model parameter 0.002486794
global model 0.002482208
model local 0.002426679
local model 0.002426679
model parameters 0.002342737
above model 0.002342223
final model 0.002279981
probabilistic model 0.002254524
entropy model 0.002183248
model parame 0.00216752
model param 0.002163132
physical model 0.002161405
model 0.00193972
unknown word 0.00188686
training data 0.001809662
word dictionaries 0.0017247109999999999
word sense 0.001708428
known word 0.0017018889999999998
pos tag 0.001600942
data test 0.0015997860000000002
test data 0.0015997860000000002
such pos 0.001579659
such words 0.001568637
ing data 0.001524247
procedure data 0.0014961660000000002
whole data 0.001482723
words corpus 0.001472456
data unlabeled 0.001450462
unlabeled data 0.001450462
language models 0.001439873
result data 0.001424051
probability distribution 0.001413973
pos tags 0.001404224
words tags 0.001393202
input data 0.001388547
mixed data 0.001387261
possible pos 0.0013665980000000001
data flow 0.00135325
data sub 0.001352122
same training 0.001320472
corpus training 0.001294667
training corpus 0.001294667
unknown words 0.001285611
pos tagging 0.00128133
language analysis 0.00122101
candidate pos 0.001204479
such methods 0.001186504
many words 0.001184823
training test 0.0011483280000000001
method models 0.0011396090000000002
conditional distribution 0.001134281
language mod 0.001134135
standard tags 0.0011337080000000002
optimal pos 0.001127453
language processing 0.001120109
joint distribution 0.001117937
encounter words 0.0011144100000000001
exponential language 0.001112845
natural language 0.001111486
sampling methods 0.00111012
known words 0.00110064
gibbs sampling 0.001099413
pos guess 0.001090705
pos guessing 0.001090105
test corpus 0.0010847909999999999
global features 0.0010840020000000001
unique words 0.001083108
surrounding words 0.001078422
fundamental language 0.001074077
initial distribution 0.001059926
feature function 0.00105575
entire training 0.001043046
other variables 0.001034862
local features 0.001028473
marginal distribution 0.0010244310000000001
such examples 0.001019517
test results 0.001017326
global information 0.0010154
tag pair 0.001012399
true distribution 0.001006858
same label 0.001006769
boltzmann distribution 0.001005383
objective function 9.95506E-4
joint probability 9.79054E-4
probability distributions 9.785570000000001E-4
other approaches 9.76991E-4
special tag 9.675259999999999E-4
other examples 9.67267E-4
local information 9.598709999999999E-4
tag unk 9.55474E-4
other solutions 9.5426E-4
corpora corpus 9.53857E-4
same form 9.487860000000001E-4
corpus accuracy 9.42679E-4
treebank corpus 9.41931E-4
university corpus 9.36862E-4
such parts 9.36559E-4
such cases 9.36495E-4
such convention 9.364499999999999E-4
sampling technique 9.360939999999999E-4
