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Home / Archives / Volume-5 / Issue-3 / Article-1

Volume - 5 | Issue - 3 | september 2023

Winnowing vs Extended-Winnowing: A Comparative Analysis of Plagiarism Detection Algorithms
Shiva Shrestha  , Sushan Shakya, Sandeep Gautam
Pages: 213-232
Cite this article
Shrestha, S., Shakya, S. & Gautam, S. (2023). Winnowing vs Extended-Winnowing: A Comparative Analysis of Plagiarism Detection Algorithms. Journal of Trends in Computer Science and Smart Technology, 5(3), 213-232. doi:10.36548/jtcsst.2023.3.001
Published
05 July, 2023
Abstract

Plagiarism is the main problem in the digital world, as people use others’ content without giving prior credit to the creator. Therefore, there should be proper and efficient algorithms to find plagiarized content on the Internet. This research proposes two algorithms: the winnowing algorithm and the extended winnowing algorithm. The winnowing algorithm can only calculate the similarity rate between documents, whereas the extended algorithm can mark the plagiarized text segment in the compared records along with their similarity rates. The similarity rate in both algorithms has been calculated using the Jaccard Coefficient. Although the extended algorithm is beneficial as it provides a text marking feature, it consumes more computation power, which is discussed in this study. There are research works done previously using this approach, but none has compared the algorithms’ performance on small texts. Thus, this research utilizes the Twitter form of data to test these algorithms’ performance, as it contains a maximum of 280 characters. The application proposed to detect plagiarism in tweets has been developed using Python as the backend and React as the front-end technology.

Keywords

Winnowing Algorithm Extended Winnowing Algorithm Jaccard Coefficient Twitter Python React

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