Il “Digital Maktaba LP”
Proposta di un dataset completo per l'OCR dei titoli di pagina in scrittura araba nel contesto delle biblioteche digitali e degli archivi religiosi
DOI:
https://doi.org/10.60923/issn.2532-8816/22019Parole chiave:
OCR alfabeto arabo, Dataset, Frontespizi, Biblioteche Digitali, Archivi Religiosi, IRCDL2025Abstract
Il riconoscimento ottico dei caratteri (OCR) svolge un ruolo fondamentale nella digitalizzazione e nell'accesso ai documenti storici nelle biblioteche digitali. Tuttavia, le tecnologie OCR spesso incontrano difficoltà nell'interpretare e categorizzare le intricate strutture dei documenti, in particolare nei materiali storici con layout e lingue diverse. Questo studio iniziale affronta il problema proponendo la creazione di un ricco set di dati di pagine di titoli arabi disponibili al pubblico, sfruttando modelli linguistici di visione (VLM) avanzati insieme alle tecniche OCR. Estraendo le prime pagine di ogni documento in alta risoluzione, ci siamo concentrati sull'identificazione accurata dei frontespizi e sulla loro separazione dal testo principale per migliorare l'accuratezza dei metadati e la scoperta dei documenti negli archivi digitali. Il modello Qwen-2vl-72B è stato utilizzato per determinare se ogni pagina è un “frontespizio” o un “non frontespizio” attraverso un prompt personalizzato. I frontespizi rilevati saranno elaborati con l'intelligenza artificiale di Google Vision per generare i dati di Ground Truth, successivamente esaminati da specialisti linguistici prima di finalizzare il set di dati. I piani futuri prevedono l'addestramento di modelli open source come Kraken OCR per valutare l'utilità del set di dati. Questa nuova strategia affronta le attuali lacune del set di dati e aumenta le prestazioni degli archivi digitali, anche in progetti come Digital Maktaba.
Riferimenti bibliografici
Adams, Richard M. 2022. ‘Defining Digital Pedagogy in Theological Libraries’. In Digital Humanities and Libraries and Archives in Religious Studies: An Introduction, edited by Clifford Anderson, 111–22. De Gruyter. https://doi.org/10.1515/9783110536539-008.
Adnan, Kiran, and Rehan Akbar. 2019. ‘Limitations of Information Extraction Methods and Techniques for Heterogeneous Unstructured Big Data’. International Journal of Engineering Business Management 11:1–23. https://doi.org/10.1177/1847979019890771.
Afli, Haithem, Loïc Barrault, and Holger Schwenk. 2016. ‘OCR Error Correction Using Statistical Machine Translation’. Int. J. Comput. Linguistics Appl. 7 (1): 175–91.
Ahmed, Muna, and Ali Abidi. 2019. ‘Review on Optical Character Recognition’. International Research Journal of Engineering and Technology (IRJET) 6 (6): 3666–69.
AIB. Gruppo biblioteche digitali. 2005. ‘Manifesto per le biblioteche digitali’. 2005. https://www.aib.it/aib/cg/gbdigd05a.htm3.
Alayrac, Jean-Baptiste, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, et al. 2022. ‘Flamingo: A Visual Language Model for Few-Shot Learning’. In . https://openreview.net/forum?id=EbMuimAbPbs.
Al-Hashim, Amin G., and Sabri A. Mahmoud. 2010. ‘Printed Arabic Text Database (PATDB) for Research and Benchmarking’. In Proceedings of the 9th WSEAS International Conference on Applications of Computer Engineering, 62–68. ACE’10. Stevens Point, Wisconsin, USA: World Scientific and Engineering Academy and Society (WSEAS).
Al-Kurdī, Muhammad Ṭāhir. 1939. Tārīḫ al-ḫaṭṭ al-ʿarabī wa ’ādābi-hi. 1st ed. Egitto: Maktaba al-hilāl.
Al-Muhtaseb, H. A. 2010. ‘Arabic Text Recognition of Printed Manuscripts : Efficient Recognition of off-Line Printed Arabic Text Using Hidden Markov Models, Bigram Statistical Language Model, and Post-Processing’. Ph.D., University of Bradford. http://hdl.handle.net/10454/4426.
Alsheikh, Idris, and Masnizah Mohd. 2019. ‘A Quranic Dataset for Text Recognition’. In Proceedings of the 1st International Conference on Informatics, Engineering, Science and Technology. Bandung, Indonesia. https://doi.org/10.4108/eai.18-7-2019.2287842.
