GreediRIS: Scalable influence maximization using distributed streaming maximum cover

Influence maximization—the problem of identifying a subset of k influential seeds (vertices) in a network—is a classical problem in network science with numerous applications. The problem is NP-hard, but there exist efficient polynomial time approximations. However, scaling these algorithms still re...

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Veröffentlicht in:	Journal of parallel and distributed computing Jg. 198; S. 105037
Hauptverfasser:	Barik, Reet, Cappa, Wade, Ferdous, S.M., Minutoli, Marco, Halappanavar, Mahantesh, Kalyanaraman, Ananth
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States Elsevier Inc 01.04.2025 Elsevier
Schlagworte:	Distributed influence maximization Distributed submodular maximization Parallel graph algorithms Streaming maximum k-cover Distributed submodular maximization Streaming maximum k-cover Distributed influence maximization Parallel graph algorithms
ISSN:	0743-7315
Online-Zugang:	Volltext
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