[Klein & Vuppala2007 slides] 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 [by link analysis, eg. HITS, SALSA]. 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 [Google] and to user navigation.

In this paper, we have taken on the audacious task of condensing every page on the World Wide Web into a single number, its PageRank. PageRank is a global ranking of all web pages, regardless of their content, based solely on their location in the Web’s graph structure.

Using PageRank, we are able to order search results so that more important and central Web pages are given preference. In experiments, this turns out to provide higher quality search results to users.

The intuition behind PageRank is that it uses information which is external to the Web pages themselves—their backlinks, which provide a kind of peer review. Furthermore, backlinks from “important” pages are more important than backlinks from average pages. This is encompassed in the recursive definition of PageRank (§2.4).

PageRank could be used to separate out a small set of commonly used documents which can answer most queries. The full database only needs to be consulted when the small database is not adequate to answer a query.

Finally, PageRank may be a good way to help find representative pages to display for a cluster center.

We have found a number of applications for PageRank in addition to search which include traffic estimation, and user navigation [ie. annotating links with their PageRank—no longer possible as Google shut down public access to PageRank estimates ~2013].

Overall, our experiments with PageRank suggest that the structure of the Web graph is very useful for a variety of information retrieval tasks.

…7.4 Other Uses of PageRank: The original goal of PageRank was a way to sort backlinks so if there were a large number of backlinks for a document, the “best” backlinks could be displayed first. We have implemented such a system.

It turns out this view of the backlinks ordered by PageRank can be very interesting when trying to understand your competition. For example, the people who run a news site always want to keep track of any important backlinks the competition has managed to get. Also, PageRank can help the user decide if a site is trustworthy or not. For example, a user might be inclined to trust information that is directly cited from the Stanford homepage.

[from “The Anatomy of a Large-Scale Hypertextual Web Search Engine”, Brin & Page1998]: …Appendix A: Advertising and Mixed Motives: …Currently, the predominant business model for commercial search engines is advertising. The goals of the advertising business model do not always correspond to providing quality search to users. For example, in our prototype search engine one of the top results for cellular phone is “The Effect of Cellular Phone Use Upon Driver Attention”, a study which explains in great detail the distractions and risk associated with conversing on a cell phone while driving. This search result came up first because of its high importance as judged by the PageRank algorithm, an approximation of citation importance on the web.

It is clear that a search engine which was taking money for showing cellular phone ads would have difficulty justifying the page that our system returned to its paying advertisers. For this type of reason and historical experience with other media (Bagdikian1983 [The Media Monopoly—ironic]), we expect that advertising funded search engines will be inherently biased towards the advertisers and away from the needs of the consumers…Furthermore, advertising income often provides an incentive to provide poor quality search results.

…In general, it could be argued from the consumer point of view that the better the search engine is, the fewer advertisements will be needed for the consumer to find what they want. This of course erodes the advertising-supported business model of the existing search engines. [cf. Hohnhold2015, OKCupid]

See Also: