aspect sentiment 0.00406197
aspect ranking 0.002977028
aspect term 0.002833608
aspect terms 0.002684293
important aspect 0.002638478
aspect sen 0.002591443
aspect identification 0.0025805330000000003
aspect frequency 0.0025401860000000003
accurate aspect 0.002513684
aspect identifi 0.002505573
aspect fre 0.0025048690000000003
aspect 0.00226887
svm sentiment 0.002254949
sentiment terms 0.002208523
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level sentiment 0.002196028
sentiment classifier 0.002171096
sentiment classification 0.0021378309999999998
product review 0.0021035999999999997
sentiment lexicon 0.002070701
sentiment classi 0.0020371029999999997
tain sentiment 0.002029167
product aspects 0.00195657
opinion rating 0.0018562140000000001
review data 0.001812822
sentiment 0.0017931
domain review 0.0017278419999999998
text reviews 0.0016778560000000001
text review 0.001627596
online reviews 0.001591869
opinion ratings 0.0015865700000000003
consumer reviews 0.0015508280000000002
opinion terms 0.0015120230000000001
several aspects 0.001496288
overall opinion 0.0014750310000000001
numerous reviews 0.001473436
model parameter 0.001472927
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reviews corpus 0.001463631
sumer reviews 0.0014599740000000002
ranking approach 0.001448979
model parameters 0.0014423419999999999
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review corpus 0.001413371
review influences 0.001402759
opinion vectors 0.001400372
various aspects 0.001398809
important aspects 0.001388428
specific aspects 0.001354647
opinion ork 0.001334256
opinion ratingor 0.0013326710000000001
aspects identification 0.001330483
frequent aspects 0.0013198569999999998
multiple aspects 0.001316942
online product 0.001313509
important product 0.001307358
unique aspects 0.0013057049999999999
specific product 0.0012735770000000001
cific aspects 0.001264716
tant aspects 0.001262891
ranking results 0.001260153
aspects ork 0.0012564759999999999
arem aspects 0.001255101
iphone product 0.001247078
feature feature 0.001239874
other methods 0.001227625
reviews 0.00121611
product development 0.001212002
product name 0.0012087040000000001
cific product 0.001183646
prior distribution 0.001182514
feature vector 0.001178222
product reputa 0.001173993
product devel 0.001173993
ranking algorithm 0.001170322
review 0.00116585
gaussian distribution 0.001158267
data set 0.001129288
opinion 0.0010966
ranking framework 0.001089898
identification approach 0.001052484
model 0.0010397
method canon 0.001025341
such results 0.001021153
aspects 0.00101882
effective approach 9.90301E-4
supervised method 9.848349999999999E-4
ranking list 9.83427E-4
feature price 9.76945E-4
unsupervised method 9.74202E-4
ing results 9.600990000000001E-4
supervised methods 9.531559999999999E-4
importance score 9.517009999999999E-4
ranking algo 9.47272E-4
classification methods 9.45289E-4
perfect ranking 9.444249999999999E-4
product 9.3775E-4
hybrid method 9.37131E-4
data sets 9.15882E-4
mean vector 9.111950000000001E-4
