model word 0.0026535639999999997
space model 0.002607864
baseline model 0.002520225
preference model 0.002447
preferences model 0.002438977
simple model 0.002434113
model parameters 0.00243386
variable model 0.002364608
cut model 0.0023644679999999998
generative model 0.00236092
hard model 0.002344178
germanet model 0.002342638
lda model 0.0023391749999999998
sun model 0.002337812
model con 0.002333414
wsm model 0.0023166519999999998
model partitions 0.002312837
korhonen model 0.0023056129999999998
model polysemy 0.0023056129999999998
model 0.0021059
clustering models 0.001976036
such models 0.001756669
noun clustering 0.0017407310000000001
noun class 0.00173902
different models 0.001725711
semantic classes 0.001711579
space models 0.0016594040000000002
semantic classification 0.0015694289999999998
noun classes 0.001557424
corpus data 0.0015195220000000001
statistical models 0.00150184
preference models 0.00149854
data set 0.001485632
different scf 0.0014743769999999998
syntactic information 0.001467462
object noun 0.001442742
semantic role 0.001421978
ent models 0.001416119
cut models 0.001416008
clustering method 0.00140908
noun cluster 0.001394985
lda models 0.001390715
noun types 0.00139042
test data 0.0013830819999999999
scf types 0.001374391
clustering algorithm 0.001370431
wsm models 0.001368192
clustering evaluation 0.0013671339999999999
semantic roles 0.001354143
first noun 0.001350353
training data 0.001301583
clustering verbs 0.0013010790000000001
preference data 0.001292699
semantic relatedness 0.001279775
other words 0.001277733
scf type 0.00126309
noun arguments 0.001255989
scf preference 0.0012472059999999998
noun clusters 0.0012414330000000001
scf preferences 0.001239183
particular noun 0.001231092
standard clustering 0.001227551
subject noun 0.001224131
example noun 0.001213475
unseen data 0.001209285
noun vectors 0.001208258
different classes 0.00120356
lexical information 0.001203209
potential data 0.0012025220000000001
data sparsity 0.001188758
class map 0.001184288
noun concepts 0.001177192
multiple scf 0.0011756429999999999
clustering performance 0.001169891
alternative noun 0.0011671610000000001
specific noun 0.0011625630000000001
scf tag 0.001161718
germanet noun 0.001158873
models 0.00115744
noun partition 0.001156965
data sparseness 0.00115485
class label 0.001154239
sun noun 0.001154047
scf inventory 0.001152768
word vector 0.0011527360000000001
unlabelled data 0.001152583
scf tags 0.0011510959999999999
verbal scf 0.001141033
standard information 0.001138308
noun categorisation 0.001138139
singleton noun 0.001134756
nouns classes 0.001132864
clustering methods 0.001131824
noun tokens 0.0011285190000000001
scf tagger 0.001124386
noun votes 0.001121862
noun observation 0.001121862
noun hier 0.001121862
effective noun 0.001121862
scf code 0.00111554
