Probabilistic k-Testable Tree Languages

  • Juan Ramón Rico-Juan
  • Jorge Calera-Rubio
  • Rafael C. Carrasco
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1891)

Abstract

In this paper, we present a natural generalization of k-gram models for tree stochastic languages based on the k-testable class. In this class of models, frequencies are estimated for a probabilistic regular tree grammar wich is bottom-up deterministic. One of the advantages of this approach is that the model can be updated in an incremental fashion. This method is an alternative to costly learning algorithms (as inside-outside-based methods) or algorithms that require larger samples (as many state merging/splitting methods).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Juan Ramón Rico-Juan
    • 1
  • Jorge Calera-Rubio
    • 1
  • Rafael C. Carrasco
    • 1
  1. 1.Departament de Llenguatges i Sistemes InformàticsUniversitat d’AlacantAlacanSpain

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