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Propose hybrid ACO and NB to enhance spam filtering system
Joint Authors
Abd al-Ghafur, Huda Adil
Hashim, Sukaynah Hasan
Source
Engineering and Technology Journal
Issue
Vol. 34, Issue 2B (29 Feb. 2016), pp.204-215, 12 p.
Publisher
Publication Date
2016-02-29
Country of Publication
Iraq
No. of Pages
12
Main Subjects
Information Technology and Computer Science
Abstract EN
Unwanted e-mails became one of the most risk experienced by e-mail users, which may be either harmless or e-mails that represent a threat to the internet.
Filtering systems are used to filter e-mail messages from spam.
This paper introduces a proposed hybrid system to filter the spam; the proposal hybrid Ant Colony System (ACS) and Naive Bayesian (NB) classifier.
Where, ACS will depend on the Information Gain (IG) as a heuristic measure to guide the ants search to select the optimal worst features then omitting these features.
The remind features will be the subset which is used to train and test NB classifier to classify whether the mail message spam or not.
The proposal is experimented on spambase dataset, and the results show that; the accuracy, precision and recall with NB which use a subset of features extracted by proposing IG-based ACS is higher than the traditional NB with all set of features.
American Psychological Association (APA)
Hashim, Sukaynah Hasan& Abd al-Ghafur, Huda Adil. 2016. Propose hybrid ACO and NB to enhance spam filtering system. Engineering and Technology Journal،Vol. 34, no. 2B, pp.204-215.
https://search.emarefa.net/detail/BIM-689167
Modern Language Association (MLA)
Hashim, Sukaynah Hasan& Abd al-Ghafur, Huda Adil. Propose hybrid ACO and NB to enhance spam filtering system. Engineering and Technology Journal Vol. 34, no. 2B (2016), pp.204-215.
https://search.emarefa.net/detail/BIM-689167
American Medical Association (AMA)
Hashim, Sukaynah Hasan& Abd al-Ghafur, Huda Adil. Propose hybrid ACO and NB to enhance spam filtering system. Engineering and Technology Journal. 2016. Vol. 34, no. 2B, pp.204-215.
https://search.emarefa.net/detail/BIM-689167
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 215
Record ID
BIM-689167