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

Yajun Xie, Lihua Hu and Changfeng Ma ()
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Yajun Xie: College of Economics and Management, Nanchang Normal College of Applied Technology, Nanchang 330108, China
Lihua Hu: College of Economics and Management, Nanchang Normal College of Applied Technology, Nanchang 330108, China
Changfeng Ma: School of Big Data, Fuzhou University of International Studies and Trade, Fuzhou 350202, China

Mathematics, 2023, vol. 11, issue 15, 1-12

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.

Keywords: PageRank; inner–outer iterations; multi-parameter iteration; inner subsystems (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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