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Movie Recommendation System Using Social Network Analysis and k-Nearest Neighbor

机译:电影推荐系统使用社交网络分析和k最近邻居

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Many types of research have been conducted in recommendation system to develop approaches to solve the challenges for collaborative filtering problem such as cold start problem; in this paper, we proposed the approach to solving the problem of collaborative by using social network analysis and k-nearest neighbor (k-NN). We used the centrality of social network to detect the community or cluster group to the user, and then apply the k-NN method to find a group for new users with similar personal information such as age, gender, and occupation after that recommendation system will recommend items that users in the group were previously interested for the new.
机译:在推荐系统中进行了许多研究,以开发解决诸如冷启动问题等协作过滤问题的挑战的方法;在本文中,我们提出了通过使用社交网络分析和k最近邻(K-Nn)来解决协作问题的方法。我们使用社交网络的中心地区来检测到用户的社区或群集组,然后应用K-NN方法,为新用户寻找一个具有类似个人信息的组,例如年龄,性别和职业,在该建议系统之后推荐本集团用户的项目以前对新的新感兴趣。

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