A Persian Fuzzy Plagiarism Detection Approach

Plagiarism is one of the common problems that is present in all organizations that deal with electronic content. At present, plagiarism detection tools, only detect word by word or exact copy phrases and paraphrasing is often mixed. One of the successful and applicable methods in paraphrasing detection is fuzzy method. In this study, a new fuzzy approach has been proposed to detect external plagiarism in Persian texts which is called Persian Fuzzy Plagiarism Detection (PFPD). The proposed approach compares paraphrased texts with the aim to recognize text similarities. External plagiarism detection, evaluates through a comparison between query document and a document collection. To avoid un-necessary comparisons this tool employs intelligent technology for comparing, suspicious documents, in different levels hierarchically. This method intends to conformed Fuzzy model to Persian language and improves previous methods to evaluate similarity degree between two sentences. Experiments on three corpora TMC, Irandoc and extracted corpus from prozhe.com, are performed to get confidence on proposed method performance. The obtained results showed that using proposed method in candidate documents retrieval, and in evaluating text similarity, increases the precision, recall and F measurement in comparing with one of the best previous fuzzy methods, respectively 22.41, 17.61, and 18.54 percent on the average.

Keywords:

Text Retrieval , Plagiarism Detection , External Plagiarism Detection , Text Similarity , Fuzzy Similarity Detection