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Detecting Overlapping Communities in Directed Networks Based on Link Similarity

机译:基于链路相似性检测定向网络中的重叠社区

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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 are 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:识别网络中的重叠社区最近引起了不断的关注,但是这个问题的最常见方法已经忽略了边缘方向并应用了在无向网络中的方法。在本文中,提出了一种定向网络中的重叠社区检测算法,其分区社区是链路组。 E.COLI的转录调节网络(TRN)用于评估算法。实验结果表明,所提出的算法是用于检测定向网络中的重叠社区的算法。

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