Journal
SIAM REVIEW
Volume 48, Issue 3, Pages 569-581Publisher
SIAM PUBLICATIONS
DOI: 10.1137/050623280
Keywords
linear algebra; PageRank; eigenvector; stochastic matrix
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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-liulman.edu/similar to bryan.
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