Extending tree kernels with topological information

Authors:
Fabio Aiolli;Giovanni Da San Martino;Alessandro Sperduti
Affiliations:
Dept. of Pure and Applied Mathematics, University of Padova, Padova, Italy;Dept. of Pure and Applied Mathematics, University of Padova, Padova, Italy;Dept. of Pure and Applied Mathematics, University of Padova, Padova, Italy
Venue:
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
Year:
2011

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Abstract

The definition of appropriate kernel functions is crucial for the performance of a kernel method. In many of the state-of-the-art kernels for trees, matching substructures are considered independently from their position within the trees. However, when a match happens in similar positions, more strength could reasonably be given to it. Here, we give a systematic way to enrich a large class of tree kernels with this kind of information without affecting, in almost all cases, the worst case computational complexity. Experimental results show the effectiveness of the proposed approach.