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Journal articles on the topic 'Plagiarism detector'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Lanke, Ms Minakshi, Ms Aishwarya Porwal, Ms Sejal Sarolkar, Mr Gaurang Palaskar, and Prof Shital Kakad. "AI Based Student’s Assignments Plagiarism Detector." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (2022): 991–99. http://dx.doi.org/10.22214/ijraset.2022.48080.

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Abstract: The increase in plagiarizing academic contents led to efficient plagiarism detectors. In the conventional plagiarism detection tools, we have to put the contents from our paper or assignment and paste it into the input box for checking plagiarism or we have to load our files separately. Software under the domain artificial intelligence is moving towards the creation of a systems that can make tasks hassle-free and it also saves the time. “Smart Assignment Plagiarism Detector” can provide easy and efficient way of checking plagiarised data for teachers just in a single click by upload

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2

Stone, R. "Court test for plagiarism detector?" Science 254, no. 5037 (1991): 1448. http://dx.doi.org/10.1126/science.1962200.

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Nwohiri, Anthony, Opemipo JODA, and Olasupo Ajayi. "AI-POWERED PLAGIARISM DETECTION: LEVERAGING FORENSIC LINGUISTICS AND NATURAL LANGUAGE PROCESSING." FUDMA JOURNAL OF SCIENCES 5, no. 3 (2021): 207–18. http://dx.doi.org/10.33003/fjs-2021-0503-700.

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Plagiarism of material from the Internet is nothing new to academia and it is particularly rampant. This challenge can range from borrowing a particularly apt phrase without attribution, to paraphrasing someone else’s original idea without citation, to wholesale contract cheating. Plagiarized content can infringe on copyright laws and could incur hefty fines on publishers and authors. Unintentional plagiarism mostly occurs due to inaccurate citation. Most plagiarism checkers ignore this fact. Moreover, plagiarizers are increasingly becoming negatively “smarter”. All these necessitate a plagiar

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4

Wali, Muhammad, and Safrizal Safrizal. "Similar text sebagai Pengkodean Aplikasi Plagiarisme." Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) 2, no. 1 (2018): 11. http://dx.doi.org/10.35870/jtik.v2i1.43.

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a b s t r a c tThis research is intended to make a coding technique with a function similar to a plagiarism detector similar_text as text. By using the text function is similar, this research resulted in a detection of the document against the 10 (ten) of selected journal with, the document is the document with extension doc, docx, pdf, and txt. The document will be converted into html form and would henceforth be done making the string with the marker dots (.) And the comma (,) will be fetched a new string. By specifying a percentage string similarity of 90% then produced a text, in this case

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Mahmoodi, Maryam, and Mohammad Mahmoodi Varnamkhasti. "Design a Persian Automated Plagiarism Detector (AMZPPD)." International Journal of Engineering Trends and Technology 8, no. 8 (2014): 465–67. http://dx.doi.org/10.14445/22315381/ijett-v8p280.

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6

Bouarara, Hadj Ahmed, Reda Mohamed Hamou, and Amine Rahmani. "BHA2." International Journal of Swarm Intelligence Research 8, no. 1 (2017): 30–53. http://dx.doi.org/10.4018/ijsir.2017010102.

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In the last decade, the plagiarism cases were increased and become a topical problem in the modern scientific world, caused by the quantity of textual information available online/offline. The authors' work deals on the development of a new plagiarism detector system called BHA2 which has as input the suspicious text (to be analysed) and the original texts (learning basis). It can detect the different forms of plagiarism based on: Google API to detect the cases of plagiarism with translation; text summarization to detect the plagiarism of idea; conceptual transformation to detect the plagiaris

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Sobowale, Adedayo, Adebimpe Esan, Adebiyi Tomilayo, Bunmi Jooda, and Adekemi Bolajoko. "Automatic plagiarism detection using fuzzy-logic." Dutse Journal of Pure and Applied Sciences 9, no. 3a (2023): 312–18. http://dx.doi.org/10.4314/dujopas.v9i3a.31.

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Plagiarism occurs when a researcher copies fellow researcher’s work verbatim without acknowledging the author. This work developed an automatic plagiarism detector using fuzzy logic. The system developed was tested with 4 different text documents and evaluated using portability, efficiency, functionality, ease of use and accuracy metrics. Results show that the developed plagiarism detector is very easy to use with high functionality and accuracy as well as moderate efficiency and portability based on user’s assessment. However, future work can increase the data size for model training and cons

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Kikuchi, Hiroshi, Takaaki Goto, Mitsuo Wakatsuki, and Tetsuro Nishino. "A Source Code Plagiarism Detecting Method Using Sequence Alignment with Abstract Syntax Tree Elements." International Journal of Software Innovation 3, no. 3 (2015): 41–56. http://dx.doi.org/10.4018/ijsi.2015070104.

