186 / 2016-12-20 13:54:30
Local Community Detection Algorithm Based on Links And Content
Social network,Local Community Detection,Links and Content,Seed Set
全文录用
Cuijuan Wang / School of Computer Science and Engineering, Beihang University
Wenzhong Tang / School of Computer Science and Engineering, Beihang University
Yanyang Wang / School of Aeronautic Science and Engineering, Beihang University
Jing Fang / National Computer Network Emergency Response Technical Team/Coordination Center of China
Shan Yao / National Computer Network Emergency Response Technical Team/Coordination Center of China
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 can’t represent weather 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 test results on Enron email dataset have shown the superior performance of our proposed method in community detection.
重要日期
  • 会议日期

    03月25日

    2017

    03月26日

    2017

  • 11月10日 2016

    初稿截稿日期

  • 11月20日 2016

    初稿录用通知日期

  • 11月30日 2016

    终稿截稿日期

  • 03月26日 2017

    注册截止日期

主办单位
IEEE Beijing Section
联系方式
移动端
在手机上打开
小程序
打开微信小程序
客服
扫码或点此咨询