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.
- 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 ScholarDigital Library
- Martin Braschler. Combination approaches for multilingual text retrieval. Information Retrieval, 7(1-2):183--204, 2004. Google ScholarDigital Library
- 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 ScholarDigital Library
- 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 ScholarDigital Library
- 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 Scholar
- Philipp Koehn. Europarl: A multilingual corpus for evaluation of machine translation. unpublished draft. 2002.Google Scholar
- Wessel Kraaij. Variations on Language Modeling on Information Retrieval. P h. D. thesis, University of Twente, 2004. Google ScholarDigital Library
- 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 ScholarDigital Library
- 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 ScholarDigital Library
- 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 Scholar
- 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 ScholarDigital Library
- Douglas W. Oard and Funda Ertunc. Translation-based indexing for cross-language retrieval. In Proceedings of ECIR'02, 2002. Google ScholarDigital Library
- 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 ScholarDigital Library
- Franz Josef Och and Hermann Ney. The alignment template approach to statistical machine translation. Computational Linguistics, 30(4), 2004. Google ScholarDigital Library
- 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 ScholarDigital Library
- 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 ScholarDigital Library
- S. E. Robertson and Karen Sparck-Jones. Simple proven approaches to text retrieval. Cambridge University Computer Laboratory, 1997.Google Scholar
- 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 ScholarDigital Library
- Jianqiang Wang. Matching Meaning for Cross-Language Information Retrieval. Ph.D. thesis, University of Maryland, 2005. Google ScholarDigital Library
- 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 Scholar
Index Terms
- Combining bidirectional translation and synonymy for cross-language information retrieval
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