Harmful Contents Classification Using the Harmful Word Filtering and SVM

Authors:
Wonhee Lee;Samuel Sangkon Lee;Seungjong Chung;Dongun An
Affiliations:
Dept. of Computer Engineering, Chonbuk National University, South Korea;Dept. of Computer Engineering, Jeonju University, South Korea;Dept. of Computer Engineering, Chonbuk National University, South Korea;Dept. of Computer Engineering, Chonbuk National University, South Korea
Venue:
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
Year:
2007

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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%.