PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Languages as Hyperplanes: grammatical inference with string kernels
Alexander Clark, Christophe Costa Florencio and Chris Watkins
In: ECML 2006, 18-22 September 2006, Berlin.

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.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Theory & Algorithms
ID Code:2175
Deposited By:Alexander Clark
Deposited On:12 August 2006