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We classify twenty-one Indo-European languages starting from written text. Weuse neural networks in order to define a distance among different languages,construct a dendrogram and analyze the ultrametric structure that emerges. Fouror five subgroups of languages are identified, according to the "cut" of thedendrogram, drawn with an entropic criterion. The results and the method arediscussed.

Language discrimination and clustering via a neural network approach