电子学报Issue(4)：723-729,7.DOI:10.3969/j.issn.0372-2112.2014.04.016
基于贪婪优化技术的网络社区发现算法研究
Community Detection in Complex Networks Based on Greedy Optimization
冷作福1
作者信息
- 1. 烟台市电化教育馆，山东烟台 264003
- 折叠
摘要
Abstract
In social network ,the important and crucial problem is community detection .Classical modularity function opti-mization approaches such as CNM and BGLL are widely used methods for identifying communities which are quite efficient .As we have known ,modularity function (Q) suffers from its resolution limit .Recently ,surprise function(S) was proposed and experimen-tally proved to be better than Q function .However ,up to now ,there is not any method which is based on direct surprise maximiza-tion .In this paper ,an efficient community detection algorithm which is based on greedy surprise optimization is proposed and does not suffer from a resolution limit .The new method does not need community number K .Test results on experimental networks show that our method is robust ,not sensitive to noises and has better performances .关键词
复杂网络/社区发现/模块度函数/surpriseKey words
complex network/community structure/modularity function/surprise分类
自科综合引用本文复制引用
冷作福..基于贪婪优化技术的网络社区发现算法研究[J].电子学报,2014,(4):723-729,7.
