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On Modularity Clustering

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BRANDES, Ulrik, Daniel DELLING, Marco GAERTLER, Robert GÖRKE, Martin HOEFER, Zoran NIKOLOSKI, Dorothea WAGNER, 2008. On Modularity Clustering. In: IEEE Transactions on Knowledge and Data Engineering. 20(2), pp. 172-188. Available under: doi: 10.1109/TKDE.2007.190689

@article{Brandes2008Modul-5853, title={On Modularity Clustering}, year={2008}, doi={10.1109/TKDE.2007.190689}, number={2}, volume={20}, journal={IEEE Transactions on Knowledge and Data Engineering}, pages={172--188}, author={Brandes, Ulrik and Delling, Daniel and Gaertler, Marco and Görke, Robert and Hoefer, Martin and Nikoloski, Zoran and Wagner, Dorothea} }

<rdf:RDF xmlns:dcterms="" xmlns:dc="" xmlns:rdf="" xmlns:bibo="" xmlns:dspace="" xmlns:foaf="" xmlns:void="" xmlns:xsd="" > <rdf:Description rdf:about=""> <dcterms:isPartOf rdf:resource=""/> <dcterms:available rdf:datatype="">2011-03-24T16:00:42Z</dcterms:available> <dc:contributor>Gaertler, Marco</dc:contributor> <dc:creator>Brandes, Ulrik</dc:creator> <bibo:uri rdf:resource=""/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <dc:creator>Delling, Daniel</dc:creator> <dc:contributor>Brandes, Ulrik</dc:contributor> <dc:creator>Nikoloski, Zoran</dc:creator> <dspace:hasBitstream rdf:resource=""/> <dc:creator>Hoefer, Martin</dc:creator> <dc:date rdf:datatype="">2011-03-24T16:00:42Z</dc:date> <dc:format>application/pdf</dc:format> <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights> <dcterms:title>On Modularity Clustering</dcterms:title> <dc:language>eng</dc:language> <dc:contributor>Hoefer, Martin</dc:contributor> <dc:contributor>Görke, Robert</dc:contributor> <dc:creator>Görke, Robert</dc:creator> <dcterms:abstract xml:lang="eng">Modularity is a recently introduced quality measure for graph clusterings. It has immediately received considerable attention in several disciplines, and in particular in the complex systems literature, although its properties are not well understood. We study the problem of finding clusterings with maximum modularity, thus providing theoretical foundations for past and present work based on this measure. More precisely, we prove the conjectured hardness of maximizing modularity both in the general case and with the restriction to cuts, and give an Integer Linear Programming formulation. This is complemented by first insights into the behavior and performance of the commonly applied greedy agglomerative approach.</dcterms:abstract> <dcterms:hasPart rdf:resource=""/> <dc:contributor>Nikoloski, Zoran</dc:contributor> <dc:creator>Wagner, Dorothea</dc:creator> <dc:creator>Gaertler, Marco</dc:creator> <dc:contributor>Delling, Daniel</dc:contributor> <dc:contributor>Wagner, Dorothea</dc:contributor> <foaf:homepage rdf:resource="http://localhost:8080/jspui"/> <dcterms:issued>2008</dcterms:issued> <dspace:isPartOfCollection rdf:resource=""/> <dcterms:rights rdf:resource=""/> <dcterms:bibliographicCitation>First publ. in: IEEE Transactions on Knowledge and Data Engineering ; 20 (2008), 2. - S. 172-188</dcterms:bibliographicCitation> </rdf:Description> </rdf:RDF>

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