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A Bayesian Approach to Filtering Junk E-Mail (1998) [236 citations — 5 self]

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by Mehran Sahami , Susan Dumais , David Heckerman , Eric Horvitz

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@MISC{Sahami98abayesian,
    author = {Mehran Sahami and Susan Dumais and David Heckerman and Eric Horvitz},
    title = {A Bayesian Approach to Filtering Junk E-Mail},
    year = {1998}
}

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Abstract:

In addressing the growing problem of junk E-mail on the Internet, we examine methods for the automated construction of filters to eliminate such unwanted messages from a user's mail stream. By casting this problem in a decision theoretic framework, we are able to make use of probabilistic learning methods in conjunction with a notion of differential misclassification cost to produce filters which are especially appropriate for the nuances of this task. While this may appear, at first, to be a straight-forward text classification problem, we show that by considering domain-specific features of this problem in addition to the raw text of E-mail messages, we can produce much more accurate filters. Finally, we show the efficacy of such filters in a real world usage scenario, arguing that this technology is mature enough for deployment. Introduction As the number of users connected to the Internet continues to skyrocket, electronic mail (E-mail) is quickly becoming one of the fastest and m...

Citations

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