Local Community Detection Algorithm Based on Links and Content
Community detection is an important field in research of social networks.There exist a lot of algorithms which most of them are based on the density of connections between groups of nodes.On the one hand, the error and lack of links may lead to great impact on the result of community detection.On the other hand,there are users with deep relation but without much communication,so the density of connections cant represent whether the users belong to the same community or not.With the network becoming more and more complicated,the traditional global method will cost much time and space.In this paper,we proposed a local method based on links and content,and the method focuses on particular users communities.The results on Enron email dataset have shown the superior performance and accuracy rate of our proposed method in community detection.
Social Network Local Community Detection Links And Content Seed Set
Cuijuan Wang Wenzhong Tang Yanyang Wang Jing Fang Shan Yao
School of Computer Science and Engineering,Beihang University School of Aeronautic Science and Engineering,Beihang University National Computer Network Emergency Response Technical Team/Coordination Center of China Beijing,Chi
国际会议
重庆
英文
1805-1808
2017-03-25（万方平台首次上网日期，不代表论文的发表时间）