From mboxrd@z Thu Jan 1 00:00:00 1970 X-Spam-Checker-Version: SpamAssassin 3.4.4 (2020-01-24) on polar.synack.me X-Spam-Level: X-Spam-Status: No, score=-1.9 required=5.0 tests=BAYES_00 autolearn=ham autolearn_force=no version=3.4.4 X-Google-Language: ENGLISH,ASCII-7-bit X-Google-Thread: 103376,c7ee0d960296483 X-Google-Attributes: gid103376,public X-Google-ArrivalTime: 2003-09-23 10:44:22 PST Path: archiver1.google.com!news1.google.com!newsfeed.stanford.edu!logbridge.uoregon.edu!newshub.sdsu.edu!elnk-nf2-pas!newsfeed.earthlink.net!stamper.news.pas.earthlink.net!newsread4.news.pas.earthlink.net.POSTED!not-for-mail From: Jeffrey Carter Organization: jrcarter commercial-at acm [period | full stop] org User-Agent: Mozilla/5.0 (Windows; U; Win98; en-US; rv:1.4) Gecko/20030624 X-Accept-Language: en-us, en MIME-Version: 1.0 Newsgroups: comp.lang.ada Subject: Re: Current "Swen" worm attack - a tip References: In-Reply-To: Content-Type: text/plain; charset=us-ascii; format=flowed Content-Transfer-Encoding: 7bit Message-ID: Date: Tue, 23 Sep 2003 17:44:22 GMT NNTP-Posting-Host: 63.184.105.215 X-Complaints-To: abuse@earthlink.net X-Trace: newsread4.news.pas.earthlink.net 1064339062 63.184.105.215 (Tue, 23 Sep 2003 10:44:22 PDT) NNTP-Posting-Date: Tue, 23 Sep 2003 10:44:22 PDT Xref: archiver1.google.com comp.lang.ada:42815 Date: 2003-09-23T17:44:22+00:00 List-Id: Preben Randhol wrote: > > I have found that the baysian filtering is very good when you have > taught it what is spam and what is not. It takes a bit effort in the > beginning, but now I get about 40-50 spams a day and I have some 5-7 > mailinglists and it filters all for me into correct folders. Sometimes a > spam ends in the wrong place, but then it is simply (for me) to press a > key and it is relearnt as spam and moved into that folder. > > I have heard talk that the naive baysian statisical methods used could > be improved and other statistical methods might do better, however there > has not been an implementation yet. So if anybody here knows statistics > it is a nice chance to make a killer spam filter :-) I've long felt that a neural network should be able to learn to distinguish spam from real mail very accurately. The problem is figuring out a good way to represent a mail message to the network. I haven't had much success on that, but once you have that, training the network is simple. -- Jeff Carter "I've got to stay here, but there's no reason why you folks shouldn't go out into the lobby until this thing blows over." Horse Feathers 50