Language discrimination and clustering via a neural network approach

2015/07/15 by Mariano, Angelo, Parisi, Giorgio, Pascazio, Saverio
#Computation and Language (cs.CL) #Disordered Systems and Neural Networks (cond-mat.dis-nn) #FOS: Computer and information sciences #FOS: Physical sciences #Neural and Evolutionary Computing (cs.NE) #Physics and Society (physics.soc-ph)

paper · doi:10.48550/arxiv.1507.04116

Abstract

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

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