کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
403205 | 677066 | 2007 | 6 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: An empirical study of three machine learning methods for spam filtering An empirical study of three machine learning methods for spam filtering](/preview/png/403205.png)
The increasing volumes of unsolicited bulk e-mail (also known as spam) are bringing more annoyance for most Internet users. Using a classifier based on a specific machine-learning technique to automatically filter out spam e-mail has drawn many researchers’ attention. This paper is a comparative study the performance of three commonly used machine learning methods in spam filtering. On the other hand, we try to integrate two spam filtering methods to obtain better performance. A set of systematic experiments has been conducted with these methods which are applied to different parts of an e-mail. Experiments show that using the header only can achieve satisfactory performance, and the idea of integrating disparate methods is a promising way to fight spam.
Journal: Knowledge-Based Systems - Volume 20, Issue 3, April 2007, Pages 249–254