Mining translations of OOV terms from the web through cross-lingual query expansion

  • Authors:
  • Ying Zhang;Fei Huang;Stephan Vogel

  • Affiliations:
  • Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA;Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
  • Year:
  • 2005

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Abstract

Translating out-of-vocabulary (OOV) terms is a great challenge for the Cross-lingual Information Retrieval and Data-driven Machine Translation systems. Several approaches have been proposed to mine translations for OOV terms from the web, especially from pages containing mixed languages. In this paper, we propose a novel approach to automatically translate OOV terms on the fly through cross-lingual query expansion. The proposed approach does not require any web crawling and has achieved an inclusion rate of 95% and overall translation accuracy of 90%, outperforming state-of-the-art OOV translation techniques.