Plagiarism means taking another person's work and not giving any credit to
them for it. Plagiarism is one of the most serious problems in academia and
among researchers. Even though there are multiple tools available to detect
plagiarism in a document but most of them are domain-specific and designed to
work in English texts, but plagiarism is not limited to a single language only.
Bengali is the most widely spoken language of Bangladesh and the second most
spoken language in India with 300 million native speakers and 37 million
second-language speakers. Plagiarism detection requires a large corpus for
comparison. Bengali Literature has a history of 1300 years. Hence most Bengali
Literature books are not yet digitalized properly. As there was no such corpus
present for our purpose so we have collected Bengali Literature books from the
National Digital Library of India and with a comprehensive methodology
extracted texts from it and constructed our corpus. Our experimental results
find out average accuracy between 72.10 % - 79.89 % in text extraction using
OCR. Levenshtein Distance algorithm is used for determining Plagiarism. We have
built a web application for end-user and successfully tested it for Plagiarism
detection in Bengali texts. In future, we aim to construct a corpus with more
books for more accurate detection.

通过 OCR 技术和 Levenshtein Distance 算法，我们构建了一个能够成功检测孟加拉文文本抄袭的网络应用，并利用国家数字图书馆的文献构建了一个文本语料库以提高准确性。