We describe a joint probabilistic model for modeling the contents and inter-connectivity of document collections such as sets of web pages or research paper archives. The model is...
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian m...
Relevance-based language models operate by estimating the probabilities of observing words in documents relevant (or pseudo relevant) to a topic. However, these models assume that ...
In this paper we propose the multirelational topic model (MRTM) for multiple types of link modeling such as citation and coauthor links in document networks. In the citation networ...
Jia Zeng, William K. Cheung, Chun-hung Li, Jiming ...
Topic models such as Latent Dirichlet Allocation (LDA) and Correlated Topic Model (CTM) have recently emerged as powerful statistical tools for text document modeling. In this pap...
Duangmanee Putthividhya, Hagai Thomas Attias, Srik...