2002 FastKernelsForStringAndTreeMatching

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Subject Headings: Relational Data Kernel Function

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Abstract

In this paper we present a new algorithm suitable for matching discrete objects such as strings and trees in linear time, thus obviating dynamic programming with quadratic time complexity. Furthermore, prediction cost in many cases can be reduced to linear cost in the length of the sequence to be classified, regardless of the number of support vectors. This improvement on the currently available algorithms makes string kernels a viable alternative for the practitioner.

References


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 AuthorvolumeDate ValuetitletypejournaltitleUrldoinoteyear
2002 FastKernelsForStringAndTreeMatchingS. V. N. Vishwanathan
Alexander J. Smola
Fast Kernels for String and Tree Matchinghttp://www.stat.purdue.edu/~vishy/papers/VisSmo03.ps.gz