A study of content based Spam Filtering Techniques - Softcover

Khairy, Marwa; M. Mahmoud, Tarek; Hemdan, Tarek

Softcover

ISBN 10: 365959069X ISBN 13: 9783659590696

Publisher: LAP LAMBERT Academic Publishing, 2014

Synopsis

The Internet has almost become an indispensable part of everyday life. Internet usage will continue to grow and therefore online communication and information exchange is gaining immense popularity, affecting users’ social and commercial lives. Along with the growth of e-mail and social networking websites, there has been an increased production of spam over the years. Spam is nothing but unsolicited messages.Many spam-filtering techniques based on supervised machine learning algorithms have been proposed to automatically classify email messages as spam or legitimate (ham). Naive Bayesian classifier is one of the most popular learning algorithms that give promising results in separating spam from legitimate mail.Artificial Immune System (AIS) is an area of research that bridges the disciplines of immunology, computer science and engineering. Many AIS models have been proposed to solve these problems.Some prevalent ones are Clonal selection and Negative selection algorithms.The main objective of this book is building an efficient content-based system for filtering email spam messages.

About this title

About the Author

Marwa Kh. Mohamed :MSC in Computer Science , Department of Computer science , Faculty of Science , Minia University ,Egypt. Lecturer at Faculty of Computers and Information Technology.

Edition details

• Publisher: LAP LAMBERT Academic Publishing
• Publication date: 2014
• Language: English
• ISBN 10: 365959069X
• ISBN 13: 9783659590696
• Binding: Paperback
• Number of pages: 128