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The power of local information in PageRank

Marco Bressan 1 Enoch Peserico 2 Luca Pretto 3
1 TAO - Machine Learning and Optimisation
CNRS - Centre National de la Recherche Scientifique : UMR8623, Inria Saclay - Ile de France, UP11 - Université Paris-Sud - Paris 11, LRI - Laboratoire de Recherche en Informatique
Abstract : Can one assess, by visiting only a small portion of a graph, if a given node has a significantly higher PageRank score than another? We show that the answer strongly depends on the interplay between the required correctness guarantees (is one willing to accept a small probability of error?) and the graph exploration model (can one only visit parents and children of already visited nodes?).
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https://hal.inria.fr/hal-00862816
Contributor : Marco Bressan <>
Submitted on : Tuesday, September 17, 2013 - 3:22:39 PM
Last modification on : Tuesday, April 21, 2020 - 1:06:19 AM

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Marco Bressan, Enoch Peserico, Luca Pretto. The power of local information in PageRank. WWW 2013 - 22nd International World Wide Web Conference, May 2013, Rio de Janeiro, Brazil. pp.179-180, ⟨10.1145/2487788.2487878⟩. ⟨hal-00862816⟩

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