Engineering Parallel Algorithms for Community Detection in Massive Networks

The amount of graph-structured data has recently experienced an enormous growth in many applications. To transform such data into useful information, fast analytics algorithms and software tools are necessary. One common graph analytics kernel is disjoint community detection (or graph clustering). D...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems Jg. 27; H. 1; S. 171 - 184
Hauptverfasser:	Staudt, Christian L., Meyerhenke, Henning
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	IEEE 01.01.2016
Schlagworte:	Algorithm design and analysis Clustering algorithms Communities Disjoint community detection graph clustering Image edge detection Instruction sets network analysis parallel algorithm engineering parallel Louvain method Parallel processing Software algorithms network analysis Disjoint community detection parallel Louvain method parallel algorithm engineering graph clustering
ISSN:	1045-9219
Online-Zugang:	Volltext
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