A new approach for aggregated PageRank computation via distributed randomized algorithms

Hideaki Ishii; Roberto Tempo; Er-Wei Bai

doi:10.1109/CDC.2011.6160880

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Conference proceeding

A new approach for aggregated PageRank computation via distributed randomized algorithms

Hideaki Ishii, Roberto Tempo and Er-Wei Bai

2011 50th IEEE Conference on Decision and Control and European Control Conference, Vol.No, pp.6421-6426

12/2011

DOI: 10.1109/CDC.2011.6160880

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Abstract

At Google, the PageRank algorithm helps rankings in search results by providing measures of web page importance. This paper builds upon the distributed randomized approach for this algorithm proposed in our recent works. To reduce computation and communication, we develop a method to systematically aggregate web pages into groups by exploiting the sparsity inherent in the web. Each group computes an aggregated PageRank, which can be distributed among group members. We provide a decentralized scheme for its computation and analyze convergence properties.

Aggregates

Convergence

Distributed computation

Eigenvalues and eigenfunctions

Multi-agent consensus

PageRank algorithm

Protocols

Randomization

Search engines

Steady-state

Vectors

Web pages

Details

Title: Subtitle: A new approach for aggregated PageRank computation via distributed randomized algorithms
Creators: Hideaki Ishii - Tokyo Institute of Technology
Roberto Tempo - Politecnico di Torino
Er-Wei Bai - University of Iowa
Resource Type: Conference proceeding
Publication Details: 2011 50th IEEE Conference on Decision and Control and European Control Conference, Vol.No, pp.6421-6426
DOI: 10.1109/CDC.2011.6160880
ISSN: 0191-2216
Publisher: IEEE
Language: English
Date published: 12/2011
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984197352702771

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