Date of Original Version

4-2011

Type

Conference Proceeding

Rights Management

Copyright 2011 by the authors

Abstract or Description

We present the time-dependent topic-cluster model, a hierarchical approach for combining Latent Dirichlet Allocation and clustering via the Recurrent Chinese Restaurant Process. It inherits the advantages of both of its constituents, namely interpretability and concise representation. We show how it can be applied to streaming collections of objects such as real world feeds in a news portal. We provide details of a parallel Sequential Monte Carlo algorithm to perform inference in the resulting graphical model which scales to hundred of thousands of documents.

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Published In

Journal of Machine Learning Research : Workshop and Conference Proceedings, 15, 101-109.