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topic model 0.00453341
topic words 0.0044851
topic distribution 0.00435039
topic models 0.003962346
bursty topic 0.003837221
same topic 0.003770721
topic distributions 0.003728264
new topic 0.0037159809999999997
topic modeling 0.003711514
standard topic 0.0036478509999999997
topic label 0.0036168249999999997
hidden topic 0.003590556
topic detection 0.0035864449999999997
general topic 0.00357771
global topic 0.0035760339999999996
single topic 0.0035684009999999997
ing topic 0.00356226
line topic 0.0035315069999999997
temporal topic 0.003528599
own topic 0.003521523
topic ranking 0.0035208179999999998
personal topic 0.0035193399999999997
topic trends 0.0035164669999999997
subway topic 0.0034998729999999997
topic distribu 0.0034995369999999996
topic changes 0.0034885669999999997
topic detec 0.00348512
topic intensity 0.0034801899999999998
topic discovery 0.003478962
our topic 0.0034745979999999997
trendy topic 0.0034701539999999996
covered topic 0.0034682619999999997
topic composition 0.0034682619999999997
chosen topic 0.0034682619999999997
topic 0.00327549
word distribution 0.00270152
word distributions 0.002079394
times word 0.0019403320000000001
current word 0.0019203760000000001
ground word 0.001872629
word distri 0.0018462440000000001
word clustering 0.001834604
background word 0.001825529
lda model 0.0017760340000000001
bursty words 0.001771341
bursty topics 0.001669641
model parameters 0.001553529
top words 0.001551799
words example 0.0014914350000000002
complete model 0.001483326
model users 0.001464295
userlda model 0.001463294
timeuserlda model 0.001459723
background model 0.001456829
common words 0.001456063
hidden topics 0.0014229759999999998
individual words 0.00141528
stop words 0.0014108430000000002
background words 0.001408519
groups words 0.001403188
multiple topics 0.001394593
multinomial distribution 0.001381228
interesting topics 0.0013715289999999998
data set 0.0013655310000000001
unique topics 0.001340117
redundant topics 0.0013139579999999998
underlying topics 0.001312028
count data 0.001288399
other models 0.00127749
distribution θti 0.0012681419999999999
different time 0.001261663
model 0.00125792
original data 0.0012550600000000001
final data 0.0012138840000000001
words 0.00120961
twitter data 0.001202553
data streams 0.001186002
series data 0.00118219
data stream 0.001181252
topics 0.00110791
different states 0.001075201
distribution 0.0010749
other text 0.0010352640000000001
bursty state 0.001018939
other work 0.0010043300000000001
different streams 0.001003011
various models 9.90005E-4
different mod 9.82798E-4
different users 9.817790000000001E-4
same time 9.8149E-4
same documents 9.57283E-4
temporal models 9.399650000000001E-4
alternative models 9.07408E-4
user models 9.06873E-4
bursty top 9.0392E-4
userlda models 8.9223E-4
standard lda 8.90475E-4
temporal information 8.833770000000001E-4
other variables 8.67636E-4
