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Improving a user's preferences on SPAM learning, detection and filtering
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Description

A Kolab user should be able to mark an email as SPAM. This email should then be moved to a dedicated SPAM folder. Furthermore, Kolab should learn from that SPAM mail and increase its chances to classify similar mails as SPAM in the future.

Bonus points for default sieve filters that move incoming SPAM mails automatically to the junk folder, so users do not have to set those filters up manually. The SPAM filter rule could even get its own more user friendly interface similar to managesieve_vacation that lets users set the SPAM threshold and the folder to move mails to.

Details

Ticket Type
Epic

Event Timeline

grote raised the priority of this task from to 60.
grote updated the task description. (Show Details)
grote changed Ticket Type from Task to Epic.
grote moved this task from Incoming to In Triage on the Product Owners board.
grote subscribed.

This should probably be an epic on improving a user's preferences on spam learning, detection and filtering.

grote renamed this task from Add Mark As Spam Feature with Learning to Improving a user's preferences on SPAM learning, detection and filtering.May 7 2015, 2:19 AM
vanmeeuwen lowered the priority of this task from 60 to Normal.Mar 28 2019, 8:13 AM