Abstract
We now study the Lanczos algorithm for computing the PageRank vector. This algorithm is based on biorthogonalization, which transforms a nonsymmetric matrix into a tridiagonal matrix to compute PageRank. This generates better approximation of the largest eigenvalue at early stage of iterations. We propose a practical scheme of the Lanczos biorthogonalization algorithm with SVD scheme for computing PageRank. Numerical results show that the proposed algorithm converges faster than the existing Arnoldi method in the computation time.
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Teramoto, K., Nodera, T. (2016). A Note on Lanczos Algorithm for Computing PageRank. In: Chen, K., Ravindran, A. (eds) Forging Connections between Computational Mathematics and Computational Geometry. Springer Proceedings in Mathematics & Statistics, vol 124. Springer, Cham. https://doi.org/10.5176/2251-1911_CMCGS14.15_3
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DOI: https://doi.org/10.5176/2251-1911_CMCGS14.15_3
Publisher Name: Springer, Cham
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