Luciano D. S. Pacífico,  Francisco de A. T. de Carvalho. 

Clustering methods aims to organize a set of items into clusters such that items within a given cluster have a high degree of similarity, while items belonging to different clusters have a high degree of dissimilarity. The self- organizing map (SOM) is an unsupervised competitive learning neural network method which has both clustering and dimensionality reduction properties, us- ing a neighborhood function to discover the topological structure hidden in the data set. In this paper, we introduce a batch self-organizing maps algorithm based on adaptive distances (ABSOM). Experimental results obtained in real benchmark datasets show the effectiveness of our approach.

http://www.lbd.dcc.ufmg.br/colecoes/enia/2011/0020.pdf

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