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A survey of frequent subgraph mining algorithms

Published online by Cambridge University Press:  20 November 2012

Chuntao Jiang ,
Frans Coenen  and
Michele Zito
Chuntao Jiang
Affiliation:
Department of Computer Science, The University of Liverpool, Ashton Building, Ashton Street, Liverpool L69 3BX, UK; e-mail: [email protected], [email protected], [email protected]
Frans Coenen
Affiliation:
Department of Computer Science, The University of Liverpool, Ashton Building, Ashton Street, Liverpool L69 3BX, UK; e-mail: [email protected], [email protected], [email protected]
Michele Zito
Affiliation:
Department of Computer Science, The University of Liverpool, Ashton Building, Ashton Street, Liverpool L69 3BX, UK; e-mail: [email protected], [email protected], [email protected]
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Abstract

Graph mining is an important research area within the domain of data mining. The field of study concentrates on the identification of frequent subgraphs within graph data sets. The research goals are directed at: (i) effective mechanisms for generating candidate subgraphs (without generating duplicates) and (ii) how best to process the generated candidate subgraphs so as to identify the desired frequent subgraphs in a way that is computationally efficient and procedurally effective. This paper presents a survey of current research in the field of frequent subgraph mining and proposes solutions to address the main research issues.

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Articles
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The Knowledge Engineering Review , Volume 28 , Issue 1 , March 2013 , pp. 75 - 105
Copyright
Copyright © Cambridge University Press 2012

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