Research Publications Authored by SLIIT Staff
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This collection includes all SLIIT staff publications presented at external conferences and published in external journals. The materials are organized by faculty to facilitate easy retrieval.
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Publication Embargo Plagiarism Detection Tool for Enhanced Entity-Relationship Diagrams(IEEE, 2021-12-01) Dahanayake, H; Samarajeewa, D; Jayathilake, A; Bandara, D; Karunasena, A; Weerasinghe, LPlagiarism is presenting someone else’s work as one’s own work without giving credit to the original owner. Recently, plagiarism has become a serious issue in the fields of Education and Technology. To address this issue, many systems have been implemented to detect plagiarism. However, most of them are designed to deal with plagiarism of text content. Detecting plagiarism in figures and diagrams is equally important. Although there is research done on detecting plagiarism in images and flow charts, there is no research done on detecting plagiarism in more complex diagrams such as Enhanced Entity-Relationship (EER) diagrams. This paper presents a methodology to detect plagiarism in EER diagrams using Deep Neural Networks (DNN), image processing techniques, Optical Character Recognition (OCR) techniques, and text similarity detection algorithms. Since the students are aware of the existence of a plagiarism detecting tool, it will encourage the students to do work on their own and it will reduce exam offenses. The similarity report can be presented as proof to the offenders who are not accepting that they have plagiarized others' work. Using the proposed system, the EER diagram plagiarism can be detected much faster and accurately. Therefore, the efficiency of marking examinations will be increased. The final outcome of the system will be a similarity report including the plagiarized content in the compared EER diagrams.Publication Embargo Plagiarism Detection Tool for Sinhala Language with Internet Resources Using Natural Language Processing(IEEE, 2021-08-11) Rajamanthri, L; Thelijjagoda, SWith the digitalization of text through the World Wide Web, plagiarism turned into a crucial problem and a way to detect plagiarism became an essential component. Even though there are many plagiarism detection systems, applying in the world by considering other languages, for Sinhala it’s only a few, and it senses a vacuum in the domain. With the significant improvement of availability in Sinhala text on WWW, still, there is no system to detect plagiarism for these Sinhala documents by comparing resources on the internet. The purpose of this research is to address and overcome the above-mentioned gap while introducing a plagiarism detection system for the Sinhala language, by using internet resources. In the process to obtain the outcome, text pre-processing, Google searching and similarity comparison using Jaccard coefficient were the steps followed. As the final product, a Sinhala plagiarism detection tool was developed with 88% accuracy. The outcome of the work will be a support for the lectures, teachers, authors, students who are using Sinhala as their literal language.