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A New Fuzzy Information Retrieval Method Based on Document Terms Reweighting Techniques

机译:基于文档词加权技术的模糊信息检索新方法

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In this paper, we present a new method for fuzzy information retrieval based on document terms reweighting techniques. The proposed method modifies the weights of document terms in document descriptor vectors based on the user's relevance feedback. After modifying the weights of terms in document descriptor vectors, the degrees of satisfaction of relevant documents with respect to the user's query will increase, and the degrees of satisfaction of irrelevant documents with respect to the user's query will decrease. Then, the modified document descriptor vectors can be used as personal profiles for future query processing. The proposed method can make fuzzy information retrieval systems more flexible and more intelligent to deal with documents retrieval. It can increase the retrieval effectiveness of the fuzzy information retrieval systems for document retrieval.
机译:在本文中,我们提出了一种基于文档词重加权技术的模糊信息检索新方法。所提出的方法基于用户的相关性反馈来修改文档描述符向量中文档术语的权重。在修改了文档描述符向量中的术语权重之后,相关文档对用户查询的满意度将增加,而无关文档对用户查询的满意度将降低。然后,修改后的文档描述符向量可以用作个人配置文件,以用于将来的查询处理。所提出的方法可以使模糊信息检索系统更灵活,更智能地处理文档检索。它可以提高用于文档检索的模糊信息检索系统的检索效率。

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