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International Colloquium on Grammatical Inference

ICGI 1994: Grammatical Inference and Applications pp 38–44Cite as

A characterization of even Linear Languages and its application to the learning problem

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 862))

Abstract

Even Linear Language class is a subclass of context-free class. In this work we propose a characterization of this class using a relation of finite index. Theorems are provided in order to prove the consistence of the characterization. Finally, we propose a method to learn this class using a reduction to the problem of learning regular languages.

Work partially supported by the Spanish CICYT under grant TIC93-0633-CO2

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Authors and Affiliations

  1. Departamento de Sistemas Informáticos y Computación, Universidad Politécnica de Valencia, Camino de Vera s/n, 46071, Valencia, Spain

    Jose M. Sempere & Pedro García

Authors
  1. Jose M. Sempere
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  2. Pedro García
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Editor information

Rafael C. Carrasco Jose Oncina

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© 1994 Springer-Verlag Berlin Heidelberg

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Sempere, J.M., García, P. (1994). A characterization of even Linear Languages and its application to the learning problem. In: Carrasco, R.C., Oncina, J. (eds) Grammatical Inference and Applications. ICGI 1994. Lecture Notes in Computer Science, vol 862. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-58473-0_135

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  • DOI: https://doi.org/10.1007/3-540-58473-0_135

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-58473-5

  • Online ISBN: 978-3-540-48985-6

  • eBook Packages: Springer Book Archive

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