We report on the construction of an ontology that applies rules for identification of features to be used for email classification. The associated probabilities for these features are then calculated from the training set of emails and used as part of the feature vectors for an underlying Bayesian classifier.
Citation:
Kazem Taghva, Julie Borsack, Jeffrey Coombs, Allen Condit, Steve Lumos, Tom Nartker, "Ontology-based Classification of Email," itcc, pp.194, International Conference on Information Technology: Computers and Communications, 2003