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Rough Set Based Decision Model in Information Retrieval and Filtering

机译:基于粗糙集的决策模型在信息检索和过滤中

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In this paper, a model for information retrieval and filtering applications is proposed. The model uses rough set based decision approaches to deal with the relevance between users' queries and documents. In this model, the users' queries are described into two levels: the interesting categories, and the relevant terms about the interesting categories. By using the rough set based decision theory, the dynamic document stream is divided into three states - the positive region, the boundary regions, and the negative regions, instead of the two states in the traditional research which are relevant documents and irrelevant documents.
机译:本文提出了一种用于信息检索和过滤应用的模型。该模型使用基于粗糙的决策方法来处理用户查询和文档之间的相关性。在此模型中,用户查询将被描述为两个级别:有趣的类别,以及关于有趣类别的相关条款。通过使用基于粗糙集的决策理论,动态文档流被分成三个状态 - 正区域,边界区域和负区域,而不是传统研究中的两个状态,这是相关文件和无关的文件。

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