Centroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies

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dc.creatorRadev, Dragomir R.
dc.creatorJing, Hongyan
dc.creatorBudzikowska, Malgorzata
dc.date2000-05-12
dc.date.accessioned2026-07-25T16:27:13Z
dc.descriptionWe present a multi-document summarizer, called MEAD, which generates summaries using cluster centroids produced by a topic detection and tracking system. We also describe two new techniques, based on sentence utility and subsumption, which we have applied to the evaluation of both single and multiple document summaries. Finally, we describe two user studies that test our models of multi-document summarization.
dc.description10 pages Corpus availability at http://perun.si.umich.edu/~radev/mds
dc.identifierhttps://arxiv.org/abs/cs/0005020
dc.identifierhttp://arxiv.org/abs/cs/0005020
dc.identifierNAACL/ANLP Workshop on Automatic Summarization, Seattle, WA, April 30, 2000
dc.identifier.urihttps://dspace.dare.co.zw/handle/123456789/41472
dc.subjectComputation and Language
dc.subjectArtificial Intelligence
dc.subjectDigital Libraries
dc.subjectHuman-Computer Interaction
dc.subjectInformation Retrieval
dc.subjectH.3.1; H.3.4; H.3.7; H.5.2; I.2.7
dc.titleCentroid-based summarization of multiple documents: sentence extraction, utility-based evaluation, and user studies
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