Publikation: CitePlag : A Citation-based Plagiarism Detection System Prototype
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This paper presents an open-source prototype of a citation-based plagiarism detection system called CitePlag. The underlying idea of the system is to evaluate the citations of academic documents as language independent markers to detect plagiarism. CitePlag uses three different detection algorithms that analyze the citation sequence of academic documents for similar patterns that may indicate unduly used foreign text or ideas. The algorithms consider multiple citation-related factors such as proximity and order of citations within the text, or their probability of co-occurrence in order to compute document similarity scores. We present technical details of CitePlag’s detection algorithms and the acquisition of test data from the PubMed Central Open Access Subset. Future advancement of the prototype lies in increasing the reference database by enabling the system to process more document and citation formats. Improving CitePlag’s detection algorithms and scoring functions to reduce the number of false positives is another major goal. Eventually, we plan to integrate text-based detection algorithms in addition to the citation-based detection algorithms within CitePlag.
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MEUSCHKE, Norman, Bela GIPP, Corinna BREITINGER, 2012. CitePlag : A Citation-based Plagiarism Detection System Prototype. 5th International Plagiarism Conference IIP. Newcastle, 16. Juli 2012 - 18. Juli 2012. In: Proceedings of the 5th International Plagiarism Conference ‘12. 2012BibTex
@inproceedings{Meuschke2012CiteP-31362,
year={2012},
title={CitePlag : A Citation-based Plagiarism Detection System Prototype},
url={http://www.plagiarismadvice.org/research-papers/item/a-citation-based-plagiarism-detection-system-prototype},
booktitle={Proceedings of the 5th International Plagiarism Conference ‘12},
author={Meuschke, Norman and Gipp, Bela and Breitinger, Corinna}
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<dcterms:abstract xml:lang="eng">This paper presents an open-source prototype of a citation-based plagiarism detection system called CitePlag. The underlying idea of the system is to evaluate the citations of academic documents as language independent markers to detect plagiarism. CitePlag uses three different detection algorithms that analyze the citation sequence of academic documents for similar patterns that may indicate unduly used foreign text or ideas. The algorithms consider multiple citation-related factors such as proximity and order of citations within the text, or their probability of co-occurrence in order to compute document similarity scores. We present technical details of CitePlag’s detection algorithms and the acquisition of test data from the PubMed Central Open Access Subset. Future advancement of the prototype lies in increasing the reference database by enabling the system to process more document and citation formats. Improving CitePlag’s detection algorithms and scoring functions to reduce the number of false positives is another major goal. Eventually, we plan to integrate text-based detection algorithms in addition to the citation-based detection algorithms within CitePlag.</dcterms:abstract>
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