A Novel Natural Language Processing Based Model for Plagiarism Detection

In order to detect plagiarism in academic and professional contexts, this work presents an intelligent Natural Language Processing (NLP) method. The program outperforms conventional exact match algorithms by utilizing sophisticated NLP techniques, robust preprocessing and semantic analysis. It employs AHP, examines linguistic complexity, and identifies paraphrasing. Inspired by previous research, the strategy examines multi-word phrases and how frequently they are used to gain a more in-depth understanding. We contrast reputable and suspicious studies, assigning varying weights to different areas. Our comprehensive analysis demonstrates that the program performs admirably across a range of topic areas, improving plagiarism detection and maintaining the integrity of academic papers.