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Bayesovská centrálnost podle průchodnosti×Mezilehlostní centralita×
OborAnalýza sítíAnalýza sítí
RodinaMachine learningMachine learning
Rok vzniku2010s1977
TvůrceBrandes, U. (betweenness); Bayesian extension developed by multiple authors (2010s)Freeman, L. C.
TypProbabilistic network centrality measureCentrality measure
Původní zdrojNewman, M.E.J. (2010). Networks: An Introduction. Oxford University Press. ISBN: 978-0-19-920665-0Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41. DOI ↗
Další názvyBayesian BC, probabilistic betweenness centrality, uncertainty-aware betweenness centrality, posterior betweenness estimationFreeman betweenness, BC, geodesic betweenness, shortest-path betweenness
Příbuzné36
ShrnutíBayesian Betweenness Centrality estimates how often a node lies on shortest paths in a network while explicitly quantifying uncertainty arising from incomplete, sampled, or noisy edge observations. Rather than producing a single point estimate, it yields a posterior distribution over betweenness scores, enabling credible intervals and probabilistic comparisons between nodes.Betweenness centrality, formalized by Linton C. Freeman in 1977, measures how often a node lies on the shortest path connecting every other pair of nodes in a network. High-betweenness nodes act as bridges or brokers: removing them fragments the network into disconnected components more severely than removing any other nodes.
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ScholarGatePorovnat metody: Bayesian Betweenness Centrality · Betweenness Centrality. Získáno 2026-06-15 z https://scholargate.app/cs/compare