topic model 0.002382602
influence model 0.0021477830000000003
generative model 0.001831601
unsupervised model 0.0017855570000000001
probabilistic model 0.0017744890000000002
tir model 0.00173211
variable model 0.0017240290000000002
graphical model 0.001689486
tire model 0.0016862440000000002
collapsed model 0.001685752
word vector 0.001683552
flow model 0.001682261
model validation 0.001679968
dmr model 0.001679155
topic space 0.001517516
unsupervised word 0.001490267
model 0.0014783
word sense 0.0014335749999999999
models influence 0.001381169
topic distribution 0.001349962
document influence 0.001280649
topic counts 0.001238517
feature vector 0.0011864789999999998
topic assignment 0.001175635
data analysis 0.001165863
topical influence 0.001163393
topic assignments 0.00116264
topic distributions 0.001152773
novel topic 0.00115077
similar topic 0.001149045
such influence 0.001133734
document network 0.001109672
lar topic 0.0011077749999999999
topic proportions 0.001106297
topic distribu 0.0011059569999999999
scientific influence 0.001085965
citation influence 0.001080902
influence information 0.001063408
markov models 0.001047947
influence weights 0.0010276600000000001
learning algorithm 0.001027121
synthetic data 0.001022317
influence score 0.001021349
ploratory data 0.001020094
influence scores 0.001007156
influence variables 9.842940000000001E-4
probability score 9.79388E-4
edge influence 9.78332E-4
influence weight 9.67658E-4
tir models 9.654959999999999E-4
theoretical models 9.60764E-4
novel models 9.58154E-4
document content 9.56152E-4
influence mechanism 9.559939999999999E-4
log probability 9.554470000000001E-4
standard lda 9.51717E-4
influence value 9.49974E-4
influence regression 9.38266E-4
influence relationships 9.37208E-4
entropy models 9.27276E-4
such graph 9.22824E-4
binary feature 9.20568E-4
feature structures 9.17194E-4
rectly models 9.13178E-4
training set 9.118780000000001E-4
other articles 9.11806E-4
cal influence 9.10352E-4
citation network 9.09925E-4
influence values 9.091920000000001E-4
influence top 9.08756E-4
topic 9.04302E-4
posterior probability 8.932160000000001E-4
new documents 8.909839999999999E-4
feature vec 8.884609999999999E-4
feature vectors 8.87484E-4
different metrics 8.81056E-4
ical influence 8.79274E-4
entific influence 8.78645E-4
influence man 8.78126E-4
predictive probability 8.74312E-4
influence mea 8.71341E-4
same set 8.70961E-4
citation graph 8.69992E-4
influence trajectories 8.69393E-4
reverse influence 8.69393E-4
interpersonal influence 8.69393E-4
meaningful influence 8.69393E-4
new research 8.589959999999999E-4
dependency parsing 8.49973E-4
other variables 8.49611E-4
reinforcement learning 8.492739999999999E-4
document prediction 8.40625E-4
topical content 8.38896E-4
same structure 8.36666E-4
other tasks 8.3258E-4
different assumptions 8.28051E-4
text content 8.261309999999999E-4
many citations 8.17969E-4
sampling approach 8.11674E-4
other application 8.0729E-4
