Abstract
Plagiarism is a significant issue, especially among students, in the education field, where the internet has made a vast amount of information easily accessible. Although numerous plagiarism detection tools are available for English text, detecting plagiarism in low-resource languages such as Hindi remains a challenge. This study proposes a novel case-based approach to evaluate the effectiveness of various plagiarism detection tools on Hindi documents. The proposed approach maps similarities between Hindi documents at the word, phrase, and sentence levels, and generates diverse cases using stopword removal and stemming pre-processing techniques. The study calculates the similarity score between the original Hindi document and its paraphrased version at the word, sentence, and document levels. The results show that the proposed approach outperforms existing plagiarism detection tools for Hindi text, indicating its potential to enhance academic integrity and prevent plagiarism.