Off-diagonal low-rank preconditioner for difficult PageRank problems

DOI10.1016/j.cam.2018.07.015zbMath1402.65028OpenAlexW2883327543WikidataQ129457057 ScholiaQ129457057MaRDI QIDQ1624665

Xian-Ming Gu, Zhao-Li Shen, Chun Wen, Ting-Zhu Huang, Bruno Carpentieri, Xue-Yuan Tan

Publication date: 16 November 2018

Published in: Journal of Computational and Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://pure.rug.nl/ws/files/103307690/1_s2.0_S0377042718304357_main.pdf

zbMATH Keywords

preconditionerPageRanklow-rank factorizationmatrix partitionoff-diagonal

Mathematics Subject Classification ID

Searching and sorting (68P10) Numerical computation of eigenvalues and eigenvectors of matrices (65F15) Iterative numerical methods for linear systems (65F10)

Related Items

Acceleration of the generalized FOM algorithm for computing PageRank, A simpler GMRES algorithm accelerated by Chebyshev polynomials for computing PageRank, On randomized partial block Kaczmarz method for solving huge linear algebraic systems, Shifted power-GMRES method accelerated by extrapolation for solving pagerank with multiple damping factors, An adaptively preconditioned multi-step matrix splitting iteration for computing PageRank, Parametric controllability of the personalized PageRank: Classic model vs biplex approach, The coupled iteration algorithms for computing PageRank

Uses Software

• SparseMatrix
• ILUPACK
• UbiCrawler
• WebGraph

Cites Work

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