research-article

Arabic question answering system: a survey

Authors:

Tahani H. Alwaneen,

Hatim A. Aboalsamh,

Amir HussainAuthors Info & Claims

Artificial Intelligence Review, Volume 55, Issue 1

Pages 207 - 253

https://doi.org/10.1007/s10462-021-10031-1

Published: 01 January 2022 Publication History

Abstract

Question answering is a subfield of information retrieval. It is a task of answering a question posted in a natural language. A question answering system (QAS) may be considered a good alternative to search engines that return a set of related documents. The QAS system is composed of three main modules; question analysis, passage retrieval, and answer extraction. Over the years, numerous QASs have been presented for use in different languages. However, the the development of Arabic QASs has been slowed by linguistic challenges and the lack of resources and tools available to researchers. In this survey, we start with the challenges due to the language and how these challenges make the development of new Arabic QAS more difficult. Next, we do a detailed review of several Arabic QASs. This is followed by an in-depth analysis of the techniques and approaches in the three modules of a QAS. We present an overview of important and recent tools that were developed to help the researchers in this field. We also cover the available Arabic and multilingual datasets, and a look at the different measures used to assess QASs. Finally, the survey delves into the future direction of Arabic QAS systems based on the current state-of-the-art techniques developed for question answering in other languages.

References

[1]

Abdelali A, Darwish K, Durrani N, Mubarak H (2016) Farasa: a fast and furious segmenter for Arabic. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: Demonstrations, Association for Computational Linguistics. San Diego, California, pp 11–16

[2]

Abdelnasser H, Ragab M, Mohamed R, Mohamed A, Farouk B, El-Makky NM, Torki M (2014) Al-Bayan: an Arabic question answering system for the Holy Quran. In: Proceedings of the EMNLP 2014 workshop on Arabic natural language processing (ANLP), Association for Computational Linguistics. Doha, Qatar, pp 57–64

[3]

Abouenour L, Bouzoubaa K, Rosso P (2008) Improving Q/A using Arabic WordNet. In: International Arab conference on information technology (ACIT’2008)

[4]

Abouenour L, Bouzouba K, and Rosso P An evaluated semantic query expansion and structure-based approach for enhancing Arabic question/answering Int J Inf Commun Technol 2010 3 3 37-51

[5]

Abouenour L, Bouzoubaa K, Rosso P (2012) IDRAAQ: New Arabic question answering system based on query expansion and passage retrieval. In: CLEF, (2012) conference and labs of the evaluation forum. Computer Science, Rome, Italy

[6]

Abouenour L, Bouzoubaa K, and Rosso P On the evaluation and improvement of Arabic WordNet coverage and usability Lang Resour Eval 2013 47 3 891-917

[7]

Ahmed W and Anto B Answer extraction for how and why questions in question answering systems Int J Comput Eng Res 2016 06 18-22

[8]

Ahmed W, Ahmed A, Babu AP (2017a) Web-based Arabic question answering system using machine learning approach. Int J Adv Res Comput Sci 8(1)

[9]

Ahmed W, Babu D, and Anto P Question analysis for Arabic question answering systems Int J Nat Lang Comput 2017 5 6 21-30

[10]

Akour M, Abufardeh SO, Magel K, and Al-Radaideh Q QArabPro: a rule based question answering system for reading comprehension tests in Arabic Am J Appl Sci 2011 8 6 652-661

[11]

Al-Anazi S, AlMahmoud H, and Al-Turaiki I Finding similar documents using different clustering techniques Proc Comput Sci 2016 82 1 28-34

[12]

Al-Chalabi H, Ray S, Shaalan K (2015) Semantic based query expansion for Arabic question answering systems. In: 2015 first international conference on Arabic computational Linguistics (ACLing). IEEE, pp 127–132

[13]

AL-Khawaldeh FT Answer extraction for why Arabic questions answering systems: EWAQ World Comput Sci Inf Technol J 2019 5 5 82-86

[14]

Albarghothi A, Khater F, and Shaalan K Arabic question answering using ontology Proc Comput Sci 2017 117 183-191

[15]

