Identifying topics by position

  • Authors:
  • Chin-Yew Lin;Eduard Hovy

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

  • Venue:
  • ANLC '97 Proceedings of the fifth conference on Applied natural language processing
  • Year:
  • 1997

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Abstract

This paper addresses the problem of identifying likely topics of texts by their position in the text. It describes the automated training and evaluation of an Optimal Position Policy, a method of locating the likely positions of topic-bearing sentences based on genre-specific regularities of discourse structure. This method can be used in applications such as information retrieval, routing, and text summarization.