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.Comment: 10 pages Corpus availability at http://perun.si.umich.edu/~radev/md

Information Fusion in the Context of Multi-Document Summarization

We present a method to automatically generate a concise summary by identifying and synthesizing similar elements across related text from a set of multiple documents. Our approach is unique in its usage of language generation to reformulate the wording of the summary