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Learning to program is an important subject in computer science courses. During programming exercises, plagiarism by copying and pasting can lead to problems for fair evaluation. Some methods of plagiarism detection are currently available, such as sim. However, because sim is easily influenced by changing the identifier or program statement order, it fails to do enough to support plagiarism detection. In this paper, the authors propose a plagiarism detection method which is not influenced by changing the identifier or program statement order. The authors also explain our method's capabilities

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Ibrahim, Karim Hesham Shaker, Dhari Al Otaibi, and Fadi N. Sibai. "The Robustness of AI-Classifiers in the Face of AI-Assisted Plagiarism." International Journal of Computer-Assisted Language Learning and Teaching 15, no. 1 (2025): 1–27. https://doi.org/10.4018/ijcallt.375428.

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The release of ChatGPT marked the beginning of a new era of artificial intelligence (AI)-assisted plagiarism that disrupted traditional assessment practices. In response to this existential threat, Turnitin added an AI content detector to its platform, which is the most used plagiarism detection software in most academic institutions. However, several early studies suggest that AI detectors have questionable accuracy rates, especially when dealing with English as a second language writings or modified AI texts. To explore this uncharted territory in second language writing research, the presen

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Satish, SVS. "Intellicheck – Plagiarism Detector Using HMM, BERT and Abstract Syntax Tree." International Journal of Science, Engineering and Technology 13, no. 2 (2025): 1–9. https://doi.org/10.61463/ijset.vol.13.issue2.196.

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11

Stephanie, Stephanie, Dali Santun Naga, and Viny Christanti Mawardi. "PENDETEKSIAN KEMIRIPAN TEKS DESKRIPSI DIRI PADA E-RECRUITMENT KARYAWAN DENGAN METODE RABIN KARP DAN JARO WINKLER DISTANCE." Jurnal Ilmu Komputer dan Sistem Informasi 9, no. 1 (2021): 187. http://dx.doi.org/10.24912/jiksi.v9i1.11593.

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E-recruitment is a web-based application that is used to recruit employees for several available companies. The e-recruitment system has a plagiarism checker feature. Plagiarism itself has the meaning of actions that are considered fraud by taking someone's idea or writing without mentioning a reference and claiming it as their own. So that the e-recruitment application requires a plagiarism detector which functions to make it easier for companies to assess the characteristics of their prospective employees. The plagiarism checker feature applies a string matching algorithm to a text to search

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12

Prashjeev Rai, Sadikshya Gyawali, Shuvechhya Bajracharya, Sparsh Nidhi, and Sudeep Shakya. "AI Content Detection." KEC Journal of Science and Engineering 9, no. 1 (2025): 34–44. https://doi.org/10.3126/kjse.v9i1.78343.

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AI (Artificial Intelligence) content detection is the task of predicting if the given content is written by humans or AI. This project is a detection tool aimed at eliminating issues created by AI-generated text content such as fake academic reports and papers, articles, news, misinformation, and propaganda by combining multiple detection methods. Three models, LSTM (Long short-term memory), BERT (Bidirectional Encoder Representations from Transformers), and distilBERT (distilled Bidirectional Encoder Representations from Transformers) were fine-tuned on a small labelled dataset of 2492 rows.

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Sousa-Silva, Rui. "Detecting translingual plagiarism and the backlash against translation plagiarists." Language and Law / Linguagem e Direito 1, no. 1 (2014): 70–94. https://doi.org/10.5281/zenodo.47258.

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Plagiarism detection methods have improved signi cantly over the last decades, and as a result of the advanced research conducted by computa- tional and mostly forensic linguists, simple and sophisticated textual borrowing strategies can now be identi ed more easily. In particular, simple text compari- son algorithms developed by computational linguists allow literal, word-for-word plagiarism (i.e. where identical strings of text are reused across di erent docu- ments) to be easily detected (semi-)automatically (e.g. Turnitin or SafeAssign), although these methods tend to perform less well whe

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VERGUN, A. R., S. P. YAGELO, O. M. VERGUN, I. M. HAVRYLIUK, and Z. M. KIT. "Academic integrity of applicants: curriculum and examination of scientific papers in the context of counteraction to academic plagiarism." Higher Education of Ukraine in the Context of Integration to European Educational Space 88, no. (I) (2021): 31–53. http://dx.doi.org/10.38014/osvita.2021.88.03.

