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Extracting User Profiles from E-mails Using the Set-Oriented Classifier

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2417))

Abstract

More and more people rely on e-mails rather than postal letters to communicate to each other. Although e-mails are more convenient, letters still have many positive features. The ability to handle “anonymous recipient” is one of them. This paper proposes a software agent that performs the routing task as human beings for the anonymous recipient e-mails. The software agent named “TWIMC (To Whom It May Concern)” receives anonymous recipient e-mails, analyze it, and then routes the e-mail to the mostly qualified person (i.e., e-mail account) inside the organization. The agent employs the Set-oriented Classifier System (SCS) that is a genetic algorithm classifier that uses set representation internally. The comparison of SCS with the Support Vector Machine (SVM) shows that the SCS outperforms SVM under noisy environment.

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© 2002 Springer-Verlag Berlin Heidelberg

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Ku, S., Lee, B., Ha, E. (2002). Extracting User Profiles from E-mails Using the Set-Oriented Classifier. In: Ishizuka, M., Sattar, A. (eds) PRICAI 2002: Trends in Artificial Intelligence. PRICAI 2002. Lecture Notes in Computer Science(), vol 2417. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45683-X_50

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  • DOI: https://doi.org/10.1007/3-540-45683-X_50

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44038-3

  • Online ISBN: 978-3-540-45683-4

  • eBook Packages: Springer Book Archive

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