Scalable Online Betweenness Centrality in Evolving Graphs
نویسندگان
چکیده
منابع مشابه
Further Results on Betweenness Centrality of Graphs
Betweenness centrality is a distance-based invariant of graphs. In this paper, we use lexicographic product to compute betweenness centrality of some important classes of graphs. Finally, we pose some open problems related to this topic.
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Betweenness centrality ranks the importance of nodes by their participation in all shortest paths of the network. Therefore computing exact betweenness values is impractical in large networks. For static networks, approximation based on randomly sampled paths has been shown to be significantly faster in practice. However, for dynamic networks, no approximation algorithm for betweenness centrali...
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Finding central nodes is a fundamental problem in network analysis. Betweenness centrality is a well-known measure which quantifies the importance of a node based on the fraction of shortest paths going though it. Due to the dynamic nature of many today’s networks, algorithms that quickly update centrality scores have become a necessity. For betweenness, several dynamic algorithms have been pro...
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We present fully dynamic algorithms for maintaining betweenness centrality (BC) of vertices in a directed graph G = (V,E) with positive edge weights. BC is a widely used parameter in the analysis of large complex networks. We achieve an amortized O(ν∗ · log n) time per update with our basic algorithm, and O(ν∗ · log n) time with a more complex algorithm, where n = |V |, and ν∗ bounds the number...
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ژورنال
عنوان ژورنال: IEEE Transactions on Knowledge and Data Engineering
سال: 2015
ISSN: 1041-4347
DOI: 10.1109/tkde.2015.2419666