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2011

The Push Algorithm for Spectral Ranking

Boldi, Paolo, Vigna, Sebastiano

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Understand

The push algorithm was proposed first by Jeh and Widom in the context of personalized PageRank computations (albeit the name "push algorithm" was actually used by Andersen, Chung and Lang in a subsequent paper).

In this note we describe the algorithm at a level of generality that make the computation of the spectral ranking of any nonnegative matrix possible.
Actually, the main contribution of this note is that the description is very simple (almost trivial), and it requires only a few elementary linear-algebra computations.
Along the way, we give new precise ways of estimating the convergence of the algorithm, and describe some of the contribution of the existing literature, which again turn out to be immediate when recast in our framework.

The Push Algorithm for Spectral Ranking · Around

Built on

The PageRank citation ranking: Bringing order to the web
Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd · 1998
Earlier work this paper cites.
Scaling personalized web search
Glen Jeh and Jennifer Widom · 2003
Earlier work this paper cites.
Bookmark-coloring approach to personalized PageRank computing
Pavel Berkhin · 2006
Earlier work this paper cites.

Similar

Graph fibrations, graph isomorphism, and PageRank
Paolo Boldi, Violetta Lonati, Massimo Santini, and Sebastiano Vigna · 2006
Cited alongside, same era.
Using PageRank to locally partition a graph
Reid Andersen, Fan R. K. Chung, and Kevin J. Lang · 2007
Cited alongside, same era.
Traps and pitfalls of topic-biased PageRank
Paolo Boldi, Roberto Posenato, Massimo Santini, and Sebastiano Vigna · 2008
Cited alongside, same era.

Then

PageRank: Functional dependencies
Paolo Boldi, Massimo Santini, and Sebastiano Vigna · 2009
Later among the works it cites.
Spectral ranking, 2009
Sebastiano Vigna · 2009
Later among the works it cites.

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