Abstract
This article presents a new approach to an automatic categorization of email messages which is based on Ant Colony Optimization algorithms (ACO). The aim of this paper is to create an algorithm that would allow one to improve the classification of emails into folders (the email foldering problem) by using solutions that have been applied in Ant Colony algorithms, data mining and Social Network Analysis (SNA). The new algorithm which is proposed here has been tested on the publicly available Enron email data set. The obtained results confirm that this approach allows one to improve the accuracy with which new emails are assigned to particular folders based on an analysis of previous correspondence.
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Boryczka, U., Probierz, B., Kozak, J. (2014). An Ant Colony Optimization Algorithm for an Automatic Categorization of Emails. In: Hwang, D., Jung, J.J., Nguyen, NT. (eds) Computational Collective Intelligence. Technologies and Applications. ICCCI 2014. Lecture Notes in Computer Science(), vol 8733. Springer, Cham. https://doi.org/10.1007/978-3-319-11289-3_59
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DOI: https://doi.org/10.1007/978-3-319-11289-3_59
Publisher Name: Springer, Cham
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