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    政大機構典藏 > 理學院 > 心理學系 > 期刊論文 >  Item 140.119/111428
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/111428


    Title: An efficient incremental learning mechanism for tracking concept drift in spam filtering
    Authors: Sheu, Jyh-Jian
    許志堅
    Chu, Ko-Tsung
    Lee, Cheng-Chi
    Li, Nien-Feng
    Contributors: 廣播電視學系
    Keywords: data mining;decision tree;e-mail;filtration;learning
    Date: 2017
    Issue Date: 2017-07-27 12:54:39 (UTC+8)
    Abstract: This research manages in-depth analysis on the knowledge about spams and expects to propose an efficient spam filtering method with the ability of adapting to the dynamic environment. We focus on the analysis of email's header and apply decision tree data mining technique to look for the association rules about spams. Then, we propose an efficient systematic filtering method based on these association rules. Our systematic method has the following major advantages: (1) Checking only the header sections of emails, which is different from those spam filtering methods at present that have to analyze fully the email's content. Meanwhile, the email filtering accuracy is expected to be enhanced. (2) Regarding the solution to the problem of concept drift, we propose a window-based technique to estimate for the condition of concept drift for each unknown email, which will help our filtering method in recognizing the occurrence of spam. (3) We propose an incremental learning mechanism for our filtering method to strengthen the ability of adapting to the dynamic environment. © 2017 Sheu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
    Relation: PLoS ONE, 12(2), 論文編號 e0171518
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1371/journal.pone.0171518
    DOI: 10.1371/journal.pone.0171518
    Appears in Collections:[心理學系] 期刊論文

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