- Papers by Googlers - Google supplies a partial list of papers written by people now at Google.
- 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. (June 6, 2006)
- 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. [PDF] (September, 2005)
- An Analysis of Factors Used in Search Engine Ranking - Investigates the influence of different page features on the ranking of Google search engine results. [PDF] (May, 2005)
- 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. (April, 2004)
- An Analytical Comparison of Approaches to Personalizing PageRank - Taher H. Haveliwala, Sepandar D. Kamvar, and Glen Jeh compare three approaches to personaliizing PageRank. [PDF] (June, 2003)
- 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. [PDF] (May, 2003)
- 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. [PDF] (April, 2003)
- 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. [PDF] (March, 2003)
- 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. [PDF] (March, 2003)
- 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. (March, 2003)
- United States Patent: 6,526,440 - Ranking search results by reranking the results based on local inter-connectivity. Inventor Krishna Bharat; assignee Google. (February 25, 2003)
- 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. (May, 2002)
- 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. (May, 2001)
- A Case Study in Web Search using TREC Algorithms - Paper from WWW10 by Google employees Amit Singhal and Marcin Kaszkiel. (May, 2001)
- 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 eliminates aggregate values that are below some specified threshold. [PDF] (November 11, 1999)
- Dynamic Data Mining: Exploring Large Rule Spaces by Sampling - Paper by Sergey Brin and Lawrence Page, available in Postscript, PDF, and plain text formats. (November 11, 1999)
- 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. [PDF] (November 11, 1999)
- 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. (November 11, 1999)
- PageRank Calculation Techniques - Paper by T. Haveliwala, describing efficient techniques for computing PageRank. [PDF] (September, 1999)
- 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. (April 10, 1998)
- Efficient Crawling Through URL Ordering - Paper by Junghoo Cho, Hector Garcia-Molina, and Lawrence Page. Available in Postscript, PDF, and plain text formats. [PDF] (April, 1998)
- Finding Near-replicas of Documents on the Web - By Narayanan Shivakumar and Hector Garcia-Molina. Available in Postscript format. (March, 1998)
|