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Automatic Email Multi-category Classification Using Dynamic Category Hierarchy and Non-negative Matrix Factorization  

Park, Sun (전북대학교 전자정보고급인력양성사업단)
An, Dong-Un (전북대학교 전자정보공학부)
Publication Information
Journal of KIISE:Software and Applications / v.37, no.5, 2010 , pp. 378-385 More about this Journal
Abstract
The explosive increase in the use of email has made to need email classification efficiently and accurately. Current work on the email classification method have mainly been focused on a binary classification that filters out spam-mails. This methods are based on Support Vector Machines, Bayesian classifiers, rule-based classifiers. Such supervised methods, in the sense that the user is required to manually describe the rules and keyword list that is used to recognize the relevant email. Other unsupervised method using clustering techniques for the multi-category classification is created a category labels from a set of incoming messages. In this paper, we propose a new automatic email multi-category classification method using NMF for automatic category label construction method and dynamic category hierarchy method for the reorganization of email messages in the category labels. The proposed method in this paper, a large number of emails are managed efficiently by classifying multi-category email automatically, email messages in their category are reorganized for enhancing accuracy whenever users want to classify all their email messages.
Keywords
email multi-category classification; NMF; dynamic category hierarchy;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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