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A personalized recommendation agent system for e-mail document classification

Title
A personalized recommendation agent system for e-mail document classification
Authors
Jeong O.-R.Cho D.-S.
Ewha Authors
조동섭
SCOPUS Author ID
조동섭scopus
Issue Date
2004
Journal Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ISSN
0302-9743JCR Link
Citation
vol. 3045, pp. 558 - 565
Indexed
SCOPUS WOS scopus
Abstract
Overload of information due to rapidly developing Internet and increases of e-mails are inconvenience for all Netizens now. Many existing recommendation systems or text classification using personalization techniques are mostly focused on recommending the products for the commercial purposes or web documents. This study aims to apply these application categories to e-mail more necessary to users. Moreover, this study tries to improve the accuracy as eliminating the limits of misclassification that can be key in classifying e-mails by category and deleting Spam mails. This paper suggests a Personalized Recommendation Agent System (PRAS) recommending the relevant category to enable users directly to manage the optimum classification when new e-mail is received as the effective method for e-mail management. While the existing Bayesian Learning Algorithm mostly uses the fixed threshold, this study proves to improve the satisfaction of users as increasing the accuracy by changing the fixed threshold to the dynamic threshold. © Springer-Verlag Berlin Heidelberg 2004.
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엘텍공과대학 > 컴퓨터공학과 > Journal papers
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