谱分析与启发式遗传算法相结合的多尺度社区检测方法

Heuristic genetic algorithm associated with spectral analysis uncovering multi-scale community of complex networks

针对常规的社区检测方法不能揭示出社区结构的多尺度特征这一问题,本文通过对复杂网络传导率函数C与社区平均凝聚概率的分析,提出了一种局部启发变异策略,同时将复杂网络谱分析与遗传算法相结合,提出了多尺度社区检测算法HGASA。在人工网络和现实网络上对HGASA算法进行了测试,实验结果表明了HGASA算法的有效性和高效性。

The community structure of complex networks has attracted much attention.However,previous methods can not investigate the multi-scale property of the community.To address this problem,by analyzing conduct function C and average agglomerate probability,a local heuristic heteromorphosis strategy is proposed;then,spectral analysis of complex networks is combined with genetic algorithm;finally a multi-scale community detection algorithm HGASA（Heuristic genetic algorithm with spectral analysis）is proposed.Extensive tests on artificial networks and real world networks justify the superiority of the HGASA algorithm.