期刊文献+

中文垃圾邮件变异特征检测研究

Research on Chinese Spam Variation Features Detection
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摘要 通过对比垃圾邮件的变化,以及对垃圾邮件制造者目的的分析,总结出中文垃圾邮件特性变异的趋势。针对中文垃圾邮件变异的几个重要特性,以及中文的语言特点,在反垃圾邮件系统中加入拼音转换模块、繁简体转换模块和正则表达式匹配模块。实验结果表明,该方法能够取得较高的垃圾邮件变异特征识别率。 By comparing the changes of spam and analyzing purpose of spam senders, summaries the trends of Chinese spam variation features. De- pends on several important characteristics of the Chinese spam variation and the characteristics of Chinese language, the Pinyin conver- sion module, the traditional and simplified conversion module, and the regular expressions module are added to the anti-spam system. Test results show that the proposed method can well detect variation features of spam.
出处 《现代计算机(中旬刊)》 2014年第3期10-14,共5页 Modern Computer
基金 广东省部产学研结合项目(No.2011A090200072) 广东省大学生创新训练计划项目(No.1056412154)
关键词 中文垃圾邮件 变异特征 特征提取 Chinese-spare Variation Features Features Extraction
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参考文献5

  • 1中国互联网协会反垃圾邮件中心,2013年第二季度中国反垃圾邮件状况调查报告[EB/OL].[2013-12-30].http://www.12321.cn/pdf/net20131105.pdf.
  • 2Caruana, G. and Li, M. 2012. A Survey of Emerging Approaches to Spam Filtering[J]. ACM Comput. Surv,2012, 44(2), Article 9.
  • 3Blanzieri E., Bryl A. A Survey of Learning-Based Techniques of Email Spam Filtering [J]. Artif. Intell. Rev., 2008, 29( 1 ): 63-92.
  • 4CalaisP., Guedes D., Meirajr W., et al. Spamming Chains: a New Way of Understanding Spammer Behavior[C]. In Proceedings of the 6th Conference on Email and Anti-Spam (CEAS), 2009.
  • 5Chang C.-C. and Lin C.-J. LIBSVM: a Library for Support Vector Machines, 2001. http://www.csie.ntu.edu.tw/-cjlin/libsvm/.

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