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http://dx.doi.org/10.9708/jksci.2011.16.2.033

A proper folder recommendation technique using frequent itemsets for efficient e-mail classification  

Moon, Jong-Pil (KT Innotz)
Lee, Won-Suk (Dept. of Computer Science, Yonsei University)
Chang, Joong-Hyuk (Dept. of Computer & Information Technology, Daegu University)
Publication Information
Journal of the Korea Society of Computer and Information / v.16, no.2, 2011 , pp. 33-46 More about this Journal
Abstract
Since an e-mail has been an important mean of communication and information sharing, there have been much effort to classify e-mails efficiently by their contents. An e-mail has various forms in length and style, and words used in an e-mail are usually irregular. In addition, the criteria of an e-mail classification are subjective. As a result, it is quite difficult for the conventional text classification technique to be adapted to an e-mail classification efficiently. An e-mail classification technique in a commercial e-mail program uses a simple text filtering technique in an e-mail client. In the previous studies on automatic classification of an e-mail, the Naive Bayesian technique based on the probability has been used to improve the classification accuracy, and most of them are on an e-mail in English. This paper proposes the personalized recommendation technique of an email in Korean using a data mining technique of frequent patterns. The proposed technique consists of two phases such as the pre-processing of e-mails in an e-mail folder and the generating a profile for the e-mail folder. The generated profile is used for an e-mail to be classified into the most appropriate e-mail folder by the subjective criteria. The e-mail classification system is also implemented, which adapts the proposed technique.
Keywords
E-mail classification; Customized recommendation; Customized classification; Frequent itemsets; Document classification;
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Times Cited By KSCI : 5  (Citation Analysis)
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