Hi, I'm setting up a new anti-spam gateway for a fairly busy site (about 20k messages a day) using Postfix/Amavis/SpamAssassin/ClamAV on a Debian etch system that delivers incoming (ham) mail to an Exchange 2003 server.
Since the old gateway was using a similar setup, there are already SPAM and HAM public mail folders which our users contribute to. The SPAM folder usually gets a lot of (untagged) spam, about 500 every day, while the HAM gets very little, and most of it is internal (within Exchange) mail that never passes through the gateway. I'm wondering whether it's worthwhile to use that kind of data to feed sa-learn, since a) a lot more spam than spam gets reported and b) most of the ham reported is mail that just moves within different Exchange mailboxes and never passes through the gateway. If indeed it's mostly useless (or maybe even harmful for the Bayes filter) then I was wondering if it would be more logical to have only the technical team feed the SPAM and HAM folders with proper messages (ie good mail that comes from an external source in the case as HAM). In that case, I'm wondering if the fact that only specific users report SPAM and HAM could trigger the Bayes filter to think that a message would be more hammy or spammy depending on the recipient. In short, I'm looking for a way to feed sa-learn that's at least minimally effective in a situation where only a little useful HAM is being reported by our users at large. -- Jérôme Charaoui <[EMAIL PROTECTED]> Service informatique - Collège de Maisonneuve
