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 structured instances directly.
%0 Journal Article
%1 959248
%A Gärtner, Thomas
%C New York, NY, USA
%D 2003
%I ACM
%J SIGKDD Explor. Newsl.
%K graph-matching kernel-methods
%N 1
%P 49--58
%R http://doi.acm.org/10.1145/959242.959248
%T A survey of kernels for structured data
%U http://portal.acm.org/citation.cfm?id=959248
%V 5
%X 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 structured instances directly.
@article{959248,
abstract = {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 structured instances directly.},
added-at = {2009-10-08T09:50:40.000+0200},
address = {New York, NY, USA},
author = {G\"{a}rtner, Thomas},
biburl = {https://www.bibsonomy.org/bibtex/202ed899eed46b754ee9c3914459db6e5/ahmedjawwad4u},
description = {A survey of kernels for structured data},
doi = {http://doi.acm.org/10.1145/959242.959248},
interhash = {6c0747dee495ca023eb3863aa7164684},
intrahash = {02ed899eed46b754ee9c3914459db6e5},
issn = {1931-0145},
journal = {SIGKDD Explor. Newsl.},
keywords = {graph-matching kernel-methods},
number = 1,
pages = {49--58},
publisher = {ACM},
timestamp = {2009-10-08T09:50:40.000+0200},
title = {A survey of kernels for structured data},
url = {http://portal.acm.org/citation.cfm?id=959248},
volume = 5,
year = 2003
}