A Large-Scale Evaluation of an E-mail Management Assistant

@article{Wobcke2008ALE,
  title={A Large-Scale Evaluation of an E-mail Management Assistant},
  author={Wayne Wobcke and Alfred Krzywicki and Yiu-Wa Chan},
  journal={2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology},
  year={2008},
  volume={2},
  pages={438-442}
}
EMMA is an e-mail management assistant based on Ripple Down Rules, providing a high degree of classification accuracy while simplifying the task of maintaining the consistency of the rule base. A Naive Bayes algorithm is used to improve the usability of EMMA by suggesting keywords to help the user define rules. In this paper, we report on an experimental evaluation of EMMA on 16 998 pre-classified messages. The aim of the evaluation was to show that the Ripple Down Rule technique used in EMMA… CONTINUE READING

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