Great summary! I surmise you would also need to map the multi-dimension
surface of non-spam and make sure you were below the surface of that to not
risk a false positive. In other words, since you are correlating variates that
have cross-correlation between spam and non-spam, then there are two surfaces
(spam and non-spam) which can intersect. If your email is caught between the
two surfaces, then you have NEUTRAL answer.
The Laplacians I believe are used to approximate the surface in useful way for
this measurement.
On Wednesday 25 August 2004 09:07 am, Holm, Mark wrote:
I know this is OT, but anybody even tangentially involved in spam
fighting ought to read this article.
http://zdnet.com.com/2100-1107_2-5323437.html?tag=zdfd.newsfeed
I won't mention it again on this list.
Unfortunately, I will mention it. ;-)
This machine isn't hyperdimensional - the vectors it calculates are. (Turn
on your multi-variable geometry brain now.) The idea is you have multiple
characteristics of a piece of mail - whether it passes SPF, whether it
passes a Bayesian filter, etc, etc... If you create a vector for each mail,
where each coordinate of that vector is the score it gets based on that
measurement, then you can determine whether the email is spam or not based
on whether the vector is above the surface of spam or below the surface of
spam. The trick lies in being able to determine if a piece of mail is
definitively above or below the surface of spam based on only one or two
characteristics. Hyperdimensional means "more than 3 dimensions". It sounds
wild and crazy, but in something as esoteric as determining if a bunch of
bytes is spam or not, it is appropriate.
- --
Jonathan M. Gardner
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