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International Conference on Algorithmic Learning Theory

ALT 2005: Algorithmic Learning Theory pp 297–311Cite as

Algorithms for Learning Regular Expressions

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3734))

Abstract

We describe algorithms that directly infer regular expressions from positive data and characterize the regular language classes that can be learned this way.

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Author information

Authors and Affiliations

  1. University of Hertfordshire, College Lane, Hatfield, Herts, AL10 9AB, UK

    Henning Fernau

  2. Wilhelm-Schickard-Institut für Informatik, Universität Tübingen, Sand 13, D-72076, Tübingen, Germany

    Henning Fernau

Authors
  1. Henning Fernau
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Editor information

Editors and Affiliations

  1. School of Computing, National University of Singapore, 117590, Singapore

    Sanjay Jain

  2. Ruhr-Universität Bochum, Germany

    Hans Ulrich Simon

  3. Department of Information and Communication Engineering, Faculty of Electro-Communications, The University of Electro-Communications, Chofugaoka 1–5–1, Chofu, 182-8585, Tokyo, Japan

    Etsuji Tomita

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© 2005 Springer-Verlag Berlin Heidelberg

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Fernau, H. (2005). Algorithms for Learning Regular Expressions. In: Jain, S., Simon, H.U., Tomita, E. (eds) Algorithmic Learning Theory. ALT 2005. Lecture Notes in Computer Science(), vol 3734. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11564089_24

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  • DOI: https://doi.org/10.1007/11564089_24

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29242-5

  • Online ISBN: 978-3-540-31696-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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