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Pornography web sites classification using principle component analysis with neural network

Internet users have begun to protect themselves and their wards by using so-called web content filters, which allow access to legitimate content and block access to objectionable, illegal, and otherwise harmful content. Next to active filtering technologies, which use heuristics, machine learning an...

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Main Authors: Lee, Zhi Sam, Maarof, Mohd. Aizaini, Selamat, Ali, Shamsuddin, Siti Mariyam
Format: Conference or Workshop Item
Published: 2007
Subjects:
QA75 Electronic computers. Computer science
Online Access:http://eprints.utm.my/id/eprint/14360/
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spelling my.utm.143602017-08-06T04:33:50Z http://eprints.utm.my/id/eprint/14360/ Pornography web sites classification using principle component analysis with neural network Lee, Zhi Sam Maarof, Mohd. Aizaini Selamat, Ali Shamsuddin, Siti Mariyam QA75 Electronic computers. Computer science Internet users have begun to protect themselves and their wards by using so-called web content filters, which allow access to legitimate content and block access to objectionable, illegal, and otherwise harmful content. Next to active filtering technologies, which use heuristics, machine learning and similar techniques from the area of text and image classification to analyze web pages, there is the complementary category of passive content filters, which rely on (mostly voluntary) content rating systems to classify web pages. 2007 Conference or Workshop Item PeerReviewed Lee, Zhi Sam and Maarof, Mohd. Aizaini and Selamat, Ali and Shamsuddin, Siti Mariyam (2007) Pornography web sites classification using principle component analysis with neural network. In: Malaysia-Japan International Symposium on Advanced Technology 2007 (MJISAT 2007), 2007, Kuala Lumpur.
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Lee, Zhi Sam
Maarof, Mohd. Aizaini
Selamat, Ali
Shamsuddin, Siti Mariyam
Pornography web sites classification using principle component analysis with neural network
description Internet users have begun to protect themselves and their wards by using so-called web content filters, which allow access to legitimate content and block access to objectionable, illegal, and otherwise harmful content. Next to active filtering technologies, which use heuristics, machine learning and similar techniques from the area of text and image classification to analyze web pages, there is the complementary category of passive content filters, which rely on (mostly voluntary) content rating systems to classify web pages.
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 Pornography web sites classification using principle component analysis with neural network
title_short Pornography web sites classification using principle component analysis with neural network
title_full Pornography web sites classification using principle component analysis with neural network
title_fullStr Pornography web sites classification using principle component analysis with neural network
title_full_unstemmed Pornography web sites classification using principle component analysis with neural network
title_sort pornography web sites classification using principle component analysis with neural network
publishDate 2007
url http://eprints.utm.my/id/eprint/14360/
_version_ 1643646379522785280
score 13.2014675

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