Showing papers on "Plagiarism detection published in 2001"

Actions Do Speak Louder than Words: Deterring Plagiarism with the Use of Plagiarism-Detection Software

Abstract: Introduction In recent years, the availability of online source material and online papers has increased instructors' concerns regarding plagiarism in the classroom. Many instructors do not realize, however, that the digital revolution has also created a niche for fast and (at least somewhat) reliable plagiarism-detection software.

Towards an error free plagarism detection process

Abstract: For decades many computing departments have deployed systems for the detection of plagiarised student source code submissions. Automated systems to detect free-text student plagiarism are just becoming available and the experience of computing educators is valuable for their successful deployment.This paper describes a Four-Stage Plagiarism Detection Process that attempts to ensure no suspicious similarity is missed and that no student is unfairly accused of plagiarism. Required characteristics of an effective similarity detection engine are proposed and an investigation of a simple engine is described. An innovative prototype tool designed to decrease the workload of tutors investigating undue similarity is also presented.

Visualising intra-corpal plagiarism

Abstract: Describes the VAST (Visualisation and Analysis of Similarity Tool) prototype system, which tutors can use to investigate student submissions for intra-corpal plagiarism. VAST displays a pair of student submissions and a graphical representation of their similarity, allowing tutors to navigate directly to areas of potential plagiarism. It improves on the human-eye approach by identifying similarities which a tutor might otherwise miss, thus saving investigative time. VAST is demonstrated using noise-free synthetic texts and actual student submissions containing intra-corpal plagiarism. Associated ideas, including similarity visualisations, similarity intersections and the "four-stage plagiarism detection process" are also introduced.

Reducing Effects of Plagiarism in Programming Classes

Abstract: Large programming classes are traditionally an area of concern for maintaining the integrity of the educational process. Systematic inspection of all program solutions for evidence of plagiarism can be done using an automated tool. The ``Measure Of Software Similarity'' tool developed by Alex Aiken at the University of California at Berkeley analyzes a set of programs to detect evidence of “duplicates.” However, experience in applying this sort of plagiarism detection in a large programming class indicates that the main long-term effect may be to simply shift the source of plagiarism. This possibility leads to considering the reason for fighting plagiarism and then to exploring additional techniques aimed at reducing the perceived motivation for plagiarism.

Using the MatchDetectReveal System for Comparative Analysis of Texts

Abstract: In this paper we are introducing the MatchDetectReveal system, which is capable of identifying the similarity between documents. Different applications of the system are discussed including cross-referencing multiple editions of literary works, plagiarism detection, organizing collections of documents and comparative analysis of texts. The system uses suffix trees and suffix vectors for comparing documents. These data structures are very fast and powerful, which allows fast comparison of documents. The front-end of the system is fully Web-based, thus users only need to use a Web browser to access the system. The results are also presented as HTML files utilising the hyperlink capabilities of HTML documents.