Route kernels for trees

Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

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.

Original languageEnglish
Title of host publicationProceedings of the 26th International Conference On Machine Learning, ICML 2009
Pages17-24
Number of pages8
Publication statusPublished - 9 Dec 2009
Event26th International Conference On Machine Learning, ICML 2009 - Montreal, QC, Canada
Duration: 14 Jun 200918 Jun 2009

Publication series

NameProceedings of the 26th International Conference On Machine Learning, ICML 2009

Conference

Conference26th International Conference On Machine Learning, ICML 2009
CountryCanada
CityMontreal, QC
Period14/6/0918/6/09

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

Cite this

Aiolli, F., Da San Martino, G., & Sperduti, A. (2009). Route kernels for trees. In Proceedings of the 26th International Conference On Machine Learning, ICML 2009 (pp. 17-24). (Proceedings of the 26th International Conference On Machine Learning, ICML 2009).