A comparison of models of word meaning in context

  • Authors:

  • Georgiana Dinu;Stefan Thater;Sören Laue

  • Affiliations:

  • Universität des Saarlandes, Saarbrücken, Germany;Universität des Saarlandes, Saarbrücken, Germany;Friedrich-Schiller Universität, Jena, Germany

  • Venue:
  • NAACL HLT '12 Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Year:
  • 2012

  • Saarland: vector-based models of semantic textual similarity

    SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation

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Abstract

This paper compares a number of recently proposed models for computing context sensitive word similarity. We clarify the connections between these models, simplify their formulation and evaluate them in a unified setting. We show that the models are essentially equivalent if syntactic information is ignored, and that the substantial performance differences previously reported disappear to a large extent when these simplified variants are evaluated under identical conditions. Furthermore, our reformulation allows for the design of a straightforward and fast implementation.