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- W2330806721 abstract "Social media applications have become the mainstream of Web application.User-oriented and content generated by users are pivotal characteristics of social media sites.Data sharing and recommendation approaches play an important role in dealing with the problem of information overload in social media environment.In this paper,we analyze the flaws of current group-based information sharing mechanism and the common problem of traditional recommender approaches,and then we propose a novel approach of group automatic generating for social media sharing and recommendation.Intuitively,the essential idea of our approach is that we switch user's preference from the media objects to the interest elements which media objects imply.Then we gather the users who have common preference,namely users have the same interestingness in a set of interest elements,together as Common Preference Group(CPG).We also propose a new social media data sharing and recommendation system architecture based on CPG and design a CPG automatic mining algorithm.By compare our CPG mining algorithm with other algorithm which has similar functionality,it is shown that our algorithm could be applicable to real social media application with massive users." @default.
- W2330806721 created "2016-06-24" @default.
- W2330806721 creator A5001711907 @default.
- W2330806721 date "2012-01-01" @default.
- W2330806721 modified "2023-09-25" @default.
- W2330806721 title "A User Preference Based Automatic Potential Group Generation Method for Social Media Sharing and Recommendation" @default.
- W2330806721 hasPublicationYear "2012" @default.
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