Alūsī, ʿĀdil al-. 2008. al-ḫaṭṭ al-ʿarabī: naša’tuhu wa taṭwwuruhu. al-Qāhira: Maktaba al-dār al-ʿarabiyya li-l-kitāb.
Amara, Najoua Essoukri Ben, Omar Mazhoud, Noura Bouzrara, and Noureddine Ellouze. 2005. ‘ARABASE: A Relational Database for Arabic OCR Systems.’ Int. Arab J. Inf. Technol. 2 (January):259–66.
Anderson, Clifford, ed. 2022. ‘Introduction’. In Digital Humanities and Libraries and Archives in Religious Studies: An Introduction, 1–10. De Gruyter. https://doi.org/10.1515/9783110536539.
Badry, Mahmoud, Hesham Hassan, Hanaa Bayomi, and Hussien Oakasha. 2018. ‘QTID: Quran Text Image Dataset’. International Journal of Advanced Computer Science and Applications (IJACSA) 9 (3): 385–91. https://doi.org/10.14569/IJACSA.2018.090351.
Bai, Jinze, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou. 2023. ‘Qwen-VL: A Versatile Vision-Language Model for Understanding, Localization, Text Reading, and Beyond’. arXiv. https://doi.org/10.48550/arXiv.2308.12966.
Balāḏurī, ’Aḥmad bin Yaḥyà al-. 1987. Futūḥ al-buldān. Bayrūt: Mu’assasat al-maʿārif.
Bassil, Youssef, and Mohammad Alwani. 2012. ‘OCR Post-Processing Error Correction Algorithm Using Google Online Spelling Suggestion’.
Bataineh, Bilal. 2017. ‘A Printed PAW Image Database of Arabic Language for Document Analysis and Recognition’. Journal of ICT Research and Applications 11 (August):199–211. https://doi.org/10.5614/itbj.ict.res.appl.2017.11.2.6.
Bergamaschi, Sonia, Stefania De Nardis, Riccardo Martoglia, Federico Ruozzi, Luca Sala, Matteo Vanzini, and Riccardo Amerigo Vigliermo. 2022a. ‘Novel Perspectives for the Management of Multilingual and Multialphabetic Heritages through Automatic Knowledge Extraction: The DigitalMaktaba Approach’. Sensors 22 (11): 3995. https://doi.org/10.3390/s22113995.
———. 2022b. ‘Novel Perspectives for the Management of Multilingual and Multialphabetic Heritages through Automatic Knowledge Extraction: The DigitalMaktaba Approach’. Sensors 22 (11): 3995. https://doi.org/10.3390/s22113995.
Bergamaschi, Sonia, Riccardo Martoglia, Federico Ruozzi, Riccardo Amerigo Vigliermo, Stefania De Nardis, Luca Sala, and Matteo Vanzini. 2021. ‘Preserving and Conserving Culture: First Steps towards a Knowledge Extractor and Cataloguer for Multilingual and Multi-Alphabetic Heritages’. In Proceedings of the Conference on Information Technology for Social Good, 301–4. GoodIT ’21. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3462203.3475927.
Bian, Xiaohang, Bo Qin, Xiaozhe Xin, Jianwu Li, Xuefeng Su, and Yanfeng Wang. 2022. ‘Handwritten Mathematical Expression Recognition via Attention Aggregation Based Bi-Directional Mutual Learning’. arXiv. https://doi.org/10.48550/arXiv.2112.03603.
Burdick, Anne, Johanna Drucker, Peter Lunenfeld, Todd Presner, and Jeffrey Schnapp. 2016. Digital_Humanities. MIT Press.
Buzzetti, Dino. 2006. ‘Biblioteche digitali e oggetti digitali complessi: esaustività e funzionalità nella conservazione’. In Archivi informatici per il patrimonio culturale, 114:36. Contributi del centro linceo interdisciplinare ‘Beniamino Segre’. Roma: Bardi Editore.
———. 2023. ‘Towards an Operational Approach to Computational Text Analysis’. In On Making in the Digital Humanities: The Scholarship of Digital Humanities Development in Honour of John Bradley, edited by Julianne Nyhan, Geoffrey Rockwell, Stéfan Sinclair, and Alexandra Ortolja-Baird, First, 179–212. London: UCL Press. https://press.uchicago.edu/ucp/books/book/distributed/O/bo208645506.html.
