different word 0.003513712
word vector 0.00350317
word sense 0.003368581
word vectors 0.003220942
word space 0.003202581
word meaning 0.003124315
target word 0.0030905869999999997
word work 0.003003984
context words 0.0029964199999999996
particular word 0.00295044
original word 0.0029098229999999997
word senses 0.002902199
accurate word 0.002838303
complete word 0.0028349739999999997
whole word 0.0028169859999999996
word usage 0.0027883559999999996
vidual word 0.0027883559999999996
vector model 0.00278708
space model 0.002486491
latent model 0.002433097
context vectors 0.002419512
context features 0.002296298
noun model 0.002283035
factorization model 0.002280472
our model 0.002177929
composition model 0.002164825
nmf model 0.002163556
particular context 0.00214901
small context 0.0021294589999999998
variable model 0.00209991
combined model 0.0020983269999999997
svd model 0.002080898
ization model 0.002075366
model instantiations 0.0020735619999999997
nmfcontext model 0.002072632
context window 0.0020717649999999997
multiple context 0.0020558209999999998
broad context 0.002040635
individual context 0.00201774
context fea 0.002000606
ular context 0.001986896
semantic similarity 0.001973244
semantic space 0.0019164009999999999
different models 0.001898022
model 0.00184492
similar words 0.0017715779999999998
target words 0.001766417
context 0.00175958
semantic analysis 0.001754635
semantic dimensions 0.001671418
same vector 0.001651339
space models 0.001586891
vector space 0.0015837310000000001
semantic dimen 0.001513962
meaning vector 0.001505465
semantic fingerprint 0.0015025400000000001
semantic compositionality 0.001501999
stop words 0.001466987
probability vector 0.001428347
computational models 0.001362716
different instances 0.0013155530000000001
sense distribution 0.001298331
different senses 0.0012938910000000001
original vector 0.001290973
different contexts 0.001284913
different methods 0.001270866
vector composition 0.0012620650000000001
different values 0.001247192
same features 0.0012458970000000002
feature vector 0.001237975
different parts 0.0012376800000000001
words 0.00123684
different functions 0.001233378
latent space 0.001229748
different baselines 0.001225763
different sentences 0.001206597
language phenomena 0.001205322
different modes 0.001193849
different measures 0.001186668
vector com 0.0011850390000000001
vector addition 0.001182527
different evalua 0.001180669
vector adaptation 0.001174809
sense disambiguation 0.001167103
standard number 0.001163048
evaluation results 0.001163018
sense induction 0.001161093
original sense 0.0011563839999999999
standard data 0.001147026
probability vectors 0.0011461190000000001
dependency relations 0.001134745
dependency features 0.001110922
other algorithms 0.001076965
latent probability 0.001074364
music sense 0.001071627
same way 0.001069682
same ranking 0.001066623
similarity measure 0.001046605
sense inventory 0.0010445419999999999
sense assignment 0.001036979
