Dynamic feature selection for spam filtering using support vector machine
Islam, Md. Rafiqul, Zhou, Wanlei and Chowdhury, Morshed 2007, Dynamic feature selection for spam filtering using support vector machine, in 6th IEEE/ACIS International Conference on Computer and Information Science : (ICIS 2007) in conjunction with 1st IEEE/ACIS International Workshop on e-Activity (IWEA 2007) : proceedings : 11-13 July, 2007, Melbourne, Australia, IEEE Computer Society, Los Alamitos, Calif., pp. 757-762.
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6th IEEE/ACIS International Conference on Computer and Information Science : (ICIS 2007) in conjunction with 1st IEEE/ACIS International Workshop on e-Activity (IWEA 2007) : proceedings : 11-13 July, 2007, Melbourne, Australia
Lee, Roger Chowdhury, Morshed U. Ray, Sid Lee, Thuy
International Conference on Computer and Information Science
Spam is commonly defined as unsolicited email messages and the goal of spam filtering is to differentiate spam from legitimate email. Much work have been done to filter spam from legitimate emails using machine learning algorithm and substantial performance has been achieved with some amount of false positive (FP) tradeoffs. In this paper, architecture of spam filtering has been proposed based on support vector machine (SVM,) which will get better accuracy by reducing FP problems. In this architecture an innovative technique for feature selection called dynamic feature selection (DFS) has been proposed which is enhanced the overall performance of the architecture with reduction of FP problems. The experimental result shows that the proposed technique gives better performance compare to similar existing techniques.
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