A fingerprinting structure model for Arabic document plagiarism detection | [ARPN Journal of Engineering and Applied Sciences • 2024]

Author(s):

1. Yahya Ali Adelrahman Ali: College of Computer Science, Najran University, Kingdom of Saudi Arabia,KSA

Abstract:

Plagiarism, which is a significant problem in the academic world worldwide, is particularly challenging to detect in Arabic due to the language's complex structure. Methodology: The ADPDM model and framework for detecting plagiarism in Arabic documents are presented in this dissertation. It is designed to detect plagiarism within academic contexts. By organizing documents logically into paragraphs, sentences, and words, the model seeks to establish a robust system that can identify duplicated content and search for similar documents within identifying corresponding sets. In particular, the study examines preprocessing techniques such as stop word removal, stemming, and rootage processing, followed by content-based methods utilizing fingerprinting and heuristic algorithms that are tailored to Arabic language features. To aid in efficient detection, the BKDR hash function is used for chunk having. To optimize computation time, heuristic algorithms are implemented at different levels of document representation, using metrics such as Longest Common Substring (LCS). To evaluate the ADPDM system, a corpus of 100 documents is utilized, which includes datasets from AraPlagDet and the Decision Support System (DSS). The performance of ADPDM is compared with other plagiarism detection methods using WCopyFind, but the latter has a higher computational speed than ADBDM. Its recall, precision, and F-measure values of 0. 78035, 0. 994264, and 0. 865688 respectively (ADPDM) are particularly notable for its ability to detect plagiarized content in Arabic documents. ADPDM is a successful anti-pluralist solution for Arabic text, even though it requires a longer processing time than WCopyFind.

Page(s): 1140-1151

DOI: DOI not available

Published: Journal: ARPN Journal of Engineering and Applied Sciences, Volume: 19, Issue: 17, Year: 2024

Keywords:

Arabic Language , Similarity , fingerprinting , Recall , preprocessing plagiarism detection , hashvalue precision , Fmeasure

References:

[1] Khan N.,Agrawal C.,Nishat Ansari T. .2018 .A Review of Various Plagiarism Detection Systems Based on Exterior and Interior Methods. IJARCCE. 7, : 6-12.

[2] Chidera Ugo,Nwokonkwo Obi .2020 .Plagiarism Detection Systems. International Journal of Scientific and Research Publications (IJSRP), 10 : .

[3] Abdelrahman Y. A.,Khalid A.,Osman and I. M. .2017 .A Method for Arabic Documents Plagiarism Detection. International Journal of Computer Science and Information Security, 4(6) : 34-38.

[4] Abdelrahman Y. A.,Khalid A.,Osman and I. M. .2015 .A Survey of Plagiarism Etection for Arabic Documents. International Journal Of Advanced Computer Technology, 4(6) : 34-38.

[5] Al Muna,Sallal Muna,Iqbal Rahat,Chang Victor .2017 .An integrated approach for intrinsic plagiarism detection. Future Generation Computer Systems, 11 : 700-712.

[6] Boulieris P.,Pavlopoulos J.,Xenos A. .2023 .Fraud detection with natural language processing. Mach 06354-5, : .

[7] El Moatez Billah Nagoudi Didier,Schwab Didier,Online ISSN .2018 .Statement-based fuzzy-set versus fingerprints matching for plagiarism detection in Arabic documents, cybernetics. -0011, 18(1) : 1314-9702.

[8] Abakush Intisar,E-Business Related Intisar,- Intisar .2020 .Methods and Tools for Plagiarism Detection in Arabic Documents. , 12 : .

[9] Hoad T. C.,Zobel J. .2003 .Methods for identifying versioned and plagiarized documents. Journal of the American Society for Information Science and Technology, 54(3) : 203-215.

[10] .2020 .. , 12 : .

[11] Nahas M. N. .2017 .Survey and Comparison between Plagiarism Detection Tools. Mahmoud Nadim Nahas. Survey and Comparison between Plagiarism Detection Tools. American Journal of Data Mining and Knowledge Discovery, 20170202(2) : 50-53.

[12] El Moatez Billah Nagoudi,Didier Schwab .2018 .A Two-Level Plagiarism Detection System for Arabic Documents. Cybernetics and Information Technologies, 18 : .

