Spectral methods for graph clustering – A survey

Graph clustering is an area in cluster analysis that looks for groups of related vertices in a graph. Due to its large applicability, several graph clustering algorithms have been proposed in the last years. A particular class of graph clustering algorithms is known as spectral clustering algorithms...

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Veröffentlicht in:	European journal of operational research Jg. 211; H. 2; S. 221 - 231
Hauptverfasser:	Nascimento, Mariá C.V., de Carvalho, André C.P.L.F.
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Amsterdam Elsevier B.V 01.06.2011 Elsevier Elsevier Sequoia S.A
Schriftenreihe:	European Journal of Operational Research
Schlagworte:	Algorithmics. Computability. Computer arithmetics Algorithms Applied sciences Cluster analysis Clustering Computer science; control theory; systems Cutting stock problem Data processing. List processing. Character string processing Exact sciences and technology Graph algorithms Graphs Information retrieval. Graph Laplace transforms Mathematical analysis Matrix Memory organisation. Data processing Min-cut Modularity ncut Operational research Partitioning Ratio cut Software Spectra Spectral clustering Spectral clustering Min-cut Ratio cut ncut Modularity Spectral methods Studies Theoretical computing Spectral clustering Ratio cut Modularity Min-cut ncut Cluster analysis Spectral method Modular system Graph theory Data mining Weighted graph Laplacian Graph decomposition Graph cut Classification Graph method
ISSN:	0377-2217, 1872-6860
Online-Zugang:	Volltext
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