Graph-based Approach to Text Alignment for Plagiarism Detection in Persian Documents

This paper presents a new approach for Persian plagiarism detection. This approach uses a graph structure as well as one of the graph similarity methods (iterative methods) for similarity detection of two Persian documents. In this approach, documents are represented by a graph with specified length, then each part of suspicious document is compared to that of the source document. The graph is made if these parts have more common bigrams than a predefined threshold. Once graphs are made, an iterative method is used to find analogous nodes in graphs. Two graphs are marked as similar if they contain at least a certain number of similar nodes. In order to evaluate the proposed method, it was run on PAN2015 and PAN2016 Persian Text Alignment dataset. The Plagdet score is defined to evaluate plagiarism detection methods in PAN contest. The gained Plagdet of proposed method is 90% on PAN2015 and 87% on PAN2016. CCS Concepts • Information systems➝ Plagiarism Detection software • Computing methodologies➝ Graph-based