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A GPU-based solution for fast calculation of the betweenness centrality in large weighted networks
2017
PeerJ Computer Science
Betweenness, a widely employed centrality measure in network science, is a decent proxy for investigating network loads and rankings. However, its extremely high computational cost greatly hinders its applicability in large networks. Although several parallel algorithms have been presented to reduce its calculation cost for unweighted networks, a fast solution for weighted networks, which are commonly encountered in many realistic applications, is still lacking. In this study, we develop an
doi:10.7717/peerj-cs.140
fatcat:pnwzap6dsbcjphb4bwent7hcsi