Detecting Plagiarism in Arabic E-Learning Using Text Mining

Abstract

Being a growing problem, plagiarism is generally defined as a “literary theft” and an “academic dishonesty” in the literature, and it is really has to be well-informed on this topic to prevent the problem and stick to the ethical principles. Due to the hug of digital libraries and the information on World Wide Web, Plagiarism became a very important problem for researcher’s fields, schools and universities. Students can easily use web search engine to find journals or documents. So plagiarism is a global problem, which occurs in many different areas of our life. It is pivotal to mention here that detecting plagiarism is a challenging task. On the other hand, electronic learning systems in countries with native language Arab require specified technology for plagiarism detection in documents written in Arabic language. Although Google and all search engines can be easy utilized, there will be very tedious efforts to copy a few words or sentences and paste them into the browser of the search engine to find resources of similar. For this reason, developing a tool for detecting plagiarism in Arabic electronic learning systems ease and speed up the process because plagiarism can be easily detected and automatically highlighted by just submitting the Arabic document to the system. Therefore, this paper propose An effective web-enabled system for Arabic plagiarism detection Using Text mining, ZPLAG, that can be integrated with electronic learning systems to judge students’ assignments, papers and dissertations, And presents its experimental results.