Paul N. Bennett

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Researcher, Context, Learning, and User Experience for Search, Microsoft Research

E-mail: paul.n.bennett@microsoft.com
Mail: One Microsoft Way, Redmond WA 98052-6399, USA

Research Activities:

I am interested in the development, improvement, and analysis of machine learning methods with a focus on systems that can aid in the automatic analysis of natural language as components of adaptive systems or information retrieval systems. My current focus is on hierarchical and large-scale classification, search query classification and characterization, classification-aided IR ranking, diversity in retrieval results, preferences, and data mining via human computation applications.

My past work has examined a variety of areas — primarily text learning, ensemble methods, active learning, and obtaining reliable probability estimates, but also extending to machine translation, recommender systems, and knowledge bases.

Before coming to Microsoft, I obtained my Ph.D. from the Computer Science Department at Carnegie Mellon under Jaime Carbonell and John Lafferty.   Prior to that I worked closely with Ray Mooney and Robert Causey during my undergraduate days in the Computer Science, Philosophy, and Plan II Honors departments at the University of Texas at Austin.

I'm co-orgainzing a SIGIR 2009 Workshop on Redundancy, Diversity, and Interdependent Document Relevance.

Workshops, Collaborations and Papers:

Tutorials:

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Other Activities:

Last Updated: 7/8/2009