domain corpus 0.00318197
learner corpus 0.002765129
corpus first 0.00253544
native corpus 0.002532456
esl corpus 0.0024900630000000003
ukwac corpus 0.0023516780000000003
jiem corpus 0.002350721
scale corpus 0.002341443
nus corpus 0.002306943
corpus 0.00203665
language learning 0.001888414
learner domain 0.001873799
training data 0.0018083499999999998
context features 0.0018002320000000001
target domain 0.001755438
original word 0.001745545
domain adaptation 0.00174117
various features 0.001697434
specific features 0.001685275
word clus 0.0016775639999999999
clustering features 0.00167168
error correction 0.001654483
head features 0.0016242650000000002
domain information 0.001596372
parse features 0.001590223
source domain 0.001588262
selection error 0.001546696
various error 0.001546664
domain dataset 0.001499621
error types 0.001489509
certain error 0.00148033
correct sentences 0.0014779749999999999
grammatical error 0.0014774369999999998
tional data 0.001471188
error type 0.001462017
error tag 0.0014493429999999999
data sparseness 0.001429339
linear model 0.001426573
error patterns 0.001421322
domain adapta 0.001417712
domain adap 0.001415936
error pat 0.001405622
suggestion model 0.001403835
placement error 0.001402228
learner corpora 0.001397419
feature vector 0.001373262
second language 0.001363913
model the 0.001329611
learner errors 0.0013159679999999998
dimensional model 0.001310583
model sug 0.001290105
features 0.00128205
suggestion method 0.001264308
japanese learner 0.0012468779999999999
feature space 0.001218333
feature vectors 0.001215359
ing learner 0.00121287
learner english 0.001204841
head words 0.001198087
translation table 0.001195597
other businessmen 0.001178672
other classes 0.0011712930000000001
other busi 0.0011666670000000001
native corpora 0.001164746
learner writing 0.001158043
standard approach 0.0011571889999999999
feature augmentation 0.001151362
candidate set 0.00114897
domain 0.00114532
same characteristics 0.001144456
various learner 0.001143863
error 0.00113128
mented feature 0.0011230580000000001
esl corpora 0.001122353
classifier models 0.001114986
translation tables 0.001111122
learning website 0.001109958
main adaptation 0.001100183
target verbs 0.00109807
glish sentences 0.001091955
same url 0.001080783
same hypernyms 0.001080783
set size 0.0010663600000000001
correction candidate 0.0010660679999999999
first work 0.0010646100000000001
available learner 0.0010612249999999998
language 0.00105793
candidate sets 0.001041935
actual learner 0.001034443
scale learner 0.001033272
common errors 0.001026498
model 0.00101877
correct usages 0.001015805
selection errors 0.001002905
learner writings 9.98692E-4
bridge learner 9.98692E-4
gestion models 9.92794E-4
correction pairs 9.80884E-4
suggestion performance 9.7271E-4
japanese esl 9.718120000000001E-4
