PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Fast kernels for string and tree matching
S V N Vishwanathan and Alex Smola
In: Kernels and Bioinformatics (2004) MIT Press , Cambridge, MA, USA .

Abstract

In this chapter we present a new algorithm suitable for matching discrete ob jects such as strings and trees in linear time, thus obviating dynamic programming with quadratic time complexity. This algorithm can be extended in various ways to provide linear time prediction cost in the length of the sequence to be classified. We demonstrate extensions in the case of position dependent weights, sliding window classifiers for a long sequence, and efficient algorithms for dealing with weights given in the form of dictionaries. This improvement on the currently available algorithms makes string kernels a viable alternative for the practitioner.

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EPrint Type:Book Section
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Natural Language Processing
Theory & Algorithms
ID Code:2056
Deposited By:Alex Smola
Deposited On:16 January 2006