A Survey of Content-based Spam Classifiers
نویسنده
چکیده
Unsolicited bulk e-mail (spam) is a growing problem with tangible costs felt by virtually every Internet user. There are many solutions to this problem, ranging from simple blacklisting to advanced text classification and collaborative filtering. None of these techniques provides a total solution, but new technologies and their application offer increasingly effective filters. This paper provides an overview and comparison of the advanced spam filtering techniques that classify messages based on their content. This includes statistical classifiers, collaborative filters and combinations of different classifiers.
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