Enhancing Academic Integrity: Plagiarism Detection with Machine Learning

This project presents an advanced machine learning-based system designed to empower students to uphold academic integrity and foster originality in their research endeavours. Seamlessly integrated into the research process, the system enables students to input project information, utilizing a sophisticated algorithm and vast academic dataset to compute a matching percentage, facilitating the assessment of work uniqueness. Beyond mere plagiarism detection, the tool serves as an educational resource, promoting self-awareness and improvement among students. It encourages responsible research practices, offers comprehensive reports, and personalized recommendations, and integrates with existing learning management systems for accessibility. Addressing evolving research methodologies, promoting interdisciplinary exploration, and maintaining adaptability to shifting trends, the system significantly contributes to academic integrity preservation and originality cultivation. Key Words: academic integrity, originality, machine learning, plagiarism detection, educational resources, research methodologies.