An Overview of Efficient Computation of PageRank

With the rapid growth of the Web, users get easily lost in the rich hyper structure. Providing relevant information to the users to cater to their needs is the primary goal of website owners. Therefore, finding the content of the Web and retrieving the users’ interests and needs from their behavior have become increasingly important. Web mining is used to categorize users and pages by analyzing the users’ behavior, the content of the pages, and the order of the URLs that tend to be accessed in order. Web structure mining plays an important role in this approach. Two page ranking algorithms, HITS and PageRank, are commonly used in web structure mining. Both algorithms treat all links equally when distributing rank scores. Several algorithms have been developed to improve the performance of these methods. This paper discusses efficient techniques for computing PageRank. How to rank Web resources is critical to Web Resource Discovery (Search Engine). This paper points out the weakness of current approaches, we discuss several methods for analyzing the convergence of PageRank based on the induced ordering of the pages KeywordsHITS, Web search, web graph, link analysis, PageRank, search in context, personalized search, ranking algorithm, Weighted PageRank, Adaptive PageRank.