Spam Email Detection Using Deep Support Vector Machine, Support Vector Machine and Artificial Neural Network

被引:5
|
作者
Roy, Sanjiban Sekhar [1 ]
Sinha, Abhishek [1 ]
Roy, Reetika [1 ]
Barna, Cornel [2 ]
Samui, Pijush [3 ]
机构
[1] VIT Univ, Sch Comp Sci & Engn, Vellore, Tamil Nadu, India
[2] Aurel Vlaicu Univ Arad, Automat & Appl Informat, Arad, Romania
[3] NIT Patna, Dept Civil Engn, Patna, Bihar, India
来源
SOFT COMPUTING APPLICATIONS, SOFA 2016, VOL 2 | 2018年 / 634卷
关键词
Spam; Classification; Deep Support Vector Machine; Support Vector Machine; Artificial Neural Network;
D O I
10.1007/978-3-319-62524-9_13
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Emails are a very important part of our life today for information sharing. It is used for both personal communication as well as business purposes. But the internet also opens up the prospect of an enormous amount of junk and useless information which overwhelms and irritates us. These unnecessary and unsolicited emails are what comprise of spam. This study presents the application of a classification model to classify spam emails from using a model-Deep Support Vector Machine (Deep SVM). Moreover, other classifier models like Support Vector Machine (SVM), Artificial Neural Network models have also been implemented to compare the performance of proposed Deep SVM model. Furthermore analysis has been done to compare all the performances using available numerical statistics obtained from these models to find the best model for the purpose. Spam filtering is a very essential feature in most email services and thus effective spam classification models are pertinent to the current digital communication scenario and various work has been done in this area.
引用
收藏
页码:162 / 174
页数:13
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