Chabchoub, Fatma, Yousri Kessentini, Slim Kanoun, and Véronique Eglin. 2016. ‘SmartATID: A Mobile Captured Arabic Text Images Dataset for Multi-Purpose Recognition Tasks’. In Internation Conference in Frontiers on Handwriting Recognition. Internation Conference in Frontiers on Handwriting Recognition. Shenzhen, China. https://hal.archives-ouvertes.fr/hal-01403764.
Chen, Zhe, Jiannan Wu, Wenhai Wang, Weijie Su, Guo Chen, Sen Xing, Muyan Zhong, et al. 2024. ‘InternVL: Scaling up Vision Foundation Models and Aligning for Generic Visual-Linguistic Tasks’. arXiv. https://doi.org/10.48550/arXiv.2312.14238.
Chiron, Guillaume, Antoine Doucet, Mickael Coustaty, Muriel Visani, and Jean-Philippe Moreux. 2017. ‘Impact of OCR Errors on the Use of Digital Libraries: Towards a Better Access to Information’. In 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL), 1–4. https://doi.org/10.1109/JCDL.2017.7991582.
Chtourou, Imen, Ahmed Cheikh Rouhou, Faten Kallel Jaiem, and Slim Kanoun. 2015. ‘ALTID : Arabic/Latin Text Images Database for Recognition Research’. In 2015 13th International Conference on Document Analysis and Recognition (ICDAR), 836–40. IEEE Computer Society. https://doi.org/10.1109/ICDAR.2015.7333879.
Davidson, R., and R. Hopely. 1997. ‘Arabic and Persian OCR Training and Test Data Sets’. In Proc. of Symp. on Document Image Understanding Technology, 303–7.
Ding, Yihao, Siwen Luo, Hyunsuk Chung, and Soyeon Caren Han. 2023. ‘PDF-VQA: A New Dataset for Real-World VQA on PDF Documents’. In Machine Learning and Knowledge Discovery in Databases: Applied Data Science and Demo Track: European Conference, ECML PKDD 2023, Turin, Italy, September 18–22, 2023, Proceedings, Part VI, 585–601. Berlin, Heidelberg: Springer-Verlag. https://doi.org/10.1007/978-3-031-43427-3_35.
Djeddi, Chawki, Abdeljalil Gattal, Labiba Souici-Meslati, Imran Siddiqi, Youcef Chibani, and Haikal El Abed. 2014. ‘LAMIS-MSHD: A Multi-Script Offline Handwriting Database’. In 2014 14th International Conference on Frontiers in Handwriting Recognition, 93–97. https://doi.org/10.1109/ICFHR.2014.23.
Durand, Olivier, Angela Daiana Langone, and Giuliano Mion. 2010. Corso di arabo contemporaneo. Milano: Hoepli.
Escolano Rodríguez, Elena, Adelaida Caro Martín, Judit Fejes, Isabel García-Monge Carretero, Massimo Gentili-Tedeschi, Dorothy McGarry, Rehab Ouf, Ricardo Santos Muñoz, Hollie C. White, and ISBD Review Group. 2022. ‘ISBD International Standard Bibliographic Description : 2021 Update to the 2011 Consolidated Edition’, February. https://repository.ifla.org/handle/123456789/1939.
Experimental HumanitiesLabat theIliffSchoolof Theology. 2022. ‘Library as Interface for Digital Humanities’. In Digital Humanities and Libraries and Archives in Religious Studies: An Introduction, edited by Clifford B. Anderson, 147–64. De Gruyter. https://doi.org/10.1515/9783110536539-010.
Faḍā’ilī, Ḥabīb Allah. 2002. ’aṭlas al-ḫaṭṭ wa al-ḫuṭūṭ. 2nd ed. Dimašq: Maktaba al-ṭalās.
Garbini, Giovanni, and Olivier Durand. 1994. Introduzione alle lingue semitiche. Studi sul Vicino Oriente antico. Paideia.
Ġarīd al-Šayḫ, Muḥammad. 2010. ‘al-Muʿǧam fī al-luġa wa al-naḥw wa al-ṣarf wa al-’iʿrāb wa al-muṣṭalaḥāt al-ʿilmiyya wa al-falsafiyya wa al-qānūniyya wa al-ḥadīṯa’. In . Vol. 5. Bayrūt: Mu’assasa al-nuḫba li-l-ta’līf wa al-tarǧama wa al-našr.
Gemini Team. 2024. ‘Gemini: A Family of Highly Capable Multimodal Models’. arXiv. https://doi.org/10.48550/arXiv.2312.11805.
