An Efficient Approximation of Betweenness Centrality for Uncertain Graphs

Betweenness centrality measures the centrality of nodes and edges in a graph based on the concept of shortest paths. However, such a definition is unsuitable for uncertain graphs due to the uncertainty of links. In the possible-world semantics, the Monte Carlo method is proposed to estimate the betw...

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Bibliographic Details
Main Authors: Chenxu Wang, Ziyuan Lin
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8710331/

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