Abstract
Currently, process for blocking the deviant teaching website is done manually by Malaysia authorities. In addition there are no Web filtering product offered to filter religion content and especially for Malay language. Web filtering can be used as protection against inappropriate and prevention of misuse of the network and hence, it can be used to filter the content of suspicious websites and alleviate the dissemination of such Web page. The purpose of the paper is to filter the deviant teachings Web page and classify them into three categories which are deviate, suspicious and clean. There are three Term Weighting Scheme techniques were used as feature selection included Term Frequency Inverse Document Frequency (TFIDF), Entropy and Modified Entropy. Support Vector Machine (SVM) will be used for classification process. As a result, M. Entropy shows the most suitable term weighting scheme to use in Islamic web pages filtering rather than TFIDF and Entropy.
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Zamry, N.M., Maarof, M.A., Zainal, A. (2014). Islamic Web Content Filtering and Categorization on Deviant Teaching. In: Herawan, T., Ghazali, R., Deris, M. (eds) Recent Advances on Soft Computing and Data Mining. Advances in Intelligent Systems and Computing, vol 287. Springer, Cham. https://doi.org/10.1007/978-3-319-07692-8_63
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DOI: https://doi.org/10.1007/978-3-319-07692-8_63
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