Acceleration of an adaptive generalized Arnoldi method for computing PageRank
Chun Wen, Qian-Ying Hu, Bing-Yuan Pu, Yu-Yun Huang
Source abstract
By considering a weighted inner product, an adaptive generalized Arnoldi (GArnoldi) method was constructed by <sup>[<span class="xref"><a href="#b13" ref-type="bibr">13</a></span>]</sup> for computing PageRank. In order to accelerate the adaptive GArnoldi method, this paper proposes a new method by using the power method with extrapolation process based on Google matrix's trace (PET) as an accelerated technique of the adaptive GArnoldi method. The new method is called as GArnoldi-PET method, whose implementation and convergence analysis are discussed in detail. Numerical experiments are used to illustrate the effectiveness of our proposed method.
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