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First ammendment Only recently, has such a solution been developed in the form of Bayesian filters. The Bayesian statistical method, upon which the filters are based, works on the premise of dividing emails into categories. The software takes a log of the emails which you choose to open and those you simply delete. All the while, it monitors the characteristics of both those emails you opened and those you did not. Over time, it learns from these aggregate figures. It will recognize certain words that appear frequently in those emails which you constantly ignore. The software will then be more prone to categorizing emails with a high frequency of that particular word as spam. buick porthole

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Minnesota theater But lest you be concerned that not opening a few emails from your Aunt Sue will suddenly cause all emails with the word ‘Sue’ to be categorized as spam you should know that the Bayesian filters work in the aggregate. This means, that while your decisions on which emails to open and which to not will affect the algorithm, so will the activities of thousands if not tens of thousands of other users. Spread across such a wide body of users, and aggregating data over such a period, there is only a minimal danger of false labeling. Rather, what you get is a very accurate long term tool to block spam. Unfortunately, those same characteristics which prevent false blocking also limit the Bayesian spam filter from blocking the front wave of a new spamming technique. So, often the effect is a few days or weeks of a new technique in spamming sneaking through the cracks until it is worked out into the algorithm.

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