Abstract
As World Wide Web is more popularized nowadays, it is also creating many problems due to uncontrolled flood of information. The pornographic, violent and other harmful information freely available to the youth, who must be protected by the society, or other users who lack the power of judgment or self-control is creating serious social problems. To resolve those harmful words, various methods proposed and studied. This paper proposes and implements the protecting system that protects internet youth user from harmful contents. To effectively classify harmful/harmless contents, this system uses two steps of classification: harmful word filtering and SVM learning based filtering. We achieved result that the average precision of 92.1%.
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Hsu, C.-W., Chang, C.-C., Lin, C.-J.: A Practical Guide to Support Vector Classification, http://www.csie.ntu.edu.tw/~cjlin/libsvm/
Hunter, C.D.: Internet Filter Effectiveness: Testing Over and Underinclusive Blocking Decisions of Four Popular Filters. In: Proceedings of the Tenth Conference on Computers, Freedom and Privacy: Challenging the Assumptions, pp. 287–294 (2000)
Zheng, D., Hu, Y., Zhao, T., Yu, H., Li, S.: Research of Machine Learning Method for Specific Information Recognition on the Internet. In: IEEE International Conference on Multimedia Interfaces, ICMI (2002)
Zheng, H., Liu, H., Daoudi, M.: Blocking Objectionable Image: Adult Images and Harmful Symbols. In: IEEE International Conference on Multimedia and Expo (ICME), pp. 1223–1226 (2004)
Lee, J.-S., Jeon, Y.-H.: A Study on the Effective Selective Filtering Technology of Harmful Website Using Internet Content Rating Service. Communication of KIPS Review 9(2) (2002)
Kim, K.-H., Choi, J.-M., Lee, J.-H.: Detecting Harmful Web Documents Based on Web Document Analyses. Communication of KIPS Review D 12(5), 683–688 (2005)
Jeong, J.H., Lee, W.H., Lee, S.W., An, D.U., Chung, S.J.: Study of Feature Extraction Algorithm for Harmful word Filtering (in Korean) . In: KCC Summer Conference, Vol. 33. No. 01, pp. 7-9 (2006)
Hammami, M., Chahir, Y., Chen, L.: WebGuard: A Web Filtering Engine Combining Textual, Structural, and Visual Content-Based Analysis. IEEE Transaction on Knowledge and Data Engineering 18(2) (2006)
Cristianini, N., Shawe-Taylor, J.: An Introduction to Support Vector Machines and Other Kernel-based Learning Methods. Cambridge University Press, Cambridge (2000)
Lee, P.Y., Hui, S.C.: An Intelligent Categorization Engine for Bilingual Web Content Filtering. IEEE Transaction on Multimedia 7(6) (2005)
Lee, P.Y., Hui, S.C., Fong, A.C.M.: Neural Networks for Web Content Filtering. IEEE Intelligent Systems, 48-57 (2002)
Jang, Y.-J., Lee, T., Jung, K.C., Park, K.: The Method of Hurtfulness Site Interception Using Poisonous Character Weight (in Korean). KIPS Spring Conference, Vol. 10, No. 1, pp. 2185–2188 (2003)
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Lee, W., Lee, S.S., Chung, S., An, D. (2007). Harmful Contents Classification Using the Harmful Word Filtering and SVM. In: Shi, Y., van Albada, G.D., Dongarra, J., Sloot, P.M.A. (eds) Computational Science – ICCS 2007. ICCS 2007. Lecture Notes in Computer Science, vol 4489. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72588-6_3
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DOI: https://doi.org/10.1007/978-3-540-72588-6_3
Publisher Name: Springer, Berlin, Heidelberg
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