Publication | Closed Access
Plagiarism detection using stopword n-grams
131
Citations
40
References
2011
Year
EngineeringPart-of-speech TaggingInformation ForensicsCorpus LinguisticsText MiningNatural Language ProcessingLanguage DocumentationInformation RetrievalComputational LinguisticsLanguage StudiesMachine TranslationPlagiarized PassagesKnowledge DiscoveryTerminology ExtractionDifficult Plagiarism CasesPlagiarism DetectionContent Similarity DetectionKeyword ExtractionText ProcessingLinguistics
In this paper a novel method for detecting plagiarized passages in document collections is presented. In contrast to previous work in this field that uses content terms to represent documents, the proposed method is based on a small list of stopwords (i.e., very frequent words). We show that stopword n-grams reveal important information for plagiarism detection since they are able to capture syntactic similarities between suspicious and original documents and they can be used to detect the exact plagiarized passage boundaries. Experimental results on a publicly available corpus demonstrate that the performance of the proposed approach is competitive when compared with the best reported results. More importantly, it achieves significantly better results when dealing with difficult plagiarism cases where the plagiarized passages are highly modified and most of the words or phrases have been replaced with synonyms.
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