We consider the problem of content-based spam filtering for short text messages that arise in three contexts: mobile (SMS) communication, blog comments, and email summary informa...
In this paper, we report our work on spam filtering with three novel bayesian classification methods: Aggregating One-Dependence Estimators (AODE), Hidden Naïve Bayes (HNB), Loca...
To circumvent prevalent text-based anti-spam filters, spammers have begun embedding the advertisement text in images. Analogously, proprietary information (such as source code) ma...
Hrishikesh Aradhye, Gregory K. Myers, James A. Her...
The results of the 2006 ECML/PKDD Discovery Challenge suggest that semi-supervised learning methods work well for spam filtering when the source of available labeled examples diff...
The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques ...