Spam image email filtering using K-NN and SVM
نویسندگان
چکیده
منابع مشابه
Combining SVM Classifiers for Email Anti-spam Filtering
Spam, also known as Unsolicited Commercial Email (UCE) is becoming a nightmare for Internet users and providers. Machine learning techniques such as the Support Vector Machines (SVM) have achieved a high accuracy filtering the spam messages. However, a certain amount of legitimate emails are often classified as spam (false positive errors) although this kind of errors are prohibitively expensiv...
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1 Dep. of Information Systems/Algoritmi, University of Minho, 4800-058 Guimarães, Portugal, [email protected] WWW home page: http://www3.dsi.uminho.pt/pcortez 2 Dep. of Informatics, University of Minho, 4710-059 Braga, Portugal, {pns, mrocha}@di.uminho.pt 3 Department of Electronic and Electrical Engineering, University College London, Torrington Place, WC1E 7JE, London, UK, [email protected]
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As a side effect of e-marketing strategy the number of spam e-mails is rocketing, the time and cost needed to deal with spam as well. Spam filtering is one of the most difficult tasks among diverse kinds of text categorization, sad consequence of spammers dynamic efforts to escape filtering. In this paper, we investigate the use of Kolmogorov complexity theory as a backbone for spam filtering, ...
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On Email Spam Filtering Using Support Vector Machine
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ژورنال
عنوان ژورنال: International Journal of Electrical and Computer Engineering (IJECE)
سال: 2019
ISSN: 2088-8708,2088-8708
DOI: 10.11591/ijece.v9i1.pp245-254