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A Review On Language Specific Multi Document Similarity Detection

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dc.contributor.author Piyarathna, Achala
dc.contributor.author Poravi, Guhanathan
dc.date.accessioned 2020-05-27T18:30:13Z
dc.date.available 2020-05-27T18:30:13Z
dc.date.issued 2019
dc.identifier.citation Piyarathna, A and Poravi, G (2019) ‘A Review On Language Specific Multi Document Similarity Detection’ In: 2019 IEEE 5th International Conference for Convergence in Technology (I2CT), Pune, India. 29-31 March 2019. pp. 1-6 IEEE DOI: 10.1109/I2CT45611.2019.9033688 en_US
dc.identifier.uri https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9033688
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/451
dc.description.abstract Plagiarism is exploitation of others work and presents them as your own without referencing the original work. There are various detection tools that are being developed in order to detect these plagiarized content. Most of the available detection tools are based on the English language. Though there are language independent and language-specific detection tools, there is no comprehensive multi-document plagiarism detection mechanism. If the already available work on other language-specific tools and Similarity detection tools are analyzed and find what has been missing, it will be a stepping stone to continue research on this area. This paper contains the underlying piece of a continuous research, and later on, we plan to use this learning to present a comprehensive research on the subject area. en_US
dc.publisher IEEE en_US
dc.subject Plagiarism en_US
dc.subject Tools en_US
dc.subject Feature extraction en_US
dc.subject Language dependent model en_US
dc.title A Review On Language Specific Multi Document Similarity Detection en_US
dc.type Article en_US


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