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As you know, the principles of academic culture and integrity in the current state of university education in Ukraine are often simply perceived as an abstract, but necessary for the European integration of education postulate. Codes of ethics and regulations on combating academic plagiarism are created on the basis of recommendations of the Ministry of Education and Science, regulate the activities of employees and students in the context of prevention and detection of falsifications, violations of academic integrity, including academic plagiarism. The establishment of the principles of acade

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15

Gosling, Samuel David, Kate Ybarra, and Sara K. Angulo. "A widely used Generative-AI detector yields zero false positives." Aloma: Revista de Psicologia, Ciències de l'Educació i de l'Esport 42, no. 2 (2024): 31–43. https://doi.org/10.51698/aloma.2024.42.2.31-43.

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The widespread availability of generative-AI using Large Language Models (LLMs) has provided the means for students and others to easily cheat on written assignments – that is, students can use AI to generate text and then submit that work as their own. A variety of technical solutions have been developed to detect such cheating. However, concerns have been raised about the dangers of falsely identifying real students’ responses as having been generated by AI. Here we evaluate a Generative AI detector that comes as an option with Turnitin, a widely used plagiarism-detection platform already in

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16

Zhang, Yan-Ya, and Ming Li. "Find Me if You Can: Deep Software Clone Detection by Exploiting the Contest between the Plagiarist and the Detector." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 5813–20. http://dx.doi.org/10.1609/aaai.v33i01.33015813.

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Code clone is common in software development, which usually leads to software defects or copyright infringement. Researchers have paid significant attention to code clone detection, and many methods have been proposed. However, the patterns for generating the code clones do not always remain the same. In order to fool the clone detection systems, the plagiarists, known as the clone creator, usually conduct a series of tricky modifications on the code fragments to make the clone difficult to detect. The existing clone detection approaches, which neglects the dynamics of the “contest” between th

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Shen, Victor R. L. "Novel Code Plagiarism Detection Based on Abstract Syntax Tree and Fuzzy Petri Nets." International Journal of Engineering Education 1, no. 1 (2019): 46–56. http://dx.doi.org/10.14710/ijee.1.1.46-56.

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Those students who major in computer science and/or engineering are required to design program codes in a variety of programming languages. However, many students submit their source codes they get from the Internet or friends with no or few modifications. Detecting the code plagiarisms done by students is very time-consuming and leads to the problems of unfair learning performance evaluation. This paper proposes a novel method to detect the source code plagiarisms by using a high-level fuzzy Petri net (HLFPN) based on abstract syntax tree (AST). First, the AST of each source code is generated

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Velásquez, Juan D., Yerko Covacevich, Francisco Molina, Edison Marrese-Taylor, Cristián Rodríguez, and Felipe Bravo-Marquez. "DOCODE 3.0 (DOcument COpy DEtector): A system for plagiarism detection by applying an information fusion process from multiple documental data sources." Information Fusion 27 (January 2016): 64–75. http://dx.doi.org/10.1016/j.inffus.2015.05.006.

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19

Vergun, A. R., S. P. Yagelo та Н. M. Stechak. "АКАДЕМІЧНА ДОБРОЧЕСНІСТЬ ТА АНТИПЛАГІАТНА ЕКСПЕРТИЗА У ЛЬВІВСЬКОМУ НАЦІОНАЛЬНОМУ МЕДИЧНОМУ УНІВЕРСИТЕТІ ІМЕНІ ДАНИЛА ГАЛИЦЬКОГО: КЛЮЧОВІ ЗАСАДИ І МЕТОДОЛОГІЯ". Медична освіта, № 4 (6 січня 2021): 116–22. http://dx.doi.org/10.11603/me.2414-5998.2020.4.11673.

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У статті розглянуто й охарактеризовано ключові засади, методологію та комплекс заходів щодо імплементації і забезпечення академічної доброчесності та високих професійних стандартів у Львівському національному медичному університеті імені Данила Галицького, запобігання порушенням академічної доброчесності; честі, гідності, взаємної поваги і довіри, забезпечення рівноправності та толерантності всіх учасників освітнього процесу шляхом дотримання принципів і загальноприйнятих норм щодо етичної поведінки, протидії академічному плагіату з урахуванням вимог Законів України «Про освіту», «Про вищу осв

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20

Noever, David, and Matt Ciolino. "The Turing Deception." International Journal on Cybernetics & Informatics 12, no. 1 (2023): 1–16. http://dx.doi.org/10.5121/ijci.2023.120108.

