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Efficient algorithms for updating betweenness centrality in fully dynamic graphs

机译:在全动态图中更新中间性中心的高效算法

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摘要

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. (C) 2015 Elsevier Inc. All rights reserved.
机译:图中顶点(边缘)的中间居中性是度量顶点(边缘)在图中最短路径中的相对参与程度的度量。中间性中间性在生物学,交通和社会网络等各个领域中得到广泛使用。在本文中,我们研究了完全动态图中中介中心性的更新问题。所提出的更新算法大大减少了最短路径的数量,当更改图形时应重新计算这些最短路径。此外,我们使用提出的算法对社区检测算法进行了调整,以显示在实际应用中可以从提出的算法中获得多少收益。在真实图形上的实验结果表明,所提出的算法有效地更新了中间性中心和检测图形中的社区。 (C)2015 Elsevier Inc.保留所有权利。

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