文章基本信息

标题：Fuzz-PageRanking for Google Search Engine
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作者：Tahseen Jilani ; Ubaida Fatima ; Mirza Mahmood Baig 等
期刊名称：International Journal of Computer Science Issues
印刷版ISSN：1694-0784
电子版ISSN：1694-0814
出版年度：2015
卷号：12
期号：6
出版社：IJCSI Press
摘要：In this research we have proposed a novel approach for the computation of PageRank vector of Google web search engine and appellate this approach as Fuzz-PageRank Approach (FUPRA). Practically, the number of web connections is a fuzzy concept and thus can be modeled using fuzzy logic and fuzzy sets. Through fuzzification of the fuzzy transition probability matrix, the proposed approach have accelerated the convergence rate of PageRank and renamed this vector as Fuzz-PageRank. For simplicity, we have assumed a triangular membership function for each element in a Google matrix. We have compared the convergence rate and number of iterations of the standard PageRank algorithms with our proposed method. The results has shown that our proposed approach has clearly outperformed the PageRank techniques.
关键词：Fuzz;PageRank; Eigenvalues; PageRank; Power Method; Fuzzy Adaptive Method