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November 27, 2012

User-Driven Page Ranking System up for Auction

By Julie Griffin, Contributing Writer

ICAP Patent Brokerage has announced it will auction the license to patents on a system to improve Internet page rankings.

Google’s (News - Alert) PageRank orders pages according to the probability that a user will land on a certain page via any number of sequences that link to that page. The algorithm, however, assumes the user selects links at random with every link assigned an equal probability of being selected – something this patent seeks to amend by including a variable that represents the probability that the user will select any individual link leading up to the page.

This probability is calculated by simply counting the number of times a particular link led a user to a given source.

The process will most likely rely on the computing power of the user – specifically an extension or a cookie loaded on the user’s Web browser that “observes” his or her browsing habits. The counts, in turn, can be stored and analyzed throughout the network according to a distributed hash table.

The upside to this system is that it would provide a real-world assessment of page rankings according to how popular they actually are, as opposed to the more abstract model currently in use, which does not differentiate between links to popular sources and links to spam sources (though it would be susceptible to “bot users”).

But if widely implemented, this system might face resistance from concerned users, privacy advocate groups, and governments – a situation with which Google, who is selling the patent, is all too familiar.  

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Edited by Braden Becker
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