Parallel Algorithm for Incremental Betweenness Centrality on Large Graphs

Betweenness centrality quantifies the importance of nodes in a graph in many applications, including network analysis, community detection and identification of influential users. Typically, graphs in such applications evolve over time. Thus, the computation of betweenness centrality should be perfo...

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Veröffentlicht in:	IEEE transactions on parallel and distributed systems Jg. 29; H. 3; S. 659 - 672
Hauptverfasser:	Jamour, Fuad, Skiadopoulos, Spiros, Kalnis, Panos
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York IEEE 01.03.2018 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithm design and analysis Algorithms Betweenness centrality dynamic graph algorithms Graphs Heuristic algorithms Measurement Memory management Network analysis Parallel algorithms parallel graph algorithms Random access memory Social network services State of the art
ISSN:	1045-9219, 1558-2183
Online-Zugang:	Volltext
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