11/30/2023 0 Comments Spamsieve coupon![]() ![]() SpamSieve accomplishes this by using the AppleScript capabilities of these email programs to pass information to and from SpamSieve itself. Once it has identified messages as spam, it can mark or move them, and in some of the email programs, your filters can continue to work on the marked messages. SpamSieve works with any number of accounts and filters mail from any source your email program supports. I’m not interested in using Mail, and other spam utilities (such as Matterform Media’s points-based Spamfire utility, which also has many proponents) work outside of your email program, forcing you to scan for false positives in a separate interface). Although it’s not available for Mac OS 9, it does also work with Emailer running in Classic mode. SpamSieve - Along with its implementation of Bayesian filter, I especially appreciate the fact that SpamSieve works inside Eudora, and also inside a number of other email programs, including Entourage, Mailsmith, and PowerMail. There are two main implementations of statistical Bayesian filtering for Mac OS X: Apple’s Mail and Michael Tsai’s SpamSieve, the latter of which I’ve been testing with Eudora 5.2 for some months now. ![]() On the positive side, it’s possible that improved algorithms can address these problems. It’s also possible for spammers to pollute your corpus of good and bad words by including lots of good words in a spam message, thus reducing the accuracy of the filter over time. Spam may get through when it’s sufficiently related to your profession for instance, I get spam advertising translation services because of the TidBITS translations. Legitimate mail, such as promotional mailings from companies you’ve bought from in the past, can look a lot like spam at first, and it’s also hard to identify spam messages with minimal text accurately. That’s because you must train a Bayesian filter with a sample of both spam and legitimate messages, and because the Bayesian filter continually examines new messages, it can adapt to the kind of mail you receive, both good and bad.īayesian filters aren’t perfect. Statistical (or Bayesian) filters, which were most popularly described in relation to spam in August of 2002 (and refined last month) by Paul Graham, use a statistical approach that combines the probability that any given word or phrase (implementations vary) to decide if the message is spam.īayesian Filters - The beauty of Bayesian filtering is that it works on the contents of your email, which is probably rather different from mine and anyone else’s. Points-based filters refine that approach, assigning (or removing) points for each criteria matched by a given message they decide if a message is spam or not by how many points that message accumulates. Put simply, a Boolean filter looks for string of text, and if it’s found, considers the message spam. You can reduce the flow, though, with one of three basic approaches to filtering spam out of your email stream: Boolean filters, points-based filters, and so-called "Bayesian" statistical filters. Having to sort through the increasingly repulsive spam that’s rushing into our electronic mailboxes is becoming more unpleasant than ever. ![]() #1668: Updated Rapid Security Responses, OS public betas, screen saver bug fixed, “Red Team Blues” book review.#1669: OS security updates, ambiguity of emoji, small business payments with Melio, Twitter now X.#1670: Arc Web browser hits 1.0 release, “Do You Use It?” polls about Apple features. ![]() #1671: Apple Q3 2023 earnings, new Beats headphones and earbuds, Stage Manager adoption rate, do you use Spotlight?.1672: The hidden power of Google Sheets, Launchpad usage levels, Emergency SOS via satellite in the Maui fires, do you use proxy icons?. ![]()
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