E-mail classification agent using category generation and dynamic category hierarchy

  • Authors:
  • Sun Park;Sang-Ho Park;Ju-Hong Lee;Jung-Sik Lee

  • Affiliations:
  • School of Computer science and Information Engineering, Inha University, Incheon, Korea;School of Computer science and Information Engineering, Inha University, Incheon, Korea;School of Computer science and Information Engineering, Inha University, Incheon, Korea;School of Electronic & Information Engineering, Kunsan National University, Kunsan, Korea

  • Venue:
  • AIS'04 Proceedings of the 13th international conference on AI, Simulation, and Planning in High Autonomy Systems
  • Year:
  • 2004

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Abstract

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