On Wed, 31 Mar 2004, Michel Py wrote:
1. Reduce the efficiency of Bayesian-like filters: Trouble with this kind of email is that they are a) of sufficient length b) contain only "real" words c) contain none of the words regularly used by spammers such as the v. word.
Good bayesian filters do not score on single words alone, they also score on "phrases" (ie multiple words). Random strings of words will result in neutral scores (presuming those words are also used in non-spam), while the phrases will be slightly higher. Re-used gibberish (ie apparently random) strings of words will result in "phrases" from that gibberish having high scores. Also, a good bayesian filter should prune its database regularly of phrases (including one word phrases) that have not had their score updated recently, further reducing "pollution" by random words and phrases. noise is just noise. the spam specific stuff will still be statistically significant, hopefully. regards, -- Paul Jakma paul@clubi.ie paul@jakma.org Key ID: 64A2FF6A warning: do not ever send email to spam@dishone.st Fortune: It's currently a problem of access to gigabits through punybaud. -- J. C. R. Licklider