Leveraging disjoint communities for detecting overlapping community structure

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چکیده

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Leveraging disjoint communities for detecting overlapping community structure

Network communities represent mesoscopic structure for understanding the organization of real-world networks, where nodes often belong to multiple communities and form overlapping community structure in the network. Due to non-triviality in finding the exact boundary of such overlapping communities, this problem has become challenging, and therefore huge effort has been devoted to detect overla...

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Many algorithms have been designed to discover community structure in networks. Most of these detect disjoint communities, while a few can find communities that overlap. We propose a new, two-phase, method of detecting overlapping communities. In the first phase, a network is transformed to a new one by splitting vertices, using the idea of split betweenness; in the second phase, the transforme...

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Community detection is a fundamental problem in the analysis of complex networks. Recently, many researchers have concentrated on the detection of overlapping communities, where a vertex may belong to more than one community. However, most current methods require the number (or the size) of the communities as a priori information, which is usually unavailable in real-world networks. Thus, a pra...

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ژورنال

عنوان ژورنال: Journal of Statistical Mechanics: Theory and Experiment

سال: 2015

ISSN: 1742-5468

DOI: 10.1088/1742-5468/2015/05/p05017