A Framework for Plagiarism Detection in Arabic Documents

2022

In academia, plagiarism is certainly not an emerging concern, but it became of a greater magnitude with the popularisation of the Internet and the ease of access to a worldwide source of content, rendering human-only intervention insufficient. Despite that, plagiarism is far from being an unaddressed problem, as computer-assisted plagiarism detection is currently an active area of research that falls within the field of Information Retrieval (IR) and Natural Language Processing (NLP). Many software solutions emerged to help fulfil this task, and this paper presents an overview of plagiarism detection systems for use in Arabic, French, and English academic and educational settings. The comparison was held between eight systems and was performed with respect to their features, usability, technical aspects, as well as their performance in detecting three levels of obfuscation from different sources: verbatim, paraphrase, and cross-language plagiarism. An indepth examination of technica...

Plagiarism has become an infamous problem in the global academic community. Detecting plagiarism in Arabic documents is particularly a challenging task due to the complexity of the structure of the language. This paper introduces a framework and methods for detection of plagiarism in Arabic documents, which is based on a logical representation of a document as paragraphs, sentences, and words.

A corpus is a collection of documents. It is a valuable resource in linguistics research to perform statistical analysis and testing hypothesis for different linguistic rules. An annotated corpus consists of documents or entities annotated with some task related labels such as part of speech tags, sentiment etc One such task is plagiarism detection that seeks to identify if a given document is plagiarized or not. This paper describes our efforts to build a plagiarism detection corpus for Arabic. The corpus consists of about 350 plagiarized – source document pairs and more than 250 documents where no plagiarism was found. The plagiarized documents consists of students submitted assignments. For each of the plagiarized documents, the source document was located from the Web and downloaded for further investigation. We report corpus statistics including number of documents, number of sentences and number of tokens for each of the plagiarized and source categories.

Cybernetics and Information Technologies

Measuring the amount of shared information between two documents is a key to address a number of Natural Language Processing (NLP) challenges such as Information Retrieval (IR), Semantic Textual Similarity (STS), Sentiment Analysis (SA) and Plagiarism Detection (PD). In this paper, we report a plagiarism detection system based on two layers of assessment: 1) Fingerprinting which simply compares the documents fingerprints to detect the verbatim reproduction; 2) Word embedding which uses the semantic and syntactic properties of words to detect much more complicated reproductions. Moreover, Word Alignment (WA), Inverse Document Frequency (IDF) and Part-of-Speech (POS) weighting are applied on the examined documents to support the identification of words that are most descriptive in each textual unit. In the present work, we focused on Arabic documents and we evaluated the performance of the system on a data-set of holding three types of plagiarism: 1) Simple reproduction (copy and past...

2014

The present paper introduces the first corpus for the evaluation of Arabic intrinsic plagiarism detection. The corpus consists of 1024 artificial suspicious documents in which 2833 plagiarism cases have been inserted automatically from source documents.

With the hug of the information on WWW and digital libraries, Plagiarism became one of the most important issues for universities, schools and researcher's fields. While there are many systems for detecting plagiarism in Arabic language documents, the complexity of writing Arabic documents make such scheme a big challenge. On the other hand, although search engines such as Google can be utilized, there would be boring efforts to copy some sentences and paste them into the search engine to find similar resources. For that reason, developing Arabic plagiarism detection tool accelerate the process since plagiarism can be detected and highlighted automatically, and one only needs to submit the document to the system. This paper presents an effective web-enabled system for Arabic plagiarism detection called APDS, which can be integrated with e-learning systems to judge students' assignments, papers and dissertations. The experimental results are provided to evaluate APDS regarding the precision and recall ratios. The result shows that the average percentage of the precision is 82% and the average percentage of the recall is 92.5%.

Kurdistan Journal for Applied Research

Plagiarism is generally defined as literary theft and academic dishonesty. This considered as the serious issue in an academic documents and texts. There are numerous of plagiarism detection techniques have been developed for various natural languages, mainly English. In this paper we investigate and review the plagiarism detection techniques and algorithms which have been developed for Arabic Script Languages (ASL), and providing a literature review of the utilized methods in terms of techniques and outcomes. The result of this paper will help the researchers who are going to commence their development and extend their researches in ASL like Arabic, Persian, Urdu, and Kurdish.

The present paper introduces the first corpus for the evaluation of Arabic intrinsic plagiarism detection. The corpus consists of 1024 artificial suspicious documents in which 2833 plagiarism cases have been inserted automatically from source documents.

2nd Spanish Conference on Information Retrieval (CERI 2012), 2012

This paper presents a preliminary study on intrinsic plagiarism detection in Arabic textual documents. A set of experiments were conducted to gain an insight into the effect of some well-known language-independent stylistic features on Arabic text discrimination. We used Stylysis tool to measure these features on our small-sized corpus.

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. With the hug of the information on WWW and digital libraries, Plagiarism became one of the most important issues for universities, schools and researcher's fields. It is so easy through the internet and due to using advanced search engine to find documents or journals by students. 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.