## Google PageRank Algorithm – References

## Google PageRank – Algorithms and Computation

- The PageRank Citation Ranking: Bringing Order to the Web, Brin & Page et al (January 29, 1998)

This is the original description of PageRank - The Anatomy of a Large-Scale Hypertextual Web Search Engine, Brin & Page

This is the original description of Google - US Patents 7269587, 6799176, 7058628, 6285999

PageRank patents - Efficient Computation of PageRank.Haveliwala (1999)

Shows how PageRank calculation can be scaled to very large web sizes on modest hardware by partitioning, use of single precision arithmetic, and the minimum number of iterations to produce a stable ordering. - The Google Pagerank Algorithm

and How It Works (2002)

Description of algorithm with many examples - Web Page Scoring Systems

for Horizontal and Vertical SearchDiligenti, Gori, Maggini (2002)

Describes PageRank and HITS and extends application to search within a vertical. - The Mathematical Model of Google Tal-EzerAnother description of the PageRank algorithm and computational issues using the power method
- US Patent 7028029 – Adaptive computation of ranking

Describes a method to reduce PageRank computation load by exploiting the fact that a high percentage of nodes in a PageRank computation converge quickly, so can be removed from subsequent computations, thereby adaptively reducing the order of the computation. - Analysis and Computation of Google’s PageRank (2006) (slides)

Looks at convergence and error bounds on PageRank computation; includes consideration of TrustRank/personalisation vector

## Toolbar PageRank, SEO

- Page Rank Export History

Historical list of when Google has updated the PageRank information for the Google Toolbar. - Google PageRank: How to Get It (2004)

Estimates how many PR x links are required to achieve a page with PR y. Provides useful rule of thumb, although underlying assumptions won’t always be met - Page Rank Explained – PageRank (PR) Made Clear

Toolbar PageRank and discussion of simple link structures from an SEO perspective

## Related Research

- Graph fibrations, graph isomorphism, and PageRank (2006) (slides)

Describes fibrations, which in this context are mappings of link structures into smaller link structures that retain key properties under the PageRank calculation, therefore providing a possible way to reduce the size of the PageRank computation (at the cost of first determining the mapping) - Combating Web Spam with TrustRank Z. Gyöngyi, H. Garcia-Molina, J. Pedersen

Yahoo! sponsored research describing TrustRank, which incorporates flow-on effects to other sites from a relatively small set of seed sites of known good or bad reputation, using the same framework for compuation as PageRank. This is supposedly different from the Google-patented “TrustRank”, according to Matt Cutts’ comments.