Get 20M+ Full-Text Papers For Less Than $1.50/day. Start a 14-Day Trial for You or Your Team.

Learn More →

A survey of learning-based techniques of email spam filtering

A survey of learning-based techniques of email spam filtering Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Among the approaches developed to stop spam, filtering is an important and popular one. In this paper we give an overview of the state of the art of machine learning applications for spam filtering, and of the ways of evaluation and comparison of different filtering methods. We also provide a brief description of other branches of anti-spam protection and discuss the use of various approaches in commercial and non-commercial anti-spam software solutions. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Artificial Intelligence Review Springer Journals

A survey of learning-based techniques of email spam filtering

Loading next page...
 
/lp/springer-journals/a-survey-of-learning-based-techniques-of-email-spam-filtering-Ki0I2tElf4

References (115)

Publisher
Springer Journals
Copyright
Copyright © 2009 by Springer Science+Business Media B.V.
Subject
Computer Science; Computer Science, general; Artificial Intelligence (incl. Robotics)
ISSN
0269-2821
eISSN
1573-7462
DOI
10.1007/s10462-009-9109-6
Publisher site
See Article on Publisher Site

Abstract

Email spam is one of the major problems of the today’s Internet, bringing financial damage to companies and annoying individual users. Among the approaches developed to stop spam, filtering is an important and popular one. In this paper we give an overview of the state of the art of machine learning applications for spam filtering, and of the ways of evaluation and comparison of different filtering methods. We also provide a brief description of other branches of anti-spam protection and discuss the use of various approaches in commercial and non-commercial anti-spam software solutions.

Journal

Artificial Intelligence ReviewSpringer Journals

Published: Jul 10, 2009

There are no references for this article.