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This research revisits the classic Turing test and compares recent large language models such as ChatGPT for their abilities to reproduce human-level comprehension and compelling text generation. Two task challenges- summary and question answering- prompt ChatGPT to produce original content (98-99%) from a single text entry and sequential questions initially posed by Turing in 1950. We score the original and generated content against the OpenAI GPT2 Output Detector from 2019, and establish multiple cases where the generated content proves original and undetectable (98%). The question of a mach

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Haque, Muhammed Shahriar. "Plagiarism in Graduate Research:." Crossings: A Journal of English Studies 2, no. 1 (2009): 155–74. http://dx.doi.org/10.59817/cjes.v2i1.406.

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Empirical work on plagiarism in graduate research, particularly in English studies, in the Bangladeshi institutions of higher learning (private and public), is so scarce that it could be considered as almost negligible. Plagiarism is a crime and a violation of intellectual property, and needs to be addressed; but it seems to be overlooked and or neglected by the University Grants Commission (UGC) as well as the concerned universities. Moreover, when plagiarism is detected in graduate research, the blame predominantly falls on the plagiarists/students, who are held accountable for their actions

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Muluk, Safrul, Fani Rahma Yanis, Syarifah Dahliana, and Amiruddin Amiruddin. "Scrutinizing EFL students' plagiarism practice." Englisia: Journal of Language, Education, and Humanities 9, no. 1 (2021): 145. http://dx.doi.org/10.22373/ej.v9i1.10492.

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The current study was designed to investigate the types of plagiarism that appear in EFL students’ theses at Ar-Raniry State Islamic University, Indonesia. It sought to examine the plagiarism level, and investigate the triggering factors encouraging these EFL students of the 2019 batch to plagiarize. This study used a qualitative method with a case study approach. The participants in this study were ten EFL students of the 2019 batch and their theses. The participants were randomly selected. The data collection was carried out using two research instruments, namely document analysis, and inter

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ВЕРГУН, А. Р., С. П. ЯГЕЛО та О. М. ВЕРГУН. "ДОСВІД АНТИПЛАГІАТНОЇ ЕКСПЕРТИЗИ: АНАЛІЗ ДЕЯКИХ ПРОГРАМ ТА АВТОРСЬКІ ПОГЛЯДИ В КОНТЕКСТІ АКАДЕМІЧНОЇ ДОБРОЧЕСНОСТІ". АКАДЕМІЧНІ СТУДІЇ. СЕРІЯ «ПЕДАГОГІКА» 1, № 4 (2022): 44–56. http://dx.doi.org/10.52726/as.pedagogy/2021.4.1.7.

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Активно здійснюються заходи щодо запобігання оприлюдненню (частково або повністю) наукових результатів, отриманих іншими особами, як результатів власного дослідження та/або відтворенню опублікованих текстів інших авторів без відповідного посилання. У Львівському національному медичному університеті імені Данила Галицького розроблено та імплементовано Положення про протидію академічному плагіату. Кодекс академічної етики Львівського національного медичного університету імені Данила Галицького визначає основні поняття, завдання академічної доброчесності, регламентує основні засади організації та

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Wiwanitkit, Viroj. "How to Verify and Manage the Translational Plagiarism?" Open Access Macedonian Journal of Medical Sciences 4, no. 3 (2016): 533. http://dx.doi.org/10.3889/oamjms.2016.070.

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The use of Google translator as a tool for determining translational plagiarism is a big challenge. As noted, plagiarism of the original papers written in Macedonian and translated into other languages can be verified after computerised translation in other languages. Attempts to screen the translational plagiarism should be supported. The use of Google Translate tool might be helpful. Special focus should be on any non-English reference that might be the source of plagiarised material and non-English article that might translate from an original English article, which cannot be detected by si

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Tapan, kumar Mahato, Mohanbhai Baria Hetalbahen, Naimeshbhai Suthar Dhvaniben, Kalpeshbhai Bamaniya Madhuri, and pulandarsinh kushvah Radha. "PLAGIARISM: AN ACT AGAINST THE RESEARCH ETHICS." Indian Journal of science and research 3, no. 3 (2023): 114–19. https://doi.org/10.5281/zenodo.8025951.

