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Conference Papers Year : 2014

Core decomposition in Directed Networks: Kernelization and Strong Connectivity

Abstract

In this paper, we propose a method allowing decomposition of directed networks into cores, which final objective is the detection of communities.We based our approach on the fact that a community should be composed of elements having communication in both directions. Therefore, we propose a method based on digraph kernelization and strongly p-connected components. By identifying cores, one can use based-centers clustering methods to generate full communities. Some experiments have been made on three real-world networks, and have been evaluated using the V-Measure, having a more precise analysis through its two sub-measures: homogeneity and completeness. Our work proposes different directions about the use of kernelization into structure analysis, and strong connectivity concept as an alternative to modularity optimization.
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Dates and versions

hal-00961165 , version 1 (19-03-2014)

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Vincent Levorato. Core decomposition in Directed Networks: Kernelization and Strong Connectivity. Complex Networks, Mar 2014, Bologne, Italy. pp.129-140, ⟨10.1007/978-3-319-05401-8_13⟩. ⟨hal-00961165⟩
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