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https://ah.lib.nccu.edu.tw/handle/140.119/112126
題名: | An intelligent three-phase spam filtering method based on decision tree data mining | 作者: | 許志堅 Sheu, Jyh-Jian Chen, Yin-Kai Chu, Ko-Tsung Tang, Jih-Hsin Yang, Wei-Pang |
貢獻者: | 廣播電視學系 | 關鍵詞: | Artificial intelligence; Decision trees; Electronic mail; Internet; Learning systems; Supervised learning; Trees (mathematics); Filtering method; Learning mechanism; Operating efficiency; Overall accuracies; Spam; Spam filtering; Supervised machine learning; Three phase; Data mining | 日期: | Nov-2016 | 上傳時間: | 23-Aug-2017 | 摘要: | In this paper, we proposed an efficient spam filtering method based on decision tree data mining technique, analyzed the association rules about spams, and applied these rules to develop a systematized spam filtering method. Our method possessed the following three major superiorities: (i) checking only an e-mail`s header section to avoid the low-operating efficiency in scanning an e-mail`s content. Moreover, the accuracy of filtering was enhanced simultaneously. (ii) In order that the probable misjudgment in identifying an unknown e-mail could be “reversed”, we had constructed a reversing mechanism to help the classification of unknown e-mails. Thus, the overall accuracy of our filtering method will be increased. (iii) Our method was equipped with a re-learning mechanism, which utilized the supervised machine learning method to collect and analyze each misjudged e-mail. Therefore, the revision information learned from the analysis of misjudged e-mails incrementally gave feedback to our method, and its ability of identifying spams would be improved. | 關聯: | Security and Communication Networks, 9(17), 4013-4026 | 資料類型: | article | DOI: | http://dx.doi.org/10.1002/sec.1584 |
Appears in Collections: | 期刊論文 |
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