On adaptively accelerated Arnoldi method for computing PageRank

被引:20
作者
Yin, Jun-Feng [2 ]
Yin, Guo-Jian [2 ]
Michael Ng [1 ]
机构
[1] Hong Kong Baptist Univ, Dept Math, Kowloon Tong, Hong Kong, Peoples R China
[2] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
关键词
PageRank; eigenvalue and eigenvector; power method; Arnoldi process; weighted least squares problem; ALGORITHM;
D O I
10.1002/nla.789
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
A generalized refined Arnoldi method based on the weighted inner product is presented for computing PageRank. The properties of the generalized refined Arnoldi method were studied. To speed up the convergence performance for computing PageRank, we propose to change the weights adaptively where the weights are calculated based on the current residual corresponding to the approximate PageRank vector. Numerical results show that the proposed Arnoldi method converges faster than existing methods, in particular when the damping factor is large. Copyright (C) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:73 / 85
页数:13
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