Using Retrieved Sources for Semantic and Lexical Plagiarism Detection

Plagiarism is described as using someone else's ideas or work without their permission. Using lexical and semantic text similarity notions, this paper presents a plagiarism detection system for examining suspicious texts against available sources on the Web. The user can upload files in pdf docx formats. will search three popular engines source (Google, Bing, Yahoo) try to identify top five results each engine first retrieved page. corpus made up of downloaded scraped web page engines' results. documents then be encoded vectors. For detection, leverage Jaccard Term Frequency-Inverse Document Frequency (TFIDF) techniques, while Doc2Vec Sentence Bidirectional Encoder Representations from Transformers (SBERT) intelligent representation models used. Following that, compares text. Finally, generated report show total ratio, ratio source, other details.