	1	“	"	``
14-hansen-can	153	2	Microsoft	Microsoft	NNP
14-hansen-can	153	3	Academic	Academic	NNP
14-hansen-can	153	4	Increases	Increases	NNPS
14-hansen-can	153	5	Power	Power	NNP
14-hansen-can	153	6	of	of	IN
14-hansen-can	153	7	Semantic	Semantic	NNP
14-hansen-can	153	8	Search	Search	NNP
14-hansen-can	153	9	by	by	IN
14-hansen-can	153	10	Adding	add	VBG
14-hansen-can	153	11	More	More	JJR
14-hansen-can	153	12	Fields	field	NNS
14-hansen-can	153	13	of	of	IN
14-hansen-can	153	14	Study	Study	NNP
14-hansen-can	153	15	.	.	.
14-hansen-can	153	16	”	"	''
14-hansen-can	153	17	2018	2018	CD
14-hansen-can	153	18	.	.	.
14-hansen-can	154	1	Microsoft	Microsoft	NNP
14-hansen-can	154	2	Academic	Academic	NNP
14-hansen-can	154	3	(	(	-LRB-
14-hansen-can	154	4	blog	blog	NN
14-hansen-can	154	5	)	)	-RRB-
14-hansen-can	154	6	.	.	.
14-hansen-can	155	1	February	February	NNP
14-hansen-can	155	2	15	15	CD
14-hansen-can	155	3	,	,	,
14-hansen-can	155	4	2018	2018	CD
14-hansen-can	155	5	.	.	.
14-hansen-can	156	1	?	?	.
14-hansen-can	156	2	iiTb	iitb	UH
14-hansen-can	156	3	,	,	,
14-hansen-can	156	4	ffrrrXKB+`QbQ7iX+Q	ffrrrXKB+`QbQ7iX+Q	NNP
14-hansen-can	156	5	Kf2M@mbf`2b2	Kf2M@mbf`2b2	NNP
14-hansen-can	156	6	�	�	NNP
14-hansen-can	156	7	`+?fT`QD2+if	`+?ft`qd2+if	CD
14-hansen-can	156	8	�	�	NNP
14-hansen-can	156	9	+	+	SYM
14-hansen-can	156	10	�	�	ADD
14-hansen-can	156	11	/2KB+f	/2KB+f	NFP
14-hansen-can	156	12	�	�	NNP
14-hansen-can	156	13	`iB+H2bfKB+`QbQ7i@	`ib+h2bfkb+`qbq7i@	NN
14-hansen-can	156	14	�	�	NNP
14-hansen-can	156	15	+	+	SYM
14-hansen-can	156	16	�	�	NNP
14-hansen-can	156	17	/2KB+@BM	/2KB+@BM	NFP
14-hansen-can	156	18	+	+	SYM
14-hansen-can	156	19	`	`	''
14-hansen-can	156	20	2	2	CD
14-hansen-can	156	21	�	�	NN
14-hansen-can	156	22	b2b@TQr2`@b2K	b2b@TQr2`@b2K	''
14-hansen-can	156	23	�	�	NNP
14-hansen-can	156	24	MiB+@b2	MiB+@b2	NNS
14-hansen-can	156	25	�	�	NN
14-hansen-can	156	26	`+?@	`+?@	CD
14-hansen-can	156	27	�	�	NNP
14-hansen-can	156	28	//BM;@7B2H	//BM;@7B2H	.
14-hansen-can	156	29	/	/	SYM
14-hansen-can	156	30	b@bim	b@bim	NNP
14-hansen-can	156	31	/	/	SYM
14-hansen-can	156	32	vf	vf	NN
14-hansen-can	156	33	.	.	.
