Features extraction for illicit web pages identification using identification component analysis
The illicit Web content such as pornography, violence, gambling, etc. have greatly polluted the mind of immature web users. Pornography perhaps is one of the biggest threats related to current childrenpsilas and teenagerspsila healthy mental life. A proper way to identify illicit web pages efficient...
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my.utm.139792017-08-06T04:27:58Z http://eprints.utm.my/id/eprint/13979/ Features extraction for illicit web pages identification using identification component analysis Lee, Zhi Sam Maarof, Mohd. Aizaini Selamat, Ali Shamsuddin, Siti Mariyam QA75 Electronic computers. Computer science The illicit Web content such as pornography, violence, gambling, etc. have greatly polluted the mind of immature web users. Pornography perhaps is one of the biggest threats related to current childrenpsilas and teenagerspsila healthy mental life. A proper way to identify illicit web pages efficiently is highly desired. In this paper, we analyze the textual content of web pages such as pornography, gynecology, sex education and general business news using independent component analysis (ICA) algorithm. We establish three similar models which are principal component analysis (PCA) model, ICA model and PCA-ICA model as comparison. We evaluate the effectiveness of these proposed models using information retrieval measurement such as precision, recall, F1 and accuracy. Our experiment result shown that PCA and PCA-ICA models are capable to identify illicit web pages correctly with overall performance above than 90%. The idea of this research would give researchers an insight into textual content-based for web pages categorization. 2007 Conference or Workshop Item PeerReviewed Lee, Zhi Sam and Maarof, Mohd. Aizaini and Selamat, Ali and Shamsuddin, Siti Mariyam (2007) Features extraction for illicit web pages identification using identification component analysis. In: International Conference on Intelligent and Advanced Systems (ICIAS’07), 2007, Kuala Lumpur. |
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QA75 Electronic computers. Computer science Lee, Zhi Sam Maarof, Mohd. Aizaini Selamat, Ali Shamsuddin, Siti Mariyam Features extraction for illicit web pages identification using identification component analysis |
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The illicit Web content such as pornography, violence, gambling, etc. have greatly polluted the mind of immature web users. Pornography perhaps is one of the biggest threats related to current childrenpsilas and teenagerspsila healthy mental life. A proper way to identify illicit web pages efficiently is highly desired. In this paper, we analyze the textual content of web pages such as pornography, gynecology, sex education and general business news using independent component analysis (ICA) algorithm. We establish three similar models which are principal component analysis (PCA) model, ICA model and PCA-ICA model as comparison. We evaluate the effectiveness of these proposed models using information retrieval measurement such as precision, recall, F1 and accuracy. Our experiment result shown that PCA and PCA-ICA models are capable to identify illicit web pages correctly with overall performance above than 90%. The idea of this research would give researchers an insight into textual content-based for web pages categorization. |
format |
Conference or Workshop Item |
author |
Lee, Zhi Sam Maarof, Mohd. Aizaini Selamat, Ali Shamsuddin, Siti Mariyam |
author_facet |
Lee, Zhi Sam Maarof, Mohd. Aizaini Selamat, Ali Shamsuddin, Siti Mariyam |
author_sort |
Lee, Zhi Sam |
title |
Features extraction for illicit web pages identification using identification component analysis |
title_short |
Features extraction for illicit web pages identification using identification component analysis |
title_full |
Features extraction for illicit web pages identification using identification component analysis |
title_fullStr |
Features extraction for illicit web pages identification using identification component analysis |
title_full_unstemmed |
Features extraction for illicit web pages identification using identification component analysis |
title_sort |
features extraction for illicit web pages identification using identification component analysis |
publishDate |
2007 |
url |
http://eprints.utm.my/id/eprint/13979/ |
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1643646303826083840 |
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13.18916 |