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Combining bidirectional translation and synonymy for cross-language information retrieval

Published:06 August 2006Publication History

ABSTRACT

This paper introduces a general framework for the use of translation probabilities in cross-language information retrieval based on the notion that information retrieval fundamentally requires matching what the searcher means with what the author of a document meant. That perspective yields a computational formulation that provides a natural way of combining what have been known as query and document translation. Two well-recognized techniques are shown to be a special case of this model under restrictive assumptions. Cross-language search results are reported that are statistically indistinguishable from strong monolingual baselines for both French and Chinese documents.

References

  1. M. Boughanem, C. Chrisment, and N. Nassr. Investigation on disambiguation in CLIR: Aligned corpus and bi-directional translation-based strategies. In Evaluation of Cross-Language Information Retrieval Systems: Second Workshop of the Cross-Language Evaluation Forum, pages 158--167. Springer-Verlag GmbH, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Martin Braschler. Combination approaches for multilingual text retrieval. Information Retrieval, 7(1-2):183--204, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. David Chiang, Adam Lopez, Nitin Madnani, Christof Monz, Philip Resnik, and Michael Subotin. The hiero machine translation system: Extensions, evaluation, and analysis. In Proceedings of HLT/EMNLP 2005, pages 779--786, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Kareem Darwish and Douglas W. Oard. Probabilistic structured query methods. In Proceedings of the 21st Annual 26th International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 338--344. ACM Press, July 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. In-Su Kang, Seung-Hoon Na, and Jong-Hyeok Lee. POSTECH at NTCIR -4: CJKE monolingual and K orean-related cross-language retrieval experiments. In Working Notes of the 4th NTCIR Workshop. National Institute of Informatics, 2004. http://research.nii.ac.jp/ntcir/index--en.html.Google ScholarGoogle Scholar
  6. Philipp Koehn. Europarl: A multilingual corpus for evaluation of machine translation. unpublished draft. 2002.Google ScholarGoogle Scholar
  7. Wessel Kraaij. Variations on Language Modeling on Information Retrieval. P h. D. thesis, University of Twente, 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. K. L. Kwok. Exploiting a chinese-english bilingual wordlist for english-chinese cross language information retrieval. In Proceedings of the 5th International Workshop on Information Retrieval with Asian languages, pages 173--179, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Victor Lavrenko and W. Bruce Croft. Relevance-based language models. In Proceedings of the 24th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 120--127. ACM Press, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Gina-Anne Levow and Douglas W. Oard. Evaluating lexical coverage for cross-language information retrieval. In Workshop on Multilingual Information Processing and Asian Language Processing, pages 69--74, February 2000.Google ScholarGoogle Scholar
  11. J. Scott McCarley. Should we translate the documents or the queries in cross-language information retrieval? In Proceedings of the 37th Annual Conference of the Association for Computational Linguistics, pages 208--214, 1999. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Douglas W. Oard and Funda Ertunc. Translation-based indexing for cross-language retrieval. In Proceedings of ECIR'02, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. F. J. Och and H. Ney. Improved statistical alignment models. In Proceedings of the 38th Annual Conference of the Association for Computational Linguistics, pages 440--447, October 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. Franz Josef Och and Hermann Ney. The alignment template approach to statistical machine translation. Computational Linguistics, 30(4), 2004. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. Ari Pirkola. The effects of query structure and dictionary setups in dictionary-based cross-language information retrieval. In Proceedings of the 21st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pages 55--63. ACM Press, August 1998. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. Philip Resnik and David Yarowsky. Distinguishing systems and distinguishing senses: New evaluation methods for word sense disambiguation. Natural Language Engineering, 5(2):113--133, 2000. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. S. E. Robertson and Karen Sparck-Jones. Simple proven approaches to text retrieval. Cambridge University Computer Laboratory, 1997.Google ScholarGoogle Scholar
  18. Jacques Savoy. Report on CLEF -2001 experiments: Effective combined query-translation approach. In Evaluation of Cross-Language Information Retrieval Systems: Second Workshop of the Cross-Language Evaluation Forum. Springer-Verlag GmbH, 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Jianqiang Wang. Matching Meaning for Cross-Language Information Retrieval. Ph.D. thesis, University of Maryland, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Jinxi Xu and Ralph Weischedel. TREC -9 cross-lingual retrieval at BBN. In The Nineth Text RE trieval Conference. National Institutes of Standards and Technology, November 2000. http://trec.nist.gov.Google ScholarGoogle Scholar

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      cover image ACM Conferences
      SIGIR '06: Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
      August 2006
      768 pages
      ISBN:1595933697
      DOI:10.1145/1148170

      Copyright © 2006 ACM

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      Publication History

      • Published: 6 August 2006

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