Alkhairy M, Jafri A, Smith DA (2020) Finite state machine pattern-root Arabic morphological generator, analyzer and diacritizer. In: Proceedings of The 12th language resources and evaluation conference. European Language Resources Association, pp 3834–3841

[16]

ALMarwi H, Ghurab M, and Al-Baltah I A hybrid semantic query expansion approach for Arabic information retrieval J Big Data 2020 7 1 39:1-39:19

[17]

Almiman A, Osman N, and Torki M Deep neural network approach for Arabic community question answering Alexandria Eng J 2020 59 6 4427-4434

[18]

Almuzaini HA and Azmi AM Impact of stemming and word embedding on deep learning-based Arabic text categorization IEEE Access 2020 8 127913-127928

[19]

Alsabbagh L, AlDakkak O, Ghneim N (2020) A new passage retrieval method in Arabic question answering systems. https://assets.researchsquare.com/files/rs-119562/v1_stamped.pdf. Accessed 26 April 2021

[20]

Antoun W, Baly F, Hajj H (2020) Arabert: transformer-based model for Arabic language understanding. arXiv preprint arXiv:200300104

[21]

Aouichat A, Guessoum A (2017) Building TALAA-AFAQ, a corpus of Arabic FActoid question-answers for a question answering system. In: International conference on applications of natural language to information systems, pp 380–386

[22]

Artetxe M, Ruder S, Yogatama D (2019) On the cross-lingual transferability of monolingual representations. arXiv preprint arXiv:191011856

[23]

Azmi AM and Aljafari EA Universal web accessibility and the challenge to integrate informal Arabic users: a case study Univ Access Inf Soc 2018 17 1 131-145

[24]

Azmi AM and Almajed RS A survey of automatic Arabic diacritization techniques Nat Lang Eng 2015 21 3 477

[25]

Azmi AM and Alsaiari A A calligraphic based scheme to justify Arabic text improving readability and comprehension Comput Hum Behav 2014 39 177-186

[26]

Azmi AM and Alshenaifi NA Answering Arabic why-questions: baseline vs. RST-based approach ACM Trans Inf Syst (TOIS) 2016 35 1 6:1-6:19

[27]

Azmi AM and Alshenaifi NA LEMAZA: an Arabic why-question answering system Nat Lang Eng 2017 23 6 877-903

[28]

Bakari W, Neji M (2020) A novel semantic and logical-based approach integrating RTE technique in the Arabic question-answering. Int J Speech Technol 1–17

[29]

Bakari W, Trigui O, Neji M (2014) Logic-based approach for improving Arabic question answering. In: 2014 IEEE international conference on computational intelligence and computing research, pp 1–6

[30]

Bakari W, Bellot P, and Neji M AQA-WebCorp: web-based factual questions for Arabic Proc Comput Sci 2016 96 275-284

[31]

Bakari W, Bellot P, Neji M (2016b) Researches and reviews in Arabic question answering: principal approaches and systems with classification. In: International Arab conference on information technology (ACIT ’16)

[32]

Bakari W, Bellot P, and Neji M A logical representation of Arabic questions toward automatic passage extraction from the web Int J Speech Technol 2017 20 2 339-353

[33]

Bdour WN and Gharaibeh NK Development of yes/no Arabic question answering system Int J Artif Intell Appl (IJAIA) 2013 4 1 51-63

[34]

Bekhti S, Al-Harbi M (2013) AQuASys: a question-answering system for Arabic. In: Recent advances in applied computer science and digital services (WSEAS international conference—recent advances in computer engineering series), vol 12, pp 130–139

[35]

Ben-Sghaier M, Bakari W, Neji M (2017) An Arabic question-answering system combining a semantic and logical representation of texts. In: International conference on intelligent systems design and applications, pp 735–744

[36]

Benajiba Y, Rosso P, Benedíruiz JM (2007) Anersys: an Arabic named entity recognition system based on maximum entropy. In: International conference on intelligent text processing and computational Linguistics. Springer, pp 143–153

[37]

Bernstein P (2013) Searchyourcloud survey, it takes up to 8 attempts to find an accurate search result

[38]

