An adaptively preconditioned multi-step matrix splitting iteration for computing PageRank

被引:2
|
作者
Wen, Chun [1 ]
Hu, Qian-Ying [2 ]
Shen, Zhao-Li [3 ]
机构
[1] Univ Elect Sci & Technol China, Sch Math Sci, Chengdu 610054, Sichuan, Peoples R China
[2] Guizhou Normal Univ, Sch Math Sci, Guiyang 550025, Peoples R China
[3] Sichuan Agr Univ, Coll Sci, Yaan 625000, Sichuan, Peoples R China
基金
中国国家自然科学基金;
关键词
PageRank; Multi-step matrix splitting iteration; Generalized Arnoldi method; Power method; The inner-outer iteration; INNER-OUTER ITERATION; EXTRAPOLATION METHOD; ARNOLDI ALGORITHM; GMRES;
D O I
10.1007/s11075-022-01337-4
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The multi-step matrix splitting iteration (MPIO) for computing PageRank is an efficient iterative method by combining the multi-step power method with the inner-outer iterative method. In this paper, with the aim of accelerating the computation of PageRank problems, a new method is proposed by preconditioning the MPIO method with an adaptive generalized Arnoldi (GArnoldi) method. The new method is called as an adaptive GArnoldi-MPIO method, whose construction and convergence analysis are discussed in detail. Numerical experiments on several PageRank problems are reported to illustrate the effectiveness of our proposed method.
引用
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页码:1213 / 1231
页数:19
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