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.
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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.
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Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germania
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Khairy MarwaMarwa Kh. Mohamed :MSC in Computer Science , Department of Computer science , Faculty of Science , Minia University ,Egypt. Lecturer at Faculty of Computers and Information Technology.The Internet has almost become an. Codice articolo 5167079
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Taschenbuch. Condizione: Neu. This item is printed on demand - Print on Demand Titel. Neuware VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 128 pp. Englisch. Codice articolo 9783659590696
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Taschenbuch. Condizione: Neu. A study of content based Spam Filtering Techniques | Marwa Khairy (u. a.) | Taschenbuch | 128 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659590696 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. Codice articolo 105049307
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