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Learning deterministic regular grammarsfrom stochastic samples in polynomial time

Published online by Cambridge University Press:  15 August 2002

Rafael C. Carrasco
Affiliation:
Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, 03071 Alicante, Spain; (carrasco@dlsi.ua.es)
Jose Oncina
Affiliation:
Departamento de Lenguajes y Sistemas Informáticos, Universidad de Alicante, 03071 Alicante, Spain; (oncina@dlsi.ua.es)
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Abstract

In this paper, the identification of stochasticregularlanguages is addressed.For this purpose, we propose a class of algorithms which allowfor the identification of the structureof the minimal stochastic automaton generating the language. It is shown that the time needed grows only linearly with the size of the sample set and a measure of the complexity of the task is provided.Experimentally, our implementation proves very fast for application purposes.

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Type
Research Article
Copyright
© EDP Sciences, 1999

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