Community Detection Based on Adaptive Kernel Affinity Propagation

摘要：

Detecting community structure in complex networks is a challenging problem which has attracted great interest in recent years. In this paper, a method called adaptive kernel affinity propagation is proposed to detect communities in networks, in which Markov diffusion kernel is transformed to implicitly measure the dissimilarities between different nodes and then adaptive affinity propagation is applied to determine the optimal number of communities and the corresponding membership assignment automatically. Experimental results on both computer-generated and real-world networks demonstrate that adaptive kernel affinity propagation can detect the correct and meaningful communities efficiently.

关键词： community detection Markov diffusion kernel adaptive affinity propagation

作者: Shuzhong Yang Siwei Luo

会议类型: 国际会议

会议名称: 2009 2nd IEEE International Conference on Computer Science and Information Technology(第二届计算机科学与信息技术国际会议 ICCSIT2009)

会议地点: 北京

会议语种:英文

页码: 1317-1320

在线出版日期: 2009-08-08（万方平台首次上网日期，不代表论文的发表时间）