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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
Published: UNIVERSITI MALAYSIA TERENGGANU 2022
Online Access:http://umt-ir.umt.edu.my:8080/handle/123456789/16013
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id my.umt.ir-16013
record_format eprints
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 2022-01-19T08:04:07Z 2022-01-19T08:04:07Z 2020-08 Thesis http://umt-ir.umt.edu.my:8080/handle/123456789/16013 en application/pdf application/pdf UNIVERSITI MALAYSIA TERENGGANU
institution Universiti Malaysia Terengganu
building Perpustakaan Sultanah Nur Zahirah
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Terengganu
content_source UMT-IR
url_provider http://umt-ir.umt.edu.my:8080/
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
publisher UNIVERSITI MALAYSIA TERENGGANU
publishDate 2022
url http://umt-ir.umt.edu.my:8080/handle/123456789/16013
_version_ 1738395567436857344
score 13.211869

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