Centroid-based summarization of multiple documents

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 eva...

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Bibliographic Details
Published in:Information processing & management 2004-11, Vol.40 (6), p.919-938
Main Authors: Radev, Dragomir R., Jing, Hongyan, Styś, Małgorzata, Tam, Daniel
Format: Article
Language:English
Subjects:
Automatic abstracting
Automatic indexing
Automatic text analysis
Centroid-based summarization
Centroids
Cluster analysis
Cluster-based relative utility
Content analysis
Cross-sentence informational subsumption
Exact sciences and technology
Indexing. Classification. Abstracting. Syntheses
Information and communication sciences
Information and document structure and analysis
Information processing
Information processing and retrieval
Information science. Documentation
Multi-document summarization
Sciences and techniques of general use
Studies
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Description
Summary: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.
ISSN:0306-4573
1873-5371
DOI:10.1016/j.ipm.2003.10.006