The coupled iteration algorithms for computing PageRank

被引：0
作者：
Zhaolu Tian
Zhongyun Liu
Yinghui Dong
机构：
[1] Shanxi University of Finance and Economics,College of Applied Mathematics
[2] Changsha University of Science and Technology,School of Mathematics and Statistics
[3] Suzhou University of Science and Technology,College of Mathematics
来源：
Numerical Algorithms | 2022年 / 89卷
关键词：
PageRank problem; Coupled iteration algorithm; Convergence; Matrix splitting; Optimal parameter; MSC 65F08; MSC 65F10;
D O I：
暂无
中图分类号：
学科分类号：
摘要：
In this paper, based on the splittings of the coefficient matrix in the PageRank problem, the coupled iteration algorithms are presented for computing PageRank vector. Convergence conditions of the proposed algorithms are analyzed in detail. Furthermore, the choices of the optimal parameters are discussed for some special cases. Finally, several numerical examples are given to illustrate the effectiveness of the proposed algorithms.
引用
收藏
页码：1603 / 1637
页数：34
相关论文
共 111 条
[1]  
Xie YJ(2018)A relaxed two-step splitting iteration method for computing PageRank Comp. Appl. Math. 37 221-233
[2]  
Ma CF(2018)The general inner-outer iteration method based on regular splittings for the PageRank problem Appl. Math. Comput. 271 337-343
[3]  
Tian ZL(2017)A note on the two-step matrix splitting iteration for computing PageRank J. Comput. Appl. Math. 315 87-97
[4]  
Liu Y(2013)On the multi-splitting iteration method for computing PageRank J. Appl. Math. Comput. 42 479-490
[5]  
Zhang Y(2005)Inside PageRank ACM Trans. Internet Technol. 5 92-128
[6]  
Liu ZY(2015)Parallel multisplitting iteration methods based on M-splitting for the PageRank problem Appl. Math. Comput. 271 337-343
[7]  
Tian MY(2015)A two-step matrix splitting iteration for computing PageRank J. Comput. Appl. Math. 278 19-28
[8]  
Wen C(1978)Accelerated overrelaxation method Math. Comp. 32 149-157
[9]  
Huang TZ(1997)On the convergence of the MAOR method J. Comput. Appl. Math. 79 299-317
[10]  
Shen ZL(2017)An efficient elimination strategy for solving PageRank problems Appl. Math. Comput. 298 111-122
12345678910