the advantage of Bayesian spam filtering is that it can be trained on a per-user basis The spam that a user receives is often related to the online users activities For example a user may have been subscribed to an online newsletter that the user considers to be spam This online newsletter is likely to contain words that are common to all newsletters such as the name of the newsletter and its originating email address A Bayesian spam filter will eventually assign a higher probability based on the users specific patterns