Centroid-based summarization of multiple documents: sentence extraction,   utility-based evaluation, and user studies
  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. 
Dragomir R. Radev (University of Michigan), Hongyan Jing (Columbia   University), Malgorzata Budzikowska (IBM TJ Watson Rese...