Interactive email filtering: Learning from misclassified examples

Chen, D., Li, X., Dong, Z. Y. and Smith, P.A. (2004). Interactive email filtering: Learning from misclassified examples. In: S. Ge and K. Tan, Proceedings of the 2004 IEEE Conference on Cybernetics and Intelligent Systems. The 2004 IEEE Conference on Cybernetics and Intelligent Systems, Singapore, (1060-1065). 1-3 December, 2004. doi:10.1109/ICCIS.2004.1460736


Author Chen, D.
Li, X.
Dong, Z. Y.
Smith, P.A.
Title of paper Interactive email filtering: Learning from misclassified examples
Conference name The 2004 IEEE Conference on Cybernetics and Intelligent Systems
Conference location Singapore
Conference dates 1-3 December, 2004
Proceedings title Proceedings of the 2004 IEEE Conference on Cybernetics and Intelligent Systems
Place of Publication Los Alamitos, CA, U.S.A.
Publisher IEEE
Publication Year 2004
Sub-type Fully published paper
DOI 10.1109/ICCIS.2004.1460736
ISBN 0-7803-8643-4
Editor S. Ge
K. Tan
Volume 2
Start page 1060
End page 1065
Total pages 6
Collection year 2004
Language eng
Abstract/Summary Learning from mistakes has proven to be an effective way of learning in the interactive document classifications. In this paper we propose an approach to effectively learning from mistakes in the email filtering process. Our system has employed both SVM and Winnow machine learning algorithms to learn from misclassified email documents and refine the email filtering process accordingly. Our experiments have shown that the training of an email filter becomes much effective and faster
Subjects E1
280103 Information Storage, Retrieval and Management
700103 Information processing services
Q-Index Code E1

 
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Created: Thu, 23 Aug 2007, 19:25:27 EST