The paper describes an approach to plagiarism detection within PlagEvalRus-2017 competition. Our system leverages deep parsing techniques to be able to detect moderately disguised plagiarism. We participated in the two tracks of the competition: source retrieval (sources detection) and text alignment (paraphrased plagiarism detection). There are various cases of plagiarism presented in datasets of both tracks. They vary by the level of disguise that was used while reusing text. The results show that our method performed quite well for detecting moderately disguised forms of plagiarism.
PDF at the Dialogue International Conference: http://www.dialog-21.ru/media/3965/zubarevdvsochenkoviv.pdf
Download PDF or read online at ResearchGate: https://www.researchgate.net/publication/330401166_PARAPHRASED_PLAGIARISM_DETECTION_USING_SENTENCE_SIMILARITY
Semantic Scholar: https://api.semanticscholar.org/CorpusID:15149652
Zubarev D. V., Sochenkov I. V. Paraphrased Plagiarism Detection Using Sentence Similarity. Computational Linguistics and Intellectual Technologies. Papers from the Annual International Conference "Dialogue" 2017, v. 1, pp. 408–418 (2017)