摘要
PageRank向量是一个离散时间、有限状态马尔可夫链的稳态分布。同时,马尔可夫链理论已经得到了充分发展,利用马尔可夫链可以更好地理解和分析有关PageRank的问题。本文基于循环或者排名下沉所造成的PageRank收敛问题,通过对马尔可夫链的数学内容进行研究的方法,得出不可约马尔可夫链的暂态行为和极限行为,并对不可约马尔可夫链的特征进行总结。
PageRank vector is a discrete-time, finite-state Markov Chains steady state distribution. At the same time, the theory of Markov Chains has been fully developed, with which we can understand and analyze the problem about PageRank. Based on convergence of PageRank resulted from loops or sinking rank, this paper analyzes transient behavior and limited behavior of irreducible Markov Chains and concludes the feature of them with the study of overarching ideas of Markov Chains.
出处
《电子设计工程》
2017年第9期36-38,共3页
Electronic Design Engineering
基金
江苏省社科联研究基金(201035)
