Artificial Method for Building Monolingual Plagiarized Arabic Corpus

Adnen Mahmoud, Mounir Zrigui


Plagiarism in textual documents is a widespread problem seen the large digital repository existing on the web. Moreover, it is difficult to make evaluation and comparison between solutions because of the lack of plagiarized resources in Arabic language publicly available. In this context, this paper describes automatic construction of a paraphrased corpus in order to deal with these issues and conduct our experiments, as follows: First, we collected a large corpus containing more than 12 million sentences from different resources. Then, we cleaned it up unnecessary data by applying a set of preprocessing techniques. After that, we used word2vec algorithm to create a vocabulary from the collected corpus. It extracted efficiently the semantic relationships between words to exploit. Subsequently, we replaced each word of the source corpus with the most similar vocabulary word based on an index used randomly to eventually obtain a suspect corpus. Different experiments are done. Thus, we varied the dimensions of vectors and window sizes to predict the correct context of words and identify the semantically closest words of the target.


Arabic language, automatic creation, data collection, word embedding, paraphrase, plagiarism, semantic analysis

Full Text: PDF