基于谱聚类的复杂网络社团发现算法

复杂网络社团发现的研究对于控制疾病传播、网络病毒的传播等具有重大意义.针对已有社团发现算法时间复杂度过高,不适用于结构未知的大型网络等问题,结合谱聚类在识别未知分布数据集聚类方面的优势,以及模块度函数能够在大型网络中搜寻出最佳社团数目的能力,提出了基于谱聚类的社团发现算法--SCCF算法.实验结果表明,与已有的社团发现算法相比,SCCF算法效率更高,并且能够在网络节点数上万的大型网络中得到高质量的社团结构.

Community-finding Algorithm in Complex Networks Based on Spectral Clustering

Research on community finding is very helpful to control virus spreading in networks.Most of the proposed community-finding algorithms are not suitable for very large networks because of their time-complexity.Combined with the advantage of solving the clustering of unknown distributed data set of the spectral clustering,and the ability of mo-dularity function in finding good community number in large networks,a community-finding algorithm based on spectral clustering was proposed.Experimental results indica...