Incorporating auxiliary information in betweenness measure for input-output networks
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Publication:2096770
DOI10.1016/j.physa.2022.128200OpenAlexW4296545198MaRDI QIDQ2096770
Shiying Xiao, Panpan Zhang, Jun Yan
Publication date: 11 November 2022
Published in: Physica A (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.physa.2022.128200
supply chainauxiliary informationDijkstra's algorithminput-output analysisbetweenness centralitystrongest path
Small world graphs, complex networks (graph-theoretic aspects) (05C82) Statistical mechanics, structure of matter (82-XX)
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Cites Work
- A note on two problems in connexion with graphs
- Fast approximation of betweenness centrality through sampling
- Dynamical topology of highly aggregated input-output networks
- Input-output networks offer new insights of economic structure
- A faster algorithm for betweenness centrality*
- Input-Output Analysis
- Stability and Continuity of Centrality Measures in Weighted Graphs
- KADABRA is an ADaptive Algorithm for Betweenness via Random Approximation
- Better Approximation of Betweenness Centrality
- Approximating Betweenness Centrality
- CENTRALITY ESTIMATION IN LARGE NETWORKS
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