Résumé 167 :
Self-organizing maps for clustering and visualization of bipartite graphs
Olteanu, Madalina ; Villa-Vialaneix, Nathalie
INRA de Toulouse, UnitÃ© MIA-T
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.