Approximating PageRank from In-Degree

  • Santo Fortunato
  • Marián Boguñá
  • Alessandro Flammini
  • Filippo Menczer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4936)

Abstract

PageRank is a key element in the success of search engines, allowing to rank the most important hits in the top screen of results. One key aspect that distinguishes PageRank from other prestige measures such as in-degree is its global nature. From the information provider perspective, this makes it difficult or impossible to predict how their pages will be ranked. Consequently a market has emerged for the optimization of search engine results. Here we study the accuracy with which PageRank can be approximated by in-degree, a local measure made freely available by search engines. Theoretical and empirical analyses lead to conclude that given the weak degree correlations in the Web link graph, the approximation can be relatively accurate, giving service and information providers an effective new marketing tool.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Santo Fortunato
    • 1
    • 2
  • Marián Boguñá
    • 3
  • Alessandro Flammini
    • 1
  • Filippo Menczer
    • 1
  1. 1.School of InformaticsIndiana UniversityBloomingtonUSA
  2. 2.Complex Networks Lagrange Laboratory (CNLL)ISI FoundationTorinoItaly
  3. 3.Departament de Física FonamentalUniversitat de BarcelonaBarcelonaSpain

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