Boudchiche M, Mazroui A, Bebah M Ould Abdallahi Ould, Lakhouaja A, and Boudlal A AlKhalil Morpho Sys 2: a robust Arabic morpho-syntactic analyzer J King Saud Univ Comput Inf Sci 2017 29 2 141-146

[39]

Boudlal A, Lakhouaja A, Mazroui A, Meziane A, Bebah M, Shoul M (2010) Alkhalil morpho sys1: a morphosyntactic analysis system for Arabic texts. In: International Arab conference on information technology. Elsevier Science Inc New York, NY, pp 1–6D

[40]

Bounhas I, Soudani N, and Slimani Y Building a morpho-semantic knowledge graph for Arabic information retrieval Inf Process Manag 2019 57 6 102-124

[41]

Brini W, Ellouze M, Mesfar S, Belguith LH (2009) An Arabic question-answering system for factoid questions. In: 2009 international conference on natural language processing and knowledge engineering. IEEE, pp 1–7

[42]

Buckwalter T (2002) Buckwalter Arabic morphological analyzer version 1.0. Linguistic Data Consortium. University of Pennsylvania

[43]

Cambria E, Poria S, Bisio F, Bajpai R, Chaturvedi I (2015) The CLSA model: a novel framework for concept-level sentiment analysis. In: LNCS, vol 9042. Springer, pp 3–22

[44]

Cambria E, Chattopadhyay A, Linn E, Mandal B, and White B Storages are not forever Cogn Comput 2017 9 646-658

[45]

Chui M, Manyika J, Bughin J (2012) The social economy: unlocking value and productivity through social technologies. Technical report, McKinsey Global Institute

[46]

Clark JH, Choi E, Collins M, Garrette D, Kwiatkowski T, Nikolaev V, Palomaki J (2020) TyDi QA: a benchmark for information-seeking question answering in typologically diverse languages. arXiv preprint arXiv:200305002

[47]

Devlin J, Chang MW, Lee K, Toutanova K (2019) BERT: pre-training of deep bidirectional transformers for language understanding. arXiv:1810.04805

[48]

Diab M (2009) Second generation AMIRA tools for Arabic processing: fast and robust tokenization, POS tagging, and base phrase chunking. In: 2nd international conference on Arabic language resources and tools, vol 110, p 198

[49]

El Adlouni Y, Rodríguez H, Meknassi M, El Alaoui SO, and En-nahnahi N A multi-approach to community question answering Expert Syst Appl 2019 137 432-442

[50]

El-Affendi MA, Al-Tayeb M (2014) The SWAM Arabic morphological tagger: multilevel tagging and diacritization using lexicon driven morphotactics and viterbi. In: Proceedings on the international conference on artificial intelligence (ICAI 2014)

[51]

El-Affendi MA, Abuhaimed I, and AlRajhi K A simple Galois Power-of-Two real time embedding scheme for performing Arabic morphology deep learning tasks Egypt Inf J 2020 22 1 35-43

[52]

Etaiwi W and Awajan A Graph-based Arabic text semantic representation Inf Process Manag 2020 57 3 102183

[53]

Ezzeldin AM, Shaheen M (2012) A survey of Arabic question answering: challenges, tasks, approaches, tools, and future trends. In: Proceedings of The 13th international Arab conference on information technology (ACIT 2012), pp 1–8

[54]

Fareed NS, Mousa HM, Elsisi AB (2014) Syntactic open domain Arabic question/answering system for factoid questions. In: The 9th international conference on informatics and systems (INFOS2014). IEEE, pp 1–9

[55]

Gaizauskas RJ, Humphreys K (2000) A combined IR/NLP approach to question answering against large text collections. In: Proceeding of the RIAO’00: content-based multimedia information access, pp 1288–1304

[56]

Ghwanmeh S, Kanaan G, Al-Shalabi R, Rabab’ah S (2009) Enhanced algorithm for extracting the root of Arabic words. In: 2009 sixth international conference on computer graphics, imaging and visualization, pp 388–391

[57]

Guo J, Fan Y, Pang L, Yang L, Ai Q, Zamani H, Wu C, Croft WB, and Cheng X A deep look into neural ranking models for information retrieval Inf Proc Manag 2019 57 6 102067

[58]

