model algorithm 0.002398309
model corpus 0.002315206
character model 0.001974984
word segmentation 0.001913898
markov model 0.00191372
extended model 0.001806491
model selection 0.001790843
word type 0.001751032
word induction 0.0017481950000000001
word boundaries 0.001741532
unique word 0.001737695
unsupervised word 0.001727442
word distributions 0.001710587
novel word 0.001700183
word seg 0.001687919
word segmenta 0.001681662
word induc 0.001681601
word prefix 0.001680317
word typesm 0.001679126
word segmen 0.001678798
corpus language 0.001612349
model 0.00157062
training corpus 0.001451087
language data 0.001444904
such models 0.001306779
training data 0.001283642
segmentation algorithm 0.001275577
corpus length 0.0012499920000000001
small language 0.001191051
standard search 0.001185256
japanese language 0.001178684
target language 0.001152967
language size 0.00113675
mdl models 0.001134992
probabilistic models 0.001123935
bayesian models 0.00111915
language sample 0.0011139119999999999
complex models 0.001100951
different data 0.0010942410000000001
tion models 0.001090793
language samples 0.001090617
induction models 0.001089752
language acquisition 0.001086575
native language 0.001079905
search path 0.001079486
language acquisi 0.001079279
adequate language 0.001079279
search algorithms 0.001072418
efficient algorithm 0.001069971
kyoto corpus 0.001068297
university corpus 0.001054663
search routine 0.001044109
exhaustive search 0.001026955
test data 0.00102601
semble models 0.001019234
corpus size 0.001013573
training corpora 0.001012953
childes corpus 0.001012669
annotated corpus 0.001002043
bisection search 9.94298E-4
standardized search 9.92094E-4
focused search 9.92094E-4
whole corpus 9.90365E-4
asahi corpus 9.74526E-4
threshold parameter 9.66577E-4
segmented corpus 9.65593E-4
best corpus 9.64699E-4
annotated training 9.63958E-4
testing corpus 9.62827E-4
oto corpus 9.56852E-4
inal corpus 9.56852E-4
lexicon data 9.529639999999999E-4
same time 9.48361E-4
character set 9.419350000000001E-4
prior probability 9.39559E-4
training datasets 9.32354E-4
new length 9.24635E-4
such approaches 9.243189999999999E-4
unannotated training 9.17814E-4
different method 9.107960000000001E-4
description length 9.022430000000001E-4
different values 8.82809E-4
language 8.67763E-4
development data 8.664969999999999E-4
segmentation task 8.66199E-4
different languages 8.619210000000001E-4
threshold value 8.548869999999999E-4
standard segmentation 8.53509E-4
data size 8.46128E-4
length framework 8.393770000000001E-4
context length 8.31702E-4
algorithm 8.27689E-4
first character 8.24935E-4
same way 8.248089999999999E-4
description time 8.243980000000001E-4
different corpora 8.235520000000001E-4
threshold values 8.14126E-4
hypothesis space 8.12984E-4
step parameter 8.11072E-4
labeled data 8.09008E-4