14-hansen-can	157	1	Mikolov	Mikolov	NNP
14-hansen-can	157	2	,	,	,
14-hansen-can	157	3	Tomas	Tomas	NNP
14-hansen-can	157	4	,	,	,
14-hansen-can	157	5	Ilya	Ilya	NNP
14-hansen-can	157	6	Sutskever	Sutskever	NNP
14-hansen-can	157	7	,	,	,
14-hansen-can	157	8	Kai	Kai	NNP
14-hansen-can	157	9	Chen	Chen	NNP
14-hansen-can	157	10	,	,	,
14-hansen-can	157	11	Greg	Greg	NNP
14-hansen-can	157	12	S	S	NNP
14-hansen-can	157	13	Corrado	Corrado	NNP
14-hansen-can	157	14	,	,	,
14-hansen-can	157	15	and	and	CC
14-hansen-can	157	16	Jeff	Jeff	NNP
14-hansen-can	157	17	Dean	Dean	NNP
14-hansen-can	157	18	.	.	.
14-hansen-can	158	1	2013	2013	CD
14-hansen-can	158	2	.	.	.
14-hansen-can	159	1	“	"	``
14-hansen-can	159	2	Distributed	distribute	VBN
14-hansen-can	159	3	Representations	Representations	NNPS
14-hansen-can	159	4	of	of	IN
14-hansen-can	159	5	Words	Words	NNPS
14-hansen-can	159	6	and	and	CC
14-hansen-can	159	7	Phrases	Phrases	NNPS
14-hansen-can	159	8	and	and	CC
14-hansen-can	159	9	Their	-PRON-	PRP$
14-hansen-can	159	10	Compositionality	compositionality	NN
14-hansen-can	159	11	.	.	.
14-hansen-can	159	12	”	"	''
14-hansen-can	159	13	In	in	IN
14-hansen-can	159	14	Advances	advance	NNS
14-hansen-can	159	15	in	in	IN
14-hansen-can	159	16	Neu-	Neu-	NNP
14-hansen-can	159	17	ral	ral	NNP
14-hansen-can	159	18	Information	Information	NNP
14-hansen-can	159	19	Processing	Processing	NNP
14-hansen-can	159	20	Systems	Systems	NNP
14-hansen-can	159	21	26	26	CD
14-hansen-can	159	22	,	,	,
14-hansen-can	159	23	edited	edit	VBN
14-hansen-can	159	24	by	by	IN
14-hansen-can	159	25	C.	C.	NNP
14-hansen-can	159	26	J.	J.	NNP
14-hansen-can	159	27	C.	C.	NNP
14-hansen-can	159	28	Burges	Burges	NNP
14-hansen-can	159	29	,	,	,
14-hansen-can	159	30	L.	L.	NNP
14-hansen-can	159	31	Bottou	Bottou	NNP
14-hansen-can	159	32	,	,	,
14-hansen-can	159	33	M.	M.	NNP
14-hansen-can	159	34	Welling	Welling	NNP
14-hansen-can	159	35	,	,	,
14-hansen-can	159	36	Z.	Z.	NNP
14-hansen-can	159	37	Ghahramani	Ghahramani	NNP
14-hansen-can	159	38	,	,	,
14-hansen-can	159	39	and	and	CC
14-hansen-can	159	40	K.	K.	NNP
14-hansen-can	159	41	Q.	Q.	NNP
14-hansen-can	159	42	Weinberger	Weinberger	NNP
14-hansen-can	159	43	,	,	,
14-hansen-can	159	44	3111–3119	3111–3119	CD
14-hansen-can	159	45	.	.	.
14-hansen-can	160	1	Curran	Curran	NNP
14-hansen-can	160	2	Associates	Associates	NNPS
14-hansen-can	160	3	,	,	,
14-hansen-can	160	4	Inc.	Inc.	NNP
14-hansen-can	160	5	?	?	.
14-hansen-can	160	6	iiT	iiT	NNP
14-hansen-can	160	7	,	,	,
14-hansen-can	160	8	ffT	ffT	NNP
14-hansen-can	160	9	�	�	NNP
14-hansen-can	160	10	T2	t2	NN
14-hansen-can	160	11	`	`	''
14-hansen-can	160	12	bXMBTbX++fT	bXMBTbX++fT	NNS
14-hansen-can	160	13	�	�	NNP
14-hansen-can	160	14	T2`f8ykR@/Bbi`B#mi2/@`2T`2b2Mi	T2`f8ykR@/Bbi`B#mi2/@`2T`2b2Mi	NNS
14-hansen-can	160	15	�	�	NNP
14-hansen-can	160	16	iBQMb@Q7@rQ`/b@	ibqmb@q7@rq`/b@	ADD
14-hansen-can	160	17	�	�	NN
14-hansen-can	160	18	M/@T	m/@t	JJ
14-hansen-can	160	19	?	?	.