Hamed SK and Ab Aziz MJ A question answering system on holy quran translation based on question expansion technique and neural network classification J Comput Sci 2016 12 3 169-177

[59]

Hammo B, Abu-Salem H, Lytinen SL, Evens M (2002) QARAB: a question answering system to support the Arabic language. In: Proceedings of the ACL-02 workshop on computational approaches to semitic languages. Association for Computational Linguistics, pp 1–11

[60]

Hamza A, En-Nahnahi N, Zidani KA, Ouatik SEA (2019) An Arabic question classification method based on new taxonomy and continuous distributed representation of words. J King Saud Univ Comput Inf Sci

[61]

Hamza A, En-Nahnahi N, Ouatik SEA (2020) Exploring contextual word representation for Arabic question classification. In: 2020 1st international conference on innovative research in applied science. Engineering and Technology (IRASET). IEEE, pp 1–5

[62]

Harman D How effective is suffixing? J Am Soc Inf Sci 1991 42 1 7-15

[63]

Ismail WS and Homsi MN DAWQAS: a dataset for Arabic why question answering system Proc Comput Sci 2018 142 123-131

[64]

Joulin A, Grave E, Bojanowski P, Douze M, Jégou H, Mikolov T (2016) Fasttext.zip: compressing text classification models. arXiv preprint arXiv:161203651

[65]

Karpagam K and Saradha A A framework for intelligent question answering system using semantic context-specific document clustering and wordnet Sādhanā 2019 44 3 62

[66]

Khalifi H, Cherif W, El Qadi A, and Ghanou Y Query expansion based on clustering and personalized information retrieval Prog Artif Intell 2019 8 2 241-251

[67]

Khoja S and Garside R Stemming Arabic text 1999 Lancaster Computing Department, Lancaster University

[68]

Kurdi H, Alkhaider S, and Alfaifi N Development and evaluation of a web based question answering system for Arabic language Comput Sci Inf Technol (CS&IT) 2014 4 02 187-202

[69]

Lahbari I, Ouatik S, Zidani KA (2017a) Arabic question classification using machine learning approaches. In: The 18th international Arab conference on information technology (ACIT’2017)

[70]

Lahbari I, Ouatik SEA, Zidani KA (2017b) A rule-based method for Arabic question classification. In: 2017 international conference on wireless networks and mobile communications (WINCOM), pp 1–6

[71]

Lewis P, Oğuz B, Rinott R, Riedel S, Schwenk H (2019) MLQA: evaluating cross-lingual extractive question answering. arXiv preprint arXiv:191007475

[72]

Li X, Roth D (2002) Learning question classifiers. In: COLING 2002: the 19th international conference on computational Linguistics, pp 1–7

[73]

Lo SL, Cambria E, Chiong R, and Cornforth D Multilingual sentiment analysis: from formal to informal and scarce resource languages Artif Intell Rev 2017 48 4 499-527

[74]

Longpre S, Lu Y, Daiber J (2020) MKQA: a linguistically diverse benchmark for multilingual open domain question answering. arXiv:2007.15207

[75]

Malhas R and Elsayed T AyaTEC: building a reusable verse-based test collection for Arabic question answering on the Holy Qur’an ACM Trans Asian Low Resour Lang Inf Process (TALLIP) 2020 19 6 78:1-78:21

[76]

Mann WC and Thompson SA Rhetorical structure theory: toward a functional theory of text organization Text 1988 8 3 243-281

[77]

Marie-Sainte SL, Alalyani N, Alotaibi S, Ghouzali S, and Abunadi I Arabic natural language processing and machine learning-based systems IEEE Access 2018 7 7011-7020

[78]

Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. In: International conference on learning representations (ICLR)

[79]

Monti J and Monti MSJ Formalising natural languages with NooJ 2015 Tyne Cambridge Scholars Publishing

[80]

Mozannar H, Hajal KE, Maamary E, Hajj H (2019) Neural Arabic question answering. In: Proceedings of the 4th Arabic natural language processing workshop. Association for Computational Linguistics, Florence, Italy

[81]

Mustafa M, Eldeen AS, Bani-Ahmad S, Elfaki AO, et al. A comparative survey on Arabic stemming: approaches and challenges Intell Inf Manag 2017 9 02 39-67

