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KEYWORDS="email mail spam filter"
SHORT='server-side anti-spam agent for UNIX email servers'
cat << EOF
-DSPAM is a scalable and open-source content-based spam filter designed for
-multi-user enterprise systems. On a properly configured system, many users
-experience results between 99.5% - 99.95%, or one error for every 200 to 2000
-messages. DSPAM supports many different MTAs and can also be deployed as a
-stand-alone SMTP appliance. For developers, the DSPAM core engine (libdspam) can
-be easily incorporated directly into applications for drop-in filtering (GPL
+DSPAM is a scalable and open-source content-based spam filter designed for
+multi-user enterprise systems. On a properly configured system, many users
+experience results between 99.5% - 99.95%, or one error for every 200 to 2000
+messages. DSPAM supports many different MTAs and can also be deployed as a
+stand-alone SMTP appliance. For developers, the DSPAM core engine (libdspam)
+can
+be easily incorporated directly into applications for drop-in filtering (GPL
applies; commercial licenses are also available).
-DSPAM has been implemented on many large and small scale systems with the largest
-being reported at about 350,000 mailboxes. It is presently being used or planned
+DSPAM has been implemented on many large and small scale systems with
+the largest
+being reported at about 350,000 mailboxes. It is presently being used
+or planned
for use in multiple commercial solutions.
-DSPAM is an adaptive filter which means it is capable of learning and adapting to
-each user's email. Instead of working off of a list of "rules" to identify spam,
-DSPAM's probabilistic engine examines the content of each message and learns what
-type of content the user deems as spam (or nonspam). This approach to
+DSPAM is an adaptive filter which means it is capable of learning and
+adapting to
+each user's email. Instead of working off of a list of "rules" to identify
+spam,
+DSPAM's probabilistic engine examines the content of each message and
+learns what
+type of content the user deems as spam (or nonspam). This approach to
machine-learning provides much higher levels of accuracy than commercial
-"hodge-podge" solutions, and with minimal resources. DSPAM's best recorded levels
-of accuracy have included 99.991% by one avid user (2 errors in 22,786) and 99.987%
-by the author (1 error in 7000), which is ten times more accurate than a human being!
+"hodge-podge" solutions, and with minimal resources. DSPAM's best recorded
+levels
+of accuracy have included 99.991% by one avid user (2 errors in 22,786)
+and 99.987%
+by the author (1 error in 7000), which is ten times more accurate than a
+human being!
EOF