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A Faster Algorithm to Update Betweenness Centrality after Node Alteration

机译：节点改建后更新居中性之间的速度较快算法

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摘要

Betweenness centrality is a centrality measure that is widely used, with applications across several disciplines. It is a measure which quantifies the importance of a vertex based on its occurrence in shortest paths between all possible pairs of vertices in a graph. This is a global measure, and in order to find the betweenness centrality of a node, one is supposed to have complete information about the graph. Most of the algorithms that are used to find betwenness centrality assume the constancy of the graph and are not efficient for dynamic networks. We propose a technique to update betweenness centrality of a graph when nodes are added or deleted. Our algorithm experimentally speeds up the calculation of betweenness centrality (after updation) from 7 to 412 times, for real graphs, in comparison to the currently best known technique to find betweenness centrality.
机译：中心性之间是一种广泛使用的中心度量，在几个学科中有应用程序。它是一种量度，其基于其在图表中所有可能对顶点之间的最短路径中的发生基础上的重要性。这是一个全球措施，并且为了找到节点之间的中心中心，一个应该有关于图表的完整信息。用于查找间中心性的大多数算法假设图形的恒定性，并且对动态网络不高效率。当添加或删除节点时，我们提出了一种技术来更新图形的中心性之间的中心性。与当前最着名的技术相比，我们的算法通过7至412次从7到412次开始计算从7到412次之间的计算（经过更新）的计算。

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