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Cross Lingual Information Retrieval Using Data Mining Methods

机译:使用数据挖掘方法进行跨语言信息检索

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One of the challenges in cross lingual information retrieval is the retrieval of relevant information for a query expressed in a native language. While retrieval of relevant documents is slightly easier, analyzing the relevance of the retrieved documents and the presentation of the results to the users are non-trivial tasks. A method for information retrieval for a query expressed in a native language is presented in this paper. It uses insights from data mining and intelligent search for formulating the query and parsing the results. It also uses heuristic methods for the categorization of documents in terms of relevance. Our approach compliments the search engine's inbuilt methods for identifying and displaying the results of queries. A prototype has been developed for analyzing Tamil-English corpora. The initial results have shown that this approach is suitable for on the fly retrieval of documents.
机译:跨语言信息检索的挑战之一是检索以母语表达的查询的相关信息。尽管检索相关文档稍微容易一些,但是分析检索文档的相关性以及将结果呈现给用户并不是一件容易的事。本文提出了一种以本国语言表示的查询信息检索方法。它使用来自数据挖掘和智能搜索的见解来制定查询和解析结果。它还根据相关性使用启发式方法对文档进行分类。我们的方法补充了搜索引擎的内置方法,用于识别和显示查询结果。已经开发出用于分析泰米尔语-英语语料库的原型。初步结果表明,该方法适用于即时检索文档。

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