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Detecting Overlapping Communities in Directed Networks Based on Link Similarity

机译:基于链路相似度的定向网络重叠社区检测

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Identifying overlapping communities in networks has attracted increasing attention recently, but the most common approach to this problem has been to ignore the edge direction and apply the methods in undirected networks. In this paper, an overlapping communities detecting algorithm in directed networks is proposed whose partition communities as groups of links. The transcriptional regulatory network (TRN) of E. coli are used to evaluate the algorithm. Experimental results demonstrate that the algorithm proposed is efficient for detecting overlapping communities in directed networks.
机译:识别网络中重叠的社区最近引起了越来越多的关注,但是解决此问题的最常用方法是忽略边缘方向,并将这些方法应用于无向网络。本文提出了一种有向网络中的重叠社区检测算法,该算法以分区社区为链接组。大肠杆菌的转录调控网络(TRN)用于评估算法。实验结果表明,该算法对定向网络中重叠社区的检测是有效的。

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