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Learning a subclass of linear languages from positive structural information

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Grammatical Inference (ICGI 1998)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1433))

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Abstract

A method to infer a subclass of linear languages from positive structural information (i.e. skeletons) is presented. The characterization of the class and the analysis of the time and space complexity of the algorithm is exposed too. The new class, Terminal and Structural Distinguishable Linear Languages (TSDLL), is defined through an algebraic characterization and a pumping lemma. We prove that the proposed algorithm correctly identifies any TSDL language in the limit if structural information is presented. Furthermore, we give a definition of a characteristic structural set for any target grammar. Finally we present the conclusions of the work and some guidelines for future works.

Part of this work was carried out during a visit of J. Sempere to Prof. G. Nagaraja at IIT, Mumbai. The visit was granted by the área de Programas Internacionales (API) of the Universidad Politécnica de Valencia

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Author information

Authors and Affiliations

  1. DSIC, Universidad Politécnica de Valencia, 46071, Valencia, Spain

    José M. Sempere

  2. DCSE, Indian Institute of Technology, 400 076, Powai, Mumbai, India

    G. Nagaraja

Authors
  1. José M. Sempere
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  2. G. Nagaraja
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Editor information

Vasant Honavar Giora Slutzki

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© 1998 Springer-Verlag Berlin Heidelberg

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Sempere, J.M., Nagaraja, G. (1998). Learning a subclass of linear languages from positive structural information. In: Honavar, V., Slutzki, G. (eds) Grammatical Inference. ICGI 1998. Lecture Notes in Computer Science, vol 1433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0054073

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  • DOI: https://doi.org/10.1007/BFb0054073

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-64776-8

  • Online ISBN: 978-3-540-68707-8

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