کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
403205 677066 2007 6 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
An empirical study of three machine learning methods for spam filtering
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
An empirical study of three machine learning methods for spam filtering
چکیده انگلیسی

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Knowledge-Based Systems - Volume 20, Issue 3, April 2007, Pages 249–254
نویسندگان
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