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Electronic Plagiarism Detection System Architecture: Incorporating Porter Stemmer and K Nearest Neighbors Algorithm
PROCEEDINGS

, , , UNLV, United States

E-Learn: World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, in Las Vegas, Nevada, USA ISBN 978-1-880094-66-2 Publisher: Association for the Advancement of Computing in Education (AACE), San Diego, CA

Abstract

A common problem that all teachers face is the problem of plagiarism. With content on the internet readily available students, an A+ term paper is a Google search. Therefore, teachers must be equipped with tools that can assist them to make sure that students are turning in their own work. This paper investigates the methods of manual detection of plagiarized documents and proposes the rule based references validation process, string frequency analysis with stem porter algorithm, the similarity value calculation and using K nearest neighbors algorithm on the selected relevant documents.

Citation

Rongratana, N., Oh-Young, C. & Levitt, G. (2008). Electronic Plagiarism Detection System Architecture: Incorporating Porter Stemmer and K Nearest Neighbors Algorithm. In C. Bonk, M. Lee & T. Reynolds (Eds.), Proceedings of E-Learn 2008--World Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education (pp. 3886-3890). Las Vegas, Nevada, USA: Association for the Advancement of Computing in Education (AACE). Retrieved July 23, 2019 from .

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