Title
The $25,000,000,000 eigenvector: the linear algebra behind Google
Contributors
Creator: Leise, Tanya (Amherst College. Department of Mathematics and Statistics)
Creator: Bryan, Kurt, 1962- (Rose-Hulman Institute of Technology. Department of Mathematics)
Creator: Bryan, Kurt, 1962- (Rose-Hulman Institute of Technology. Department of Mathematics)
Genre
Publication Information
Published Version
Date Issued
2006-08-03
Note
Final published version appeared in SIAM Review.
Abstract
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
Identifier (DOI)
10.1137/050623280
Language
English
Files referenced in this Digital Object
- Download Leise_2006_thelinearalgebra.pdf
- Download Leise_2006_thelinearalgebra.pdf
- Download Leise_2006_thelinearalgebra.pdf
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