14-hansen-can	160	20	`	`	''
14-hansen-can	160	21	�	�	:
14-hansen-can	160	22	b2b@	b2b@	NN
14-hansen-can	160	23	�	�	NNS
14-hansen-can	160	24	M/@i?2B`@+QKTQbBiBQM	m/@i?2b`@+qktqbbibqm	CD
14-hansen-can	160	25	�	�	NNP
14-hansen-can	160	26	HBivXT/7	hbivxt/7	UH
14-hansen-can	160	27	.	.	.
14-hansen-can	161	1	Parloff	Parloff	NNP
14-hansen-can	161	2	,	,	,
14-hansen-can	161	3	Roger	Roger	NNP
14-hansen-can	161	4	.	.	.
14-hansen-can	162	1	2016	2016	CD
14-hansen-can	162	2	.	.	.
14-hansen-can	163	1	“	"	``
14-hansen-can	163	2	From	from	IN
14-hansen-can	163	3	2016	2016	CD
14-hansen-can	163	4	:	:	:
14-hansen-can	163	5	Why	why	WRB
14-hansen-can	163	6	Deep	deep	JJ
14-hansen-can	163	7	Learning	learning	NN
14-hansen-can	163	8	Is	be	VBZ
14-hansen-can	163	9	Suddenly	suddenly	RB
14-hansen-can	163	10	Changing	change	VBG
14-hansen-can	163	11	Your	-PRON-	PRP$
14-hansen-can	163	12	Life	life	NN
14-hansen-can	163	13	.	.	.
14-hansen-can	163	14	”	"	''
14-hansen-can	163	15	For-	For-	NNP
14-hansen-can	163	16	tune	tune	NN
14-hansen-can	163	17	.	.	.
14-hansen-can	164	1	September	September	NNP
14-hansen-can	164	2	28	28	CD
14-hansen-can	164	3	,	,	,
14-hansen-can	164	4	2016	2016	CD
14-hansen-can	164	5	.	.	.
14-hansen-can	165	1	?	?	.
14-hansen-can	165	2	iiTb	iitb	UH
14-hansen-can	165	3	,	,	,
14-hansen-can	165	4	ff7Q`imM2X+QKfHQM;7Q`Kf	ff7q`imm2x+qkfhqm;7q`kf	ADD
14-hansen-can	165	5	�	�	NNP
14-hansen-can	165	6	B@	B@	NNP
14-hansen-can	165	7	�	�	.
14-hansen-can	165	8	`iB7B+B	`iB7B+B	NNP
14-hansen-can	165	9	�	�	JJ
14-hansen-can	165	10	H@B	H@B	NNP
14-hansen-can	165	11	Mi2HHB;2M+2@/22T@K	Mi2HHB;2M+2@/22T@K	NNS
14-hansen-can	165	12	�	�	NNP
14-hansen-can	165	13	+?BM2@H2	+?bm2@h2	DT
14-hansen-can	165	14	�	�	NNS
14-hansen-can	165	15	`MBM;f	`mbm;f	ADD
14-hansen-can	165	16	.	.	.
14-hansen-can	165	17	Rahimi	Rahimi	NNP
14-hansen-can	165	18	,	,	,
14-hansen-can	165	19	Ali	Ali	NNP
14-hansen-can	165	20	,	,	,
14-hansen-can	165	21	and	and	CC
14-hansen-can	165	22	Benjamin	Benjamin	NNP
14-hansen-can	165	23	Recht	Recht	NNP
14-hansen-can	165	24	.	.	.
14-hansen-can	166	1	2017	2017	CD
14-hansen-can	166	2	.	.	.
