Plagiarism checker for Persian (PCP) texts using hash-based tree representative fingerprinting | ||
| Journal of AI and Data Mining | ||
| مقاله 1، دوره 4، شماره 2، مهر 2016، صفحه 125-133 اصل مقاله (1.02 M) | ||
| نوع مقاله: Original/Review Paper | ||
| شناسه دیجیتال (DOI): doi: 10.5829/idosi.JAIDM.2016.04.02.01 | ||
| نویسندگان | ||
| Sh. Rafieian* 1؛ A. Baraani dastjerdi2 | ||
| 1Computer Engineering Department, Sheikh Bahaii University, Isfahan, Iran | ||
| 2Computer Engineering Department, University of Isfahan, Isfahan, Iran. | ||
| چکیده | ||
| With due respect to the authors’ rights, plagiarism detection, is one of the critical problems in the field of text-mining that many researchers are interested in. This issue is considered as a serious one in high academic institutions. There exist language-free tools which 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 lack of reliable plagiarism checkers in Persian there is a need for a method to improve the accuracy of detecting plagiarized Persian phrases. Attempt is made in the article to present the PCP solution. This solution is a combinational method that in addition to meaning and stem of words, synonyms and pluralization is dealt with by applying the document tree representation based on manner fingerprinting the text in the 3-grams words. The obtained grams are eliminated from the text, hashed through the BKDR hash function, and stored as the fingerprint of a document in fingerprints of reference documents repository, for checking suspicious documents. The PCP proposed method here is evaluated by eight experiments on seven different sets, which include suspicions document and the reference document, from the Hamshahri newspaper website. The results indicate that accuracy of this proposed method in detection of similar texts in comparison with "Winnowing" localized method has 21.15 percent is improvement average. The accuracy of the PCP method in detecting the similarity in comparison with the language-free tool reveals 31.65 percent improvement average. | ||
| کلیدواژهها | ||
| Text-Mining؛ Natural Language Processing؛ Plagiarism detection؛ External plagiarism detection؛ Persian Language | ||
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