计算机工程与应用 ›› 2012, Vol. 48 ›› Issue (31): 36-39.

• 研究、探讨 • 上一篇    下一篇

复杂网络健壮社团挖掘算法

王  艳1,李应兴2,靳二辉3   

  1. 1.西北民族大学 图书馆,兰州 730030
    2.西北民族大学 数学与计算机科学学院,兰州 730030
    3.西安电子科技大学 计算机学院,西安 710071
  • 出版日期:2012-11-01 发布日期:2012-10-30

Novel algorithm for robust community in complex networks

WANG Yan1, LI Yingxing2, JIN Erhui3   

  1. 1.Library of Northwest University for Nationalities, Lanzhou 730030, China
    2.School of Mathematics and Computer Science Institute, Northwest University for Nationalities, Lanzhou 730030, China
    3.School of Computer Science and Technology, Xidian University, Xi’an 710071, China
  • Online:2012-11-01 Published:2012-10-30

摘要: 提出了一种基于贝叶斯网络的健壮社团挖掘算法,通过对每个普通社团分别构建贝叶斯网络,并根据条件概率表和证据信息进行推理,得到贝叶斯网络中每个节点隶属于健壮社团的后验概率以提取健壮社团。实验结果证明了该方法对健壮社团发现的有效性。

关键词: 复杂网络, 社团发现, 健壮社团, 贝叶斯网络

Abstract: A Bayesian network based algorithm for robust community in complex network is developed. Through constructing Bayesian network for every common community, according to conditional probabilities table and prior probabilities for reasoning, the posterior probabilities of every node being in a robust community is obtained to extract robust communities. It experimentally verifies the effectiveness of two algorithms in networks.

Key words: complex network, community discovering, robust community, Bayesian network