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1 LaBRI - Laboratoire Bordelais de Recherche en Informatique 2 GRAVITE - Graph Visualization and Interactive Exploration Université Sciences et Technologies - Bordeaux 1, Inria Bordeaux - Sud-Ouest, École Nationale Supérieure d-Électronique, Informatique et Radiocommunications de Bordeaux ENSEIRB, CNRS - Centre National de la Recherche Scientifique : UMR 3 INRA Toulouse - Institut national de la recherche agronomique Toulouse

Abstract : Dynamic networks raise new knowledge discovery challenges. To handle efficiently this kind of data, an analysis method has to both decompose the network modelled by a graph into similar set of nodes and let the user detect structural changes in the graph. In this article we present a graph decomposition algorithm generating overlapping clusters. The complexity of this algorithmis O|E|·deg max^2+|V| · log|V|. This algorithm is particularly efficient due to its ability to detect major modifications along dynamic processes such as time related ones.

Keywords : Overlapping Clustering Clusters Evolution Social Network Analy





Autor: Romain Bourqui - Paolo Simonetto - Fabien Jourdan -

Fuente: https://hal.archives-ouvertes.fr/



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