{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,10]],"date-time":"2026-06-10T16:12:14Z","timestamp":1781107934660,"version":"3.54.1"},"reference-count":39,"publisher":"IGI Global Scientific Publishing","issue":"2","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"am","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/3.0\/deed.en_US"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<p>Due to the rapid increase of internet-based data, there is urgent need for a robust intelligent documents security mechanism. Although there are many attempts to build a plagiarism detection system in natural language documents, the unlimited variation and different writing styles of each character in Arabic documents make building such systems challenging. Based on its position in a word, the same Arabic letter can be written three different ways, which makes the handwritten character recognition a cumbersome process. This article proposes an intelligent unsupervised model to detect plagiarism in these documents called ASTAP. First, a handwritten Arabic character recognition system is proposed using the Grey Wolf Optimization (GWO) algorithm. Then, a modified Abstract Syntax Tree (AST) is used to match the contents of the Arabic documents to detect any similarity. Compared to the state-of-the-art methods, ASTAP improves the effectiveness of the plagiarism detection in terms of the matched similarity ratio, the precision ratio, and the processing time.<\/p>","DOI":"10.4018\/joeuc.2020040103","type":"journal-article","created":{"date-parts":[[2019,12,27]],"date-time":"2019-12-27T13:25:21Z","timestamp":1577453121000},"page":"42-66","source":"Crossref","is-referenced-by-count":33,"title":["Unsupervised Model for Detecting Plagiarism in Internet-based Handwritten Arabic Documents"],"prefix":"10.4018","volume":"32","author":[{"given":"Mahmoud","family":"Zaher","sequence":"first","affiliation":[{"name":"Faculty of Computers and Information, Mansoura University, Mansoura, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Abdulaziz","family":"Shehab","sequence":"additional","affiliation":[{"name":"Faculty of Computers and Information, Mansoura University, Mansoura, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohamed","family":"Elhoseny","sequence":"additional","affiliation":[{"name":"Faculty of Computers and Information, Mansoura University, Mansoura, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Farahat Farag","family":"Farahat","sequence":"additional","affiliation":[{"name":"Sadat Academy, Cairo, Egypt"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"2432","reference":[{"issue":"6","key":"JOEUC.2020040103-0","first-page":"34","article-title":"A survey of plagiarism detection for Arabic documents","volume":"4","author":"Y.Abdelrahman","year":"2014","journal-title":"International Journal of Advancements in Computing Technology"},{"key":"JOEUC.2020040103-1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2015.07.048"},{"issue":"2","key":"JOEUC.2020040103-2","first-page":"124","article-title":"A Fuzzy-based approach to programming language independent source-code plagiarism detection","volume":"14","author":"G.Acampora","year":"2015","journal-title":"Journal of Digital Information Management"},{"key":"JOEUC.2020040103-3","unstructured":"Ahtiainen, A., Surakka, S., & Rahikainen, M. 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