Centroid-based summarization of multiple documents

Authors:
Dragomir R. Radev;Hongyan Jing;Małgorzata Styś;Daniel Tam
Affiliations:
University of Michigan, Ann Arbor, MI;IBM T.J. Watson Research Center, Yorktown Heights, NY;IBM T.J. Watson Research Center, Yorktown Heights, NY;University of Michigan, Ann Arbor, MI
Venue:
Information Processing and Management: an International Journal
Year:
2004

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Abstract

We present a multi-document summarizer, MEAD, which generates summaries using cluster centroids produced by a topic detection and tracking system. We describe two new techniques, a centroid-based summarizer, and an evaluation scheme based on sentence utility and subsumption. We have applied this evaluation to both single and multiple document summaries. Finally, we describe two user studies that test our models of multi-document summarization.