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Sentence-based natural language plagiarism detection
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White, D. R. and Joy, Mike (2004) Sentence-based natural language plagiarism detection. ACM Journal on Educational Resources in Computing, Volume 4 (Number 4). pp. 1-20. Article number 2. doi:10.1145/1086339.1086341
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Official URL: http://dx.doi.org/10.1145/1086339.1086341
Abstract
With the increasing levels of access to higher education in the United Kingdom, larger class sizes make it unrealistic for tutors to be expected to identify instances of peer-to-peer plagiarism by eye and so automated solutions to the problem are required. This document details a novel algorithm for comparison of suspect documents at a sentence level and has been implemented as a component of plagiarism detection software for detecting similarities in both natural language documents and comments within program source-code. The algorithm is capable of detecting sophisticated obfuscation (such as paraphrasing, reordering, merging, and splitting sentences) as well as direct copying. The implemented algorithm has also been used to successfully detect plagiarism on real assignments at the university. The software has been evaluated by comparison with other plagiarism detection tools.
Item Type: | Journal Article | ||||
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Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Journal or Publication Title: | ACM Journal on Educational Resources in Computing | ||||
Publisher: | ACM | ||||
Official Date: | December 2004 | ||||
Dates: |
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Volume: | Volume 4 | ||||
Number: | Number 4 | ||||
Page Range: | pp. 1-20 | ||||
Article Number: | Article number 2 | ||||
DOI: | 10.1145/1086339.1086341 | ||||
Status: | Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Date of first compliant deposit: | 28 July 2016 |
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