The PageRank Citation Ranking: Bringing Order to the Web

Publication Type: 
Publisher: 
Stanford Digital Library Technologies Project
Year: 
1 998
Abstract: 
The importance of a Web page is an inherently subjective matter, which depends on the readers interests, knowledge and attitudes. But there is still much that can be said objectively about the relative importance of Web pages. This paper describes PageRank, a method for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. We compare PageRank to an idealized random Web surfer. We show how to efficiently compute PageRank for large numbers of pages. And, we show how to apply PageRank to search and to user navigation.
Notes: 

PageRank: a method for rating Web pages objectively and mechanically, effectively measuring the human interest and attention devoted to them. A method for computing a ranking for every web page based on the graph of the web.
Unlike "flat" document collections, the WWW is hypertext and provides considerable auxiliary information on top of the text of the web pages, such as link structure and link text. In this paper, we take advantage of the link structure of the Web to produce a global "importance" ranking of every web page. This ranking, called PageRank, helps search engines and users quickly make sense of the vast heterogeneity of the WWW.
Web pages proliferate free of quality control or publishing costs.
Kleinberg has developed an interesting model of the web as Hubs and Authorities, based on an eigenvector calculation on the co-citation matrix of the web.
A page has high rank if the sum of the ranks of its backlinks is high. This cover both the case when a page has many backlinks and when a page has a few highly ranked backlinks.
Google: full text search engine that utilizes a number of factors to rank search results including standard IR measures, proximity, anchor text (text of links pointing to web pages), and PageRank.