Plagiarism detection using feature-based neural networks

Authors:
Steve Engels;Vivek Lakshmanan;Michelle Craig
Affiliations:
University of Toronto, Toronto, ON, Canada;University of Toronto at Mississauga, Mississauga, ON, Canada;University of Toronto, Toronto, ON, Canada
Venue:
Proceedings of the 38th SIGCSE technical symposium on Computer science education
Year:
2007

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Abstract

This paper focuses on the use of code features for automatic plagiarism detection. Instead of the text-based analyses employed by current plagiarism detectors, we propose a system that is based on properties of assignments that course instructors use to judge the similarity of two submissions. This system uses neural network techniques to create a feature-based plagiarism detector and to measure the relevance of each feature in the assessment. The system was trained and tested on assignments from an introductory computer science course, and produced results that are comparable to the most popular plagiarism detectors.