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Application of Maximum Entropy Method in Chinese-English Cross Language Information Retrieval

机译:最大熵法在汉英跨语言信息检索中的应用

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摘要

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.
机译:在诸如汉英信息检索的跨语言信息检索中,查询语句通常包含一些查询关键字,但不包括完整的句子。由于查询关键字缺少必要的上下文和句法信息,因此很难翻译准确地查询句子并返回最适合查询的结果。因此,在汉英跨语言信息检索中,如何获得有效的网页并评估翻译候选是两个具有挑战性的问题。本文提出了一种基于方法的最大熵方法(MEM)来获得有效的网页。为了获得正确的翻译清单,我们建立了英汉,汉英专用词典。因此,通过基于MEM的双向歧义翻译,可以尽可能准确地翻译查询。实验结果表明,该方法在汉英跨语言信息检索中具有良好的性能,准确率达到86.8%。

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