Advertisement

Korean Documents Copy Detection Based on Ferret

  • Byung Ryul Ahn
  • Won-gyum Kim
  • Won Young Yu
  • Moon-Hyun Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6838)

Abstract

With the development of electronic documents, plagiarism is rapidly increasing and, given the difficulty of manual detection, need for plagiarism detection systems to help protect intellectual property has emerged. Many content-based detection systems have been developed and are actually used in some foreign countries, but they are still insufficient for documents in Korean. In particular, the high variance of Hangul makes the development of detection systems more difficult. This study proposes a Hangul document detection method based on Ferret’s trigrams. Ferret only considered the frequency of trigram matches as a way to detect similarity, but in this study the system is developed further by weighting results depending on the degree of trigram match, thereby improving the accuracy of similarity detection.

Keywords

Intelligent Computing in Pattern Recognition 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Brin, S., Davis, J., et al.: Copy Detection Mechanisms for Digital Documents. In: Proceedings of the ACM SIGMOD Annual Conference (1995)Google Scholar
  2. 2.
    Shivakumar, Garcia-Monlina: SCAM: A Copy Detection Mechanisms for Digital Documents. In: Proceedings of International Conference on Theory and Practice of Digital Libraries (1995)Google Scholar
  3. 3.
    Bao, J.P., Shen, J.Y., et al.: Document Copy Detection Based On Kernel Method. In: International Conference on Natural, pp. 250–255 (2003)Google Scholar
  4. 4.
    Bao, J.-P., Shen, J.-Y., Liu, X.-D., Liu, H.-Y., Zhang, X.-D.: Semantic Sequence Kin: A Method of Document Copy Detection. In: Dai, H., Srikant, R., Zhang, C. (eds.) PAKDD 2004. LNCS (LNAI), vol. 3056, pp. 529–538. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  5. 5.
    Kang, N., Gelbukh, A., Han, S.-Y.: PPChecker: Plagiarism Pattern Checker in Document Copy Detection. In: Sojka, P., Kopeček, I., Pala, K. (eds.) TSD 2006. LNCS (LNAI), vol. 4188, pp. 661–667. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  6. 6.
    Lyon, C., Barret, R., et al.: A Theoretical Basis to the Automated Detection of Copying Between Texts, and Its Practical Implementation in the Ferret Plagiarism and Collusion Detector (2004)Google Scholar
  7. 7.
    Bao, J.P., Lyon, C., et al.: Copy detection in Chinese Documents Using the Ferret: a Report on Experiments. Technical Report 456 (2006)Google Scholar
  8. 8.
  9. 9.

Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Byung Ryul Ahn
    • 1
  • Won-gyum Kim
    • 2
  • Won Young Yu
    • 3
  • Moon-Hyun Kim
    • 1
  1. 1.Artificial Intelligence Lab, School of Computer EngineeringSungKyunKwan Univ.Suwon-siSouth Korea
  2. 2.Copyright Protection CenterSeoulSouth Korea
  3. 3.Contents Research DivisionETRIDaejonSouth Korea

Personalised recommendations