# On a Family of Decomposable Kernels on Sequences

Andrea Baisero, Florian T. Pokorny, Carl Henrik Ek
In arXiv, 2015

## Abstract

In many applications data is naturally presented in terms of orderings of some basic elements or symbols. Reasoning about such data requires a notion of similarity capable of handling sequences of different lengths. In this paper we describe a family of Mercer kernel functions for such sequentially structured data. The family is characterized by a decomposable structure in terms of symbol-level and structure-level similarities, representing a specific combination of kernels which allows for efficient computation. We provide an experimental evaluation on sequential classification tasks comparing kernels from our family of kernels to a state of the art sequence kernel called the Global Alignment kernel which has been shown to outperform Dynamic Time Warping.

## Files

@article{baisero2015b, title = {On a Family of Decomposable Kernels on Sequences}, author = {Baisero, Andrea and Pokorny, Florian T. and Ek, Carl Henrik}, booktitle = {arXiv}, year = {2015}, url = {http://arxiv.org/abs/1501.06284} }