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2009
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Topic-link LDA: joint models of topic and author community

9 years 2 months ago
Topic-link LDA: joint models of topic and author community
Given a large-scale linked document collection, such as a collection of blog posts or a research literature archive, there are two fundamental problems that have generated a lot of interest in the research community. One is to identify a set of high-level topics covered by the documents in the collection; the other is to uncover and analyze the social network of the authors of the documents. So far these problems have been viewed as separate problems and considered independently from each other. In this paper we argue that these two problems are in fact inter-dependent and should be addressed together. We develop a Bayesian hierarchical approach that performs topic modeling and author community discovery in one unified framework. The effectiveness of our model is demonstrated on two blog data sets in different domains and one research paper citation data from CiteSeer.
Yan Liu, Alexandru Niculescu-Mizil, Wojciech Gryc
Added 19 May 2010
Updated 19 May 2010
Type Conference
Year 2009
Where ICML
Authors Yan Liu, Alexandru Niculescu-Mizil, Wojciech Gryc
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