PageRank algorithm optimization and improvement
Yongji Tan · Computer Engineering and Applications Journal · 2009
The original PageRank algorithm uses the Power Method to compute successive iterations that converge to the principal eigenvector of the Markov matrix representing the Web link graph.Authors use the sparse of the Google matrix P in the iterative matrix A=[CP+(1-c)E]T,optimize the computation of each iteration and reduce storage space.Linear Extrapolation Method is an adjusted extrapolation method,which is proposed based on the Power Method.It utilizes the property of the second eigenvalue of the Google matrix to acheive the high rate convergence in the computing performance of Power Method.Therefore,the computing time is shortened without extra space storage.After some simulation work,the theoretical proof can be verified by the satisfactory practical result.