PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Factored sequence kernels
Pierre Mahe' and Nicola Cancedda
In: ESANN 2008, 23-25 April 2008, Bruges, Belgium.

Abstract

In this paper we propose an extension of sequence kernels to the case where the symbols that define the sequences have multiple representations. This configuration occurs in natural language processing for instance, where words can be characterized according to different linguistic dimensions. The core of our contribution is to integrate early the different representations in the kernel, in a way that generates rich composite features defined across the various symbol dimensions.

EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Learning/Statistics & Optimisation
Natural Language Processing
ID Code:3671
Deposited By:Pierre Mahe'
Deposited On:14 February 2008