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- W2338017847 abstract "it is important to carry out email classification to determine its topic [2],[3],[4],[5],[6],[7],[8]. This paper is aimed at making new agents model to determine the email topic by classifying them based on the subject and content autonomously. This domain model is university archiving. The email topic is the keyword of the job description in the university’s units. The email target, except the one to the university director, is based on the email topic. The classification method used was Naive Bayesian and Gaussian Density Methods. The agents used were those with proactive characteristic that can work autonomously in classifying emails. The development of this new model results in the detailed email target. Using this model, most emails can be classified correctly according to the categories." @default.
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- W2338017847 date "2016-04-15" @default.
- W2338017847 modified "2023-09-29" @default.
- W2338017847 title "An Agent Model using Naïve Bayesian for Email Classification" @default.
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- W2338017847 doi "https://doi.org/10.5120/ijca2016909393" @default.
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