Document overlap detection system for distributed digital libraries
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Methods for identifying versioned and plagiarized documents
Journal of the American Society for Information Science and Technology
Proceedings of the 21st ACM conference on Hypertext and hypermedia
An evaluation framework for plagiarism detection
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
Language Resources and Evaluation
Proceedings of the 11th ACM symposium on Document engineering
Demonstration of citation pattern analysis for plagiarism detection
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
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Various approaches for plagiarism detection exist. All are based on more or less sophisticated text analysis methods such as string matching, fingerprinting or style comparison. In this paper a new approach called Citation-based Plagiarism Detection is evaluated using a doctoral thesis, in which a volunteer crowd-sourcing project called GuttenPlag identified substantial amounts of plagiarism through careful manual inspection. This new approach is able to identify similar and plagiarized documents based on the citations used in the text. It is shown that citation-based plagiarism detection performs significantly better than text-based procedures in identifying strong paraphrasing, translation and some idea plagiarism. Detection rates can be improved by combining citation-based with text-based plagiarism detection.