semantic patterns 0.0036873920000000003
seed patterns 0.0031709150000000003
succession patterns 0.003091033
irrelevant patterns 0.003060199
good patterns 0.003051287
tion patterns 0.003041962
candidate patterns 0.002997436
potential patterns 0.0029618210000000003
accepted patterns 0.002961165
quire patterns 0.0029600760000000003
acquire patterns 0.0029600760000000003
ered patterns 0.0029600760000000003
disfavor patterns 0.0029600760000000003
pattern set 0.002838826
patterns 0.0027127
pattern precision 0.002695503
unsupervised pattern 0.002620312
pattern learning 0.002420252
pattern learner 0.002313953
pattern acquisition 0.00231146
supervised pattern 0.002298241
good pattern 0.002273757
pattern accuracy 0.00227372
pattern matching 0.002271913
pattern ranking 0.002263748
automatic pattern 0.002263592
single pattern 0.00224271
pattern generalization 0.002222578
candidate pattern 0.002219906
panded pattern 0.002182278
person person 0.00203074
pattern 0.00193517
extraction system 0.0016416629999999998
information extraction 0.0016127749999999999
document set 0.001520883
training corpus 0.00150505
test corpus 0.001479622
unsupervised algorithm 0.001439152
relevant document 0.001419952
chairman person 0.001382242
erence corpus 0.001375637
news corpus 0.001363985
semantic pat 0.001357548
semantic class 0.001326579
person merger 0.0012936100000000002
semantic features 0.001290538
resignation person 0.001285662
relevant documents 0.001261211
semantic classification 0.001251923
good set 0.001242243
learning algorithm 0.001239092
document recall 0.001233025
semantic cate 0.001223746
formation extraction 0.00120038
precision scores 0.001196932
high precision 0.001186187
other scenarios 0.001182662
unsupervised learning 0.001170224
document relevance 0.001154419
comprehensive set 0.001151523
such documents 0.001142798
entity classes 0.001108094
such events 0.0010890029999999998
corpus 0.00108814
other learners 0.001077684
unsupervised pat 0.0010679980000000001
other domains 0.00106578
same scenarios 0.001065427
unsupervised learner 0.001063925
same technique 0.001062079
other categories 0.001061441
baseline algorithm 0.001061148
basic algorithm 0.001047536
other kinds 0.001043398
point precision 0.001043207
other recognizers 0.001038846
precision drops 0.001026078
main features 0.001018581
person 0.00101537
algorithm ter 0.001003282
main steps 0.001002235
main differences 9.91896E-4
different scenarios 9.86923E-4
document space 9.82624E-4
relevance scores 9.737910000000001E-4
unsupervised learners 9.72567E-4
unsupervised methods 9.72504E-4
same application 9.706930000000001E-4
same time 9.70606E-4
such thresholds 9.70589E-4
high relevance 9.63046E-4
new relevance 9.62832E-4
same experiment 9.62155E-4
main idea 9.590989999999999E-4
own relevance 9.585450000000001E-4
extraction 9.53626E-4
purpose information 9.44591E-4
first iteration 9.442020000000001E-4
particular relevance 9.3712E-4
unsupervised meth 9.34431E-4
