A coarse-to-fine framework to efficiently thwart plagiarism

Abstract

This paper presents a systematic framework using multilevel matching approach for plagiarism detection (PD). A multilevel structure, i.e. document–paragraph–sentence, is used to represent each document. In document and paragraph level, we use traditional dimensionality reduction technique to project high dimensional histograms into latent semantic space. The Earth Mover’s Distance (EMD), instead of exhaustive matching, is employed to retrieve relevant documents, which enables us to markedly shrink the searching domain. Two PD algorithms are designed and implemented to efficiently flag the suspected plagiarized document sources. We conduct extensive experimental verifications including document retrieval, PD, the study of the effects of parameters, and the empirical study of the system response. The results corroborate that the proposed approach is accurate and computationally efficient for performing PD.