A Fast Content-Based Spam Filtering Algorithm with Fuzzy-SVM and K-means
Shengnan Wang, Xiaoyong Zhang, Yijun Cheng, Fu Jiang, Wentao Yu, Jun Peng · 2018
Nowadays, spam is pervasive in the mailbox, and not only caused a waste of network resources, but also brings a lot of trouble to people's daily life. How to filter spam quickly and accurately is a challenge we are facing. For handling this challenge, this paper proposes a fast content-based spam filtering algorithm with fuzzy-SVM and k-means. First, K-means clustering algorithm is used to compress data with retain most of the effective information. Then, fuzzy support vector machine is used to train classification model, in order to deal with uncertain factors better. The experimental results show that this algorithms could improve the spam filtering speed and filtering accuracy rate effectively.