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The ARF format is designed to be extensible, providing for generic spam reporting, e.g. from users to some anti-spam center or help desk, or for opt-out operations. The format defines a new MIME type to be included in a multipart/report attachment, and includes at least the headers of the offending message.
The feedback provider and the feedback consumer are the two formal endpoints of the feedback loop (blue arrow). Senders need to subscribe, possibly using a web form similar to the one depicted on the upper left corner, in order to become feedback consumers. Recipients typically click a spam button on a web mail page to start the process.
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Various anti-spam techniques are used to prevent email spam (unsolicited bulk email).. No technique is a complete solution to the spam problem, and each has trade-offs between incorrectly rejecting legitimate email (false positives) as opposed to not rejecting all spam email (false negatives) – and the associated costs in time, effort, and cost of wrongfully obstructing good mail.
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With this additional contextual recognition, it is one of the more accurate spam filters available. Initial testing in 2002 by author Bill Yerazunis [ 1 ] gave a 99.87% accuracy; [ 2 ] Holden [ 3 ] and TREC 2005 and 2006 [ 4 ] [ 5 ] gave results of better than 99%, with significant variation depending on the particular corpus.
While 99.9% of spam, malware and phishing emails are being caught by our spam filters, occasionally some can slip through. When this happens, it's very important to mark the email as spam, then our system will learn that messages from a specific sender aren't good and helps us make AOL Mail even better at recognizing future spam emails.
Here's the 411: your spam folder is basically a catchall spot in your email account that automatically filters out junk mail, or "spam." Digital junk mail is just like the unwanted coupons, flyers ...