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Betweenness centrality - Incremental and faster
Published in Springer Verlag
2014
Volume: 8635 LNCS
   
Issue: PART 2
Pages: 577 - 588
Abstract
We present an incremental algorithm that updates the betweenness centrality (BC) score of all vertices in a graph G when a new edge is added to G, or the weight of an existing edge is reduced. Our incremental algorithm runs in O(v * · n) time, where v * is bounded by m *, the number of edges that lie on a shortest path in G. We achieve the same bound for the more general incremental vertex update problem. Even for a single edge update, our incremental algorithm is the first algorithm that is provably faster on sparse graphs than recomputing with the well-known static Brandes algorithm. It is also likely to be much faster than Brandes on dense graphs since m * is often close to linear in n. Our incremental algorithm is very simple, and we give an efficient cache-oblivious implementation that incurs O(n · sort(v *)) cache misses, where sort is a well-known measure for caching efficiency. © 2014 Springer-Verlag Berlin Heidelberg.
About the journal
JournalData powered by TypesetLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherData powered by TypesetSpringer Verlag
ISSN03029743
Open AccessYes
Concepts (10)
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    Algorithms
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    BETWEENNESS CENTRALITY
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    CACHE MISS
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    CACHE-OBLIVIOUS
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    DENSE GRAPHS
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    INCREMENTAL ALGORITHM
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    RE-COMPUTING
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    Shortest path
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    SPARSE GRAPHS
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    Graph theory