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Fully Dynamic Betweenness Centrality Maintenance on Massive Networks

Summary: Fully dynamic method for maintaining betweenness centrality of all vertices in massive networks. Uses a weighted hyperedge shortest-path sketch (hypergraph sketch) plus two indices (two-ball, reachability) to accelerate updates, delivering millisecond updates on 100M–3.7B-edge graphs with accuracy guarantees, and experiments show real-world scalability across large networks. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11338
Venue
VLDB
Year
2016
Pagerank
4.4937074e-05
Overall Rank
8,542 | 40.58%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
11,064 Efficient Betweenness Centrality Computation over Large Heterogeneous Information Networks 2024 VLDB 4.1945683e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank Cited Paper Year Venue Pagerank
1,777 Reachability Queries on Large Dynamic Graphs: A Total Order Approach 2014 SIGMOD 0.00010589591
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