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November 2003

Reduce spam with Bayesian filtering

If you're like most people, your email inbox is a catch basin for the daily torrent of offers for sex performance-enhancing drugs, weight-loss programs and Third World moneymaking schemes. Me? I get very few, thanks to a fairly straightforward application of statistical analysis applied to text processing -- Bayesian filtering. Thomas Bayes didn't have spam in 1760 when he wrote his "Essay Towards Solving a Problem in the Doctrine of Chances," which introduced the mathematical basis for statistical inference. In layman's terms, it's the calculation that something will occur in the future, based on the number of times it hasn't occurred in the past. When applied to email, a Bayesian filter will calculate the likelihood that I will want to participate in a money-laundering scheme with the widow of a former African president or deposed minister based on the number of times I have deleted their previous messages. Bayesian filtering works very well, measured at greater than 99.9% accuracy at detecting spam and other unwanted emails. ...

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