In many real-world applications, data cannot be accurately represented by vectors. In those situations, one possible solution is to rely on dissimilarity measures that enable a se...
Abstract. This paper proposes to apply the branch and bound principle from combinatorial optimization to the Dissimilarity Self-Organizing Map (DSOM), a variant of the SOM that can...
Self-Organizing Maps (SOM) are very powerful tools for data mining, in particular for visualizing the distribution of the data in very highdimensional data sets. Moreover, the 2D m...
Abstract. We describe a scalable parallel implementation of the self organizing map (SOM) suitable for datamining applications involving clustering or segmentation against large da...
Richard D. Lawrence, George S. Almasi, Holly E. Ru...
The knowledge discovery process encounters the difficulties to analyze large amount of data. Indeed, some theoretical problems related to high dimensional spaces then appear and de...