word sense 0.0045553699999999996
different word 0.003949246
word alignment 0.003942785
other word 0.003917241
word senses 0.003677397
frequent word 0.003647159
word form 0.003631098
word alignments 0.003627329
focus word 0.0035778
ambiguous word 0.003557193
content word 0.00355244
automated word 0.003533697
word align 0.003531646
polysemous word 0.0035314
words features 0.00277759
translation features 0.00273141
training feature 0.002342701
test feature 0.002090999
wsd features 0.002085572
context features 0.002071311
test words 0.002010139
feature vector 0.001981646
training data 0.001902681
bilingual features 0.00185577
feature sets 0.001852872
full feature 0.001778758
dutch translation 0.001773946
machine translation 0.001770492
feature selection 0.001763972
current feature 0.001750635
feature base 0.001749361
feature weighting 0.001738739
correct translation 0.0017327240000000002
feature vectors 0.0017275699999999999
ratio feature 0.001722776
joint feature 0.001720376
feature vec 0.001716615
translation framework 0.001711513
feature selec 0.0017108099999999999
focus words 0.0016801200000000002
correct sense 0.0016686140000000001
translation fea 0.001661853
ambiguous words 0.001659513
content words 0.0016547600000000001
test data 0.001650979
data set 0.001643404
wsd system 0.001609184
translation labels 0.001608338
sense disambiguation 0.001597672
chine translation 0.001585568
matized translation 0.001582922
sense transla 0.001580771
sense dis 0.001570033
sense inventory 0.001533081
sense disambigua 0.001522632
finer sense 0.001520029
sense inven 0.0015191739999999999
sense distinc 0.0015191739999999999
sense discrimination 0.0015191739999999999
training set 0.001496425
feature 0.00146485
target language 0.001437622
features 0.0013936
english test 0.001391979
words 0.00138399
first training 0.001375612
translation 0.00133781
europarl data 0.001329336
different set 0.00128615
semeval system 0.001283588
sense 0.0012737
same set 0.001264172
parallel corpus 0.001247413
test set 0.001244723
target languages 0.001244185
second training 0.001238732
different approach 0.0012317629999999999
training instances 0.001228679
different languages 0.001221323
english sentences 0.001219295
parasense system 0.001196042
local context 0.001191279
other languages 0.001189318
training instance 0.00116449
english senses 0.0011615570000000001
bilingual wsd 0.001154142
training phase 0.001150128
wsd systems 0.001148897
different classifiers 0.001148237
tional training 0.001131384
multilingual information 0.001127688
parallel text 0.001093029
other systems 0.001092496
target translations 0.0010867630000000001
english input 0.00108407
multilingual wsd 0.001083452
europarl corpus 0.00107272
previous wsd 0.00107048
dutch classifier 0.001052634
input sentence 0.001026714
