| Title | An Improved Spam Detection Method with Weighted Support Vector Machine |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Vishagini, V., Rajan, A. K. |
| Conference Name | 2018 International Conference on Data Science and Engineering (ICDSE) |
| Date Published | aug |
| Keywords | email users, feature extraction, Human Behavior, Internet, Kernel, KFCM, KFCM algorithm, KPCM, learning (artificial intelligence), machine learning algorithms, Metrics, pattern classification, Prediction algorithms, pubcrawl, Scalability, spam detection, spam detection method, spam filtering, Support vector machines, SVM, Training, unsolicited e-mail, Unsolicited electronic mail, weight variables, weighted support vector machine, weighted SVM, WSVM |
| Abstract | Email is the most admired method of exchanging messages using the Internet. One of the intimidations to email users is to detect the spam they receive. This can be addressed using different detection and filtering techniques. Machine learning algorithms, especially Support Vector Machine (SVM), can play vital role in spam detection. We propose the use of weighted SVM for spam filtering using weight variables obtained by KFCM algorithm. The weight variables reflect the importance of different classes. The misclassification of emails is reduced by the growth of weight value. We evaluate the impact of spam detection using SVM, WSVM with KPCM and WSVM with KFCM.UCI Repository SMS Spam base dataset is used for our experimentation. |
| DOI | 10.1109/ICDSE.2018.8527737 |
| Citation Key | vishagini_improved_2018 |
An Improved Spam Detection Method with Weighted Support Vector Machine