Visual Mining of Epidemic NetworksReport as inadecuate

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* Corresponding author 1 LTCI - Laboratoire Traitement et Communication de l-Information 2 MATCOM - Matematica y Computacion 3 LPP - Laboratoire Paul Painlevé 4 CMAP - Centre de Mathématiques Appliquées - Ecole Polytechnique

Abstract : We show how an interactive graph visualization method based on maximal modularity clustering can be used to explore a large epidemic network. The visual representation is used to display statistical tests results that expose the relations between the propagation of HIV in a sexual contact network and the sexual orientation of the patients.

Keywords : visualization of large networks HIV-AIDS epidemics maximal modularity clustering

Author: Stéphan Clémençon - Hector De Arazoza - Fabrice Rossi - Viet Chi Tran -



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