Modeling languages from graph networks

Abstract

We model and compute the probability distribution of the letters in random generated words in a language by using the theory of set partitions, Young tableaux and graph theoretical representation methods. This has been of interest for several application areas such as network systems, bioinformatics, internet search, data mining and computacional linguistics.

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