A Micro-Community Structure Merging Model Using a Community Sample Matrix  

作　　者：LI Lin PENG Hao LU Song-Nian TIAN Ying 李琳;彭浩;陆松年;田颖(Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240;Key Laboratory of Materials for High Power Laser,Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800)

机构地区：[1]Department of Electronic Engineering,Shanghai Jiao Tong University,Shanghai 200240 [2]Key Laboratory of Materials for High Power Laser,Shanghai Institute of Optics and Fine Mechanics,Chinese Academy of Sciences,Shanghai 201800

出　　处：《Chinese Physics Letters》2013年第1期227-230,共4页中国物理快报（英文版）

基　　金：Supported by the National Natural Science Foundation of China(61071152,61271316);the National Basic Research Program of China(2010CB731403,2010CB731406);the National Twelfth Five-Year Plan for Science&Technology Support(2012BAH38B04).

摘　　要：Detecting an overlapping and hierarchical community structure can give a significant insight into structural and functional properties in complex networks.We propose a micro-community structure merging model to detect overlapping and hierarchical communities.The algorithm maps communities to random variables using the community sample matrix to evaluate similarity between communities.After finding density-based micro-community structures,the algorithm merges these reasonable micro-communities iteratively to form communities.Simulation results in three real networks show that the proposed algorithm is more accurate than some existing mechanisms.In this way,we can obtain a detailed understanding of the overlapping and hierarchical communities.

关 键 词：HIERARCHICAL algorithm STRUCTURE 

分 类 号：TN9[电子电信—信息与通信工程]