Evaluation of Iterative Pagerank Algorithm for Web Page Ranking

The success behind Google Search Engine is PageRank algorithm. Many pagerank algorithms exist in the literature for ranking web pages. However, determining the optimum pagerank algorithm is an optimization problem. In this paper, we evaluated three Iterative Page Ranking methods and compare it to Power method of original Pagerank to determine the most optimum pagerank algorithm. Extensive experiment was conducted involving the four algorithms: Jacobi, Power, Gauss Seidel and induced dimension reduction (IDR). The performance metrics used to determine the efficiency and effectiveness of the algorithms includes convergence, number of iterations and time elapses. The result of the experiments indicated Jacobi and IDR method outperforms Power in the number of iterations and convergence faster than Gauss Seidel. Gauss Seidel has the shortest time elapsed followed by Jacobi, Power and IDR.