word features 0.00299253
different feature 0.002916607
feature set 0.002890111
feature vector 0.00259585
same feature 0.002566972
feature function 0.002514537
full feature 0.0023777439999999998
basic feature 0.002373551
feature common 0.002361433
only feature 0.002360133
feature sets 0.0023493809999999998
various feature 0.0023472149999999997
distribution features 0.002344517
binary feature 0.002344068
similarity features 0.002335358
sim feature 0.002334479
such features 0.002311723
next feature 0.002305993
latter feature 0.002296744
indicator feature 0.002281781
lhs feature 0.002280501
multiple features 0.00218229
distributional model 0.002159861
frequency features 0.002147384
topic model 0.002109605
baseline model 0.002100576
pair features 0.002098559
lda features 0.002079655
feature 0.00203537
analogous features 0.002023774
elaborate features 0.002007003
numerical features 0.0020065
quency features 0.002003126
motivated features 0.002003126
the model 0.001986549
variable model 0.0019327790000000001
full model 0.0019252840000000002
linear model 0.001920817
statistical model 0.0019197110000000002
lda model 0.001899015
cds model 0.001842551
latentlc model 0.001829464
fication model 0.001829322
model col 0.001827965
model aims 0.0018221910000000001
features 0.00176355
first word 0.001745047
training set 0.001638801
data set 0.001635402
model 0.00158291
other words 0.001568351
training data 0.001564721
head word 0.001538532
second word 0.001527101
content word 0.001515437
test set 0.001491532
word lemma 0.001477552
representative word 0.001473276
same set 0.001386343
function words 0.0013668
large corpus 0.0013294420000000001
multiple words 0.001306373
ing set 0.001303468
individual words 0.0012986949999999999
different lcs 0.001289585
such models 0.001268538
topic models 0.00124706
baseline models 0.0012380310000000001
lexical inference 0.001221331
set evaluation 0.001201549
head words 0.001197185
evaluation corpus 0.0011860619999999999
content words 0.00117409
reference corpus 0.001167245
tiple words 0.001166713
accurate set 0.001151462
set scenario 0.0011512010000000001
distributional similarity 0.001148759
reverb corpus 0.001139979
vector similarity 0.001132288
tent words 0.001132124
argument distribution 0.001131906
probability distribution 0.001127174
web data 0.001121343
topic distribution 0.0011076620000000001
complete set 0.00110672
set scenarios 0.001105567
pos tag 0.001098112
gous set 0.001093522
approach this 0.001087293
corpus prefbal 0.001080979
corpus prefabl 0.001080979
corpus commonal 0.0010808179999999999
ation corpus 0.001079349
corpus pmiabl 0.001079349
distributional methods 0.0010706280000000001
lexical relations 0.001059178
distributional representations 0.001046337
lexical units 0.001045907
other examples 0.0010439429999999999
