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In cross language information retrieval, such as Chinese-English information retrieval, the query sentence often comprises some query keywords, but not a complete sentence. Because of the lack of necessary context and syntactic information in the query keywords, it is difficult to translate the query sentence accurately and return the results which are the best fit to the query. So, in Chinese-English cross language information retrieval, how to obtain effective Web pages and evaluate translation candidates are two challenging issues. In this paper, an approach based maximum entropy method (MEM) is proposed to obtain effective Web pages. For obtaining a correct translation list, we establish English-Chinese, Chinese - English special dictionary. Thus we can translate the query as accurately as possible by using bi-directional translation with disambiguation based on MEM. Experimental results demonstrate that the proposed method has a good performance in Chinese-English cross language information retrieval, and achieves 86.8% accuracy.
In cross language information retrieval, such as Chinese-English information retrieval, the query sentence often comprises some query keywords, but not a complete sentence. Because of the lack of necessary context and syntactic information in the query keywords, it is difficult to translate the query sentence accurately and return the results which are the best fit to the query. So, in Chinese-English cross language information retrieval, how to obtain effective Web pages and evaluate translation candidates are two challenging issues. In this paper, an approach based maximum entropy method (MEM) is proposed to obtain effective Web pages. For obtaining a correct translation list, we establish English-Chinese, Chinese - English special dictionary. Thus we can translate the query as accurately as possible by using bi-directional translation with disambiguation based on MEM. Experimental results demonstrate that the proposed method has a good performance in Chinese-English cross language information retrieval, and achieves 86.8% accuracy.
Application of maximum entropy method in Chinese-English cross language information retrieval
2008-11-01
1884253 byte
Conference paper
Electronic Resource
English
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