Harmful Document Classification Using the Harmful Word Filtering and SVM


The KIPS Transactions:PartB , Vol. 16, No. 1, pp. 85-92, Feb. 2009
10.3745/KIPSTB.2009.16.1.85,   PDF Download:

Abstract

As World Wide Web is more popularized nowadays, the environment is flooded with the information through the web pages. However, despite such convenience of web, 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 it protects internet youth user from harmful contents. To classify effective harmful/harmless contents, this system uses two step classification systems that is harmful word filtering and SVM learning based filtering. We achieved result that the average precision of 92.1.


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Cite this article
[IEEE Style]
W. H. Lee, S. J. Chung, D. U. An, "Harmful Document Classification Using the Harmful Word Filtering and SVM," The KIPS Transactions:PartB , vol. 16, no. 1, pp. 85-92, 2009. DOI: 10.3745/KIPSTB.2009.16.1.85.

[ACM Style]
Won Hee Lee, Sung Jong Chung, and Dong Un An. 2009. Harmful Document Classification Using the Harmful Word Filtering and SVM. The KIPS Transactions:PartB , 16, 1, (2009), 85-92. DOI: 10.3745/KIPSTB.2009.16.1.85.