计算机应用研究Issue(9)：2597-2600,4.DOI:10.3969/j.issn.1001-3695.2015.09.009
基于改进 Page Rank算法和spin-g lass模型的多角度识别可控的社区发现算法
Discovery algorithm of multi-angle identify controllable based on improved PageRank algorithm and spin-glass models
摘要
Abstract
In order to effectively solve the problem of communities overlap in community discovery algorithm,and improve the community expansion model,this paper proposed a discovery algorithm of multi-angle identify controllable based on improved PageRank algorithm and spin-glass models.Firstly,it utilized optimized PageRank algorithm to sort each node,determined which of the core node.Secondly,it utilized multi-angle identification module degree based on the Potts spin-glass model to op-timize the expansion model of local community,and solved the shackles and influence of traditional modularity in terms of the resolution limit.Meanwhile in the discovery process,it introduced an improved greedy iterative algorithm to discover local com-munities,and ultimately found the overlapping structure and node exactly.After comparison and analysis the application in computer simulation network and real network environment,it is found that this algorithm has better stability and accuracy com-pared with traditional technology solutions,and the complexity of the algorithm is also within the acceptable range.关键词
社区发现/改进PageRank算法/spin-glass模型/多角度识别可控/贪心迭代算法Key words
community discovery/improved PageRank algorithm/spin-glass model/multi-angle identify controllable/greedy iterative algorithm分类
信息技术与安全科学引用本文复制引用
石云,陈钟,孙兵..基于改进 Page Rank算法和spin-g lass模型的多角度识别可控的社区发现算法[J].计算机应用研究,2015,(9):2597-2600,4.基金项目
国家自然科学基金资助项目（61170263）；广东省高等教育学会实验室管理专业委员会基金资助项目 （）
