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首页> 外文期刊>Journal of intelligent & fuzzy systems: Applications in Engineering and Technology >A method for updating ontology-based user profile in Personalized Document Retrieval System using Bayesian networks
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A method for updating ontology-based user profile in Personalized Document Retrieval System using Bayesian networks

机译:一种使用Bayesian网络更新个性化文档检索系统中基于本体的用户配置文件的方法

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Traditional approaches to content-based recommendation and collaborative filtering do not suffer from cold-start problem, which is a challenge to recommend items for an unknown user. In this paper we present a Personalized Document Retrieval System which takes into account a social network information about the users. The overall idea of the system is to cluster users into groups of similar interests based on theirs usage data and to determine a representative profile for each of the groups. When a new user joins the system, he or she is classified into one of existing group based on his or her user data and the representative profile of the group becomes a starting profile for the new user. This paper focuses on a method for updating ontology-based user profile using Bayesian network approach. We analyze some properties of proposed updating method and describe an idea of experimental evaluations.
机译:基于内容的建议和协作过滤的传统方法不会遭受冷启动问题,这是为未知用户推荐项目的挑战。 在本文中,我们介绍了一个个性化文档检索系统,该系统考虑了有关用户的社交网络信息。 该系统的整体思想是基于其使用数据将用户组成类似兴趣组,并确定每个组的代表性配置文件。 当新用户加入系统时,他或她根据他或她的用户数据分为现有组之一,并且该组的代表性配置文件成为新用户的起始配置文件。 本文侧重于使用贝叶斯网络方法更新基于本体的用户配置文件的方法。 我们分析了建议更新方法的一些性质,并描述了实验评估的思想。

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