In the information age, online collaboration and social networks are of increasing importance and quickly becoming an integral part of our lifestyle. In business, social networking...
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...
We propose a new class of spatio-temporal cluster detection methods designed for the rapid detection of emerging space-time clusters. We focus on the motivating application of pro...
Daniel B. Neill, Andrew W. Moore, Maheshkumar Sabh...
This paper presents a hybrid approach to detect source-code clones that combines evolutionary algorithms and clustering. A case-study is conducted on a small C++ code base. The pr...
Andrew Sutton, Huzefa H. Kagdi, Jonathan I. Maleti...
Abstract. In this paper we show how approximate matrix factorisations can be used to organise document summaries returned by a search engine into meaningful thematic categories. We...