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Research on Optimization of PageRank Algorithm Based on Transition Probability

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Abstract

In the current era of information explosion, information search has become the focus of research, and search engines generally use PageRank algorithm to sort web-page. Based on the situation, this paper starts with rules of PageRank algorithm, and aims at optimizing PR value problem of link page average allocation. After that, this paper carries on discriminant analysis to the probability of web-page randomly jump to any page with the probability of residual damping coefficient, and assigns the PR value according to number of downstream pages linked to specified page, namely, improving accuracy of the algorithm by optimizing transition probability matrix in the PageRank algorithm. Finally, we prove that optimized algorithm has improved accuracy of PageRank distribution, and is superior to traditional algorithm.

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Acknowledgements

Support by Chongqing Big Data Engineering Laboratory for Children, Chongqing Electronics Engineering Technology Research Center for Interactive Learning and Scientific and Technological Research Program of Chongqing Municipal Education Commission (Grant No. KJ1714355).

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Authors and Affiliations

  1. School of Mathematics and Information Engineering, Chongqing University of Education, Chongqing, 400065, China

    Xi Shi & Pengcheng Wei

  2. College of Automation, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Pengcheng Wei & Zhen Zhou

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  1. Xi Shi
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  2. Pengcheng Wei
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  3. Zhen Zhou
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Correspondence to Xi Shi.

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Shi, X., Wei, P. & Zhou, Z. Research on Optimization of PageRank Algorithm Based on Transition Probability. Wireless Pers Commun 102, 1171–1180 (2018). https://doi.org/10.1007/s11277-017-5173-4

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  • DOI: https://doi.org/10.1007/s11277-017-5173-4

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