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2-Way Text Classification for Harmful Web Documents

  • Conference paper
Computational Science and Its Applications - ICCSA 2006 (ICCSA 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3981))

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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.

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References

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Author information

Authors and Affiliations

  1. Network Security Group, Electronics and Telecommunications Research Institute (ETRI), 161 Gajeong-dong, Yuseong-gu, Daejeon, 305-350, Korea

    Youngsoo Kim & Taekyong Nam

  2. Information Security Group, School of Information and Communication Engineering, Sungkyunkwan University, 300 Cheoncheon-dong, Jangan-gu, Suwon, Gyeonggi-do, 440-746, Korea

    Youngsoo Kim & Dongho Won

Authors
  1. Youngsoo Kim
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  2. Taekyong Nam
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  3. Dongho Won
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Calgary, 2500 University Drive N.W., T2N 1N4, Calgary, AB, Canada

    Marina L. Gavrilova

  2. Department of Mathematics and Computer Science, University of Perugia, via Vanvitelli, 1, I-06123, Perugia, Italy

    Osvaldo Gervasi

  3. William Norris Professor, Head of the Computer Science and Engineering Department, University of Minnesota, USA

    Vipin Kumar

  4. OptimaNumerics Ltd., Cathedral House, 23-31 Waring Street, BT1 2DX, Belfast, UK

    C. J. Kenneth Tan

  5. Clayton School of IT, Monash University, 3800, Clayton, Australia

    David Taniar

  6. Department of Chemistry, University of Perugia, Via Elce di Sotto, 8, I-06123, Perugia, Italy

    Antonio Laganá

  7. School of Computing, Soongsil University, Seoul, Korea

    Youngsong Mun

  8. School of Information and Communication Engineering, Sungkyunkwan University, Korea

    Hyunseung Choo

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© 2006 Springer-Verlag Berlin Heidelberg

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Cite this paper

Kim, Y., Nam, T., Won, D. (2006). 2-Way Text Classification for Harmful Web Documents. In: Gavrilova, M.L., et al. Computational Science and Its Applications - ICCSA 2006. ICCSA 2006. Lecture Notes in Computer Science, vol 3981. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11751588_57

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  • DOI: https://doi.org/10.1007/11751588_57

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34072-0

  • Online ISBN: 978-3-540-34074-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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