A sequential algorithm for training text classifiers
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
GroupLens: applying collaborative filtering to Usenet news
Communications of the ACM
Type Classification of Semi-Structured Documents
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Machine learning in automated text categorisation
Machine learning in automated text categorisation
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The increased use of Internet generalizes the use of e-mail, a medium for information exchange. E-mail is used not only for individual purposes but also in a variety of purposes that users have to process significant volume. In this study, we propose a recommendation agent system the enable users for direct and optimal classification with the recommendation of the applicable category when a mail arrives as a way of efficient management of e-mail. For this purpose, three pre-processing algorithms are suggested for accurate classification, the core part of this study, and, it considers the scalability and reusability with the major filtering part is based on the rule-filtering component.