Improved web page identification method using neural networks
In this paper, an improved web page classification method (IWPCM) using neural networks to identify the illicit contents of web pages is proposed. The proposed IWPCM approach is based on the improvement of feature selection of the web pages using class based feature vectors (CPBF). The CPBF feature...
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2011
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my.utm.292132019-03-17T03:03:28Z http://eprints.utm.my/id/eprint/29213/ Improved web page identification method using neural networks Selamat, Ali Lee, Zhi Sam Maarof, Mohd. Aizaini Shamsuddin, Siti Mariyam QA75 Electronic computers. Computer science In this paper, an improved web page classification method (IWPCM) using neural networks to identify the illicit contents of web pages is proposed. The proposed IWPCM approach is based on the improvement of feature selection of the web pages using class based feature vectors (CPBF). The CPBF feature selection approach has been calculated by considering the important term's weight for illicit web documents and reduce the dependency of the less important term's weight for normal web documents. The IWPCM approach has been examined using the modified term-weighting scheme by comparing it with several traditional term-weighting schemes for non-illicit and illicit web contents available from the web. The precision, recall, and F1 measures have been used to evaluate the effectiveness of the proposed IWPCM approach. The experimental results have shown that the proposed improved term-weighting scheme has been able to identify the non-illicit and illicit web contents available from the experimental datasets. World Scientific Publishing Co. Pte Ltd 2011-03 Article PeerReviewed Selamat, Ali and Lee, Zhi Sam and Maarof, Mohd. Aizaini and Shamsuddin, Siti Mariyam (2011) Improved web page identification method using neural networks. International Journal of Computational Intelligence and Applications, 10 (1). pp. 87-114. ISSN 1469-0268 http://dx.doi.org/10.1142/S1469026811003008 DOI:10.1142/S1469026811003008 |
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QA75 Electronic computers. Computer science Selamat, Ali Lee, Zhi Sam Maarof, Mohd. Aizaini Shamsuddin, Siti Mariyam Improved web page identification method using neural networks |
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In this paper, an improved web page classification method (IWPCM) using neural networks to identify the illicit contents of web pages is proposed. The proposed IWPCM approach is based on the improvement of feature selection of the web pages using class based feature vectors (CPBF). The CPBF feature selection approach has been calculated by considering the important term's weight for illicit web documents and reduce the dependency of the less important term's weight for normal web documents. The IWPCM approach has been examined using the modified term-weighting scheme by comparing it with several traditional term-weighting schemes for non-illicit and illicit web contents available from the web. The precision, recall, and F1 measures have been used to evaluate the effectiveness of the proposed IWPCM approach. The experimental results have shown that the proposed improved term-weighting scheme has been able to identify the non-illicit and illicit web contents available from the experimental datasets. |
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Article |
author |
Selamat, Ali Lee, Zhi Sam Maarof, Mohd. Aizaini Shamsuddin, Siti Mariyam |
author_facet |
Selamat, Ali Lee, Zhi Sam Maarof, Mohd. Aizaini Shamsuddin, Siti Mariyam |
author_sort |
Selamat, Ali |
title |
Improved web page identification method using neural networks |
title_short |
Improved web page identification method using neural networks |
title_full |
Improved web page identification method using neural networks |
title_fullStr |
Improved web page identification method using neural networks |
title_full_unstemmed |
Improved web page identification method using neural networks |
title_sort |
improved web page identification method using neural networks |
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World Scientific Publishing Co. Pte Ltd |
publishDate |
2011 |
url |
http://eprints.utm.my/id/eprint/29213/ http://dx.doi.org/10.1142/S1469026811003008 |
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13.18916 |