Towards genre classification for IR in the workplace

Authors:
Luanne Freund;Charles L. A. Clarke;Elaine G. Toms
Affiliations:
University of Toronto, Canada;University of Waterloo, Canada;Dalhousie University, Canada
Venue:
IIiX Proceedings of the 1st international conference on Information interaction in context
Year:
2006

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Abstract

Use of document genre in information retrieval systems has the potential to improve the task-appropriateness of results. However, genre classification remains a challenging problem. We describe a case study of genre classification in a software engineering workplace domain, which includes the development of a genre taxonomy and experiments in automatic genre classification using supervised machine learning. We present results based on evaluation using real-life enterprise data from this work domain.