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Detecting plagiarism in multiple Sinhala documents

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dc.contributor.author Ganepola, G.A.U.E.
dc.contributor.author Wijayasiriwardhane, T.K.
dc.date.accessioned 2018-08-17T05:20:46Z
dc.date.available 2018-08-17T05:20:46Z
dc.date.issued 2018
dc.identifier.citation Ganepola,G.A.U.E. and Wijayasiriwardhane,T.K. (2018). Detecting plagiarism in multiple Sinhala documents. International Research Conference on Smart Computing and Systems Engineering - SCSE 2018, Department of Industrial Management, Faculty of Science, University of Kelaniya, Sri Lanka. p.166. en_US
dc.identifier.uri http://repository.kln.ac.lk/handle/123456789/19026
dc.description.abstract Availability of unlimited information resources over the Internet and the advancement of the Internet search engines such as Google to locate those resources much easily have contributed to an increase of plagiarism. Though there are a number of software tools available for detecting plagiarism in multiple English documents, no such a tool is yet available for the Sinhala language. This paper presents a novel language dependent approach to detect plagiarism in multiple Sinhala documents. It uses stemming, stop word removal and synonym replacement for text preprocessing and term frequency-inverse document frequency (tf-idf) and cosine similarity for similarity comparison. A prototype software tool was developed and interlinked with an operational Sinhala WordNet to demonstrate the viability of the proposed approach. The prototype tool was validated against a sample of Sinhala assignments from secondary school students. The assignments were also examined by an expert to determine whether they had actually been plagiarized. When compared the results of the prototype tool against those of the expert judgment, we found that our proposed approach for plagiarism detection in multiple Sinhala documents performs with an accuracy of over 80%. en_US
dc.language.iso en en_US
dc.publisher International Research Conference on Smart Computing and Systems Engineering - SCSE 2018 en_US
dc.subject Plagiarism detection en_US
dc.subject Sinhala language en_US
dc.subject Sinhala WordNet en_US
dc.title Detecting plagiarism in multiple Sinhala documents en_US
dc.type Article en_US


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