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Automatic Query Translation Disambiguation Using Bilingual Proximity-Based Approach

  • Wiem Ben Romdhane
  • Bilel ElayebEmail author
  • Narjès Bellamine Ben Saoud
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11231)

Abstract

In this paper, we propose a new automatic query translation disambiguation using bilingual proximity-based approach. This approach combines a traditional bilingual dictionary and parallel bilingual corpus to build a bilingual semantic dictionary of contexts (BSDC) and identify the suitable translation of a word using a proximity matching model. Besides, it uses and extends an existing probabilistic semantic distance to compute similarities between words using a bilingual semantic graph of the traditional bilingual dictionary and the BSDC. We experiment and compare this approach using the French-English parallel text corpus Europarl and the CLEF-2003 French-English CLIR test collection. Our experiments highlighted the performance of our bilingual proximity-based approach compared to both the known efficient probabilistic and the possibilistic ones, for both long and short queries and using different assessment metrics.

Keywords

Cross-language information retrieval (CLIR) Query translation disambiguation Bilingual semantic dictionary of contexts Probabilistic model Possibilistic model Proximity 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Wiem Ben Romdhane
    • 1
  • Bilel Elayeb
    • 1
    • 2
    Email author
  • Narjès Bellamine Ben Saoud
    • 1
  1. 1.RIADI Research LaboratoryENSI, Manouba UniversityManoubaTunisia
  2. 2.Emirates College of TechnologyAbu DhabiUnited Arab Emirates

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