Finding Near-replicas of Documents on the Web
- By Narayanan Shivakumar and Hector Garcia-Molina. Available in Postscript format.
- http://infolab.stanford.edu/~shiva/Pubs/web.ps

The Anatomy of a Large-Scale Hypertextual Web Search Engine
- The definitive paper by Sergey Brin and Lawrence Page describing PageRank, the algorithm that was later incorporated into the Google search engine.
- http://infolab.stanford.edu/~backrub/google.html

An Analysis of Factors Used in Search Engine Ranking
- Investigates the influence of different page features on the ranking of Google search engine results.
- http://airweb.cse.lehigh.edu/2005/bifet.pdf

An Analytical Comparison of Approaches to Personalizing PageRank
- Taher H. Haveliwala, Sepandar D. Kamvar, and Glen Jeh compare three approaches to personaliizing PageRank.
- http://www.stanford.edu/~sdkamvar/papers/comparison.pdf

PageRank Calculation Techniques
- Paper by T. Haveliwala, describing efficient techniques for computing PageRank.
- http://www-cs-students.stanford.edu/~taherh/papers/efficient-pr.pdf

Detecting Colluders in PageRank
- PhD thesis by Kahn Mason on methods of discovering groups of websites that collude to boost their reputations, distorting the results of the PageRank algorithm. Stanford University.
- http://www.stanford.edu/group/reputation/Mason_Thesis.pdf

Efficient Crawling Through URL Ordering
- Paper by Junghoo Cho, Hector Garcia-Molina, and Lawrence Page. Available in Postscript, PDF, and plain text formats.
- http://dbpubs.stanford.edu:8090/pub/1998-51

Method for Node Ranking in a Linked Database
- United States Patent 7,058,628, granted to Lawrence Page, which incorporates material from two earlier patents relating to the PageRank system used by Google.
- http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=7,058,628.PN.&OS=PN/7,058,628&RS=PN/7,058,628

Extracting Patterns and Relations from the World Wide Web
- Paper by Sergey Brin presenting a technique which exploits the duality between sets of patterns and relations to grow the target relation, starting from a small sample.
- http://maya.cs.depaul.edu/~classes/ect584/papers/brin.pdf

WWW2003: Detecting Near-replicas on the Web by Content and Hyperlink Analysis
- Paper by Ernesto Di Iorio, et. al. proposing a technique for finding lists of similar documents, based on a pair of signatures which take into account both the document contents and the hyperlink structure.
- http://www2003.org/cdrom/papers/poster/p193/p193-diiorio-IE/p193-diiorio.html

Computing Iceberg Queries Efficiently
- Paper by Min Fang, Narayanan Shivakumar, Hector Garcia-Molina, Rajeev Motwani, and Jeffrey D. Ullman, developing efficient execution strategies for a class of queries which perform an aggregate function over an attribute (or set of attributes) and then
- http://www.vldb.org/conf/1998/p299.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://www2002.org/CDROM/refereed/127/

The Nature of Meaning in the Age of Google
- Terrence A. Brooks writes a paper about how search engines are changing the way we understand the world around us.
- http://informationr.net/ir/9-3/paper180.html

Papers by Googlers
- Google supplies a partial list of papers written by people now at Google.
- http://labs.google.com/papers.html

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

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

Exploiting the Block Structure of the Web for Computing PageRank
- This paper by Sepandar Kamvar, Taher Haveliwala, Chris Manning, and Gene Golub presents an algorithm to vastly speed up the computation of PageRank.
- http://www.stanford.edu/~sdkamvar/papers/blockrank.pdf

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

United States Patent: 6,526,440
- Ranking search results by reranking the results based on local inter-connectivity. Inventor Krishna Bharat; assignee Google.
- http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO2&Sect2=HITOFF&p=1&u=/netahtml/search-bool.html&r=1&f=G&l=50&co1=AND&d=ptxt&s1=6,526,440&OS=6,526,440&RS=6,526,440

Building a Distributed Full-Text Index for the Web
- Paper from WWW10 by Sergey Melnik, Sriram Raghavan, Beverly Yang, Hector Garcia-Molina from the Computer Science Department at Stanford University.
- http://www10.org/cdrom/papers/275/

A Case Study in Web Search using TREC Algorithms
- Paper from WWW10 by Google employees Amit Singhal and Marcin Kaszkiel.
- http://www10.org/cdrom/papers/317/

Dynamic Data Mining: Exploring Large Rule Spaces by Sampling
- Paper by Sergey Brin and Lawrence Page, available in Postscript, PDF, and plain text formats.
- http://dbpubs.stanford.edu:8090/pub/1999-68

The PageRank Citation Ranking: Bringing Order to the Web
- Stanford paper by Lawrence Page, Sergey Brin, Rajeev Motwani, and Terry Winograd, describing PageRank as a static ranking, performed at indexing time, which interprets a link as a vote. Available in Postscript, PDF, and plain text formats.
- http://dbpubs.stanford.edu:8090/pub/1999-66