Abstract
We propose a novel solution to the email classification problem: the integration of temporal information with the traditional content-based classification approaches. We discover temporal relations in an email sequence in the form of temporal sequential patterns and embed the discovered information into contentbased learning methods. The new heterogeneous classification system shows a good performance reducing the classification error by up to 22%.
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Kiritchenko, S., Matwin, S., Abu-Hakima, S. (2004). Email Classification with Temporal Features. In: Kłopotek, M.A., Wierzchoń, S.T., Trojanowski, K. (eds) Intelligent Information Processing and Web Mining. Advances in Soft Computing, vol 25. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39985-8_61
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DOI: https://doi.org/10.1007/978-3-540-39985-8_61
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-21331-4
Online ISBN: 978-3-540-39985-8
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