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Improving Bilingual Lexicon Extraction from Comparable Corpora Using Window-Based and Syntax-Based Models

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Computational Linguistics and Intelligent Text Processing (CICLing 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8404))

Abstract

This paper proposes two strategies for combining a window-based and a syntax-based context representation for the task of bilingual lexicon extraction from comparable corpora. The first strategy involves combining the scores assigned to translations by both models and using them for ranking and selection; the second strategy involves a combination of the context features provided by the two models prior to applying the lexicon extraction method. The reported results show that the combination of the two context representations significantly improves the performance of bilingual lexicon extraction compared to using each of the representations individually.

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Authors and Affiliations

  1. Laboratoire d’Informatique de Nantes-Atlantique (LINA), Université de Nantes, 44322, Nantes Cedex 3, France

    Amir Hazem & Emmanuel Morin

Authors
  1. Amir Hazem
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  2. Emmanuel Morin
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Editors and Affiliations

  1. Center for Computing Research, National Polytechnic Institute, Av. Juan Dios Bátiz, Col. Nueva Industrial Vallejo, 07738, Mexico D.F, Mexico

    Alexander Gelbukh

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Hazem, A., Morin, E. (2014). Improving Bilingual Lexicon Extraction from Comparable Corpora Using Window-Based and Syntax-Based Models. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2014. Lecture Notes in Computer Science, vol 8404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54903-8_26

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  • DOI: https://doi.org/10.1007/978-3-642-54903-8_26

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54902-1

  • Online ISBN: 978-3-642-54903-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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