Almost all tree kernels proposed in the literature match substructures without taking into account their relative positioning with respect to one another. In this paper, we propose a novel family of kernels which explicitly focus on this type of information. Specifically, after defining a family of tree kernels based on routes between nodes, we present an efficient implementation for a member of this family. Experimental results on four different datasets show that our method is able to reach state of the art performances, obtaining in some cases performances better than computationally more demanding tree kernels.

Route Kernels for Trees

AIOLLI, FABIO;DA SAN MARTINO, GIOVANNI;SPERDUTI, ALESSANDRO
2009

Abstract

Almost all tree kernels proposed in the literature match substructures without taking into account their relative positioning with respect to one another. In this paper, we propose a novel family of kernels which explicitly focus on this type of information. Specifically, after defining a family of tree kernels based on routes between nodes, we present an efficient implementation for a member of this family. Experimental results on four different datasets show that our method is able to reach state of the art performances, obtaining in some cases performances better than computationally more demanding tree kernels.
Proceedings of the Twenty-Sixth International Conference on Machine Learning (ICML 2009)
9781605585161
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11577/2437509
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