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Quick Detection of Nodes with Large Degrees

Abstract : Our goal is to find top-k lists of nodes with the largest degrees in large complex networks quickly. If the adjacency list of the network is known (not often the case in complex networks), a deterministic algorithm to find the top-k list of nodes with the largest degrees requires an average complexity of O(n), where n is the number of nodes in the network. Even this modest complexity can be very high for large complex networks. We propose to use a random-walk-based method. We show theoretically and by numerical experiments that for large networks, the random-walk method finds good-quality top lists of nodes with high probability and with computational savings of orders of magnitude. We also propose stopping criteria for the random-walk method that requires very little knowledge about the structure of the network.
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Contributor : Konstantin Avrachenkov Connect in order to contact the contributor
Submitted on : Monday, December 8, 2014 - 3:08:54 PM
Last modification on : Thursday, January 20, 2022 - 5:30:44 PM

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Konstantin Avrachenkov, Nelly Litvak, Marina Sokol, Don Towsley. Quick Detection of Nodes with Large Degrees. Internet Mathematics, Taylor & Francis, 2014, 10 (1-2), pp.1-19. ⟨10.1080/15427951.2013.798601⟩. ⟨hal-01092304⟩



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