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آرشیو :
نسخه پاییز 1399
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نوع مقاله :
پژوهشی
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کد پذیرش :
1375
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موضوع :
هوش مصنوعی
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نویسنده/گان :
سمن مثقالی، جواد عسگری
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کلید واژه :
اسپم فیلترینگ، یادگیری ماشین، یادگیری تجمعی، ایمیل، پیام کوتاه.
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مراجع :
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[3] Araujo, Lourdes, and Juan Martinez-Romo. "Web spam detection: new classification features based on qualified link analysis and language models." IEEE Transactions on Information Forensics and Security 5.3 (2010): 581-590.
[4] Mahajan, Renuka. "Review of data mining techniques and parameters for recommendation of effective adaptive e-learning system." Collaborative Filtering Using Data Mining and Analysis, 1, (2016).
[5] Bagherzadeh-Khiabani, Farideh, et al. "A tutorial on variable selection for clinical prediction models: feature selection methods in data mining could improve the results." Journal of clinical epidemiology 71, 76-85, (2016).
[6] Wang, Gang, et al. "Sentiment classification: The contribution of ensemble learning." Decision support systems 57 (2014): 77-93.
[7] بستوه, پریسا، ۱۳۹۴، ارائه روشی جهت طبقه بندی نظرات افراد با استفاده از یادگیری ترکیبی، سومین کنگره سراسری فناوری¬های نوین ایران با هدف دستیابی به توسعه پایدار، تهران، موسسه آموزش عالی مهر اروند، مرکز راهکارهای دستیابی به توسعه پایدار.
[8] Zhang, Xipeng, et al. "A method of SMS spam filtering based on AdaBoost algorithm." Intelligent Control and Automation (WCICA), 2016 12th World Congress on. IEEE, 2016.
[9] Fisher, R. A. "On some extensions of Bayesian inference proposed by Mr Lindley." Journal of the Royal Statistical Society. Series B (Methodological) (1960): 299-301.
[10] Robinson, Gary. "A statistical approach to the spam problem." Linux journal2003.107, 3 (2003).
[11] Boldi, Paolo, Massimo Santini, and Sebastiano Vigna. "PageRank as a function of the damping factor." Proceedings of the 14th international conference on World Wide Web. ACM, 2005.
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[13] Spracklin, L. M., and Lawrence V. Saxton. "Filtering spam using kolmogorov complexity estimates." Advanced Information Networking and Applications Workshops, 2007, AINAW'07. 21st International Conference on. Vol. 1. IEEE, 2007.
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[15] Hsiao, Wen-Feng, and Te-Min Chang. "An incremental cluster-based approach to spam filtering." Expert Systems with Applications 34.3, 1599-1608, (2008).
[16] Lee, Sang Min, et al. "Spam detection using feature selection and parameters optimization." Complex, Intelligent and Software Intensive Systems (CISIS), 2010 International Conference on. IEEE, 2010.
[17] Saeedian, Mehrnoush Famil, and Hamid Beigy. "Spam detection using dynamic weighted voting based on clustering." Intelligent Information Technology Application, 2008. IITA'08. Second International Symposium on. Vol. 2. IEEE, 2008.
[18] Sasaki, Minoru, and Hiroyuki Shinnou. "Spam detection using text clustering." Cyberworlds, 2005. International Conference on. IEEE, 2005
[19] Cortez, Paulo, et al. "Symbiotic data mining for personalized spam filtering." Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology-Volume 01. IEEE Computer Society, 2009.
[20] Weinstein, Lauren. "Spam wars." Communications of the ACM 46.8, 136 (2003).
[21] Gburzynski, Pawel, and Jacek Maitan. "Fighting the spam wars: A remailer approach with restrictive aliasing." ACM Transactions on Internet Technology (TOIT) 4.1, 1-30 (2004).
[22] Li, Fulu, H. Mo-Han, and G. Pawel. "The community behavior of spammers." (2011).
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- صفحات : 34-41
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