Marsono, Muhammad Nadzir and M. E. Rafiq, A. Newaz and ElKharashi, Mohamed Watheq and Gebali, Farez (2007) On the effects of class noise on spam detection accuracy. In: Advances In Digital Signal Processing Applications. Penerbit UTM , Johor, p. 173. ISBN 978-983-52-0652-8
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Abstract
Spam contributes to approximately two-thirds of the e-mail traffic over the Internet [9] and is fast becoming a major problem for IT users and network administrators. Spam costs billions in lost productivity [21] and results in more problems than mere annoyance of delayed and lost non-spam e-mails. Spam continuously evolves to circumvent spam control systems and is becoming much more sophisticated [13]. Naive Bayes classification has widely been used for spam detection and several variations have been proposed [1], [25], [11]. As other supervisedlearning techniques, its accuracy (for detecting spam) depends on the quality, quantity, and timeliness of the learning corpora
| Item Type: | Book Section |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Electrical Engineering |
| ID Code: | 13679 |
| Deposited By: | Liza Porijo |
| Deposited On: | 15 Aug 2011 05:41 |
| Last Modified: | 08 Oct 2017 01:15 |
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