Method for Social Network User Feature Recognition Based on Clique
HU Kaixian1,2, LIANG Ying1, SU Lixin1,2, XU Hongbo1, FU Chuan1
1.Key Laboratory of Web Data Science and Technology, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190 2.University of Chinese Academy of Sciences, Beijing 100049
Abstract:Social network is a major media for people to get different information and make friends. As the social network keeps developing, it brings convenience to people but meanwhile identifying user identity becomes difficult. To solve this problem, a method for social network user feature recognition based on clique is proposed. According to three degrees of influence rule, the inference model is built, and through the analysis of the clique consisting of user attributes in the social network topology structure, the unknown identity of the current user is inferred. Identity feature recognition methods based on clique are put forward. They are the current user included clique identity recognition method and the multi-degree passing clique identity recognition method. In both methods,the adjacent matrix of social network topology graph of current three-degree friends of user is used to infer the unknown identity of current user via major voting scheme. By the proposed method, the problem of unstable user feature recognition caused by the lack of social relationship is effectively solved. The experimental result shows the good precision of the proposed method.
胡开先,梁英,苏立新,许洪波,傅川. 基于完全子图的社交网络用户特征识别方法*[J]. 模式识别与人工智能, 2016, 29(8): 698-708.
HU Kaixian, LIANG Ying, SU Lixin, XU Hongbo, FU Chuan. Method for Social Network User Feature Recognition Based on Clique. , 2016, 29(8): 698-708.
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