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A Parameterized Multisplitting Iterative Method for Solving the PageRank Problem
Version 1
: Received: 27 June 2023 / Approved: 27 June 2023 / Online: 27 June 2023 (13:35:48 CEST)
A peer-reviewed article of this Preprint also exists.
Xie, Y.; Hu, L.; Ma, C. A Parameterized Multi-Splitting Iterative Method for Solving the PageRank Problem. Mathematics 2023, 11, 3320. Xie, Y.; Hu, L.; Ma, C. A Parameterized Multi-Splitting Iterative Method for Solving the PageRank Problem. Mathematics 2023, 11, 3320.
Abstract
In this paper, a new multi parameter iterative algorithm is proposed to address the PageRank problem based on the multi-splitting iteration method described by Gu et al . The proposed method in each iteration needs to solve two linear subsystems by splitting the coefficient matrix, therefore, we consider 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 the certain conditions. Numerical experiments show that the proposed algorithm has better convergence and numerical stability than the existing algorithms.
Keywords
PageRank; inner-outer iterations; multi-parameter iteration; inner sub-systems
Subject
Computer Science and Mathematics, Computational Mathematics
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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