We consider the use of Bayesian topic models in the analysis of computer network traffic. Our approach utilizes latent Dirichlet allocation and time-varying dynamic latent Dirich...
Topical noise in blogs arises when bloggers digress from the central topical thrust of their blogs. We introduce a method to explicitly incorporate a model of topical noise into a...
Topic models could have a huge impact on improving the ways users find and discover content in digital libraries and search interfaces, through their ability to automatically lea...
David Newman, Youn Noh, Edmund M. Talley, Sarvnaz ...
We propose a novel technique for semi-supervised image annotation which introduces a harmonic regularizer based on the graph Laplacian of the data into the probabilistic semantic ...
Yuanlong Shao, Yuan Zhou, Xiaofei He, Deng Cai, Hu...
Statistical topic models provide a general data-driven framework for automated discovery of high-level knowledge from large collections of text documents. While topic models can p...
Chaitanya Chemudugunta, Padhraic Smyth, Mark Steyv...