> The Bayesian filtering theory is good for short term, but as email upon
> email is received and the Bayesian, as I understand it, does its work, word
> statistics go up and will be a very big problem as legitimate email gets
> blocked out because words matched what IT "thinks" is "spam" when the email
> itself could be a very long newsletter containing the very same words at the
> top of the Bayesian "spam identifier list."
>
> =============================
>
> When an email from a legitimate sender does inadvertently get blocked, then
> you add that address to the "permitted" list. Unless you routinely get
> emails from thousands of people, that's not much work.

Then this approach would only work for individuals who run their own mail
servers and not any decently sized company. Administering mail alone is a
tough job as it is without having to sift through everybody's email to figure
out what is and what isn't spam. That's unsettling in terms of privacy to the
employee despite what any company has pertaining to such policy.

As per our policies, I won't look at our employee's emails without their
knowledge and only when there are problems with communication between our mail
server and another mail server where an SBL has absolutely no intervention at
all.

You can only automate so much where the automation will just simply cease to
do anything it was intended for.

Bayesian methods need to grow up more and more testing needs to be done before
it can be widely implemented.

Personally, I see challenge response doing a much better job than Bayesian
implementations.