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TV program recommendation for multiple viewers based on user profile merging

机译:根据用户个人资料合并为多个观众推荐的电视节目

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Since today's television can receive more and more programs, and televisions are often viewed by groups of people, such as a family or a student dormitory, this paper proposes a TV program recommendation strategy for multiple viewers based on user profile merging. This paper first introduces three alternative strategies to achieve program recommendation for multiple television viewers, discusses, and analyzes their advantages and disadvantages respectively, and then chooses the strategy based on user profile merging as our solution. The selected strategy first merges all user profiles to construct a common user profile, and then uses a recommendation approach to generate a common program recommendation list for the group according to the merged user profile. This paper then describes in detail the user profile merging scheme, the key technology of the strategy, which is based on total distance minimization. The evaluation results proved that the merging result can appropriately reflect the preferences of the majority of members within the group, and the proposed recommendation strategy is effective for multiple viewers watching TV together.
机译:由于当今的电视可以接收越来越多的节目,并且电视经常被诸如家庭或学生宿舍之类的人群观看,因此本文提出了一种基于用户配置文件合并的针对多个观众的电视节目推荐策略。本文首先介绍了三种可供选择的策略,以实现针对多个电视观众的节目推荐,分别讨论和分析它们的优缺点,然后选择基于用户档案合并的策略作为我们的解决方案。所选策略首先合并所有用户配置文件以构建公共用户配置文件,然后使用推荐方法根据合并后的用户配置文件为该组生成公共节目推荐列表。然后,本文详细介绍了基于总距离最小化的用户配置文件合并方案,该策略的关键技术。评估结果证明,合并后的结果可以恰当地反映该组中大多数成员的偏好,并且所提出的推荐策略对于多个观众一起看电视是有效的。

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