2008 Second Asia International Conference on Modelling & Simulation Learning to Classify Threaten E-mail May 13-May 15 ISBN: 978-0-7695-3136-6
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/AMS.2008.100
In this paper we study supervised classification of e-mails. We consider the task of Threaten E-mail Detection (i.e. email related to terrorism, fraud, etc.). In this supervised learning setting, we investigate the use of Datamining classifiers for automatic threaten e-mail detection. We show that Decision Tree is a good choice for this task asit runs fast on large and high dimensional databases, is easy to tune and is highly accurate, outperforming popular algorithms such as Support Vector Machines, Naive Bayes. In particular, we are interested in detecting fraudulent andpossibly criminal activities from such e-mails.
Index Terms:
Data mining, Classification, DT, SVM, NB.
Citation:
Subramanian Appavu alias Balamurugan, Ramasamy Rajaram, "Learning to Classify Threaten E-mail," ams, pp.522-527, 2008 Second Asia International Conference on Modelling & Simulation, 2008 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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