Measuring the semantic similarity of texts

  • Authors:
  • Courtney Corley;Rada Mihalcea

  • Affiliations:
  • University of North Texas;University of North Texas

  • Venue:
  • EMSEE '05 Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment
  • Year:
  • 2005

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Abstract

This paper presents a knowledge-based method for measuring the semantic-similarity of texts. While there is a large body of previous work focused on finding the semantic similarity of concepts and words, the application of these word-oriented methods to text similarity has not been yet explored. In this paper, we introduce a method that combines word-to-word similarity metrics into a text-to-text metric, and we show that this method outperforms the traditional text similarity metrics based on lexical matching.