A survey of frequent subgraph mining algorithms

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 duplica...

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Bibliographic Details
Published inKnowledge engineering review Vol. 28; no. 1; pp. 75 - 105
Main Authors Jiang, Chuntao, Coenen, Frans, Zito, Michele
Format Journal Article
LanguageEnglish
Published Cambridge, UK Cambridge University Press 01.03.2013
Subjects
Algorithms
Computational efficiency
Concentrates
Data mining
Graph representations
Graphs
Knowledge engineering
Reproduction
Online AccessGet full text
ISSN0269-8889
1469-8005
DOI10.1017/S0269888912000331

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Summary: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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ISSN:0269-8889
1469-8005
DOI:10.1017/S0269888912000331