A Ranking model of proximal and structural text retrieval based on region algebra

  • Authors:
  • Katsuya Masuda

  • Affiliations:
  • University of Tokyo, Bunkyo-ku, Tokyo, Japan

  • Venue:
  • ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 2
  • Year:
  • 2003

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Abstract

This paper investigates an application of the ranked region algebra to information retrieval from large scale but unannotated documents. We automatically annotated documents with document structure and semantic tags by using taggers, and retrieve information by specifying structure represented by tags and words using ranked region algebra. We report in detail what kind of data can be retrieved in the experiments by this approach.