Topic models provide a powerful tool for analyzing large text collections by representing high dimensional data in a low dimensional subspace. Fitting a topic model given a set of...
We propose a new unsupervised learning technique for extracting information from large text collections. We model documents as if they were generated by a two-stage stochastic pro...
Mark Steyvers, Padhraic Smyth, Michal Rosen-Zvi, T...
Biomedical ontologies provide a commonly accepted scheme for the characterization of biological concepts that enable knowledge sharing and integration. Updating and maintaining an ...
Mixture models form one of the most widely used classes of generative models for describing structured and clustered data. In this paper we develop a new approach for the analysis...
With the increase in information on the World Wide Web it has become difficult to quickly find desired information without using multiple queries or using a topic-specific search ...
Sofus A. Macskassy, Arunava Banerjee, Brian D. Dav...