The automated acquisition of topic signatures for text summarization

  • Authors:
  • Chin-Yew Lin;Eduard Hovy

  • Affiliations:
  • University of Southern California, Marina del Rey, CA;University of Southern California, Marina del Rey, CA

  • Venue:
  • COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
  • Year:
  • 2000

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Abstract

In order to produce a good summary, one has to identify the most relevant portions of a given text. We describe in this paper a method for automatically training topic signatures-sets of related words, with associated weights, organized around head topics and illustrate with signatures we created with 6,194 TREC collection texts over 4 selected topics. We describe the possible integration of topic signatures with outologies and its evaluaton on an automated text summarization system.