页面排名
线性代数
域代数上的
特征向量
枫木
基质(化学分析)
矩阵代数
计算机科学
马尔可夫链
数学
情报检索
纯数学
物理
几何学
植物
材料科学
量子力学
机器学习
生物
复合材料
作者
Kurt Bryan,Tanya Leise
出处
期刊:Siam Review
[Society for Industrial and Applied Mathematics]
日期:2006-01-01
卷期号:48 (3): 569-581
被引量:257
摘要
Google's success derives in large part from its PageRank algorithm, which ranks the importance of web pages according to an eigenvector of a weighted link matrix. Analysis of the PageRank formula provides a wonderful applied topic for a linear algebra course. Instructors may assign this article as a project to more advanced students or spend one or two lectures presenting the material with assigned homework from the exercises. This material also complements the discussion of Markov chains in matrix algebra. Maple and Mathematica files supporting this material can be found at www.rose-hulman.edu/~bryan.
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