An Automatic Rule Based Neuro-Fuzzy Plagiarism Detection System

Moumita Ghosh*, Ranadhir Ghosh**, John Yearwood***
*_**_***School of Information Technology and Mathematical Sciences, University of Ballarat, Australia.
Periodicity:November - January'2006
DOI : https://doi.org/10.26634/jfet.1.2.960

Abstract

In this paper, we propose and discuss a fully automated system for marking and plagiarism detection for programming assessment using self organizing map (SOM) and fuzzy logic. The plagiarism approach involves finding similarities between programs submitted by students, and rank them depending on their similarity metrics based SOM clustering. The distance from the cluster centroid for individual assignment is calculated using fuzzy technique. The system is a syntax dependant approach for C language and is based on a tree data structure with leafs and attributes that denote the semantic translation of the given program. The system has been tested successfully on real world programming assignments from software development course.

Keywords

Automated Marking, Plagiarism, Fuzzy, SOM, Tree Structure.

How to Cite this Article?

Moumita Ghosh ,Ranadhir Ghosh and John Yearwood (2006). An Automatic Rule Based Neuro-Fuzzy Plagiarism Detection System. i-manager’s Journal on Future Engineering and Technology, 1(2), 61-69. https://doi.org/10.26634/jfet.1.2.960

References

[1]. GITCHELL, G. and TRAN, N. (1999): A Utility for Detecting Similarity in Computer Programs. Proceedings 30th SIGCSE Technical Symposium, New Orleans, LA, USA: 266-270.
[2]. WISE, M. (1992): Detection of Similarities in Student Programs: YAP'ing may be Preferable to Plague'ing. Proceedings. 23rd SCGCSE Technical Symposium, Kanas City, USA: 268-271.
[3]. WISE, M. (1996): YAP3, Improved Detection in Similarities in Computer Program and Other Texts. Proceedings 27th SIGCSE Technical Symposium, Philadelphia, PA, USA: 130-134.
[4]. AUSTIN, M. and BROWN, L. (1999): Internet Plagiarism: Developing Strategies to Curb Student Academic Dishonesty. The Internet and Higher Education 2(1): 21-33, 1999.
[5]. BOYWER, K. W. and HALL, L.O. (1999): Experience using 'MOSS' to Detect Cheating on Programming Assignments, 29th ASEE/IEEE Frontiers in Education Conference, San Juan, Puerto Rico: 18-22.
[6]. BURANEN, L. (1999): But I Wasn't Cheating: Plagiarism & Cross Cultural Mythology. In Perspectives on Plagiarism and Intellectual Property in a Postmodern World, BURANEN, L. and Roy, A. M. editors, State University of New York Press: 63-74.
[7]. CARTER, J. (1999): Collaboration or Plagiarism: What Happens When Students Work Together? Proceedings of ITiCSE : 52-55.
[8]. CLARK, I. L. (1999): Writing Centres and Plagiarism. In Perspectives on Plagiarism and Intellectual Property in a Postmodern World. Buranen, BURANEN, L. and Roy, A. M. editors, State University of New York Press: 155-167.
[9]. DONALDSON, J. L., LANCASTER, A. and SPOSATO, P. H. (1981): A Plagiarism Detection System. Twelfth SIGSCE Technical Symposium, St. Louis, Missouri: 21-25.
[10]. FAIDHI, J. A. W. and ROBINSON S. K. (1987): An Empirical Approach for Detecting Program Similarity and Plagiarism within a University Programming Environment. Computing Education:11-19.
[11]. KOHONEN T. (1995): Self-Organizing Maps. 2nd ed., Springer-Verlag, Berlin.
[12]. GHOSH, M., VERMA, B. and N. Nguyen, (2002): An Automatic Assessment Marking and Plagiarism Detection. ICITA: 274-279.
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