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