Spam E-mail Classification Based on the IFWB Algorithm
學年 101
學期 2
發表日期 2013-03-18
作品名稱 Spam E-mail Classification Based on the IFWB Algorithm
作品名稱（其他語言）
著者 Jou, Chichang
作品所屬單位 淡江大學資訊管理學系
出版者 Springer
會議名稱 Asian Conference on Intelligent Information and Database Systems (ACIIDS 2013)
會議地點 Kuala Lumpur, Malaysia
摘要 The problem of spam e-mails has been addressed for some time. Most of the solutions are based on spam e-mail classification and filtering. However, the content of spam e-mails drifts with new concepts or social events. Thus, several spam classifiers perform effectively when their models are initially established, and their performances deteriorate with time. A learning mechanism is required to adjust the classification parameters for new and old e-mails. Because of the spread of spam e-mails, the number of spam e-mails is larger than that of legitimate e-mails. Therefore, most classifiers produce high recall for spam e-mails and low recall for legitimate e-mails. Based on the Bayesian algorithm, we propose an incremental forgetting weighted algorithm with a misclassification cost mechanism that extracts features by IGICF (Information Gain and Inverse Class Frequency) to address the problem of concept drift and data skew in spam e-mail classification. We implemented the algorithm and performed detailed tests on the effectiveness of the mechanism.
關鍵字
語言 en
收錄於 EI
會議性質 國際
校內研討會地點
研討會時間 20130318~20130320
通訊作者
國別 MYS
公開徵稿 Y
出版型式 紙本
出處 Lecture Notes in Computer Science 7802, pp.314-324
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