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Published in:
2006 | OriginalPaper | Chapter
2-Way Text Classification for Harmful Web Documents
Authors : Youngsoo Kim, Taekyong Nam, Dongho Won
Published in: Computational Science and Its Applications - ICCSA 2006
Publisher: Springer Berlin Heidelberg
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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.