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A Bayesian approach to filtering junk E-mail (1998)
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| Venue: | PAPERS FROM THE 1998 WORKSHOP, AAAI |
| Citations: | 544 - 6 self |
BibTeX
@TECHREPORT{Sahami98abayesian,
author = {Mehran Sahami and Susan Dumais and David Heckerman and Eric Horvitz},
title = {A Bayesian approach to filtering junk E-mail},
institution = {PAPERS FROM THE 1998 WORKSHOP, AAAI},
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.
