Quasi-stationary distributions as centrality measures of reducible graphs - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Reports (Research Report) Year : 2007

Quasi-stationary distributions as centrality measures of reducible graphs

Abstract

Random walk can be used as a centrality measure of a directed graph. However, if the graph is reducible the random walk will be absorbed in some subset of nodes and will never visit the rest of the graph. In Google PageRank the problem was solved by introduction of uniform random jumps with some probability. Up to the present, there is no clear criterion for the choice this parameter. We propose to use parameter-free centrality measure which is based on the notion of quasi-stationary distribution. Specifically we suggest four quasi-stationary based centrality measures, analyze them and conclude that they produce approximately the same ranking. The new centrality measures can be applied in spam detection to detect ``link farms'' and in image search to find photo albums.
Fichier principal
Vignette du fichier
RR-6263.pdf (264.07 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

inria-00166333 , version 1 (03-08-2007)
inria-00166333 , version 2 (08-08-2007)

Identifiers

  • HAL Id : inria-00166333 , version 2
  • ARXIV : 0708.0522

Cite

Konstantin Avrachenkov, Vivek S. Borkar, Danil Nemirovsky. Quasi-stationary distributions as centrality measures of reducible graphs. [Research Report] RR-6263, INRIA. 2007, pp.19. ⟨inria-00166333v2⟩
108 View
52 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More