Clustering a medieval social network by SOM using a kernel based distance measure

Nathalie Villa (1) , Romain Boulet (1)

1 IMT - Institut de Mathématiques de Toulouse UMR5219

In order to explore the social organization of a medieval peasant community before the Hundred Years' War, we propose the use of an adaptation of the well-known Kohonen Self Organizing Map to dissimilarity data. In this paper, the algorithm is used with a distance based on a kernel which allows the choice of a smoothing parameter to control the importance of local or global proximities.

Keywords: self-organizing map; clustering; diffusion kernel; graph; medieval

Domains: Statistics [math.ST]

Nathalie Villa, Romain Boulet. Clustering a medieval social network by SOM using a kernel based distance measure. European Symposium on Artificial Neural Networks, Apr 2007, Bruges, Belgium. pp.31-36. ⟨hal-00145117⟩