Research on Optimization of PageRank Algorithm Based on Transition Probability

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.