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Collaborative filters rely on users marking traffic as either spam or not-spam. Aggregate Collaborative filters can also easily become systems for collaborative censorship. For example, [http://blogs.alternet.org/oleoleolson/2010/08/05/ ...

...messages, to train a Bayesian filter accurately. Both filter training and filtering are slow, since they require significant processing of messages to extract A significant source of corpora is [[Collaborative Filtering]], q.v. ...

** [[Collaborative filters]] * [[URL filtering]] ...