A general multi-splitting iteration method for computing PageRank

被引：10
|
作者：
Tian, Maoyi [1 ]
Zhang, Yan [1 ]
Wang, Yudong [2 ]
Tian, Zhaolu [3 ]
机构：
[1] Shandong Univ Sci & Technol, Geomat Coll, Qingdao 266590, Peoples R China
[2] Taiyuan Univ Technol, Coll Text Engn, Taiyuan 030024, Shanxi, Peoples R China
[3] Shanxi Univ Finance & Econ, Coll Appl Math, Taiyuan 030006, Shanxi, Peoples R China
来源：
COMPUTATIONAL & APPLIED MATHEMATICS | 2019年 / 38卷 / 02期
关键词：
PageRank vector; Inner-outer iteration; Convergence; Matrix splitting; Preconditioning; INNER-OUTER ITERATION; ARNOLDI ALGORITHM; CONVERGENCE; COMPUTATION; GMRES;
D O I：
10.1007/s40314-019-0830-8
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this paper, based on the multi-splitting iteration (MSI) method (Gu and Wang in J Appl Math Comput 42:479-490, 2013), we present a general multi-splitting iteration (GMSI) method for solving the PageRank problem. The convergence of the GMSI method is analyzed in detail. Moreover, the same idea can be used as a preconditioning technique to accelerate Krylov subspace methods, such as the GMRES method. Finally, several numerical examples are given to illustrate the effectiveness of the proposed algorithm.
引用
收藏
页数：29
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