User-Dependent Multi-relational Community Detection in Social Networks

摘要：

　　Multi-relational community detection is a very important task in social network analysis because in the real world social networks are mostly multi-relational.In this paper,we propose a user-dependent method to detect communities in multi-relational social networks.We define a multi-relational community as a shared community over multiple single-relational graphs while the quality of a partitioning of nodes is assessed by a multi-relational modularity,and we design a desirable set of communities to represent the requests of users and use Normalized mutual information (NMI) between the desirable set of communities and the sets of communities detected in each single-relational graph as the weights for measuring the importance of all kinds of relationship types.We then use a greedy agglomerative manner to identify communities.Experiments have been conducted on synthetic networks to evaluate the effectiveness of the proposed approach.

关键词： Multi-relational social network Community detection Multi-relational modularity

作者: Peizhong Yang Lihua Zhou Hongmei Chen

作者单位: School of Information,Yunnan University,Kunming 650091,China

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 152-163

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）