Improving Random Walk Estimation Accuracy with Uniform Restarts

  • Konstantin Avrachenkov
  • Bruno Ribeiro
  • Don Towsley
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6516)


This work proposes and studies the properties of a hybrid sampling scheme that mixes independent uniform node sampling and random walk (RW)-based crawling. We show that our sampling method combines the strengths of both uniform and RW sampling while minimizing their drawbacks. In particular, our method increases the spectral gap of the random walk, and hence, accelerates convergence to the stationary distribution. The proposed method resembles PageRank but unlike PageRank preserves time-reversibility. Applying our hybrid RW to the problem of estimating degree distributions of graphs shows promising results.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Konstantin Avrachenkov
    • 1
  • Bruno Ribeiro
    • 2
  • Don Towsley
    • 2
  1. 1.INRIASophia-AntipolisFrance
  2. 2.Dept. of Computer ScienceUniversity of Massachusetts AmherstAmherstUSA

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