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.

A CoWeb is a collaborative Web space that allows people to modify content and create new pages in a very easy fashion. We modified the original CoWeb to visualize interaction history information in an effort to make it a more social space and to allow users to engage in social navigation. KEYWORDS: Social Navigation, History Enriched Environments, Visualizing Interaction Histories INTRODUCTION The CoWeb (for collaborative Web) was implemented by Mark Guzdial (based on earlier work by Ward Cunningham) to support anchored discussions. In a CoWeb everybody can modify every page [1]. After clicking on a link to "modify this page" users see a form containing the content of the current page. There is no need to use HTML, although people can use any HTML tags they need. Users create new pages and links by placing asterisks before and after a piece of text. This text then becomes the title of the new page. In a loose sense, many CoWebs become virtual communities, although there is no pro...

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.