Detecting plagiarism using Latent Semantic Analysis and Cosine Similarity Approach

Abstract

The act of using someone else’s words and/or ideas and passing them off as your own is known as plagiarism. The act of presenting one’s own thoughts or works as those of another person. Plagiarism, that point, is the willful taking of another person’s thoughts, words, or works. Finding instances of plagiarism and/or copyright violations in a work or document is what a plagiarism tool achieves. We are developing an Offline Plagiarism Tool to avoid plagiarism. This research employs latent semantic analysis and cosine similarity to compare the papers' similarity. must steer clear of any accidental or purposeful plagiarism. To arrange tasks by employing these tools to obtain the similarity score to ensure that the text is truly approved by the organizations and to prevent errors in paraphrase. Two strategies have been built to determine the similarity score of documents based on word matching and semantic meaning.This tool additionally shows to the user the percentage of plagiarism in their document and the necessity for changes in an eye-catching graphical format. This procedure will undoubtedly assist in determining whether or not content has been duplicated, and user-generated datasets have been gathered for this purpose. It aids in improving the ability to organize and paraphrase text as well as to show different graphs so that the user can quickly comprehend the outcomes.

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