14-hansen-can	167	1	“	"	``
14-hansen-can	167	2	Back	back	RB
14-hansen-can	167	3	When	when	WRB
14-hansen-can	167	4	We	-PRON-	PRP
14-hansen-can	167	5	Were	be	VBD
14-hansen-can	167	6	Kids	kid	NNS
14-hansen-can	167	7	.	.	.
14-hansen-can	167	8	”	"	''
14-hansen-can	167	9	Presentation	presentation	NN
14-hansen-can	167	10	at	at	IN
14-hansen-can	167	11	the	the	DT
14-hansen-can	167	12	NIPS	NIPS	NNP
14-hansen-can	167	13	2017	2017	CD
14-hansen-can	167	14	Conference	Conference	NNP
14-hansen-can	167	15	.	.	.
14-hansen-can	168	1	?	?	.
14-hansen-can	168	2	iiTb	iitb	UH
14-hansen-can	168	3	,	,	,
14-hansen-can	168	4	ffrrrXvQmim#2X+QKfr	ffrrrxvqmim#2x+qkfr	ADD
14-hansen-can	168	5	�	�	NNP
14-hansen-can	168	6	i+??p4ZBRu`vjjhZ1	i+??p4zbru`vjjhz1	ADD
14-hansen-can	168	7	.	.	.
14-hansen-can	169	1	Řehůřek	Řehůřek	NNP
14-hansen-can	169	2	,	,	,
14-hansen-can	169	3	Radim	Radim	NNP
14-hansen-can	169	4	,	,	,
14-hansen-can	169	5	and	and	CC
14-hansen-can	169	6	Petr	Petr	NNP
14-hansen-can	169	7	Sojka	sojka	RB
14-hansen-can	169	8	.	.	.
14-hansen-can	170	1	2008	2008	CD
14-hansen-can	170	2	.	.	.
14-hansen-can	171	1	“	"	``
14-hansen-can	171	2	Automated	Automated	NNP
14-hansen-can	171	3	Classification	Classification	NNP
14-hansen-can	171	4	and	and	CC
14-hansen-can	171	5	Categorization	Categorization	NNP
14-hansen-can	171	6	of	of	IN
14-hansen-can	171	7	Math-	Math-	NNP
14-hansen-can	171	8	ematical	ematical	JJ
14-hansen-can	171	9	Knowledge	knowledge	NN
14-hansen-can	171	10	.	.	.
14-hansen-can	171	11	”	"	''
14-hansen-can	171	12	In	in	IN
14-hansen-can	171	13	Intelligent	Intelligent	NNP
14-hansen-can	171	14	Computer	Computer	NNP
14-hansen-can	171	15	Mathematics	Mathematics	NNP
14-hansen-can	171	16	,	,	,
14-hansen-can	171	17	edited	edit	VBN
14-hansen-can	171	18	by	by	IN
14-hansen-can	171	19	Serge	Serge	NNP
14-hansen-can	171	20	Autexier	Autexier	NNP
14-hansen-can	171	21	,	,	,
14-hansen-can	171	22	John	John	NNP
14-hansen-can	171	23	Campbell	Campbell	NNP
14-hansen-can	171	24	,	,	,
14-hansen-can	171	25	Julio	Julio	NNP
14-hansen-can	171	26	Rubio	Rubio	NNP
14-hansen-can	171	27	,	,	,
14-hansen-can	171	28	Volker	Volker	NNP
14-hansen-can	171	29	Sorge	Sorge	NNP
14-hansen-can	171	30	,	,	,
14-hansen-can	171	31	Masakazu	Masakazu	NNP
14-hansen-can	171	32	Suzuki	Suzuki	NNP
14-hansen-can	171	33	,	,	,
14-hansen-can	171	34	and	and	CC
14-hansen-can	171	35	Freek	Freek	NNP
14-hansen-can	171	36	Wiedijk	Wiedijk	NNP
14-hansen-can	171	37	,	,	,
14-hansen-can	171	38	543–57	543–57	CD
14-hansen-can	171	39	.	.	.
