AI Hybrid Based Plagiarism Detection System Creation

The technological revolution in digital access and information that modern academia is facing today is an undoubtedly enormous enhancement in academic discourse, though at the same time also posing the problem of plagiarism and its threat to academic activity. Due to the increased desire to maintain high levels of scholarly ethics in institutions of higher learning, there is pressure to ensure that mechanisms for the detection of plagiarism are effective. This research paper, in light of this, seeks to explore how institutions of higher learning can improve their plagiarism detection through the use of Artificial Intelligence (AI). This paper commences with a statement of the multi-definition outline of plagiarism in academia, which includes intentional and, likewise, unintentional activities with regard to intellectual dishonesty. At first, traditional detection methods are reviewed by description of how manual examination and rule-based software prove to be inadequate and erroneous in pinpointing plagiarised textual content on the internet. However, the failure of conventional approaches underscores that extraordinary solutions need to be brought in through integrating AI technologies. It will give first an assessment of AI-enabled plagiarism detection systems that are built to use cutting-edge machine learning algorithms in scanning text materials to find traces of originality or lack of it at the highest levels of accuracy and speeds never achieved before.