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The coupled iteration algorithms for computing PageRank

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Abstract

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.

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Funding

The work is supported by the National Natural Science Foundation of China (Grant No. 12071335), Teaching Reform and Innovation Project of Shanxi University of Finance and Economics (2019112), and Teaching Reform and Innovation Project of Higher Education in Shanxi Province (J2019109).

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Authors and Affiliations

  1. College of Applied Mathematics, Shanxi University of Finance and Economics, Taiyuan, 030006, People’s Republic of China

    Zhaolu Tian

  2. School of Mathematics and Statistics, Changsha University of Science and Technology, Changsha, 410076, People’s Republic of China

    Zhongyun Liu

  3. College of Mathematics, Suzhou University of Science and Technology, Suzhou, People’s Republic of China

    Yinghui Dong

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  1. Zhaolu Tian
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  2. Zhongyun Liu
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  3. Yinghui Dong
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Correspondence to Zhaolu Tian.

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Tian, Z., Liu, Z. & Dong, Y. The coupled iteration algorithms for computing PageRank. Numer Algor 89, 1603–1637 (2022). https://doi.org/10.1007/s11075-021-01166-x

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