[13] Satija M. P.,Martínez-Ávila D. .2019 .Plagiarism: An essay in terminology. DESIDOC: Journal of, : .

[14] AlSallal M.,Iqbal R.,Palade V.,Amin S.,Chang V. .2017 .An integrated approach for intrinsic plagiarism detection. Future Generation Computer Systems, 11 : 700-712.

[15] Khoja S. .2016 .. , : .

[16] Al-Thwaib E.,Hammo B. H.,Yagi S. .2020 .1. Int J Educ Technol High Educ, 17 : .

[17] Linda Smith .2023 .An Annual Review of Information Science and Technology (ARIST) paper. Journal of the Association for Information Science and Technology, 10 : .

[18] Mehdi Abdelhamid,Azouaou Faiçal .2021 .A Survey of Plagiarism Detection Systems: Case of Use with English, French and Arabic Languages. , 62 : 30.

[19] Hamed Arabi,Akbari Mehdi .2022 .Improving plagiarism detection in a text document using hybrid weighted similarity. Expert Systems with Applications, 207 : 4174.

[20] Alruqi T. N.,Alzahrani S. M. .2023 .Evaluation of an Arabic Chatbot Based on Extractive QuestionAnswering Transfer Learning and Language Transformers. AI, 4 : 0609-691.

[21] El Amine,Hadi Amine,Erritali Mohamed .2019 .A new semantic similarity approach for improving the results of an Arabic search engine. , 04 : 1170-1175.

[22] Farah Khaled,Al-Tamimi Mohammed Khaled .2021 .Plagiarism Detection Methods. , : .

[23] Imtiaz Khan .2019 .Towards Building an Arabic Plagiarism Detection System: Plagiarism Detection in Arabic. , 9(3) : 12-22.

[24] Al-Thwaib E.,Hammo B. H.,Yagi S. .2020 .An academic Arabic corpus for plagiarism detection: design, construction, and experimentation. Int. J Educ Technol High Educ, 17 : .

[25] Gharavi E.,Veisi H.,Rosso P. .2020 .Scalable and Language-Independent Embedding-based Approach for Plagiarism Detection Considering Obfuscation Type: No Training Phase. Neural Computing and Applications, 32(14) : 10593-10607.

[26] Kamal Jambi,Mansour Jambi .2022 .Evaluation of Different Plagiarism Detection Methods: A Fuzzy MCDM Perspective. Applied Sciences, 12(9) : 4580.

[27] Foltýnek T.,Meuschke N.,Gipp B. .2019 .Association for Computing Machinery. In ACM Computing Surveys, 52(6) : .

[28] Mahmoud Zaher .2020 .Unsupervised Model for Detecting Plagiarism in Internet-based Handwritten Arabic Documents. J. Organ. End User Comput, 32(2) : 42-66.

[29] Pratomo A.,Irawan A.,Risa M. .2020 .Similarity detection design using Winnowing Algorithm as an effort to apply green computing. Journal of Physics: Conference Series, 1450 : 1742.

[30] Shrestha Shiva,Abinay Bhandari .2023 .Winnowing Algorithm: A Powerful Tool for Identifying Plagiarism in Assignments. Journal of Trends in Computer Science and Smart Technology, 2 : 006-189.

[31] Zhou Y.,Deng Y.,Chen X.,Xie J. .2014 .Algorithms and Architectures for Parallel Processing. ICA3PP 2014. Lecture Notes in Computer Science, 8631 : 11.

[32] Hussein A. S.,D. A. S. .2015 .A Plagiarism Detection System for Arabic Documents. Intelligent Systems'2014. Advances in Intelligent Systems and Computing, 323 : 47.

[33] Foltýnek T.,Dlabolová D.,Anohina-Naumeca A.,Razı S.,Kravjar J.,Kamzola L.,Guerrero-Dib J.,Çelik Ö,Weber-Wulff D. .2020 .Testing of support tools for plagiarism detection. International Journal of Educational Technology in Higher Education, 17(1) : 46.

[34] Elhoseny Mohamed .2017 .FPSS: Fingerprint-based semantic similarity detection in big data environment. Shehab Abdulaziz and Hassanien Aboul Ella, 379 : 384.

[35] Selemani A.,Chawinga W. D.,Dube G. .2018 .Why do postgraduate students commit plagiarism? An empirical study. International Journal for Educational Integrity, 14(1) : .

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