Visual Mining of Epidemic Networks

  • Stéphan Clémençon
  • Hector De Arazoza
  • Fabrice Rossi
  • Viet-Chi Tran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6692)


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.


Sexual Orientation Giant Component Sexual Network Graph Visualization Large Connected Component 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Stéphan Clémençon
    • 1
  • Hector De Arazoza
    • 2
    • 3
  • Fabrice Rossi
    • 1
  • Viet-Chi Tran
    • 3
  1. 1.Institut Télécom, Télécom ParisTech, LTCI - UMR CNRS 5141ParisFrance
  2. 2.Facultad de Matemática y ComputaciónUniversidad de la HabanaLa HabanaCuba
  3. 3.Laboratoire Paul Painlevé UMR CNRS No. 8524Villeneuve d’Ascq CedexFrance

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