14-hansen-can	172	1	Berlin	Berlin	NNP
14-hansen-can	172	2	:	:	:
14-hansen-can	172	3	Springer	Springer	NNP
14-hansen-can	172	4	Verlag	Verlag	NNP
14-hansen-can	172	5	.	.	.
14-hansen-can	173	1	Sangwani	Sangwani	NNP
14-hansen-can	173	2	,	,	,
14-hansen-can	173	3	Gaurav	Gaurav	NNP
14-hansen-can	173	4	.	.	.
14-hansen-can	174	1	2017	2017	CD
14-hansen-can	174	2	.	.	.
14-hansen-can	175	1	“	"	``
14-hansen-can	175	2	2017	2017	CD
14-hansen-can	175	3	Is	be	VBZ
14-hansen-can	175	4	the	the	DT
14-hansen-can	175	5	Year	Year	NNP
14-hansen-can	175	6	of	of	IN
14-hansen-can	175	7	Machine	Machine	NNP
14-hansen-can	175	8	Learning	Learning	NNP
14-hansen-can	175	9	.	.	.
14-hansen-can	176	1	Here	here	RB
14-hansen-can	176	2	’s	’	VBZ
14-hansen-can	176	3	Why	why	WRB
14-hansen-can	176	4	.	.	.
14-hansen-can	176	5	”	"	''
14-hansen-can	176	6	Business	Business	NNP
14-hansen-can	176	7	Insider	Insider	NNP
14-hansen-can	176	8	,	,	,
14-hansen-can	176	9	January	January	NNP
14-hansen-can	176	10	13	13	CD
14-hansen-can	176	11	,	,	,
14-hansen-can	176	12	2017	2017	CD
14-hansen-can	176	13	.	.	.
14-hansen-can	177	1	?	?	.
14-hansen-can	177	2	iiTb	iitb	UH
14-hansen-can	177	3	,	,	,
14-hansen-can	177	4	ffrrrX#mbBM2bbBMbB/2`XBMfkyRd@Bb@i?2@v2	ffrrrX#mbBM2bbBMbB/2`XBMfkyRd@Bb@i?2@v2	NNP
14-hansen-can	177	5	�	�	NNP
14-hansen-can	177	6	`@Q7@K	`@q7@k	NN
14-hansen-can	177	7	�	�	NN
14-hansen-can	177	8	+	+	JJ
14-hansen-can	177	9	?	?	.
14-hansen-can	177	10	BM2@H2	bm2@h2	RB
14-hansen-can	177	11	�	�	ADD
14-hansen-can	177	12	`MBM;@?2`2b@r?vf	`mbm;@?2`2b@r?vf	ADD
14-hansen-can	177	13	�	�	NNP
14-hansen-can	177	14	`iB+H2b?Qrf8e8R98j8X+Kb	`iB+H2b?Qrf8e8R98j8X+Kb	NNP
14-hansen-can	177	15	.	.	.
