Bayesian filtering of this group's riff raff.

Kind of on topic, let me tell ya.
Anyone happen across a good Usenet filter that uses Bayesian filtering
or the similar, to filter out unwanted articles based upon a user's (or
a community's) preference.

For those that don't know, these are commonly used in email spam
filters. I think it would work better than a crude old kill file.
It'll identify keywords, or patterns and attributes of messages that you
like (want to see), and those that you don't. It'll learn from your
feedback and then get smart enough to classify the messages. It works
_really well_ for email, in spite of spammers trying to thwart it.

This could be even more powerful by having a (secure) community of users
with common interests within the subset of RAP vote to train the
classifier with more volume and less user effort. WOuld need to think
about vandalism and make sure it is secure however.

Anything like this out there - for NNTP / news? I'd apprecaite any
leads. Guess I can just google this,,, and I will now, but also
interested in what some feedback might be.

RAP motivates me to write a crude one and see how it works, perhaps by
adopting pieces of spamassassin (a classifier commonly used for email).

T