Abstract
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.



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Acknowledgements
The authors would like to thank the anonymous referees for their valuable comments and suggestions on the original manuscript, which greatly improved the quality of this article.
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This research is supported by the National Natural Science Foundation of China (12101433), and the Two-Way Support Programs of Sichuan Agricultural University (1921993077).
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Wen, C., Hu, QY. & Shen, ZL. An adaptively preconditioned multi-step matrix splitting iteration for computing PageRank. Numer Algor 92, 1213–1231 (2023). https://doi.org/10.1007/s11075-022-01337-4
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DOI: https://doi.org/10.1007/s11075-022-01337-4
Keywords
- PageRank
- Multi-step matrix splitting iteration
- Generalized Arnoldi method
- Power method
- The inner-outer iteration