Intrinsic Plagiarism Detection

  • Sven Meyer zu Eissen
  • Benno Stein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3936)


Current research in the field of automatic plagiarism detection for text documents focuses on algorithms that compare plagiarized documents against potential original documents. Though these approaches perform well in identifying copied or even modified passages, they assume a closed world: a reference collection must be given against which a plagiarized document can be compared.

This raises the question whether plagiarized passages within a document can be detected automatically if no reference is given, e. g. if the plagiarized passages stem from a book that is not available in digital form. We call this problem class intrinsic plagiarism detection. The paper is devoted to this problem class; it shows that it is possible to identify potentially plagiarized passages by analyzing a single document with respect to variations in writing style.

Our contributions are fourfold: (i) a taxonomy of plagiarism delicts along with detection methods, (ii) new features for the quantification of style aspects, (iii) a publicly available plagiarism corpus for benchmark comparisons, and (iv) promising results in non-trivial plagiarism detection settings: in our experiments we achieved recall values of 85% with a precision of 75% and better.


plagiarism detection style analysis classifier plagiarism corpus 


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  1. 1.
    Brin, S., Davis, J., Garcia-Molina, H.: Copy detection mechanisms for digital documents. In: Proc. SIGMOD 1995, pp. 398–409 (1995)Google Scholar
  2. 2.
    Garside, R., Leech, G., McEnery, A.: Corpus Annotation: Linguistic Information from Computer Text Corpora. Longman (1997)Google Scholar
  3. 3.
    Hoad, T.C., Zobel, J.: Methods for Identifying Versioned and Plagiarised Documents. JASIST 54(3), 203–215 (2003)CrossRefGoogle Scholar
  4. 4.
    Koppel, M., Schler, J.: Authorship verification as a one-class classification problem. In: Proc. of ICML (2004)Google Scholar
  5. 5.
    McCabe, D.: Research Report of the Center for Academic Integrity (2005),
  6. 6.
    Meyer zu Eißen, S., Stein, B.: Genre Classification of Web Pages: User Study and Feasibility Analysis. In: Biundo, S., Frühwirth, T., Palm, G. (eds.) KI 2004. LNCS (LNAI), vol. 3238, pp. 256–269. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  7. 7.
    Stein, B.: Fuzzy-Fingerprints for Text-based Information Retrieval. In: Proc. of 5th Int. Conf. on Knowledge Management, Graz, Austria. JUCS (2005)Google Scholar
  8. 8.
    Stein, B., Meyer, S.: Near similarity search and plagiarism analysis. In: Proc. of GfKl 2005. Springer, Heidelberg (2005)Google Scholar
  9. 9.
    University of Leipzig. Wortschatz (1995),
  10. 10.
    Wikipedia. Plagiarism (2005),

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Sven Meyer zu Eissen
    • 1
  • Benno Stein
    • 1
  1. 1.Faculty of Media: Media SystemsBauhaus University WeimarWeimarGermany

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