Plagiarism is a infraction for world that impacts the quality, readability, and trustworthiness of scholarly publications. Improving researcher awareness of plagiarism of words, ideas, and graphics is essential for avoiding unacceptable writing practices. A lack of creative thinking and poor academic English skills are believed to compound most instances of redundant and “copy-and-paste” writing. Plagiarism detection software largely relies on reporting text similarities. However, manual checks are required to reveal inappropriate referencing, copyright violations, and substandard English writing. Additionally, the paper discusses the assumptions on technology for plagiarism detection and the importance of focuses on a culture of originality and proper practices among students and researchers. The system utilizes text-matching algorithms, natural language processing (NLP), and machine learning techniques to detect various forms of plagiarism, including direct copy-pasting, paraphrasing, synonym replacement, and code plagiarism. For making the project we used languages like Html, CSS, Bootstrap and ReactJS for front-end and JAVA for back end and MySql for data base connectivity.
Plagiarism detection, Academic Integrity, Text similarity Analysis, Plagiarism detection, Plagiarism detection techniques, Textual analysis Algorithm, Plagiarism detection Analysis.
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