Dear readers, while using Spamassassin for about one month and having a very good recognition rate I am discovering that spam that has almost or no text within does not get detected by SpamAssassin, neither by normal criteria nor by the Bayes filter. I think because there is not enough information for the Bayes filter to be able on a reliable decision.
Now I had the following thought. What about a special image database which is maintained in a Bayes-like-style. I could imagine the following. While learning spam with sa-learn, the learning process could also filter out each image in an email. Then we have to build a more unique representation of this image, comparable with a hash value of a string. Then we store this "hash value" as entry a Bayes-like image database. When new email comes in we do a comparison of all images in this email with them in our database. I don't have any idea of what resouces this addition check(s) would consume, but perhaps it would be a nice addition feature. I was concerned about some ways how to get a hash value out of an image, if someone is interested, feel free to contact me. Best regards, Manuel Schmitt ------------------------------------------------------- The SF.Net email is sponsored by EclipseCon 2004 Premiere Conference on Open Tools Development and Integration See the breadth of Eclipse activity. February 3-5 in Anaheim, CA. http://www.eclipsecon.org/osdn _______________________________________________ Spamassassin-talk mailing list [EMAIL PROTECTED] https://lists.sourceforge.net/lists/listinfo/spamassassin-talk
