Languages as Hyperplanes: Grammatical Inference with String Kernels

  • Alexander Clark
  • Christophe Costa Florêncio
  • Chris Watkins
Conference paper

DOI: 10.1007/11871842_13

Part of the Lecture Notes in Computer Science book series (LNCS, volume 4212)
Cite this paper as:
Clark A., Florêncio C.C., Watkins C. (2006) Languages as Hyperplanes: Grammatical Inference with String Kernels. In: Fürnkranz J., Scheffer T., Spiliopoulou M. (eds) Machine Learning: ECML 2006. ECML 2006. Lecture Notes in Computer Science, vol 4212. Springer, Berlin, Heidelberg

Abstract

Using string kernels, languages can be represented as hyperplanes in a high dimensional feature space. We present a new family of grammatical inference algorithms based on this idea. We demonstrate that some mildly context sensitive languages can be represented in this way and it is possible to efficiently learn these using kernel PCA. We present some experiments demonstrating the effectiveness of this approach on some standard examples of context sensitive languages using small synthetic data sets.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Alexander Clark
    • 1
  • Christophe Costa Florêncio
    • 1
  • Chris Watkins
    • 1
  1. 1.Department of Computer ScienceUniversity of LondonEgham

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