Route kernels for trees

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.

• Type: Conference
• Year: 2009
• Where: ICML
• Authors: Fabio Aiolli, Giovanni Da San Martino, Alessandro Sperduti
• Keywords: Cases Performances, ICML 2009, Literature Match Substructures, Machine Learning, Tree Kernels