- Adaptive Methods for the Computation of PageRank
This paper by Sepandar Kamvar, Taher Haveliwala, and Gene Golub describes an algorithm to speed up the computation of PageRank using the fact that pages converge at different rates.
http://www.stanford.edu/~sdkamvar/papers/adaptive.pdf
- Computing Iceberg Queries Efficiently
By Fang, Min; Shivakumar, Narayanan; Garcia-Molina, Hector; Motwani, Rajeev; Ullman, Jeffrey D. Available in Postscript, PDF, and plain text formats.
http://dbpubs.stanford.edu:8090/pub/1999-67
- Extrapolation Methods for Accelerating PageRank Computations
This paper by Sepandar Kamvar, Taher Haveliwala, Chris Manning, and Gene Golub, published in WWW13, presents an algorithm to speed up the computation of PageRank by making some initial approximations.
http://www.stanford.edu/~sdkamvar/papers/extrapolation.pdf
- Papers by Googlers
Google supplies a partial list of papers written by people now at Google.
http://labs.google.com/papers.html
- The Google File System
By Ghemawat, Sanjay; Gobioff, Howard; and Leung, Shun-Tak.
http://www.cs.rochester.edu/sosp2003/papers/p125-ghemawat.pdf
- The Second Eigenvalue of the Google Matrix
This paper by Sepandar Kamvar and Taher Haveliwala proves analytically the second eigenvalue of the Google Matrix, which has implications for the PageRank algorithm.
http://www.stanford.edu/~sdkamvar/papers/secondeigenvalue.pdf
- Topic-Sensitive PageRank
Taher H. Haveliwala's paper for the 11th International World Wide Web Conference explains that Google proposes to make PageRank reflect importance with respect to a particular topic.
http://dbpubs.stanford.edu:8090/pub/2002-6
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