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Computing the Partial Word Avoidability Indices of Ternary Patterns

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Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7643)

Abstract

We study pattern avoidance in the context of partial words. The problem of classifying the avoidable unary patterns has been solved, so we move on to binary, ternary, and more general patterns. Our results, which are based on morphisms (iterated or not), determine all the ternary patterns’ avoidability indices or at least give bounds for them.

Keywords

  • Depth Function
  • Alphabet Size
  • Partial Word
  • Pattern Avoidance
  • Full Word

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This material is based upon work supported by the National Science Foundation under Grant No. DMS–1060775. We thank Sean Simmons from the Massachusetts Institute of Technology for his very valuable comments and suggestions.

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Blanchet-Sadri, F., Lohr, A., Scott, S. (2012). Computing the Partial Word Avoidability Indices of Ternary Patterns. In: Arumugam, S., Smyth, W.F. (eds) Combinatorial Algorithms. IWOCA 2012. Lecture Notes in Computer Science, vol 7643. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35926-2_23

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  • DOI: https://doi.org/10.1007/978-3-642-35926-2_23

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35925-5

  • Online ISBN: 978-3-642-35926-2

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