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<strong>Abstract:</strong> Simply said, the goal of every research project is to uncover new information that can be used to solve an issue. Evidence from scientific research lends credibility to the work, not just in the country where it is done, but globally. That can only be accomplished with a wholly honest study. Plagiarism occurs when one uses another person's research or writing as one's own without properly attributing the source. Plagiarism is unethical and should be avoided at all costs. Plagiarism can occur for a variety of reasons, both deliberate and unintentional. Univers

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Al-Zubaidi, Khairi, Mohamed Jaafari, and Fatima Zahra Touzani. "Impact of ChatGPT on Academic Writing at Moroccan Universities." Arab World English Journal 1, no. 1 (2024): 4–25. http://dx.doi.org/10.24093/awej/chatgpt.1.

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The new wave of buzzword technology has launched the Chat Generative Pre-Trained Transformer (ChatGPT). The ChatGPT application, besides its benefits, has created a worldwide heated debate about its impact on quality and the future of education. Artificial intelligence and other computing technology advancements have dominated the academic scene The main aim of this paper is to map out the impact of the use of ChatGPT on academic writing at Moroccan universities. The researchers have designed a questionnaire for the purpose of this study. The research targets university students and educators

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Rohmad, Zaini, and Dewi Sri Wahyuni. "Tech-Rich Instruction: Raising Students’ Awareness against Plagiarism in Academic Writing." LEKSIKA 12, no. 2 (2019): 97. http://dx.doi.org/10.30595/lks.v12i2.3807.

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Plagiarism is an intolerant action in the circumstances of education; it is stealing or cheating any papers, ideas, and things related to someone’s works. This is a harmful offence with academic, professional, legal, and monetary consequences when someone is proved as a plagiarist. Students can be expelled from the class when they cheat colleagues’ works; the worst is that the university can retract their certificate of graduation when their manuscripts are investigated and proved as result of copying other works. Regarding to its danger, pla-giarism has to be avoided trough establishing curri

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Narayanan, Aditya Shankar. "A Survey on Plagiarism Detection Techniques." International Journal of Psychosocial Rehabilitation 24, no. 1 (2020): 1564–72. http://dx.doi.org/10.37200/ijpr/v24i1/pr200254.

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Barrón-Cedeño, Alberto, Marta Vila, M. Martí, and Paolo Rosso. "Plagiarism Meets Paraphrasing: Insights for the Next Generation in Automatic Plagiarism Detection." Computational Linguistics 39, no. 4 (2013): 917–47. http://dx.doi.org/10.1162/coli_a_00153.

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Although paraphrasing is the linguistic mechanism underlying many plagiarism cases, little attention has been paid to its analysis in the framework of automatic plagiarism detection. Therefore, state-of-the-art plagiarism detectors find it difficult to detect cases of paraphrase plagiarism. In this article, we analyze the relationship between paraphrasing and plagiarism, paying special attention to which paraphrase phenomena underlie acts of plagiarism and which of them are detected by plagiarism detection systems. With this aim in mind, we created the P4P corpus, a new resource that uses a pa

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Maurer, Hermann, Frank Kappe, and Bilal Zaka. "Plagiarism - A Survey." JUCS - Journal of Universal Computer Science 12, no. (8) (2006): 1050–84. https://doi.org/10.3217/jucs-012-08-1050.

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Plagiarism in the sense of "theft of intellectual property" has been around for as long as humans have produced work of art and research. However, easy access to the Web, large databases, and telecommunication in general, has turned plagiarism into a serious problem for publishers, researchers and educational institutions. In this paper, we concentrate on textual plagiarism (as opposed to plagiarism in music, paintings, pictures, maps, technical drawings, etc.). We first discuss the complex general setting, then report on some results of plagiarism detection software and finally draw attention

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Shukla, Akhandanand. "Plagiarism Detection and Avoidance Consequences in Academic World." Journal of Advanced Research in Library and Information Science 04, no. 04 (2017): 6–13. http://dx.doi.org/10.24321/2395.2288.201706.

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Maojo, Victor, Miguel García-Remesal, and Jose Crespo. "Detectors could spot plagiarism in research proposals." Nature 456, no. 7218 (2008): 30. http://dx.doi.org/10.1038/456030c.

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Balymova, Maria V., Konstantin Ye Burkin, Ainaz Z. Gainullin, Alena Yu Likhacheva, and Mikhail Ye Zhilkin. "Revealing the falsification of semi-finished beef products with mechanically deboned minced chicken using the example of dumplings." Butlerov Communications 64, no. 12 (2020): 40–44. http://dx.doi.org/10.37952/roi-jbc-01/20-64-12-40.

