The Mathematics of Recommendation?. Thomas Bayes, one of the leading mathematical lights in computing today, differs from most of his colleagues: He has argued that the existence of God can be derived from equations. His most important paper was published by someone else. And he's been dead for 241 years.
Yet the 18th-century clergyman's theories on probability have become a major part of the mathematical foundations of application development.
Search giant Google and Autonomy, a company that sells information retrieval tools, both employ Bayesian principles to provide likely (but technically never exact) results to data searches. Researchers are also using Bayesian models to determine correlations between specific symptoms and diseases, create personal robots, and develop artificially intelligent devices that "think" by doing what data and experience tell them to do.
Despite the esoteric symbols, the idea--roughly speaking--is simple: The likelihood that something will happen can be plausibly estimated by how often it occurred in the past. Researchers are applying the idea to everything from gene studies to filtering e-mail.
A detailed mathematical rundown can be found on the University of Minnesota's Web site. And a Bayes Rule Applet on Gametheory.net lets you answer questions such as "How worried should you be if you test positive for some disease?" One of the more vocal Bayesian advocates is Microsoft. The company is employing ideas based on probability--or "probabilistic" principles--in its Notification Platform. The technology will be embedded in future Microsoft software and is intended to let computers and cell phones automatically filter messages, schedule meetings without their owners' help and derive strategies for getting in touch with other people.
If successful, the technology will give rise to "context servers"--electronic butlers that will interpret people's daily habits and organize their lives under constantly shifting circumstances. [Smart Mobs]
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