近年來由於快速的資訊流通與資訊分享的便利性，使得網路上的資訊過載現象產生，因此要如何從大量的資料中取得使用者所需的知識是相當重要的，資訊檢索系統(Information Retrieval System)可幫助使用者找尋到和查詢字詞相同語言的資料，但是對於跨語言文件的搜尋結果不佳。而在目前全球化的環境中，當使用者想要了解非母語的字詞與文件時，經常需要搜尋跨語言的文件來取得母語相關的資訊來協助使用者跨越閱讀障礙問題，因此需建立跨語言資訊檢索(Cross-Language Information Retrieval, CLIR)系統來幫助使用者搜尋相關的跨語文件。
目前的研究指出查詢翻譯(Query Translation)以及查詢擴張(Query Expansion)可用來提高CLIR系統的檢索準確率，但是查詢字詞的歧義性以及越來越多的OOV(Out-of-vocabulary)字詞容易導致翻譯的錯誤，過去研究指出應用網路資源翻譯查詢字詞在OOV字詞上表現良好，但在一般字詞上成效較差，對此本研究以雙語語料庫以及Google搜尋結果和維基百科的資料來擷取正確的查詢字詞翻譯，降低字詞歧義性的問題並取得OOV字詞的翻譯，另外用Google搜尋結果以及維基百科的資料取得與查詢(Source Query)相關的字詞做為擴張字詞，用來提高CLIR的檢索效能，本研究的方法以NTCIR-8的文件集做測試，其結果顯示本研究的方法能有效的提高檢索準確率。

In recent years, due to the fast information flow and convenience of information sharing, information overload happens. How to obtain the information required by users from large amounts of data becomes important. Information retrieval systems perform well in monolingual information retrieval, but not in cross-language information retrieval. In current globalized environment, when the users intend to understand non-native words or files, they often need to search for cross-language documents to obtain native related information assisting users across dyslexia problems. Therefore, it is necessary to establish cross-language information retrieval(CLIR) systems to help users search for relevant cross-language document.
The present study indicates tjar query translation and query expansion can be used to improve the retrieval accuracy of CLIR. However, the ambiguity of query terms as well as more and more out-of vocabulary(OOV) terms easily lead to translation errors. Cheng et al. (2004) apply network resources to translate query terms, and perform well in OOV terms, but not in general terms. Therefore, this study uses bilingual corpus, Google search results and Wikipedia to extract correct query translation terms in order to reduce word ambiguity problems and thus obtain translation of OOV terms. In addition, in order to improve the performance of CLIR this study uses Google search results and Wikipedia to obtain expansion terms related to query terms. This study ways to NTCIR-8 dataset to do the test, the results show that this method can effectively improve the retrieval accuracy.

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