Plagiarism Detection in the Digital Era: A Systematic Review of Tools and Techniques

Abstract

The research performs a systematic review of plagiarism, addressing the prevalence and challenges in the digital era. It investigates into the various types of plagiarism and examines various tools and methodologies, encompassing syntactic and semantic level analysis. Prominent plagiarism detection methods, considering both monolingual and cross-lingual contexts, and offers insights into the advancements in machine learning applications are examined. A comprehensive overview of web-based plagiarism detection tools is provided, emphasizing their strengths and limitations. The study points out current issues in plagiarism detection, promoting for continued research activities to refine precision and comprehensiveness within the domain.

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