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 depend on
this one)

See www for white-paper and presentation.

WWW: http://www.nuclearelephant.com/papers/bnr.html