• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

J4 ›› 2016, Vol. 38 ›› Issue (04): 792-799.

• 论文 • 上一篇    下一篇

一种基于信息扩散的复杂网络重叠社区发现算法

吴永亮,郑伟涛,郭芳琳,闫光辉   

  1. (兰州交通大学电子与信息工程学院,甘肃 兰州 730070)
  • 收稿日期:2015-04-28 修回日期:2015-06-18 出版日期:2016-04-25 发布日期:2016-04-25
  • 基金资助:

    国家自然科学基金(61163010,11461038);兰州市科技计划项目(20141171);金川公司预研基金(JCYY2013012)

An  overlapping community detection algorithm in
complex networks based on information dissemination         

WU Yongliang,ZHENG Weitao,GUO Fanglin,YAN Guanghui   

  1. (School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China)
  • Received:2015-04-28 Revised:2015-06-18 Online:2016-04-25 Published:2016-04-25

摘要:

社区结构可以为网络的其他分析挖掘提供中观尺度的分析视角,在大规模复杂网络的各项研究中是一项非常重要而基础的工作。社区的重叠是真实世界网络中常见的一种现象,重叠社区结构可以更准确地描述网络中真实的结构信息,因此,复杂网络重叠社区发现具有更加突出的现实意义。在综合对比分析了当前主要的重叠社区发现算法的基础上,结合信息论的相关知识,给出了一种基于信息论的社区定义,并进一步借鉴信息传播理论,从单个节点对关于某种主题的信息的掌握程度的角度出发提出了一种复杂网络重叠社区结构发现算法。基于实际数据集的相关实验表明,与传统的社区定义和社区发现算法相比,本算法发现的重叠社区从内容角度来看具有更加明确的实际意义,并且具有较低的时间复杂度。

关键词: 重叠社区发现, 社区定义, 信息论, 信息扩散

Abstract:

Community structure can provide a mediumscale analysis perspective for other analysis in the networks, and its research is fundamental and important in complex networks. In complex networks, the overlapping community structure is a more actual description of the structure of social networks. So analyzing the structure of overlapping communities has practical significance. After studying the existing overlapping community detection algorithms combined with certain knowledge of information theory, we define the concept of community from the perspective of information theory, and present an algorithm which can detect the overlapping community structure in complex networks on the basis of information dissemination theory. Experiments show that compared with the traditional definition of community and detection algorithms, the proposed algorithm has a more accurate physical meaning and a lower time complexity.

Key words: overlapping community detection;definition of community;information theory;information dissemination