HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION

HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION

Spam is referred to unsolicited commercial e-mail from someone trying to give some information that the receiver did not expected. This kind of email usually defined as junk and unwanted. As a filtering step, the spam email filters are implemented in conjunction to reduce this type of e-mails. Un...

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Main Author: GHADA HAMMAD AL-RAWASHDEH
Format: Thesis
Language:English
Online Access:http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/1/Abstract.pdf
http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/2/Full%20Thesis%20-%20GHADA%20HAMMAD%20AL-RAWASHDEH.pdf
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spelling my-umt-ir.-160132022-01-19T08:04:29Z HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION GHADA HAMMAD AL-RAWASHDEH Spam is referred to unsolicited commercial e-mail from someone trying to give some information that the receiver did not expected. This kind of email usually defined as junk and unwanted. As a filtering step, the spam email filters are implemented in conjunction to reduce this type of e-mails. Unfortunately, new spam email attributes have caused the spam email filter characteristic insufficient and inefficient to handle the large amount of email. This problem is due to the large number of features that the spam classifier needs to evaluate. By the help of feature selection method, the number of features can be reduced. However, the optimal number of features remains a problem and requires further investigation. In this thesis, a new hybrid method has been introduced to make the spam email feature selection more accurate by using the metaheuristic feature selection optimization approach. The proposed method is based on the hybridization of Water Cycle Algorithm with the Simulated Annealing to optimize the results. This study used a methodology that included groundwork, induction, improvement, assessment, and comparison quality. For the training and validation datasets, cross-validation was performed, and seven datasets were used to evaluate the suggested spam classification UNIVERSITI MALAYSIA TERENGGANU 2020-08 Thesis en http://umt-ir.umt.edu.my:8080/handle/123456789/16013 http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/1/Abstract.pdf 79046f76fdcbc71944531029623cf1cc http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/2/Full%20Thesis%20-%20GHADA%20HAMMAD%20AL-RAWASHDEH.pdf 7c9fa6c620862a86e28935343140b5b8 http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33
institution Universiti Malaysia Terengganu
collection UMT Repository System
language English
description Spam is referred to unsolicited commercial e-mail from someone trying to give some information that the receiver did not expected. This kind of email usually defined as junk and unwanted. As a filtering step, the spam email filters are implemented in conjunction to reduce this type of e-mails. Unfortunately, new spam email attributes have caused the spam email filter characteristic insufficient and inefficient to handle the large amount of email. This problem is due to the large number of features that the spam classifier needs to evaluate. By the help of feature selection method, the number of features can be reduced. However, the optimal number of features remains a problem and requires further investigation. In this thesis, a new hybrid method has been introduced to make the spam email feature selection more accurate by using the metaheuristic feature selection optimization approach. The proposed method is based on the hybridization of Water Cycle Algorithm with the Simulated Annealing to optimize the results. This study used a methodology that included groundwork, induction, improvement, assessment, and comparison quality. For the training and validation datasets, cross-validation was performed, and seven datasets were used to evaluate the suggested spam classification
format Thesis
author GHADA HAMMAD AL-RAWASHDEH
spellingShingle GHADA HAMMAD AL-RAWASHDEH
HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION
author_facet GHADA HAMMAD AL-RAWASHDEH
author_sort GHADA HAMMAD AL-RAWASHDEH
title HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION
title_short HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION
title_full HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION
title_fullStr HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION
title_full_unstemmed HYBRID WATER CYCLE OPTIMIZATION ALGORITHM WITH SIMULATED ANNEALING FOR SPAM EMAIL DETECTION
title_sort hybrid water cycle optimization algorithm with simulated annealing for spam email detection
granting_institution UNIVERSITI MALAYSIA TERENGGANU
url http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/1/Abstract.pdf
http://umt-ir.umt.edu.my:8080/jspui/bitstream/123456789/16013/2/Full%20Thesis%20-%20GHADA%20HAMMAD%20AL-RAWASHDEH.pdf
_version_ 1747835890435096576

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