Combining query translation and document translation in cross-language retrieval

被引:0
|
作者
Chen, AT [1 ]
Gey, FC
机构
[1] Univ Calif Berkeley, Sch Informat Management & Syst, Berkeley, CA 94720 USA
[2] Univ Calif Berkeley, UC Data Arch & Tech Assistance, UC DATA, Berkeley, CA 94720 USA
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes monolingual, bilingual, and multilingual retrieval experiments using the CLEF 2003 test collection. The paper compares query translation-based multilingual retrieval with document translation-based multilingual retrieval where the documents are translated into the query language by translating the document words individually using machine translation systems or statistical translation lexicons derived from parallel texts. The multilingual retrieval results show that document translation-based retrieval is slightly better than the query translation-based retrieval on the CLEF 2003 test collection. Furthermore, combining query translation and document translation in multilingual retrieval achieves even better performance.
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页码:108 / 121
页数:14
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