I came across best practices from BarracudasNetwork website https://www.barracudanetworks.com/docs/other/barracuda_spam_&_virus_firewall_bayesian.pdf
These recommendations suggest to keep good quality Bayesian Learning samples on a static level of few hundred emails each type (valid emails and known spam).
Here is my question - how such a configuration handle 'seasonal spam periods'? What I mean here are spam emails related to the world events e.g. emails related to Barack Obama and presidential election or riots in Egipt. We noticed that during these events noticable portion of spam we captured with our restricted setup had some references to the events.
Now, if we were to keep adding these seasonal spam examples we would end up with thousands of emails in the spam samples.
I should add that our mail servers receive tens of thousands emails every day.
What would be the best way to handle mentioned situations?
Here is what we have been using (in case it matters):
- Firmware v3.5.12.025 (2009-09-03 19:21:07)
- Model: 600
Many thanks, Luke