Statistics and The War on Spam

Text categorization algorithms assign texts to predefined categories. The study of such algorithms has a rich history dating back at least forty years. In the last decade or so, the statistical approach has dominated the literature. The essential idea is to infer a text categorization algorithm from a set of labeled documents, i.e., documents with known category assignments. The algorithm, once learned, automatically assigns labels to new documents. Motivated by a successful application to “spam” or “unsolicited bulk e-mail” filtering, this chapter will present the “Naive Bayes” approach to statistical text categorization.