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We 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.
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Dragomir Radev
University of Geneva
Hongyan Jing
Nanjing Normal University
Malgorzata Budzikowska
IBM (United States)
University of Michigan
Columbia University
IBM (United States)
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Radev et al. (Sat,) studied this question.
synapsesocial.com/papers/6a1bd543ea84844e355f0c5a — DOI: https://doi.org/10.3115/1117575.1117578