Bayesian filtering


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Bayesian filtering

An analysis technique that has been applied to eliminating spam. It "learns" to differentiate real mail from advertising by examining the words and punctuation in large samples of both types of messages. Based on the probability theorem of Reverend Thomas Bayes (1702-1761), it selects a set of words and numbers ("tokens") from the text and compares their ratio between good mail and spam. Using the tokens, the Bayesian approach looks at new mail and calculates the probability that the message is bogus. See spam filter.
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However, the model probabilities need be memorized for Bayesian filtering recursion in the estimation cycle.
Users who decide desktop software is the right choice should look for a product that adds its controls to an e-mail program's toolbar, uses Bayesian filtering, and is frequently updated online.
Bayesian filtering goes beyond identifying spam with keywords and headers; it uses a statistical approach and analyzes the entire context of e-mail to differentiate between valid email and spam.
Content tools that run Bayesian filtering and heuristics text analyses on messages are no longer as effective as they once were on their own," noted Michael Hyatt, president of BlueCat Networks, Inc.
SpamAssassin, which is built into several different e-mail client plug-ins, uses a type of statistical analysis known as Bayesian filtering to help it learn from existing spam to identify unfamiliar spam more accurately, theoretically getting better and better over time.

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