feature selection 0.0032396829999999997
selection feature 0.0032396829999999997
model features 0.0031122500000000004
feature performance 0.003006521
feature values 0.0029662959999999998
feature space 0.002855959
feature subset 0.0028386749999999997
large feature 0.0028333589999999997
following feature 0.002824071
feature driving 0.0028011219999999996
feature discretisation 0.002785256
discretisation feature 0.002785256
dialogue features 0.0027822240000000002
single feature 0.0027699919999999998
mdl feature 0.0027574509999999997
individual feature 0.0027447319999999997
feature engineering 0.002737108
potential feature 0.0027210439999999997
feature subsets 0.002715661
all feature 0.002711204
feature spaces 0.00270719
feature distribu 0.002705408
feature dis 0.0027033649999999997
delay feature 0.002700746
feature selec 0.002696067
proper feature 0.002693363
feature engineer 0.002691958
feature screenuser 0.002691036
feature transformation 0.002691036
context features 0.00252084
feature 0.00247316
features first 0.002431925
multiple features 0.0024198120000000004
local features 0.0023920490000000003
numeric features 0.0022651710000000003
specific features 0.002263157
various features 0.0022510810000000003
runtime features 0.00224863
features global 0.0022463680000000003
independent features 0.002243749
contextual features 0.002232173
cal features 0.00221631
history features 0.002215912
dependent features 0.00221394
redundant features 0.002210014
tween features 0.002209332
uous features 0.0022081500000000003
meric features 0.0022081500000000003
user model 0.00209554
features 0.00198918
data set 0.0018474300000000002
woz data 0.0016483420000000001
data analysis 0.001647554
data sets 0.001605329
ing data 0.001601124
small data 0.001575788
discretised data 0.001565539
data base 0.0015645190000000001
model fea 0.0015476460000000002
raw data 0.001543998
sparse data 0.001531022
severe data 0.001530681
inal data 0.001530357
continuous data 0.001525338
limited data 0.001521212
dialogue information 0.0015189700000000001
data sparsity 0.001515029
tion model 0.00148083
regression model 0.001456658
previous user 0.001441058
new user 0.001384915
generative model 0.00137738
user models 0.001368878
prediction model 0.001359699
probabilistic model 0.0013419600000000001
same dialogue 0.001339979
dialogue context 0.001324704
dialogue system 0.001313233
user speech 0.001269119
different context 0.00124807
particular user 0.001237643
ferent user 0.001226826
user utterance 0.001222346
tree algorithm 0.001208024
user satisfaction 0.001193816
user preference 0.001191332
selection methods 0.001178813
current dialogue 0.001170517
selection models 0.0011629309999999999
many words 0.001147707
different fea 0.001140986
subset selection 0.001132038
model 0.00112307
ture selection 0.001119136
information state 0.001098621
dialogue systems 0.001071498
induction algorithm 0.001062
dialogue application 0.0010549280000000001
selection algorithms 0.001047844
automated dialogue 0.00103889
