Distributed Tree Kernels
Machine Learning
2012-06-22 v1 Machine Learning
Abstract
In this paper, we propose the distributed tree kernels (DTK) as a novel method to reduce time and space complexity of tree kernels. Using a linear complexity algorithm to compute vectors for trees, we embed feature spaces of tree fragments in low-dimensional spaces where the kernel computation is directly done with dot product. We show that DTKs are faster, correlate with tree kernels, and obtain a statistically similar performance in two natural language processing tasks.
Cite
@article{arxiv.1206.4607,
title = {Distributed Tree Kernels},
author = {Fabio Massimo Zanzotto and Lorenzo Dell'Arciprete},
journal= {arXiv preprint arXiv:1206.4607},
year = {2012}
}
Comments
ICML2012