Plagiarism checker for Persian (PCP) texts using hash-based tree representative fingerprinting

Abstract

With due respect to the authors' rights, plagiarism detection is one of the critical problems in the field of text-mining, in which many researchers are interested. This issue has been considered as a serious one in high academic institutions. There exist language-free tools that do not yield any reliable results since the special features of every language are ignored in them. Considering the paucity of works in the field of Persian language due to the lack of reliable plagiarism checkers in Persian, there is a need for a method to improve the accuracy of detecting plagiarized Persian phrases. An attempt is made in this work to present the PCP solution. This solution is a combinational method, in which, in addition to the meaning and stem of words, synonyms and pluralization are dealt with by applying the document tree representation based on manner fingerprinting the text in the 3-grams words. The grams obtained are eliminated from the text, hashed through the BKDR hash function, and stored as the fingerprint of a document in fingerprints of the reference document repositories in order to check the suspicious documents. The proposed PCP method here is evaluated by eight experiments on seven different sets, which include the suspicions documents and the reference document from the Hamshahri newspaper website. The results obtained indicate that the accuracy of this proposed method in detecting similar texts, in comparison with the "Winnowing" localized method, has a 21.15% average improvement. The accuracy of the PCP method in detecting the similarities, in comparison with the language-free tool, reveals a 31.65% average improvement.