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Comparing Distributional and Mirror Translation Similarities for Extracting Synonyms

  • Philippe Muller
  • Philippe Langlais
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6657)

Abstract

Automated thesaurus construction by collecting relations between lexical items (synonyms, antonyms, etc) has a long tradition in natural language processing. This has been done by exploiting dictionary structures or distributional context regularities (coocurrence, syntactic associations, or translation equivalents), in order to define measures of lexical similarity or relatedness. Dyvik had proposed to use aligned multilingual corpora and defines similar terms as terms that often share their translations. We evaluate the usefulness of this similarity for the extraction of synonyms, compared to the more widespread distributional approach.

Keywords

Semantic Similarity Word Pair Lexical Item Mean Average Precision Candidate List 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Philippe Muller
    • 1
  • Philippe Langlais
    • 2
  1. 1.IRITUniv. Toulouse & Alpage, INRIAFrance
  2. 2.DIRO, Univ. MontréalCanada

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