Distributed PageRank computation with link failures
ACC'09 Proceedings of the 2009 conference on American Control Conference
Ranking canonical views for tourist attractions
Multimedia Tools and Applications
An Inner-Outer Iteration for Computing PageRank
SIAM Journal on Scientific Computing
Clustered service rank in support of web service discovery
Proceedings of the 2012 iConference
Extracting focused locations for web pages
WAIM'11 Proceedings of the 2011 international conference on Web-Age Information Management
ProRank: a method for detecting protein complexes
Proceedings of the 14th annual conference on Genetic and evolutionary computation
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Linking cognitive and computational saliences in route information
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
Regularization-based solution of the PageRank problem for large matrices
Automation and Remote Control
Faster Ranking Using Extrapolation Techniques
International Journal of Computer Vision and Image Processing
Analysis of strategy in robot soccer game
Neurocomputing
Parallel reduction to hessenberg form with algorithm-based fault tolerance
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Power walk: revisiting the random surfer
Proceedings of the 18th Australasian Document Computing Symposium
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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-hulman.edu/~bryan.