14-hansen-can	178	1	https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence	https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence	NNP
14-hansen-can	178	2	https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence	https://www.bloomberg.com/news/articles/2015-12-08/why-2015-was-a-breakthrough-year-in-artificial-intelligence	NNP
14-hansen-can	178	3	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	NNP
14-hansen-can	178	4	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	NNP
14-hansen-can	178	5	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47	NNP
14-hansen-can	178	6	https://geodeepdive.org/about.html	https://geodeepdive.org/about.html	ADD
14-hansen-can	178	7	https://geodeepdive.org/about.html	https://geodeepdive.org/about.html	NNP
14-hansen-can	178	8	https://www.wired.com/2014/10/future-of-artificial-intelligence/	https://www.wired.com/2014/10/future-of-artificial-intelligence/	NNP
14-hansen-can	178	9	https://www.wired.com/2014/10/future-of-artificial-intelligence/	https://www.wired.com/2014/10/future-of-artificial-intelligence/	NNP
14-hansen-can	178	10	https://mathscinet.ams.org/mresubs/guide-reviewers.html	https://mathscinet.ams.org/mresubs/guide-reviewers.html	NNP
14-hansen-can	178	11	https://www.microsoft.com/en-us/research/project/academic/articles/microsoft-academic-increases-power-semantic-search-adding-fields-study/	https://www.microsoft.com/en-us/research/project/academic/articles/microsoft-academic-increases-power-semantic-search-adding-fields-study/	NNP
14-hansen-can	178	12	https://www.microsoft.com/en-us/research/project/academic/articles/microsoft-academic-increases-power-semantic-search-adding-fields-study/	https://www.microsoft.com/en-us/research/project/academic/articles/microsoft-academic-increases-power-semantic-search-adding-fields-study/	FW
14-hansen-can	178	13	https://www.microsoft.com/en-us/research/project/academic/articles/microsoft-academic-increases-power-semantic-search-adding-fields-study/	https://www.microsoft.com/en-us/research/project/academic/articles/microsoft-academic-increases-power-semantic-search-adding-fields-study/	NNP
14-hansen-can	178	14	http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf	http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf	NNP
14-hansen-can	178	15	http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf	http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf	NNP
14-hansen-can	178	16	http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf	http://papers.nips.cc/paper/5021-distributed-representations-of-words-and-phrases-and-their-compositionality.pdf	NNP
14-hansen-can	178	17	https://fortune.com/longform/ai-artificial-intelligence-deep-machine-learning/	https://fortune.com/longform/ai-artificial-intelligence-deep-machine-learning/	NN
14-hansen-can	178	18	https://fortune.com/longform/ai-artificial-intelligence-deep-machine-learning/	https://fortune.com/longform/ai-artificial-intelligence-deep-machine-learning/	NN
14-hansen-can	178	19	https://www.youtube.com/watch?v=Qi1Yry33TQE	https://www.youtube.com/watch?v=Qi1Yry33TQE	NNP
14-hansen-can	178	20	https://www.businessinsider.in/2017-is-the-year-of-machine-learning-heres-why/articleshow/56514535.cms	https://www.businessinsider.in/2017-is-the-year-of-machine-learning-heres-why/articleshow/56514535.cms	NNP
14-hansen-can	178	21	https://www.businessinsider.in/2017-is-the-year-of-machine-learning-heres-why/articleshow/56514535.cms	https://www.businessinsider.in/2017-is-the-year-of-machine-learning-heres-why/articleshow/56514535.cms	NNP
14-hansen-can	178	22	166	166	CD
14-hansen-can	178	23	Machine	Machine	NNP
14-hansen-can	178	24	Learning	Learning	NNP
14-hansen-can	178	25	,	,	,
14-hansen-can	178	26	Libraries	Libraries	NNPS
14-hansen-can	178	27	,	,	,
14-hansen-can	178	28	and	and	CC
14-hansen-can	178	29	Cross	Cross	NNP
14-hansen-can	178	30	-	-	NNP
14-hansen-can	178	31	Disciplinary	Disciplinary	NNP
14-hansen-can	178	32	ResearchǔChapter	ResearchǔChapter	NNP
14-hansen-can	178	33	14	14	CD
14-hansen-can	178	34	Shen	Shen	NNP
14-hansen-can	178	35	,	,	,
14-hansen-can	178	36	Zhihong	Zhihong	NNP
14-hansen-can	178	37	,	,	,
14-hansen-can	178	38	Hao	Hao	NNP
14-hansen-can	178	39	Ma	Ma	NNP
14-hansen-can	178	40	,	,	,
14-hansen-can	178	41	and	and	CC
14-hansen-can	178	42	Kuansan	Kuansan	NNP
14-hansen-can	178	43	Wang	Wang	NNP
14-hansen-can	178	44	.	.	.
14-hansen-can	179	1	2018	2018	CD
14-hansen-can	179	2	.	.	.
14-hansen-can	180	1	“	"	``
14-hansen-can	180	2	A	a	DT
14-hansen-can	180	3	Web	web	NN
14-hansen-can	180	4	-	-	HYPH
14-hansen-can	180	5	Scale	scale	NN
14-hansen-can	180	6	System	system	NN
14-hansen-can	180	7	for	for	IN
14-hansen-can	180	8	Scientific	Scientific	NNP
14-hansen-can	180	9	Knowl-	Knowl-	NNP
14-hansen-can	180	10	edge	edge	NN
14-hansen-can	180	11	Exploration	Exploration	NNP
14-hansen-can	180	12	.	.	.
