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An Agent Model using Naïve Bayesian for Email Classification
Author(s) -
Muhammad Hasbi,
Retantyo Wardoyo,
Jazi Eko,
Khabib Mustofa
Publication year - 2016
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/ijca2016909393
Subject(s) - computer science , bayesian probability , naive bayes classifier , artificial intelligence , machine learning , information retrieval , support vector machine
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.

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