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Human nutrition is an important factor affecting human health. Counterfeiting is one of the most pressing problems in the market, which worries manufacturers, sellers and consumers. There are a variety of product counterfeiting: substitution of expensive food products for cheaper ones, manufacturing of products with low nutritional value, deterioration of the recipe and plagiarism of the brand. It is also necessary to observe the correct labeling of the product, as this enables the consumer to meet his requirements when choosing a product. This article presents the results of our own research

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Adil, Ahnaf, Mohammad Mahmudul Hasan Hossain, Sabrin Sworna Nabila, and Hossain Nahid. "An improved extrinsic monolingual plagiarism detection approach of the Bengali text." International Journal of Electrical and Computer Engineering (IJECE) 13, no. 4 (2023): 4256–67. https://doi.org/10.11591/ijece.v13i4.pp4256-4267.

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Plagiarism is an act of literature fraud, which is presenting others’ work or ideas without giving credit to the original work. All published and unpublished written documents are under the cover of this definition. Plagiarism, which increased significantly over the last few years, is a concerning issue for students, academicians, and professionals. Due to this, there are several plagiarism detection tools or software available to detect plagiarism in different languages. Unfortunately, negligible work has been done and no plagiarism detection software available in the Bengali language w

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Meuschke, Norman, and Bela Gipp. "State of the Art in Detecting Academic Plagiarism." International Journal for Educational Integrity 9, no. 1 (2013): 50–71. https://doi.org/10.5281/zenodo.3482941.

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The problem of academic plagiarism has been present for centuries. Yet, the widespread dissemination of information technology, including the internet, made plagiarising much easier. Consequently, methods and systems aiding in the detection of plagiarism have attracted much research within the last two decades. Researchers proposed a variety of solutions, which we will review comprehensively in this article. Available detection systems use sophisticated and highly efficient character-based text comparisons, which can reliably identify verbatim and moderately disguised copies. Automatically det

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Nkue, Dumka, and Onate Taylor. "Plagiarism Detection System using an Enhanced String Matching Algorithm." Journal of Scientific and Engineering Research 8, no. 4 (2021): 99–105. https://doi.org/10.5281/zenodo.10580532.

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<strong>Abstract</strong> The issue of plagiarism in our academic institution has risen greatly over the years. There has been a very lukewarm approach to this malady by institutions. There arises a need to address this situation. Plagiarism detection techniques have been discussed extensively. In this project we designed a new model (The Knowledge-Base String Matching Algorithm) which adopts the Knuth Morris Pratt Algorithm for detecting plagiarism in text document. The methodology used was the Dynamic System Development Method and the plagiarism detection software was implemented using the J

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Weber-Wulff, Debora. "Plagiarism detectors are a crutch, and a problem." Nature 567, no. 7749 (2019): 435. http://dx.doi.org/10.1038/d41586-019-00893-5.

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Gayadhankar, Kaustubh, Rishi Patel, Hrithik Lodha, and Swapnil Shinde. "Image plagiarism detection using GAN - (Generative Adversarial Network)." ITM Web of Conferences 40 (2021): 03013. http://dx.doi.org/10.1051/itmconf/20214003013.

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In Today’s date plagiarism is a very important aspect because content originality is the client's prior requirement. Many people on the internet use others' images and get publicity while the owner of the image or data won′t get anything out of it. Many users copy the data or image features from the other users and modify it a little bit or create an artificial replica of it. With sufficient computational power and volume of data, the GAN models are capable enough to produce fake images that look very much similar to the real images. These kinds of images are generally not detected by modern p

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Sun, Thurain Moe, Mar Soe Khin, and Than Nwe Than. "A proposed approach for plagiarism detection in Myanmar Unicode text." IAES International Journal of Artificial Intelligence (IJ-AI) 14, no. 2 (2025): 1616–24. https://doi.org/10.11591/ijai.v14.i2.pp1616-1624.

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Around the world, with technology that improves over time, almost everyone can access the internet easily and quickly. With the increase in the use of the internet, the plagiarism of information that is easily available on the internet has also increased. Such plagiarism seriously undermines originality and ethical principles. In order to prevent these incidents, there is plagiarism detection software for many countries and languages, but there is no plagiarism detection software for the Myanmar language yet. In an attempt to fill that gap, this study proposed a deep learning model with Rabin-

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Ersan, Ceyhun, and Banu Uslu. "Can Plagiarism Detected by Software be Prevented through Education? An Experimental Study with Preschool Teacher Candidates." International Journal of Technology in Education and Science 4, no. 2 (2020): 118–32. http://dx.doi.org/10.46328/ijtes.v4i2.72.

