Email White Papers
An Evaluation of Naive Bayesian Anti-Spam Filtering
Overview It has recently been argued that a Naive Bayesian classifier can be used to filter unsolicited bulk e-mail ("Spam"). This paper conducts a thorough evaluation of this proposal on a corpus that they make publicly available, contributing towards standard benchmarks. At the same time they investigate the effect of attribute-set size, training-corpus size, lemmatization, and stop-lists on the filter's performance, issues that had not been previously explored. After introducing appropriate cost-sensitive evaluation measures, they reach the conclusion that additional safety nets are needed for the Naive Bayesian anti-spam filter to be viable in practice.
| Publisher | Demokritos | File Format | |
|---|---|---|---|
| Date Published | May 2000 | ||
| Format | White Papers | ||
| Topics | |||
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