A Survey and Comparative Study of Different PageRank Algorithms
نویسندگان
چکیده
Searching the World Wide Web is an NP complete problem with sparse hyperlink matrices. Thus searching the significant search results is a challenge. Google’s PageRank attempted to solve this problem using computing of principle Eigenvalues termed as PageRank vector. After this, a number of techniques were developed to speed up the convergence patterns of pages in the PageRank algorithm. This is paper, we have reviewed a number of of PageRank computation techniques. The main objective of all these techniques is the convergence rate along with space and time complexities. In this paper, a comparative study is presented among Standard Power method, Adaptive Power Method and Aitken’s method using SNAP Google web pages dataset.
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