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In this study, the effect of science and research ethics course on preschool teacher candidates’ possible plagiarism behaviors was examined. Fifteen teacher candidates were asked to prepare a written assignment (pre-test) before the start of the course. Similarly, a second written assignment (post-test) was taken at the end of the course which took approximately 12 weeks. Both assignments received from teacher candidates were evaluated in two similarity/plagiarism software programs and the similarity rates of each student's homework were calculated as a percentage. The Wilcoxon Signed Ranks Te

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Widodo, Arif, Lalu Hamdian Affandi, Dyah Indraswati, Umar Umar, and Vivi Rachmatul Hidayati. "PELATIHAN TEKNIK PARAFRASE UNTUK MENGURANGI TINGKAT PLAGIASI DALAM PENULISAN KARYA TULIS ILMIAH BAGI MAHASISWA PGSD UNIVERSITAS MATARAM." SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan 6, no. 4 (2022): 1888. http://dx.doi.org/10.31764/jpmb.v6i4.10977.

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ABSTRAKTingkat plagiasi merupakan salah satu indikator orisinalitas sebuah karya ilmiah. Tingginya tingkat plagiasi dapat mengindikasikan adanya ketidakjujuran mahasiswa dalam penulisan karya ilmiah. Kasus plagiarisme dalam penulisan karya ilmiah tidak hanya terjadi karena faktor kesengajaan, tetapi juga dapat terjadi karena keterbatasan pengetahuan mahasiswa terhadap teknik penulisan. Penyebab tingginya plagiasi dapat terjadi karena kesalahan pengutipan sumber pustaka, baik dari jurnal ilmiah, buku maupun sumber lainnya. Bentuk kesalahan yang terjadi adalah mahasiswa tidak melakukan parafrase

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Lopatin, Evgeniy. "Retraction: Assessment of Russian banking system performance and sustainability." Banks and Bank Systems 14, no. 3 (2019): 202–11. http://dx.doi.org/10.21511/bbs.14(3).2019.17.

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Retracted on August 17, 2020 by the Journal’s owner and Publisher. Type of retraction – plagiarism.There wasn’t a request for this retraction, but the reason for investigation of plagiarism fact was the Russian Academy of Sciences Committee’s report “Predatory Journals at Scopus and WoS: Translation Plagiarism from Russian Sources”: https://kpfran.ru/wp-content/uploads/plagiarism-by-translation-2.pdf” dated August 12, 2020. The publishing house has familiarized itself with the report. The article by Alexey Mikhaylov, Natalia Sokolinskaya and Evgeniy Lopatin (2019). Asset allocation in equity,

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Lavrushin, Oleg, and Natalia Sokolinskaya. "Retraction: Confidence level and credit risk analysis in Russian banks." Banks and Bank Systems 15, no. 2 (2020): 38–46. http://dx.doi.org/10.21511/bbs.15(2).2020.04.

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Retracted on August 17, 2020 by the Journal’s owner and Publisher. Type of retraction – plagiarism.There wasn’t a request for this retraction, but the reason for investigation of plagiarism fact was the Russian Academy of Sciences Committee’s report “Predatory Journals at Scopus and WoS: Translation Plagiarism from Russian Sources”: https://kpfran.ru/wp-content/uploads/plagiarism-by-translation-2.pdf” dated August 12, 2020. The publishing house has familiarized itself with the report. The article by Alexey Mikhaylov, Natalia Sokolinskaya and Evgeniy Lopatin (2019). Asset allocation in equity,

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Mikhaylov, Alexey, Natalia Sokolinskaya, and Evgeniy Lopatin. "Retraction: Asset allocation in equity, fixed-income and cryptocurrency on the base of individual risk sentiment." Investment Management and Financial Innovations 16, no. 2 (2019): 171–81. http://dx.doi.org/10.21511/imfi.16(2).2019.15.

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Retracted on August 17, 2020 by the Journal’s owner and Publisher. Type of retraction – plagiarism.There wasn’t a request for this retraction, but the reason for investigation of plagiarism fact was the Russian Academy of Sciences Committee’s report “Predatory Journals at Scopus and WoS: Translation Plagiarism from Russian Sources”: https://kpfran.ru/wp-content/uploads/plagiarism-by-translation-2.pdf” dated August 12, 2020. The publishing house has familiarized itself with the report. The article by Alexey Mikhaylov, Natalia Sokolinskaya and Evgeniy Lopatin (2019). Asset allocation in equity,

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An, Jaehyung, Alexey Mikhaylov, and Natalia Sokolinskaya. "Retraction: Oil incomes spending in sovereign fund of Norway (GPFG)." Investment Management and Financial Innovations 16, no. 3 (2019): 10–17. http://dx.doi.org/10.21511/imfi.16(3).2019.02.