14-hansen-can	180	13	”	"	''
14-hansen-can	180	14	Paper	paper	NN
14-hansen-can	180	15	presented	present	VBD
14-hansen-can	180	16	at	at	IN
14-hansen-can	180	17	the	the	DT
14-hansen-can	180	18	56th	56th	JJ
14-hansen-can	180	19	Annual	Annual	NNP
14-hansen-can	180	20	Meeting	Meeting	NNP
14-hansen-can	180	21	of	of	IN
14-hansen-can	180	22	the	the	DT
14-hansen-can	180	23	Association	Association	NNP
14-hansen-can	180	24	for	for	IN
14-hansen-can	180	25	Com-	Com-	NNP
14-hansen-can	180	26	putational	putational	JJ
14-hansen-can	180	27	Linguistics	Linguistics	NNP
14-hansen-can	180	28	,	,	,
14-hansen-can	180	29	Melbourne	Melbourne	NNP
14-hansen-can	180	30	,	,	,
14-hansen-can	180	31	July	July	NNP
14-hansen-can	180	32	2018	2018	CD
14-hansen-can	180	33	.	.	.
14-hansen-can	181	1	?	?	.
14-hansen-can	181	2	iiT	iit	JJ
14-hansen-can	181	3	,	,	,
14-hansen-can	181	4	ff	ff	VB
14-hansen-can	181	5	�	�	NNP
14-hansen-can	181	6	`tBpXQ`;f	`tbpxq`;f	CD
14-hansen-can	181	7	�	�	NNP
14-hansen-can	181	8	#bfR3y8XRkkRe	#bfr3y8xrkkre	PRP
14-hansen-can	181	9	.	.	.
14-hansen-can	182	1	Tank	tank	NN
14-hansen-can	182	2	,	,	,
14-hansen-can	182	3	Aytekin	Aytekin	NNP
14-hansen-can	182	4	.	.	.
14-hansen-can	183	1	2017	2017	CD
14-hansen-can	183	2	.	.	.
14-hansen-can	184	1	“	"	``
14-hansen-can	184	2	This	this	DT
14-hansen-can	184	3	Is	be	VBZ
14-hansen-can	184	4	the	the	DT
14-hansen-can	184	5	Year	Year	NNP
14-hansen-can	184	6	of	of	IN
14-hansen-can	184	7	the	the	DT
14-hansen-can	184	8	Machine	Machine	NNP
14-hansen-can	184	9	Learning	Learning	NNP
14-hansen-can	184	10	Revolution	Revolution	NNP
14-hansen-can	184	11	.	.	.
14-hansen-can	184	12	”	"	''
14-hansen-can	184	13	Entrepreneur	entrepreneur	NN
14-hansen-can	184	14	,	,	,
14-hansen-can	184	15	January	January	NNP
14-hansen-can	184	16	12	12	CD
14-hansen-can	184	17	,	,	,
14-hansen-can	184	18	2017	2017	CD
14-hansen-can	184	19	.	.	.
14-hansen-can	185	1	?	?	.
14-hansen-can	185	2	iiTb	iitb	UH
14-hansen-can	185	3	,	,	,
14-hansen-can	185	4	ffrrrX2Mi`2T`2M2m`X+QKf	ffrrrX2Mi`2T`2M2m`X+QKf	NNP
14-hansen-can	185	5	�	�	NNP
14-hansen-can	185	6	`iB+H2fk3djk9	`ib+h2fk3djk9	CD
14-hansen-can	185	7	.	.	.
14-hansen-can	186	1	http://arxiv.org/abs/1805.12216	http://arxiv.org/abs/1805.12216	NNP
14-hansen-can	186	2	https://www.entrepreneur.com/article/287324	https://www.entrepreneur.com/article/287324	NN