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arXiv · 1501.06284

On a Family of Decomposable Kernels on Sequences

Andrea Baisero·Florian T. Pokorny·Carl Henrik Ek
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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

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Andrea Baisero, Florian T. Pokorny, Carl Henrik Ek. 2015-01-26. On a Family of Decomposable Kernels on Sequences. https://arxiv.org/abs/1501.06284

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