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Plagiarism detection

About: Plagiarism detection is a research topic. Over the lifetime, 1790 publications have been published within this topic receiving 24740 citations.


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Proceedings ArticleDOI
01 Nov 2014
TL;DR: In this paper, a case study was conducted to imprint academics' knowledge, beliefs and strategies regarding plagiarism and cheating, and it was found that most of the academics were well informed but they did not spend time in their classroom to inform their students about plagiarism.
Abstract: Plagiarism and cheating are critical issues that jeopardize quality assurance in higher education. When it comes to e-learning and m-learning, fair use of information becomes even more crucial. This case study is an attempt to imprint academics' knowledge, beliefs and strategies regarding plagiarism and cheating. It was found that most of academics were well informed but they did not spend time in their classroom to inform their students about plagiarism. Furthermore only a small percentage used plagiarism detection software even though all of them had encountered plagiarism and cheating incidents. The grand majority of the academics recognized the need to educate students and was interested in receiving complementary learning material about plagiarism.

5 citations

Proceedings Article
21 May 2012
TL;DR: A system for generating multilingual corpora that can be used to determine performance of plagiarism detection systems and because of its scalability, can be applied to any language.
Abstract: The paper presents a system for generating multilingual corpora that can be used to determine performance of plagiarism detection systems. Implemented method uses parallel language corpora and because of its scalability, can be applied to any language. Authors have collected data from five parallel corpora and enabled corpus generation for Croatian, French, German, Spanish and Italian language.

5 citations

Journal ArticleDOI
TL;DR: In this paper, the authors compared the ability of a software tool based on Latent Semantic Analysis (LSA) and student teaching assistants to detect plagiarism in a large group of students, and found that the responsible teaching assistant did not detect the duplicates during the term and that the majority of the teaching assistants did not notice that they had read two identical essays (in vitro).
Abstract: Essays that are assigned as homework in large classes are prone to cheating via unauthorized collaboration. In this study, we compared the ability of a software tool based on Latent Semantic Analysis (LSA) and student teaching assistants to detect plagiarism in a large group of students. To do so, we took two approaches: the first approach was in vivo; that is, we observed whether LSA and the teaching assistants could detect plagiarism during the term. The second approach was in vitro; that is, we had 14 teaching assistants and LSA evaluate, after the term had ended, a sample of N = 60 essays of which two essays were identical. Results showed that the responsible teaching assistant did not detect the duplicates during the term (in vivo) and that the majority of the teaching assistants did not notice that they had read two identical essays (in vitro). Some of them even scored the duplicates in markedly different ways. However, the duplicates were easily identified and evaluated as equally good by LSA. We c...

5 citations

Journal ArticleDOI
TL;DR: This paper proposes a method to identify the English–Vietnamese cross-language paraphrase cases, using hybrid feature classes, calculated by using the fuzzy-based method as well as the siamese recurrent model, and combined to get the final result with a mathematical formula.
Abstract: Paraphrase identification plays an important role with various applications in natural language processing tasks such as machine translation, bilingual information retrieval, plagiarism detection, etc. With the development of information technology and the Internet, the requirement of textual comparing is not only in the same language but also in many different language pairs. Especially in Vietnamese, detecting paraphrase in the English–Vietnamese pair of sentences is a high demand because English is one of the most popular foreign languages in Vietnam. However, the in-depth studies on cross- language paraphrase identification tasks between English and Vietnamese are still limited. Therefore, in this paper, we propose a method to identify the English–Vietnamese cross-language paraphrase cases, using hybrid feature classes. These classes are calculated by using the fuzzy-based method as well as the siamese recurrent model, and then combined to get the final result with a mathematical formula. The experimental results show that our model achieves 87.4% F-measure accuracy.

5 citations

Proceedings ArticleDOI
01 Dec 2015
TL;DR: A flaw has been identified in this system that when a document is getting scanned for plagiarism each and every line is tested if any image is detected during scan then that image is simply discarded, which is very inappropriate because an image can also be plagiarized.
Abstract: Plagiarism is considered as a serious offence. Due to the tremendious growth of internet resources someone's idea can be used without giving them the proper credit. There are certain plagiarism detection tools available, for example: Plagiarisma.net, Viper etc. A flaw has been identified in this system that when a document is getting scanned for plagiarism each and every line is tested if any image is detected during scan then that image is simply discarded, which is very inappropriate because an image can also be plagiarized. Architecture diagram, flow diagram, UML diagrams, even snapshots of test results can be plagiarized Hence there is need to develop a system which can detect plagiarism in images too.

5 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202359
2022126
202183
2020118
2019130
2018125