Comparison of Local and Global Ranking in Networks

  • Šárka Zehnalová
  • Miloš Kudělka
  • Zdeněk Horák
  • Pavel Krömer
  • Václav Snášel
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 303)

Abstract

Many real world data and processes have a network structure and can usefully be represented as graphs. Network analysis focuses on the relations among the nodes exploring the properties of each network. Latest trend in analyzing networks is to focus on local methods and parallelization. We introduce a method to find the ranking of the nodes. The approach extracts dependency relations among the network’s nodes. Key technical parameter of the approach is locality. Since only the surrounding of examined nodes is used in computations, there is no need to analyze the entire network. We compare this proposed local ranking to the global ranking of PageRank. We present experiment using large-scale artificial and real world networks. The results of experiment show high effectiveness due to the locality of our approach and also high quality of node ranking comparable to PageRank.

Keywords

complex networks graphs node weighting dependency ranking 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Šárka Zehnalová
    • 1
  • Miloš Kudělka
    • 1
  • Zdeněk Horák
    • 2
  • Pavel Krömer
    • 1
  • Václav Snášel
    • 1
  1. 1.VSB - Technical University of OstravaOstravaCzech Republic
  2. 2.Inflex, s.r.o.OstravaCzech Republic

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