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Comparison of Four Methods of Combining Classifiers on the Basis of Dispersed Medical Data Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Automatic Categorization of Email into Folders by Ant Colony Decision Tree and Social Networks

Authors : Urszula Boryczka, Barbara Probierz, Jan Kozak

Published in: Intelligent Decision Technologies 2016

Publisher: Springer International Publishing

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Abstract

This paper presents a new approach to an automatic categorization of email messages into mailbox folders. The aim of this paper is to create an algorithm that would allow one to improve the classification of emails into folders by using solutions that have been applied in Ant Colony Decision Tree (ACDT). Additionally, elements of Social Network Analysis (SNA) were included in this algorithm. The new algorithm that is proposed here was tested on the publicly available Enron E-mail data set and all experiments were conducted on uncleaned data. For the purpose of comparing the results, additional tests were carried out by using selected classifiers which were generally available. The obtained results confirm that the proposed approach allows one to improve the accuracy with which new emails are assigned to particular folders based on an analysis of previous correspondence, even when uncleaned data sets are used.

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Metadata
Title
Automatic Categorization of Email into Folders by Ant Colony Decision Tree and Social Networks
Authors
Urszula Boryczka
Barbara Probierz
Jan Kozak
Copyright Year
2016
Book
Intelligent Decision Technologies 2016

Print ISBN: 978-3-319-39626-2

Electronic ISBN: 978-3-319-39627-9

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-39627-9_7

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