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Erschienen in:
2005 | OriginalPaper | Buchkapitel
E-mail Classification Agent Using Category Generation and Dynamic Category Hierarchy
verfasst von : Sun Park, Sang-Ho Park, Ju-Hong Lee, Jung-Sik Lee
Erschienen in: Artificial Intelligence and Simulation
Verlag: Springer Berlin Heidelberg
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With e-mail use continuing to explode, the e-mail users are demanding a method that can classify e-mails more and more efficiently. The previous works on the e-mail classification problem have been focused on mainly a binary classification that filters out spam-mails. Other approaches used clustering techniques for the purpose of solving multi-category classification problem. But these approaches are only methods of grouping e-mail messages by similarities using distance measure. In this paper, we propose of e-mail classification agent combining category generation method based on the vector model and dynamic category hierarchy reconstruction method. The proposed agent classifies e-mail automatically whenever it is needed, so that a large volume of e-mails can be managed efficiently