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Retracted on August 17, 2020 by the Journal’s owner and Publisher. Type of retraction – plagiarism.There wasn’t a request for this retraction, but the reason for investigation of plagiarism fact was the Russian Academy of Sciences Committee’s report “Predatory Journals at Scopus and WoS: Translation Plagiarism from Russian Sources”: https://kpfran.ru/wp-content/uploads/plagiarism-by-translation-2.pdf” dated August 12, 2020. The publishing house has familiarized itself with the report. The article by Alexey Mikhaylov, Natalia Sokolinskaya and Evgeniy Lopatin (2019). Asset allocation in equity,

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Díaz Arce, Dariel. "Inteligencia artificial vs.Turnitin: implicaciones para el plagio académico." Revista Cognosis 8, no. 1 (2023): 15–26. http://dx.doi.org/10.33936/cognosis.v8i1.5517.

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El presente trabajo busca evaluar la utilidad de Turnitin para identificar trabajos realizados por herramientas de Inteligencia Artificial. El diseño fue experimental con dos grupos, uno experimental formado por 50 ensayos creados por ChatGPT y otro control, formado por 50 trabajos de los mismos temas creados por estudiantes de bachillerato. Se contrastaron los índices generales de similitud (IGS), la frecuencia de trabajos en riesgo de plagio (IGS ≥14 %) y la frecuencia trabajos con signos de plagio por copy-paste después de la revisión manual. El IGS promedio resultó ser mayor en los documen

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Nguyen, Van Son, Thanh Huong Le, and Chi Thanh Nguyen. "A two-phase plagiarism detection system based on multi-layer long short-term memory networks." International Journal of Artificial Intelligence (IJ-AI) 10, no. 3 (2021): 636–48. https://doi.org/10.11591/ijai.v10.i3.pp636-648.

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Finding plagiarism strings between two given documents are the main task of the plagiarism detection problem. Traditional approaches based on string matching are not very useful in cases of similar semantic plagiarism. Deep learning approaches solve this problem by measuring the semantic similarity between pairs of sentences. However, these approaches still face the following challenging points. First, it is impossible to solve cases where only part of a sentence belongs to a plagiarism passage. Second, measuring the sentential similarity without considering the context of surrounding sentence

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Mane, Vishwasrao Sadu. "Importance of Plagiarism Software in Research." Royal International Global Journal of Advance and Applied Research 1, no. 6 (2024): 1–14. https://doi.org/10.5281/zenodo.14997923.

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<strong><u>Abstract</u></strong>   <em> </em><em>Plagiarism is a severe ethical problem in academic and scientific research that compromises the integrity and legitimacy of scholarly work. Plagiarism in research has become more common as the digital age has made information more accessible, which has led to the creation and broad adoption of plagiarism detection software. To preserve academic integrity, stop unethical behaviour, encourage originality, and promote a transparent culture, this paper explores the importance of plagiarism software in research. In academic and scientific r

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Ramadhana, Muhammad Affan. "Students Versus Plagiarism: How is Online Plagiarism Detection Service Perceived?" Ethical Lingua: Journal of Language Teaching and Literature 3, no. 2 (2016): 89–102. http://dx.doi.org/10.30605/25409190.v3.02.89-102.

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The development of information and communication technology plays a considerable role for students in writing their theses. The positive side, it will help the students to find countless number of academic sources ranging from journal articles to complete theses written by other scholars. On the other hand, it will also create a chance for the students to commit plagiarism easier. Unoriginal writing and plagiarism in this digital era can be detected in the digital way by using plagiarism detection software. This paper elaborates how students understand the concept of plagiarism, how they avoid

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Mohanan, Murali, and Philip Samuel. "Natural Language Processing Approach for UML Class Model Generation from Software Requirement Specifications via SBVR." International Journal on Artificial Intelligence Tools 27, no. 06 (2018): 1850027. http://dx.doi.org/10.1142/s0218213018500276.

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This article has been retracted due to partial plagiarism and the author Murali Mohanan takes full responsibility for the partial plagiarism detected. A notice of retraction is published in Vol. 27 No. 8

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