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Cross-language Plagiarism Detection (CLPD) is used to automatically identify and extract plagiarism among documents in different languages. The main challenge of cross-language plagiarism detection is the difference of text languages, where the original source can be analyzed and translated. This book proposes an Arabic-English cross-language plagiarism detection method by automatically detect the semantic relatedness between the words of two suspect targeted files. The proposed method consists of six phases: The first phase is a pre-processing phase, The second involves keyphrase extraction and translation, The third phase retrieves the candidate document that match with the key phrase of the proposed plagiarism text. The fourth phase is a similarity measurement between the key phrases by measuring the similarity between the original text and plagiarism text, The fifth phase is the classification process using Linear Logistic Regression (LLR) approach and the last phase is an evaluation phase using Precision, Recall and F-measure on dataset consisting of Wikipedia articles. The experimental implementation was down with C# language and achieved excellent results.
Über den Autor / die Autorin
Dr. Mohammed Hasan is a lecturer in university of Kufa. He got his bachelor in Computer Science from Almamon University College in 2001 then he got his master Degree in computer science from raqi Commission for Computers and Informatics in 2006 and he got his PhD in Computer Science from National University of Malaysia in 2015.
