About: Graph kernel

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In structure mining, a graph kernel is a kernel function that computes an inner product on graphs. Graph kernels can be intuitively understood as functions measuring the similarity of pairs of graphs. They allow kernelized learning algorithms such as support vector machines to work directly on graphs, without having to do feature extraction to transform them to fixed-length, real-valued feature vectors. They find applications in bioinformatics, in chemoinformatics (as a type of molecule kernels), and in social network analysis.

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rdf:type	yago:Ability105616246 yago:Abstraction100002137 yago:Act100030358 yago:Activity100407535 yago:Algorithm105847438 yago:Cognition100023271 yago:Event100029378 yago:Know-how105616786 yago:Method105660268 yago:Procedure101023820 yago:PsychologicalFeature100023100 yago:WikicatGraphAlgorithms yago:WikicatKernelMethodsForMachineLearning yago:YagoPermanentlyLocatedEntity disease yago:Rule105846932
rdfs:label	Graph kernel (en) Jądro grafu (pl)
rdfs:comment	Jądro grafu – podzbiór wierzchołków grafu skierowanego taki, że: * wierzchołki z jądra nie przewyższają się nawzajem (nie posiadają następników) * każdy wierzchołek grafu nie należący do jądra jest przewyższany przez co najmniej jeden wierzchołek z jądra. Każdy wierzchołek izolowany w grafie należy jednocześnie do jądra. (pl) In structure mining, a graph kernel is a kernel function that computes an inner product on graphs. Graph kernels can be intuitively understood as functions measuring the similarity of pairs of graphs. They allow kernelized learning algorithms such as support vector machines to work directly on graphs, without having to do feature extraction to transform them to fixed-length, real-valued feature vectors. They find applications in bioinformatics, in chemoinformatics (as a type of molecule kernels), and in social network analysis. (en)
dcterms:subject	Kernel methods for machine learning Graph algorithms
Wikipage page ID	39419087 (xsd:integer)
Wikipage revision ID	1092188906 (xsd:integer)
Link from a Wikipage to another Wikipage	Kernel methods for machine learning Social network analysis Feature extraction Path (graph theory) Graph algorithms John D. Lafferty Feature vector Graph (abstract data type) Tensor product of graphs Hyperlink Bioinformatics Support vector machine Positive-definite kernel Inner product space Random walk World Wide Web Structure mining Kernel trick Tree kernel Molecule mining Chemoinformatics Molecule kernel
sameAs	Graph kernel Graph kernel Graph kernel Graph kernel Graph kernel
dbp:wikiPageUsesTemplate	dbt:About dbt:Comp-sci-stub dbt:Reflist
has abstract	In structure mining, a graph kernel is a kernel function that computes an inner product on graphs. Graph kernels can be intuitively understood as functions measuring the similarity of pairs of graphs. They allow kernelized learning algorithms such as support vector machines to work directly on graphs, without having to do feature extraction to transform them to fixed-length, real-valued feature vectors. They find applications in bioinformatics, in chemoinformatics (as a type of molecule kernels), and in social network analysis. Concepts of graph kernels have been around since the 1999, when D. Haussler introduced convolutional kernels on discrete structures. The term graph kernels was more officially coined in 2002 by R. I. Kondor and J. Laffertyas kernels on graphs, i.e. similarity functions between the nodes of a single graph, with the World Wide Web hyperlink graph as a suggested application. In 2003, Gaertner et al.and Kashima et al.defined kernels between graphs. In 2010, Vishwanathan et al. gave their unified framework. In 2018, Ghosh et al. described the history of graph kernels and their evolution over two decades. (en) Jądro grafu – podzbiór wierzchołków grafu skierowanego taki, że: * wierzchołki z jądra nie przewyższają się nawzajem (nie posiadają następników) * każdy wierzchołek grafu nie należący do jądra jest przewyższany przez co najmniej jeden wierzchołek z jądra. Każdy wierzchołek izolowany w grafie należy jednocześnie do jądra. (pl)
gold:hypernym	Function
prov:wasDerivedFrom	wikipedia-en:Graph_kernel?oldid=1092188906&ns=0
page length (characters) of wiki page	5494 (xsd:nonNegativeInteger)
foaf:isPrimaryTopicOf	wikipedia-en:Graph_kernel
is Link from a Wikipage to another Wikipage of	Quantitative structure–activity relationship Kernel method Kernel methods for vector output John D. Lafferty Graph Fourier transform Structure mining Tree kernel Molecule mining Outline of machine learning
is foaf:primaryTopic of	wikipedia-en:Graph_kernel

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