Zhi-Sam Lee

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We analyze the language identification algorithms used to identify the Arabic script Web documents such as Arabic, Jawi, Persian and Urdu using independent component analysis (ICA). We have used a combination of Entropy term weighting scheme and class based feature (CPBF) vectors as feature selection methods for selecting the best features of Arabic script(More)
The exponential increase of information in Internet has raise the issue of information security. Pornography Web content is one of the biggest harmful resource that pollute the mind of children and teenagers. Several Web content based analysis approaches had been proposed to avoiding these illicit Web content accessing by the children. However(More)
As the usage and accessing of children to the web resources with porn images contain is growing, requirement of methods with high accuracy to detect and block adult images is a necessity. In this paper, a novel multi-classifier scheme is proposed based on low-level feature to exploit of advantages in classifier ensemble for achieving better accuracy(More)
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(More)
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