![]() ![]() In other words, does the new message look more You get a new message, it looks at where the words in that message Tsai: It looks at examples of your spam messages and good messages andįigures out how often each word occurs in each type of message. Gruber: Part of what makes Bayesian spam filtering so interesting is that WhitelistsĪnd blocklists are an old idea, of course, but I don’t know of anyįilters that automatically train them the way SpamSieve does. Tokenize messages, and some of them show up in SpamSieve. The SpamBayesĪnd POPFile projects have generated a lot of ideas about how to Of tricks that spammers use to obscure their messages. Influential document that describes a lot Tsai: The new math in SpamSieve is due to Gary Robinson. Gruber: Where else have you drawn from, tactically? In 2.0, there’s little that came directly from Graham, although ofĬourse he’s indirectly responsible for much of what’s in SpamSieve, The only difference was that I tokenized words a little differently. Tsai: The approach in SpamSieve 1.0 was almost exactly Graham’s. Gruber: How influential has Graham been in your approach with SpamSieve? And, also, the framework has good general purpose tools-likeĪrrays, hashes, and string routines-that are useful in writing the Needing to write a lot of code just to set up an applicationĮnvironment in which to execute the spam filtering code. which is the code you wanted to write - rather than first Gruber: In other words, you could get started writing code to filter spam It really lowers the activationĮnergy for starting a project, and that can make a lot of I say that not to brag that I’m suchĪ fast programmer, but rather to illustrate how important it is to Suddenly this looked likeĪ problem I could solve quickly, and so I took a few hours oneĮvening and wrote a prototype. Had shown how to do the spam filter part. The e-mail client nicely.) I’d already written someĬocoa-AppleScript code for BBAutoComplete and DropDMG, and Graham (Previously, I didn’t really like the idea of anĮxternal filter, but AppleScript could make it work together with Would be possible to hook an external filter up to Mailsmith viaĪppleScript. ![]() Pretty soon I wouldn’t have to worry about spam anymore.Ībout a week later I got impatient, and it occurred to me that it When I read “A Plan for Spam” around August 20, 2002, I thoughtĮvery e-mail client would add a Graham-style filter in its next TheĬore of Graham’s algorithm is only about ten lines of Lisp code. Second, it demonstrated that doing so was actually pretty easy. Said that it was absolutely possible to write a better spam filter. Paul Graham’s paper was what got me to write SpamSieve. But I hadn’t actually started writing a new spam filterīecause I was busy with other projects at the time. Than my Mailsmith filter and the other solutions that were availableĪt the time. Jaguar’s Mail, and that convinced me that it was possible to do better What to do about my personal spam problem. I had made a huge filter in Mailsmith, but I had to keep modifying it,Īnd it started to become unmaintainable. So that we didn’t lose mail when people mistyped addresses.) So I had to make the ATPM mail server bounce all messages that It rose much higher (5000/day) in the interim, and Tsai: I was thinking about spam a lot before Graham published his paper,īecause I was getting more than a thousand spams a day. ![]() Were thinking about before Paul Graham published “ A Plan for Spam”? Gruber: When did you get the idea to write SpamSieve? Was it something you (Safari users: Use the Reload Page command to force Safari to update its cached version of this site’s CSS style sheet trust me, the interview will look much better.) Needless to say, I highly recommend SpamSieve. SpamSieve is easy to set up, runs quickly, and works with every major Mac OS X email client except Apple Mail (it even works with Claris Emailer). I’ve been using SpamSieve 2 for over a month (including beta releases), and its efficacy has bordered on the incredible: flagging all but 10 of 1981 spams. SpamSieve includes several types of filtering strategies, most especially a Bayesian statistical filter. His latest software release is SpamSieve 2, a major update to his US$25 spam filtering utility. Michael is also the editor and publisher of the monthly Mac e-zine About This Particular Macintosh, and he writes a Mac-oriented weblog. Michael Tsai is a Macintosh software developer who has authored several useful utilities, including DropDMG and BBAutoComplete. ![]() Interview: Michael Tsai Wednesday, 24 September 2003 ![]()
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