Can AI help me identify repetitive content in articles?

Yes, AI technology effectively identifies repetitive content within articles. This capability is well-established and feasible using natural language processing techniques. Key mechanisms include lexical analysis to detect identical phrasing and semantic analysis to identify reworded but functionally similar text chunks. Necessary conditions involve providing the AI with clean, machine-readable text input. The approach applies to plagiarism detection, self-plagiarism checks, and enhancing writing conciseness. Precautions include understanding that similarity thresholds require contextual interpretation and that specialized jargon or field conventions may necessitate tailored detection models. AI-generated results should be used as an aid alongside expert human review. AI repetition identification offers significant application value. Its primary functions involve automating plagiarism scanning within academic integrity processes and assisting authors in refining draft manuscripts by highlighting redundant expressions during the proofreading phase. This significantly boosts efficiency in reviewing large document volumes and contributes to clearer, more impactful scholarly communication, though it does not replace critical authorial or editorial judgment.