[82]

Nabil M, Abdelmegied A, Ayman Y, Fathy A, Khairy G, Yousri M, El-Makky NM, Nagi K (2017) AlQuAnS-an Arabic language question answering system. In: Proceedings of the 9th international joint conference on knowledge engineering and knowledge management, pp 144–154

[83]

Nugaliyadde A, Wong KW, Sohel F, Xie H (2017) Reinforced memory network for question answering. In: International conference on neural information processing. Springer, pp 482–490

[84]

Obeid O, Zalmout N, Khalifa S, Taji D, Oudah M, Alhafni B, Inoue G, Eryani F, Erdmann A, Habash N (2020) CAMeL tools: an open source python toolkit for Arabic natural language processing. In: Proceedings of The 12th language resources and evaluation conference. European Language Resources Association. Marseille, pp 7022–7032

[85]

Othman N, Faiz R, and Smaïli K Enhancing question retrieval in community question answering using word embeddings Proc Comput Sci 2019 159 485-494

[86]

Ouahrani L, Bennouar D (2020) AR-ASAG an Arabic dataset for automatic short answer grading evaluation. In: Proceedings of The 12th conference language resources and evaluation conference (LREC 2020), pp 2634–2643

[87]

Oueslati O, Cambria E, HajHmida MB, and Ounelli H A review of sentiment analysis research in Arabic language Future Gener Comput Syst 2020 112 408-430

[88]

Pasha A, Al-Badrashiny M, Diab MT, El Kholy A, Eskander R, Habash N, Pooleery M, Rambow O, Roth R (2014) Madamira: A fast, comprehensive tool for morphological analysis and disambiguation of Arabic. In: Lrec. European Language Resources Association. Reykjavik, Iceland, vol 14, pp 1094–1101

[89]

Peñas A, Rodrigo A (2011) A simple measure to assess non-response. In: Proceedings of the 49th annual meeting of the association for computational linguistics: human language technologies—volume 1, pp 1415–1424

[90]

Pennington J, Socher R, Manning CD (2014) Glove: global vectors for word representation. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). Association for Computational Linguistics. Doha, Qatar, pp 1532–1543

[91]

Peters ME, Neumann M, Iyyer M, Gardner M, Clark C, Lee K, Zettlemoyer L (2018) Deep contextualized word representations. In: Proceedings of the 2018 conference of the north American chapter of the association for computational linguistics. Association for Computational Linguistics, pp 2227–2237

[92]

Ray SK and Shaalan K A review and future perspectives of Arabic question answering systems IEEE Trans Knowl Data Eng 2016 28 12 3169-3190

[93]

Romeo S, Da San Martino G, Belinkov Y, Barrón-Cedeño A, Eldesouki M, Darwish K, Mubarak H, Glass J, and Moschitti A Language processing and learning models for community question answering in Arabic Inf Process Manag 2019 56 2 274-290

[94]

Roul RK, Sahay SK (2012) An effective web document clustering for information retrieval. arXiv preprint arXiv:12111107

[95]

Saad MK, Ashour WM (2010) OSAC: Open source Arabic corpora. In: 6th international conference on electrical and computer systems. European University of Lefke. Lefke, North Cyprus, vol 10, pp 25–26

[96]

Sadek J and Meziane F A discourse-based approach for Arabic question answering ACM Trans Asian Low Resour Lang Inf Proc (TALLIP) 2016 16 2 1-18

[97]

Samy H, Hassanein EE, and Shaalan K Arabic question answering: a study on challenges, systems, and techniques Int J Comput Appl 2019 181 44 6-14

[98]

Sheker M, Saad S, Abood R, Shakir M (2016) Domain-specific ontology-based approach for Arabic question answering. J Theor Appl Inf Technol 83(1)

[99]

Shrestha P, Jacquin C, Daille B (2012) Clustering short text and its evaluation. In: International conference on intelligent text processing and computational Linguistics. Springer, pp 169–180

[100]

Soares MAC and Parreiras FS A literature review on question answering techniques, paradigms and systems J King Saud Univ Comput Inf Sci 2020 32 6 635-646

[101]

