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E-mail Classification Agent Using Category Generation and Dynamic Category Hierarchy

  • Sun Park
  • Sang-Ho Park
  • Ju-Hong Lee
  • Jung-Sik Lee
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3397)

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

Keywords

Fuzzy Subset Vector Model Category Label Index Term Implication Operator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Sun Park
    • 1
  • Sang-Ho Park
    • 1
  • Ju-Hong Lee
    • 1
  • Jung-Sik Lee
    • 2
  1. 1.School of Computer science and Information EngineeringInha UniversityIncheonKorea
  2. 2.School of Electronic & Information EngineeringKunsan National UniversityKunsanKorea

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