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Comparing the Community Structure Identified by Overlapping Methods

机译:通过重叠方法确定的社区结构进行比较

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Community detection is one of the most important tasks in network analysis. Recently, an increasing number of researchers have been dedicated to investigating networks in which the nodes participate concomitantly in more than one community. This work presents a comparative study of five state-of-art methods for overlapping community detection from the perspective of the structural properties of the communities identified by them. Experiments with benchmark and ground-truth networks show that, although the methods are able to identify modular communities, they often miss many structural properties of the communities, such as the number of nodes in the overlapping region and the membership of the nodes.
机译:社区检测是网络分析中最重要的任务之一。最近,越来越多的研究人员致力于调查节点在多个社区中参与的网络。本作品介绍了从由它们识别的社区结构特性的角度来看重叠社区检测的五种最先进方法的比较研究。基准和地理网络的实验表明,虽然这些方法能够识别模块化社区,但它们通常会错过社区的许多结构属性,例如重叠区域中的节点数量和节点的成员资格。

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