Detection of communities in directed networks based on strongly p-connected components

Vincent Levorato, Coralie Petermann
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引用次数: 18

Abstract

A lot of algorithms in communities detection have been proposed particularly for undirected networks. As methods to find communities in directed networks are few, our contribution is to propose a method based on strongly and unilaterally connected components, and more specifically on strongly p-connected components in directed graphs. The result is a clustering of nodes giving good results in generated graphs according to several clustering evaluation measures, and which practical time complexity remains acceptable.
基于强p连通分量的有向网络群体检测
针对无向网络,人们提出了许多社区检测算法。由于在有向网络中寻找社区的方法很少,我们的贡献是提出一种基于强连接和单侧连接分量的方法,更具体地说是基于有向图中的强p连接分量的方法。结果表明,根据几种聚类评价指标,生成的图的节点聚类结果良好,实际时间复杂度仍然可以接受。
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