# A survey of kernels for structured data

@article{Grtner2003ASO, title={A survey of kernels for structured data}, author={Thomas G{\"a}rtner}, journal={SIGKDD Explor.}, year={2003}, volume={5}, pages={49-58} }

Kernel methods in general and support vector machines in particular have been successful in various learning tasks on data represented in a single table. Much 'real-world' data, however, is structured - it has no natural representation in a single table. Usually, to apply kernel methods to 'real-world' data, extensive pre-processing is performed to embed the data into areal vector space and thus in a single table. This survey describes several approaches of defining positive definite kernels on…

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