文章基本信息

标题：Tag-Based Interest-Matching Users Discovery Approach in Online Social Network
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作者：Sheng Bin ; Gengxin Sun ; Peijian Zhang 等
期刊名称：International Journal of Hybrid Information Technology
印刷版ISSN：1738-9968
出版年度：2016
卷号：9
期号：5
页码：61-70
DOI：10.14257/ijhit.2016.9.5.06
出版社：SERSC
摘要：With the popularity of online social networks, such as Facebook, YouTube and Douban, have become a channel for fast information propagation and influence. The problem of discovering common interests shared by groups of users has become one of the central researches because it helps to connect users with common interests and can eventually influence as many users with common interests in the online social network as possible. Unfortunately, most of existing related works have only focused on the network topologies and so unable to identify the common interests of users who have no online connections. In an online social network, users tend to use descriptive tags to annotate the contents that they are interested in. User-generated tags are consistent with the content they are attached to. Thus, patterns of frequent co-occurrences of user tags can be used to characterize and capture topics of user interests. In this paper, we propose a novel common interests discovery approach based on user-generated tags to discover the set of interest-matching users whose interests are similar. The experiment results show that our approach can effectively discover user communities with common interests no matter if they have any online connections.
关键词：Keywords: Online social networks; tag; interest-matching; common interests