This paper describes a high performance sampling architecture for inference of latent topic models on a cluster of workstations. Our system is faster than previous work by over an...
This paper presents the Topic-Aspect Model (TAM), a Bayesian mixture model which jointly discovers topics and aspects. We broadly define an aspect of a document as a characteristi...
Intelligent access to information requires semantic integration of structured databases with unstructured textual resources. While the semantic integration problem has been widely...
Clustering layouts of software systems combine two important aspects: they reveal groups of related artifacts of the software system, and they produce a visualization of the resul...
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...