Linganisha mbinu

	Uthabiti wa Kati kati ya Bayesian (Bayesian Betweenness Centrality)	Ukalimani Kati
Nyanja	Uchanganuzi wa Mitandao	Uchanganuzi wa Mitandao
Familia	Machine learning	Machine learning
Mwaka wa asili	2010s	1977
Mwanzilishi	Brandes, U. (betweenness); Bayesian extension developed by multiple authors (2010s)	Freeman, L. C.
Aina	Probabilistic network centrality measure	Centrality measure
Chanzo asilia	Newman, M.E.J. (2010). Networks: An Introduction. Oxford University Press. ISBN: 978-0-19-920665-0	Freeman, L. C. (1977). A set of measures of centrality based on betweenness. Sociometry, 40(1), 35–41.
Majina mbadala	Bayesian BC, probabilistic betweenness centrality, uncertainty-aware betweenness centrality, posterior betweenness estimation	Freeman betweenness, BC, geodesic betweenness, shortest-path betweenness
Zinazohusiana	3	6
Muhtasari	Bayesian 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.