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Overview | Support
Junk-Out keeps junk mail out of your Microsoft Outlook Inbox, using a combination of statistical methods (Bayesian filtering) and information you provide, to show only e-mail messages you want to see. The more you use Junk-Out, the better it gets at distinguishing useful e-mail, and getting junk out of your way.
The heart of Junk-Out is its continually learning content-based / Bayesian filter mechanism. This feature can use a Fast Track word list, a 'seed' vocabulary of well over 100,000 words, to start filtering junk out of your incoming e-mail as soon as you install it. Then it gets better with every e-mail you receive, adding to its knowledge from experience and the training you give it with just a click of the mouse. For Basic users, Junk-Out keeps it simple: just use it as you find it at installation, and train it by marking any messages that are misclassified upon arrival. If a new message arrives and is not marked as junk by the program when it should have been, click the Mark Message as Junk Mail button on the Junk Mail Tools toolbar/menu to reclassify the message and 'teach' the Bayesian filter to recognize similar messages as junk from then on. Similarly, if a new message is marked as junk but should not have been, click the Mark Message as Non-Junk Mail button on the Junk Mail Tools toolbar/menu to reclassify the message and 'teach' the Bayesian filter to recognize similar messages as 'good' from now on. You can also use the Add to Friends List button on the Junk Mail Tools toolbar/menu to add the sender of good messages to your Friends list, which ensures that Junk-Out leaves all their messages in your Inbox without further filtering. Advanced users can make Junk-Out as straightforward or as sophisticated as they like. They can use all the "Basic" features, plus, they can 'fine tune' the program by choosing whether and how the features work, tailoring Junk-Out to their individual preferences. Keywords: Spam, anti-spam, junk, e-mail, mail, junk mail, junk e-mail, Outlook, add-in, plug-in, Bayesian, remover, statistical, probability
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