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Communication Dans Un Congrès Année : 2014

Self-Organizing Maps for clustering and visualization of bipartite graphs

Résumé

Graphs (also frequently called networks) have attracted a burst of attention in the last years, with applications to social science, biology, computer science... The present paper proposes a data mining method for visualizing and clustering the nodes of a peculiar class of graphs: bipartite graphs. The method is based on a self-organizing map algorithm and relies on an extension of this approach to data described by a dissimilarity matrix.
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Dates et versions

hal-01001991 , version 1 (05-06-2014)

Identifiants

  • HAL Id : hal-01001991 , version 1

Citer

Madalina Olteanu, Nathalie Vialaneix. Self-Organizing Maps for clustering and visualization of bipartite graphs. 46e Journées de Statistique de la SFdS, Jun 2014, Rennes, France. pp.109. ⟨hal-01001991⟩
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