Bayesian Noise Reduction is a statistical approach to evaluating coherence by instantiating a series of machine-generated contexts to serve as a means of contrast. This makes it possible to identify text that is out of context using a form of pattern consistency checking. BNR attempts to solve the problem commonly referred to as "Bayesian Noise" which, in its simplest definition, refers to irrelevant data present in a message being classified. Bayesian Noise Reduction dubs irrelevant text in order to provide cleaner classification and is implemented as a pre-filter to existing language classification functions. BNR is used in Dspam (mail/dspam, mail/dspam-devel - the ports don't depent on this one) See www for white-paper and presentation. WWW: http://www.nuclearelephant.com/papers/bnr.html