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Pornography web pages classification with textual content analysis using entropy term weighting scheme for small class dataset.
| Content Provider | CiteSeerX |
|---|---|
| Author | Sam, Lee Zhi Selamat, Ali Shamsuddin, Siti Mariyam Maarof, Mohd Aizaini Bin |
| Abstract | The fast growth of internet make objectionable web content such as pornography and violence easily explore to web users especially children and teenagers. Due to some popular web filtering techniques like Uniform Resource Locator blocking and Platform for Internet Content Selection checking are limited against today dynamic web content, hence content based analysis techniques with effective model are highly desired. This paper we propose textual content analysis model using entropy term weighting scheme to classify pornography and sex education web pages. We examine the entropy scheme with two other common term weighting schemes which are TFIDF and Glasgow. Those techniques are examined extensively with artificial neural network using small class dataset. We found that our proposed model archive better performance from the aspects of accuracy, convergence speed and stability. Keyword Artificial neural network, term weighting scheme, textual content analysis, web pages classification. 1. |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Keyword Artificial Neural Network Fast Growth Entropy Term Sex Education Web Page Small Class Dataset Entropy Scheme Today Dynamic Web Content Internet Make Objectionable Web Content Web Page Classification Textual Content Analysis Common Term Internet Content Selection Popular Web Textual Content Analysis Model Analysis Technique Convergence Speed Effective Model Artificial Neural Network Uniform Resource Locator Blocking Hence Content Pornography Web Page Classification |
| Content Type | Text |
| Resource Type | Article |
