Heuristic algorithm for approximation betweenness centrality using graph coarsening
M Chernoskutov, Y Ineichen, C Bekas - Procedia Computer Science, 2015 - Elsevier
Nowadays, graph analytics are widely used in many research fields and applications. One
important analytic that measures the influence of each vertex on flows through the network …
important analytic that measures the influence of each vertex on flows through the network …
A faster algorithm to update betweenness centrality after node alteration
Betweenness centrality is widely used as a centrality measure, with applications across
several disciplines. It is a measure that quantifies the importance of a vertex based on the …
several disciplines. It is a measure that quantifies the importance of a vertex based on the …
Fully-dynamic approximation of betweenness centrality
E Bergamini, H Meyerhenke - … , Patras, Greece, September 14-16, 2015 …, 2015 - Springer
Betweenness is a well-known centrality measure that ranks the nodes of a network
according to their participation in shortest paths. Since an exact computation is prohibitive in …
according to their participation in shortest paths. Since an exact computation is prohibitive in …
Parallel algorithm for incremental betweenness centrality on large graphs
F Jamour, S Skiadopoulos… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Betweenness centrality quantifies the importance of nodes in a graph in many applications,
including network analysis, community detection and identification of influential users …
including network analysis, community detection and identification of influential users …
A benchmark for betweenness centrality approximation algorithms on large graphs
Betweenness centrality quantifies the importance of graph nodes in a variety of applications
including social, biological and communication networks. Its computation is very costly for …
including social, biological and communication networks. Its computation is very costly for …
Shattering and compressing networks for centrality analysis
Who is more important in a network? Who controls the flow between the nodes or whose
contribution is significant for connections? Centrality metrics play an important role while …
contribution is significant for connections? Centrality metrics play an important role while …
An efficient estimation of a node's betweenness
Betweenness Centrality measures, erstwhile popular amongst the sociologists and
psychologists, have seen wide and increasing applications across several disciplines of …
psychologists, have seen wide and increasing applications across several disciplines of …
A Faster Algorithm for Betweenness Centrality Based on Adjacency Matrices
Y Feng, H Wang - arXiv preprint arXiv:2205.00162, 2022 - arxiv.org
Betweenness centrality is essential in complex network analysis; it characterizes the
importance of nodes and edges in networks. It is a crucial problem that exactly computes the …
importance of nodes and edges in networks. It is a crucial problem that exactly computes the …
Almost linear-time algorithms for adaptive betweenness centrality using hypergraph sketches
Y Yoshida - Proceedings of the 20th ACM SIGKDD international …, 2014 - dl.acm.org
Betweenness centrality measures the importance of a vertex by quantifying the number of
times it acts as a midpoint of the shortest paths between other vertices. This measure is …
times it acts as a midpoint of the shortest paths between other vertices. This measure is …
[HTML][HTML] Estimation and update of betweenness centrality with progressive algorithm and shortest paths approximation
N Xiang, Q Wang, M You - Scientific Reports, 2023 - nature.com
Betweenness centrality is one of the key measures of the node importance in a network.
However, it is computationally intractable to calculate the exact betweenness centrality of …
However, it is computationally intractable to calculate the exact betweenness centrality of …
