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Copy file name to clipboardExpand all lines: doc/asciidoc/algorithms/alpha/influence-maximization/celf.adoc
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@@ -25,7 +25,7 @@ The CELF algorithm for influence maximization aims to find `k` nodes that maximi
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It simulates the influence spread using the Independent Cascade model, which calculates the expected spread by taking the average spread over the `mc` Monte-Carlo simulations.
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In the propagation process, a node is influenced in case that a uniform random draw is less than the probability `p`.
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Leskovec et al. 2007 introduced the CELF algorithm in their study "https://www.cs.cmu.edu/~jure/pubs/detect-kdd07.pdf[Cost-effective Outbreak Detection in Networks]" to deal with the NP-hard problem of influence maximization.
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Leskovec et al. 2007 introduced the CELF algorithm in their study https://www.cs.cmu.edu/~jure/pubs/detect-kdd07.pdf[Cost-effective Outbreak Detection in Networks] to deal with the NP-hard problem of influence maximization.
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The CELF algorithm is based on a "lazy-forward" optimization.
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Τhe CELF algorithm dramatically improves the efficiency of the <<algorithms-greedy, Greedy>> algorithm and should be preferred for large networks.
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