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A Parameterized Multi-Splitting Iterative Method for Solving the PageRank Problem

Author

Listed:
  • Yajun Xie

    (College of Economics and Management, Nanchang Normal College of Applied Technology, Nanchang 330108, China
    These authors contributed equally to this work.)

  • Lihua Hu

    (College of Economics and Management, Nanchang Normal College of Applied Technology, Nanchang 330108, China
    These authors contributed equally to this work.)

  • Changfeng Ma

    (School of Big Data, Fuzhou University of International Studies and Trade, Fuzhou 350202, China
    These authors contributed equally to this work.)

Abstract

In this paper, a new multi-parameter iterative algorithm is proposed to address the PageRank problem based on the multi-splitting iteration method. The proposed method solves two linear subsystems at each iteration by splitting the coefficient matrix, considering therefore inner and outer iteration to find the approximate solutions of these linear subsystems. It can be shown that the iterative sequence generated by the multi-parameter iterative algorithm finally converges to the PageRank vector when the parameters satisfy certain conditions. Numerical experiments show that the proposed algorithm has better convergence and numerical stability than the existing algorithms.

Suggested Citation

  • Yajun Xie & Lihua Hu & Changfeng Ma, 2023. "A Parameterized Multi-Splitting Iterative Method for Solving the PageRank Problem," Mathematics, MDPI, vol. 11(15), pages 1-12, July.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:15:p:3320-:d:1205325
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    References listed on IDEAS

    as
    1. Huang, Na & Ma, Chang-Feng, 2015. "Parallel multisplitting iteration methods based on M-splitting for the PageRank problem," Applied Mathematics and Computation, Elsevier, vol. 271(C), pages 337-343.
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