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Two-level MicroBlog Friend Recommendation Based on Topic Model
Received date: 2014-04-08
Revised date: 2014-04-20
Online published: 2014-05-05
With users' explosive growth in the social network, it is more and more difficult for them to find potential friends of similar interests. In order to effectively solve the above problem, this paper proposes to recommend like-minded friends for social network users respectively from two dimensions of social relations and contents based on the theories of Homogeneity and Triadic closure. The paper models interested topics for Sina MicroBlog users by using extended LDA model-UserLDA, and calculates the users' similarity through user-topic probability distribution matrix, to recommend TopN two-level friend. Through the experiments on real weibo corpus, the result shows that the recommendation algorithm has better accuracy and diversity.
Key words： UserLDA; two-level friends; TF-IDF; JS distance; Sina MicroBlog
Tang Xiaobo , Zhu Li , Xie Li . Two-level MicroBlog Friend Recommendation Based on Topic Model[J]. Library and Information Service, 2014 , 58(09) : 105 -113 . DOI: 10.13266/j.issn.0252-3116.2014.09.015
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