Design of an Efficient AI-Based Plagiarism Detection System for Academic Publications: A Case Study of Usmanu Danfodiyo University, Sokoto (Wamako LGA, Sokoto State)
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Background of the Study
Plagiarism has become a critical issue in academic publishing, undermining the integrity of research and scholarly work. With the rise of digital platforms and online content, instances of plagiarism have increased, making it necessary for academic institutions to adopt efficient systems for detecting copied content. Traditional plagiarism detection methods, often manual or relying on basic software, are not always effective in identifying sophisticated forms of plagiarism, such as paraphrasing or the use of non-traditional sources.
Usmanu Danfodiyo University in Sokoto, located in Wamako LGA, Sokoto State, faces growing concerns about plagiarism in academic publications. Although the university has implemented some plagiarism detection tools, these systems have limitations in detecting advanced plagiarism techniques. With the advancements in artificial intelligence (AI) and natural language processing (NLP), there is an opportunity to design a more efficient AI-based plagiarism detection system that can identify subtle forms of plagiarism across various academic works, including journal articles, theses, and research papers.
Statement of the Problem
Despite the increasing number of plagiarism detection tools available, academic institutions like Usmanu Danfodiyo University struggle with accurately detecting various forms of plagiarism, especially more complex and nuanced instances such as text paraphrasing and idea theft. Existing systems lack the sophistication to detect content manipulation effectively, and as a result, academic integrity is compromised. This highlights the need for a more advanced, AI-driven plagiarism detection system.
Objectives of the Study
1. To design an AI-based plagiarism detection system tailored for academic publications at Usmanu Danfodiyo University.
2. To evaluate the effectiveness of the AI-based system in detecting advanced forms of plagiarism, including paraphrasing and content manipulation.
3. To compare the performance of the designed AI-based system with traditional plagiarism detection tools used at the university.
Research Questions
1. How can AI-based techniques be applied to improve the detection of plagiarism in academic publications at Usmanu Danfodiyo University?
2. What are the key features that should be included in an AI-based plagiarism detection system for academic publications?
3. How does the AI-based plagiarism detection system perform in comparison to traditional methods used at Usmanu Danfodiyo University?
Research Hypotheses
1. The AI-based plagiarism detection system will outperform traditional plagiarism detection tools in identifying advanced forms of plagiarism.
2. AI-based systems can effectively detect plagiarism in both direct and paraphrased content in academic publications.
3. The implementation of the AI-based plagiarism detection system will lead to a reduction in academic misconduct at Usmanu Danfodiyo University.
Significance of the Study
This study will provide a solution to the issue of plagiarism in academic publications by offering an advanced, AI-powered system that can detect both simple and complex instances of plagiarism. The findings will help Usmanu Danfodiyo University ensure the integrity of its academic work, fostering a culture of original research and promoting the credibility of the institution’s scholarly output.
Scope and Limitations of the Study
The study will focus on the design and evaluation of an AI-based plagiarism detection system specifically for academic publications at Usmanu Danfodiyo University, located in Wamako LGA, Sokoto State. The research will not address plagiarism in other contexts, such as student assignments or content outside of the academic domain. The study will be limited to plagiarism detection in English-language academic publications.
Definitions of Terms
• Artificial Intelligence (AI): The simulation of human intelligence processes by machines, including learning, reasoning, and self-correction.
• Plagiarism Detection: The process of identifying instances of plagiarism or unacknowledged copying in academic works.
• Paraphrasing: Rewriting someone else’s ideas or content in one’s own words without proper attribution, often used to disguise plagiarism.
• Natural Language Processing (NLP): A field of AI that focuses on the interaction between computers and human language, particularly in understanding and processing textual data.
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