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Component-based recommendation agent system for efficient email inbox management

Title
Component-based recommendation agent system for efficient email inbox management
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. 3314, pp. 812 - 818
Indexed
SCOPUS scopus
Abstract
This study suggests a recommendation agent system that the user can optimally sort out incoming email messages according to category. The system is an effective way to manage ever-increasing email documents. For more accurate classification, the Bayesian learning algorithm using dynamic threshold has been applied. As a solution to the problem of erroneous classification, we suggest the following two approaches: First is the algorithmic approach that improves the accuracy of the classification by using dynamic threshold of the existing Bayesian algorithm. Second is the methodological approach using recommendation agent that the user, not the auto-sort, can make the final decision. In addition, major modules are based on rule filtering components for scalability and reusability. © Springer-Verlag 2004.
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엘텍공과대학 > 컴퓨터공학과 > Journal papers
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