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Enhancing cross-language information retrieval by an automatic acquisition of bilingual terminology from comparable corpora
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval table of contents
Toronto, Canada
POSTER SESSION: Posters table of contents
Pages: 397 - 398  
Year of Publication: 2003
ISBN:1-58113-646-3
Authors
Fatiha Sadat  Nara Institute of Science and Technology, Ikoma, Nara, Japan
Masatoshi Yoshikawa  Nagoya University, Furo-cho, Chikusa-ku, Nagoya, Japan
Shunsuke Uemura  Nara Institute of Science and Technology, Ikoma, Nara, Japan
Sponsor
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
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ABSTRACT

This paper presents an approach to bilingual lexicon extraction from comparable corpora and evaluations on Cross-Language Information Retrieval. We explore a bi-directional extraction of bilingual terminology primarily from comparable corpora. A combined statistics-based and linguistics-based model to select best translation candidates to phrasal translation is proposed. Evaluations using a large test collection for Japanese-English revealed the proposed combination of bi-directional comparable corpora, bilingual dictionaries and transliteration, augmented with linguistics-based pruning to be highly effective in Cross-Language Information Retrieval.




Collaborative Colleagues:
Fatiha Sadat: colleagues
Masatoshi Yoshikawa: colleagues
Shunsuke Uemura: colleagues

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