word sense 0.00457839
sense label 0.003903399
sense disambiguation 0.003759836
basic sense 0.003736684
domain system 0.0037029330000000003
sense alignments 0.003699444
sense descriptions 0.003698265
scdm sense 0.003696026
good sense 0.00369238
nominal sense 0.003676584
sense align 0.003669154
specific domain 0.0036653170000000004
sense alignment 0.003662685
domain label 0.0036501990000000002
sense description 0.003644236
same domain 0.003637365
binary domain 0.003549586
domain values 0.003543994
domain labels 0.003463176
domain assignment 0.0034220780000000003
domain informa 0.0034074360000000002
final domain 0.003401238
sense 0.00339113
domain fil 0.003386881
domain 0.00313793
word senses 0.00236715
test data 0.001890896
training data 0.0017178459999999999
noun senses 0.001591692
feature specific 0.001584387
word list 0.001554823
feature vector 0.001485712
scdm senses 0.001484786
feature values 0.001463064
core senses 0.001429451
feature generic 0.001425691
basic features 0.001375894
feature selection 0.0013636640000000001
good feature 0.00135825
test set 0.001234193
similarity approach 0.001200004
words 0.00119613
senses 0.00117989
different resources 0.001173245
label wsd 0.001171956
different approaches 0.001157706
wordnet domains 0.0011463950000000001
lexical knowledge 0.001129955
other value 0.00112423
same method 0.001115162
gloss corpus 0.001108239
different forms 0.001097273
lexical resources 0.001077173
training set 0.001061143
feature 0.001057
features 0.00103034
first strategy 0.001026275
frequency score 0.001021549
frequency scores 0.0010062909999999999
same dataset 9.70866E-4
lexical match 9.63262E-4
label strategy 9.49727E-4
text descriptions 9.47325E-4
cosine similarity 9.46547E-4
main clusters 9.440780000000001E-4
rules system 9.383799999999999E-4
main difference 9.28969E-4
learning classifier 9.23241E-4
based system 9.186820000000001E-4
domains labels 9.07621E-4
same precision 9.065550000000001E-4
hybrid method 9.004320000000001E-4
other hand 8.99902E-4
future work 8.961290000000001E-4
tire set 8.91707E-4
main labels 8.847830000000001E-4
simple method 8.844090000000001E-4
label factotum 8.82855E-4
factotum label 8.82855E-4
work this 8.79979E-4
this work 8.79979E-4
test sets 8.79742E-4
frequency counts 8.69814E-4
able approach 8.61172E-4
value factotum 8.584059999999999E-4
factotum value 8.584059999999999E-4
corpus 8.50668E-4
hybrid system 8.49708E-4
high precision 8.479E-4
high values 8.46844E-4
hybrid approach 8.4479E-4
ing noun 8.41808E-4
baselinewsd system 8.37967E-4
standard precision 8.3541E-4
final system 8.28311E-4
field label 8.20388E-4
same meaning 8.12066E-4
machine learning 8.08415E-4
english translations 8.071689999999999E-4
small training 7.95722E-4
