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Conference Paper
2-Way Text Classification for Harmful Web Documents
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- Authors
- Young Soo Kim, Taek Yong Nam, Dong Ho Won
- Issue Date
- 2006-05
- Citation
- International Conference on Computational Science and Its Applications (ICCSA) 2006 (LNCS 3981), v.3981, pp.545-551
- Language
- English
- Type
- Conference Paper
- Project Code
- 06MK2300, Development of a common security core module for supporting secure and trusted service in the next generation mobile terminals, Jun Sungik
- Abstract
- The openness of the Web allows any user to access almost any type of information. However, some information, such as adult content, is not appropriate for all users, notably children. Additionally for adults, some contents included in abnormal porn sites can do ordinary people's mental health harm. In this paper, we propose an efficient 2-way text filter for blocking harmful web documents and also present a new criterion for clear classification. It filters off 0-grade web texts containing no harmful words using pattern matching with harmful words dictionaries, and classifies 1-grade,2-grade and 3-grade web texts using a machine learning algorithm. © Springer-Verlag Berlin Heidelberg 2006.
- KSP Keywords
- Machine Learning Algorithms, Ordinary people, Type of information, Web Documents, mental health, pattern matching, text classification, web texts