Internet Mathematics

Random Alpha PageRank

Paul G. Constantine and David F. Gleich

Full-text: Open access

Abstract

We suggest a revision to the PageRank random surfer model that considers the influence of a population of random surfers on the PageRank vector. In the revised model, each member of the population has its own teleportation parameter chosen from a probability distribution, and consequently, the ranking vector is random. We propose three algorithms for computing the statistics of the random ranking vector based respectively on (i) random sampling, (ii) paths along the links of the underlying graph, and (iii) quadrature formulas. We find that the expectation of the random ranking vector produces similar rankings to its deterministic analogue, but the standard deviation gives uncorrelated information (under a Kendall-tau metric) with myriad potential uses. We examine applications of this model to web spam.

Article information

Source
Internet Math., Volume 6, Number 2 (2009), 189-236.

Dates
First available in Project Euclid: 24 September 2010

Permanent link to this document
https://projecteuclid.org/euclid.im/1285339073

Mathematical Reviews number (MathSciNet)
MR2743239

Zentralblatt MATH identifier
1210.68135

Citation

Constantine, Paul G.; Gleich, David F. Random Alpha PageRank. Internet Math. 6 (2009), no. 2, 189--236. https://projecteuclid.org/euclid.im/1285339073


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