NewsInEssence: a system for domain-independent, real-time news clustering and multi-document summarization

  • Authors:
  • Dragomir R. Radev;Sasha Blair-Goldensohn;Zhu Zhang;Revathi Sundara Raghavan

  • Affiliations:
  • School of Information;School of Information;School of Information;University of Michigan, Ann Arbor, MI

  • Venue:
  • HLT '01 Proceedings of the first international conference on Human language technology research
  • Year:
  • 2001

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Abstract

NEWSINESSENCE is a system for finding, visualizing and summarizing a topic-based cluster of news stories. In the generic scenario for NEWSINESSENCE, a user selects a single news story from a news Web site. Our system then searches other live sources of news for other stories related to the same event and produces summaries of a subset of the stories that it finds, according to parameters specified by the user.