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Translating unknown queries with web corpora for cross-language information retrieval
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Source Annual ACM Conference on Research and Development in Information Retrieval archive
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval table of contents
Sheffield, United Kingdom
SESSION: Cross-language information retrieval table of contents
Pages: 146 - 153  
Year of Publication: 2004
ISBN:1-58113-881-4
Authors
Pu-Jen Cheng  Academia Sinica, Taiwan
Jei-Wen Teng  Academia Sinica, Taiwan
Ruei-Cheng Chen  Academia Sinica, Taiwan
Jenq-Haur Wang  Academia Sinica, Taiwan
Wen-Hsiang Lu  National Cheng Kung University, Taiwan
Lee-Feng Chien  Academia Sinica, Taiwan and National Taiwan University, Taiwan
Sponsors
ACM: Association for Computing Machinery
SIGIR: ACM Special Interest Group on Information Retrieval
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 14,   Downloads (12 Months): 95,   Citation Count: 21
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ABSTRACT

It is crucial for cross-language information retrieval (CLIR) systems to deal with the translation of unknown queries due to that real queries might be short. The purpose of this paper is to investigate the feasibility of exploiting the Web as the corpus source to translate unknown queries for CLIR. We propose an online translation approach to determine effective translations for unknown query terms via mining of bilingual search-result pages obtained from Web search engines. This approach can alleviate the problem of the lack of large bilingual corpora, translate many unknown query terms, provide flexible query specifications, and extract semantically-close translations to benefit CLIR tasks -- especially for cross-language Web search.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

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CITED BY  21

Collaborative Colleagues:
Pu-Jen Cheng: colleagues
Jei-Wen Teng: colleagues
Ruei-Cheng Chen: colleagues
Jenq-Haur Wang: colleagues
Wen-Hsiang Lu: colleagues
Lee-Feng Chien: colleagues