A Case Study in Web Search using TREC Algorithms
Paper from WWW10 by Google employees Amit Singhal and Marcin Kaszkiel.
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.
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.
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.
Dynamic Data Mining: Exploring Large Rule Spaces b
By Brin, Sergey; Page, Lawrence. Available in Postscript, PDF, and plain text formats.
Efficient Computation of PageRank
By Haveliwala, T. Available in Postscript, PDF, and plain text formats.
Efficient Crawling Through URL Ordering
By Cho, Junghoo; Garcia-Molina, Hector; Page, Lawrence. Available in Postscript, PDF, and plain text formats.
Exploiting the Block Structure of the Web for Comp
This paper by Sepandar Kamvar, Taher Haveliwala, Chris Manning, and Gene Golub presents an algorithm to vastly speed up the computation of PageRank.
Extracting Patterns and Relations from the World W
By Brin, Sergey. Available in Postscript, PDF, and plain text formats.
Extrapolation Methods for Accelerating PageRank Co
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.
Finding Near-replicas of Documents on the Web
By Shivakumar, N.; Garcia-Molina, H. Available in Postscript, PDF, and plain text formats.
Papers by Googlers
Google supplies a partial list of papers written by people now at Google.
The Anatomy of a Large-Scale Hypertextual Web Sear
By Brin, Sergey; Page, Lawrence. Available in Postscript, PDF, and plain text formats.
The Google File System
By Ghemawat, Sanjay; Gobioff, Howard; and Leung, Shun-Tak.
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.
The PageRank Citation Ranking: Bringing Order to t
By Page, Lawrence; Brin, Sergey; Motwani, Rajeev; Winograd, Terry. Available in Postscript, PDF, and plain text formats.
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.
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.
United States Patent: 6,526,440
Ranking search results by reranking the results based on local inter-connectivity. Inventor Krishna Bharat; assignee Google.