The power of local information in PageRank

Marco Bressan 1 Enoch Peserico 2 Luca Pretto 3
1 TAO - Machine Learning and Optimisation
LRI - Laboratoire de Recherche en Informatique, UP11 - Université Paris-Sud - Paris 11, Inria Saclay - Ile de France, CNRS - Centre National de la Recherche Scientifique : UMR8623
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?).
Type de document :
Communication dans un congrès
WWW 2013 - 22nd International World Wide Web Conference, May 2013, Rio de Janeiro, Brazil. ACM, WWW '13 Companion Proceedings of the 22nd International Conference on World Wide Web, pp.179-180, 2013, 〈http://www2013.w3c.br/〉. 〈10.1145/2487788.2487878〉
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https://hal.inria.fr/hal-00862816
Contributeur : Marco Bressan <>
Soumis le : mardi 17 septembre 2013 - 15:22:39
Dernière modification le : jeudi 14 juin 2018 - 10:54:03

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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. ACM, WWW '13 Companion Proceedings of the 22nd International Conference on World Wide Web, pp.179-180, 2013, 〈http://www2013.w3c.br/〉. 〈10.1145/2487788.2487878〉. 〈hal-00862816〉

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