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计算机工程 ›› 2011, Vol. 37 ›› Issue (6): 172-174.doi: 10.3969/j.issn.1000-3428.2011.06.059

• 人工智能及识别技术 • 上一篇    下一篇

基于共享邻居数的社团结构发现算法

刘 微，张大为，嵇 敏，谢福鼎   

  1. (辽宁师范大学计算机与信息技术学院，辽宁 大连 116081)
  • 出版日期:2011-03-20 发布日期:2011-03-29
  • 作者简介:刘 微(1986－)，女，硕士研究生，主研方向：数据挖掘，人工智能；张大为、嵇 敏，讲师；谢福鼎，教授
  • 基金项目:
    国家自然科学基金资助项目(10771092)

Community Structure Detection Algorithm Based on Number of Shared Neighbors

LIU Wei, ZHANG Da-wei, JI Min, XIE Fu-ding   

  1. (College of Computer and Information Technology, Liaoning Normal University, Dalian 116081, China)
  • Online:2011-03-20 Published:2011-03-29

PDF

2642

被引次数

27 | 3

摘要： 为了快速准确地找到复杂网络的社团结构，提出一种基于共享邻居数和局部模块度的社团结构发现算法。该方法通过不断寻找节点之间的共享邻居数找出与社团连接性最强的节点，并以局部模块度为衡量标准，判断是否将该节点加入到社团中。对3个典型复杂网络的划分结果表明，该算法是可行和有效的。

关键词: 复杂网络, 社团结构, 共享邻居, 局部模块度

Abstract: To partition complex networks into groups fast and correctly, this paper proposes an algorithm for detecting community structures in complex networks based on shared neighbors and local modularity. By looking for the numbers of shared neighbors between nodes one by one, the node connected closely with the community is found, and the local modularity is used to decide whether this found node is added into the community. Three typical complex networks are used to test the performance of the algorithm. Experimental results show that it is viable and effective.

Key words: complex network, community structure, shared neighbor, local modularity

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