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中文摘要：
针对信息过滤反馈中充斥噪声的缺陷，提出一种基于二元近似关系分布（distribution of two-dimen sionsimilarity,简称DTs）的过滤策略．DTS根据噪声和用户模型的相悖关系，为信息流建立二元近似关系模型．同时，根据信息在二维近似关系空间中的分布，采用基于LMS（least mean square）分类器的AdaBoost算法建立噪声和相关信息的分类曲线，从而辅助信息过滤系统识别和屏蔽反馈中的噪声．通过实验验证，该算法显著提高了过滤系统屏蔽噪声的能力．
英文摘要：
This paper investigates the reasons for generation of noises in feedbacks of filtering system by analyzing the knowledge expressions and text structures, and builds a two-dimension similarity （DTS） model of information based on the opposed relation between the noises and user profiles. At the same time, by using the algorithm of AdaBoost based on the LMS （least mean square） classifier, this paper builds a classification curve between the noises and related information according to their distribution in two-dimension similarity space, which helps information filtering system detect and filter the noises in feedback. Experiments validated this algorithm substantially improved the capability of filtering system to rule out the noises.
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A new query expansion approach using collocation relationships in language models for information re
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