# Document (#26352)

Author
Bryan, K.
Leise, T.
Title
¬The \$25.000.000.000 eigenvector : the linear algebra behind Google
Source
SIAM review. 48(2006) no.3, S.569-581
Abstract
Google's success derives in large part from its PageRank algorithm, which ranks the importance of webpages 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.
Content
Vgl. auch unter: http://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pdf.
Theme
Suchmaschinen
Object

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