Soliman A (2017) Arabic Q&A dataset. http://xminers.club/2017/07/22/Arabic-qa-dataset/

[102]

Soliman AB, Eissa K, and El-Beltagy SR Aravec: a set of Arabic word embedding models for use in Arabic NLP Proc Comput Sci 2017 117 256-265

[103]

Souteh Y, Bouzoubaa K (2011) SAFAR platform and its morphological layer. In: Proceeding of the eleventh conference on language engineering ESOLEC, pp 14–15

[104]

Taghva K, Elkhoury R, Coombs J (2005) Arabic stemming without a root dictionary. In: Int Conf Inf Technol Coding Comput (ITCC ’05), vol 2, pp 152–157

[105]

Trigui O, Belguith LH, Rosso P (2010) DefArabicQA: Arabic definition question answering system. In: Workshop on language resources and human language technologies for semitic languages, 7th LREC. Valletta, Malta, pp 40–45

[106]

Vilares D, Peng H, Satapathy R, Cambria E (2018) BabelSenticNet: a commonsense reasoning framework for multilingual sentiment analysis. In: IEEE symposium series on computational intelligence (SSCI), pp 1292–1298

[107]

Wong JL (2019) Real world evidence collaboration and convergence for change: big data, digital and tech—and real world applications and implications for industry

[108]

Xiong C, Merity S, Socher R (2016a) Dynamic memory networks for visual and textual question answering. In: International conference on machine learning, pp 2397–2406

[109]

Xiong C, Zhong V, Socher R (2016b) Dynamic coattention networks for question answering. In: International conference on learning representations (ICLR)

[110]

Yu AW, Dohan D, Luong MT, Zhao R, Chen K, Norouzi M, Le QV (2018) QANet: combining local convolution with global self-attention for reading comprehension. arXiv:1804.09541

[111]

Zemirli Z, Elhadj YOM (2012) Morphar+ an Arabic morphosyntactic analyzer. In: Proceedings of the international conference on advances in computing, communications and informatics, pp 816–823

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cover image Artificial Intelligence Review

Artificial Intelligence Review Volume 55, Issue 1

Jan 2022

793 pages

ISSN:0269-2821

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© The Author(s), under exclusive licence to Springer Nature B.V. 2021.

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Kluwer Academic Publishers

United States

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Published: 01 January 2022

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Guo YAi XLiu G(2024)Complex Question Answering Method on Risk Management Knowledge Graph: Multi‐Intent Information Retrieval Based on Knowledge SubgraphsInternational Journal of Intelligent Systems10.1155/2024/29070432024:1Online publication date: 24-Aug-2024
https://doi.org/10.1155/2024/2907043
Wahdan AAl-Emran MShaalan K(2024)A systematic review of Arabic text classification: areas, applications, and future directionsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-023-08384-628:2(1545-1566)Online publication date: 1-Jan-2024
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Hu XHong ZZhang CLiu AMeng SWen LKing IYu P(2023)Reading Broadly to Open Your Mind: Improving Open Relation Extraction With Search Documents Under Self-SupervisionsIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.331713936:5(2026-2040)Online publication date: 19-Sep-2023
https://dl.acm.org/doi/10.1109/TKDE.2023.3317139
AL-Smadi MHammad MAl-Zboon SAL-Tawalbeh SCambria E(2023)Gated recurrent unit with multilingual universal sentence encoder for Arabic aspect-based sentiment analysisKnowledge-Based Systems10.1016/j.knosys.2021.107540261:COnline publication date: 15-Feb-2023
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https://dl.acm.org/doi/10.1007/s11227-023-05224-0
Bensoltane RZaki T(2022)Aspect-based sentiment analysis: an overview in the use of Arabic languageArtificial Intelligence Review10.1007/s10462-022-10215-356:3(2325-2363)Online publication date: 5-Jul-2022
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Nassif AElnagar AElgendy OAfadar Y(2022)Arabic fake news detection based on deep contextualized embedding modelsNeural Computing and Applications10.1007/s00521-022-07206-434:18(16019-16032)Online publication date: 1-Sep-2022
https://dl.acm.org/doi/10.1007/s00521-022-07206-4

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