Using CBR techniques to detect plagiarism in computing assignments

Abstract

The problems of case retrieval in CBR and plagiarism detection have in common a need to detect close but not exact matches between exemplars. In this paper we describe a plagiarism detection system that has been inspired by ideas from CBR research. In particular this system can detect similarities between programs without performing exhaustive comparisons on all exemplars. Our analysis of similarity in this well controlled domain offers some insights into the kinds of profiles that can be used in similarity assessment in general. We argue that the choice of a perspicuous profile is crucial to any classification task and determining the best predictive features may require significant analysis of the problem domain.