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A Method of User Modeling and Relevance Simulation in Document Retrieval Systems

机译:文档检索系统中的用户建模和相关性仿真方法

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摘要

Modeling users' information interests and needs is one of the most important task in the personalization of information retrieval domain. Search engines' algorithms are constantly improved but they still return a lot of irrelevant documents. For this reason a user is not able to quickly find a document with necessary information. In this paper we propose a user profile that is updated based on novel relevance judgment method. Proposed algorithms are a part of personalization agent system. As performed experimental evaluations have shown, the distance between current user profile and user preferences is decreasing when our algorithm is applied.
机译:对用户的信息兴趣和需求进行建模是信息检索域个性化中最重要的任务之一。搜索引擎的算法在不断改进,但是它们仍然返回许多不相关的文档。因此,用户无法快速找到带有必要信息的文档。在本文中,我们提出了一种基于新颖的相关性判断方法进行更新的用户个人资料。提出的算法是个性化代理系统的一部分。如进行的实验评估所示,当应用我们的算法时,当前用户配置文件和用户偏好之间的距离正在减小。

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