| | 33 | |
| | 34 | === Spam Filtering === |
| | 35 | |
| | 36 | CAL is running [http://dspam.nuclearelephant.com/ DSPAM] to provide users with personalized spam filters that will adapt to your preferences. Mail messages determined by a user's filter to be spam will by default be routed into the user's `spam` subfolder (based on the `X-DSPAM-*` headers added by DSPAM). |
| | 37 | |
| | 38 | If you find a non-spam message in your `spam` folder, you should tell the filter that it made a mistake. You can do that by simply forwarding the message to `notspam-username@astro.columbia.edu` (replace "`username`" with your CAL username, of course!) |
| | 39 | |
| | 40 | Conversely, if you find a spam message in your inbox, you can retrain your filter by forwarding it to `spam-username@astro.columbia.edu`. If you conscientiously retrain your filter when it errs, it will be better able to anticipate your preferences in the future. |
| | 41 | |
| | 42 | === Personalized Filtering === |
| | 43 | Traditional UNIX-style `.forward` files are not used on the new CAL system. We're using [http://www.ietf.org/html.charters/sieve-charter.html sieve], an emerging standard for mail filtering. You can see an example sieve script [source:trunk/packages/cal-meta/src/examples/sieve/cal-default.script here] (this example script is installed by default for all CAL users, and can be found on Configured Workstations at `/usr/share/doc/cal-base/examples/sieve/cal-default.script`. It filters spam into the user's `spam` subfolder based on the `X-DSPAM` headers mentioned above). If you want to write a new sieve script, simply put it in a text file on a Configured Workstation, and use `sieveshell` to import it to `mail.astro.columbia.edu`. For example, here is [wiki:dkg] importing a sieve script located at `~/newsieve.script`: |
| | 44 | {{{ |
| | 45 | [0 dkg@kalyke ~]$ sieveshell mail |
| | 46 | connecting to mail |
| | 47 | > put newsieve.script |
| | 48 | > activate newsieve |
| | 49 | > quit |
| | 50 | [0 dkg@kalyke ~]$ |
| | 51 | }}} |
| | 52 | You can find some [http://www.cmu.edu/computing/documentation/sieve/sieve.html example sieve scripts] [http://wiki.fastmail.fm/index.php/SieveRecipes online], if you want to experiment more. |