Efficient algorithms for updating betweenness centrality in fully dynamic graphs

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Betweenness centrality of a vertex (edge) in a graph is a measure for the relative participation of the vertex (edge) in the shortest paths in the graph. Betweenness centrality is widely used in various areas such as biology, transportation, and social networks. In this paper, we study the update problem of betweenness centrality in fully dynamic graphs. The proposed update algorithm substantially reduces the number of shortest paths which should be re-computed when a graph is changed. In addition, we adapt a community detection algorithm using the proposed algorithm to show how much benefit can be obtained from the proposed algorithm in a practical application. Experimental results on real graphs show that the proposed algorithm efficiently update betweenness centrality and detect communities in a graph.
Publisher
ELSEVIER SCIENCE INC
Issue Date
2016-01
Language
English
Article Type
Article
Citation

INFORMATION SCIENCES, v.326, pp.278 - 296

ISSN
0020-0255
DOI
10.1016/j.ins.2015.07.053
URI
http://hdl.handle.net/10203/205492
Appears in Collection
CS-Journal Papers(저널논문)
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