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Graph-Based Profile Similarity Calculation Method and Evaluation

机译:基于图形的简档相似性计算方法和评估

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Collaborative Information Retrieval (CIR) is a new technique for resolving the current problem of information retrieval systems. A CIR system registers the previous user interactions to response to the subsequent user queries more efficiently. But, the goals and the characteristics of two users may be different; so when they send the same query to a CIR system, they may be interested in two different lists of documents. To resolve this problem, we have developed a personalized CIR system, called PERCIRS, which is based on the similarity between two user profiles. In this paper, we propose a new method for User Profile Similarity Calculation UPSC. Finally, we introduce a mechanism for evaluating UPSC methods.
机译:协作信息检索(CIR)是解决当前信息检索系统问题的新技术。 CIR系统将先前的用户交互登记以更有效地更有效地响应随后的用户查询。但是,两个用户的目标和特征可能不同;因此,当他们向CIR系统发送相同的查询时,他们可能对两种不同的文档列表感兴趣。为了解决这个问题,我们开发了一个名为Percir的个性化CIR系统,这是基于两个用户配置文件之间的相似性。在本文中,我们提出了一种用于用户简档相似性计算UPSC的新方法。最后,我们介绍了一种评估UPSC方法的机制。

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