[CL+NLP Lunch] Reminder: CL+NLP Lunch, Pengtao Xie, Thursday April 2nd @ 12:00pm

[Dallas Card]

Please join us for the next CL+NLP lunch at 12:00pm on Thursday April 2nd,
where Pengtao Xie will be speaking about incorporating word correlation
knowledge into topic models. Lunch will be provided!

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CL+NLP lunch <http://www.cs.cmu.edu/~nlp-lunch/>
Thursday, April 2nd at 12:00pm
GHC 6501

Speaker: Pengtao Xie, LTI

Title: Incorporating Word Correlation Knowledge into Topic Modeling

Abstract:
This work studies how to incorporate external word correlation knowledge
to improve the coherence of topic modeling. Existing topic models assume
words are generated independently and lack the mechanism to utilize the
rich similarity relationships among words to learn coherent topics. To
solve this problem, we build a Markov Random Field (MRF) regularized
Latent Dirichlet Allocation (LDA) model, which defines a MRF on the latent
topic layer of LDA to encourage words labeled as similar to share the same
topic label. Under our model, the topic assignment of each word is not
independent, but rather affected by the topic labels of its correlated
words. Similar words have a better chance to be put into the same topic
due to the regularization of the MRF, hence the coherence of topics can be
boosted. In addition, our model can accommodate the subtlety, in that
whether two words are similar depends on which topic they appear in, which
allows words with multiple senses to be properly put into different
topics. We derive a variational inference method to infer the posterior
probabilities and learn model parameters, and present techniques to deal
with the hard-to-compute partition function in the MRF. Experiments on two
datasets demonstrate the effectiveness of our model.


Speaker Bio:
Pengtao Xie is a graduate student in the Language Technologies Institute,
working with Professor Eric Xing. His primary research interests lie in
latent variable models and large scale distributed machine learning. He
received a M.E. from Tsinghua University in 2013 and a B.E. from Sichuan
University in 2010. He is the recipient of Siebel Scholarship, Goldman
Sachs Global Leader Scholarship and National Scholarship of China.


-- 
Dallas Card
Machine Learning Department
Carnegie Mellon University