George, Alain. 2010. The Rise of Islamic Calligraphy. London ; Berkekey; Beirut: Saqi Books.
Gruppo di lavoro sulle biblioteche digitali (GBDIG) and Gruppo di studio sulle tecnologie dell’informazione nelle biblioteche e biblioteche digitali. 2020. ‘Nuovo Manifesto per le biblioteche digitali’. AIB WEB. 2020. https://www.aib.it/documenti/nuovo-manifesto-per-le-biblioteche-digitali/.
Guerrini, Mauro. 2005. Verso nuovi principi e nuovi codici di catalogazione. Edited by Carlo Bianchini. Studi Bibliografici. Milano: Edizioni Sylvestre Bonnard. http://archive.org/details/versonuoviprinci0000guer.
Handelman, Matthew. 2022. ‘A Messianic Theory of Digital Knowledge: On Positivism and Visualizing Rosenzweig’s Archive’. In Digital Humanities and Libraries and Archives in Religious Studies: An Introduction, edited by Clifford B. Anderson, 31–56. De Gruyter. https://doi.org/10.1515/9783110536539-004.
Ibn al-Nadīm, Muḥammad bin ’Isḥāq Abū al-Faraǧ bin ’Abī Yaʿqūb al-Nadīm. 1997. al-Fihrist. Edited by Ibrāhīm Ramaḍān. Bayrūt: Dār al-maʿrifa.
Ibn Durayd, Abu Bakr Muḥmmad bin al-Ḥasan. 1991. al-ištiqāq. Edited by ʿAbd al-Salām Muḥammad Hārūn. Bayrūt: Dār al-Ǧīl.
Ibn ʿAbd Rabbih, Abu ʿUmar Aḥmad. 1983. al-ʿiqd al-farīd. Edited by A.M. Tarḥīnī. Vol. 4. 9 vols. Bayrūt: Dar al-kutub al-ʿilmiyya.
Jaiem, Faten Kallel, Slim Kanoun, Maher Khemakhem, Haikal El Abed, and Jihain Kardoun. 2013. ‘Database for Arabic Printed Text Recognition Research’. In Image Analysis and Processing – ICIAP 2013, edited by Alfredo Petrosino, 251–59. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer. https://doi.org/10.1007/978-3-642-41181-6_26.
Kew, Jhonathan. 2005. ‘Notes on Some Unicode Arabic Characters: Recommendations for Usage’. Draft 2.
Khosrobeygi, Z., H. Veisi, H. R. Ahmadi, and H. Shabanian. 2020. ‘A Rule-Based Post-Processing Approach to Improve Persian OCR Performance’. Scientia Iranica 27 (6): 3019–33. https://doi.org/10.24200/sci.2020.53435.3267.
Kiessling, Benjamin, Gennady Kurin, Matthew Thomas Miller, and Kader Smail. 2021. ‘Advances and Limitations in Open Source Arabic-Script OCR: A Case Study’. Digital Studies / Le Champ Numérique 11 (1). https://doi.org/10.16995/dscn.8094.
Li, Junnan, Dongxu Li, Caiming Xiong, and Steven Hoi. 2022. ‘BLIP: Bootstrapping Language-Image Pre-Training for Unified Vision-Language Understanding and Generation’. arXiv. https://doi.org/10.48550/arXiv.2201.12086.
Li, Zongxia, Xiyang Wu, Hongyang Du, Fuxiao Liu, Huy Nghiem, and Guangyao Shi. 2025. ‘A Survey of State of the Art Large Vision Language Models: Alignment, Benchmark, Evaluations and Challenges’. arXiv. https://doi.org/10.48550/arXiv.2501.02189.
Liu, Haotian, Chunyuan Li, Yuheng Li, and Yong Jae Lee. 2024. ‘Improved Baselines with Visual Instruction Tuning’. arXiv. https://doi.org/10.48550/arXiv.2310.03744.
Liu, Xiaojing, Feiyu Gao, Qiong Zhang, and Huasha Zhao. 2019. ‘Graph Convolution for Multimodal Information Extraction from Visually Rich Documents’. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Industry Papers), edited by Anastassia Loukina, Michelle Morales, and Rohit Kumar, 32–39. Minneapolis, Minnesota: Association for Computational Linguistics. https://doi.org/10.18653/v1/N19-2005.
Luqman, Hamzah, Sabri A. Mahmoud, and Sameh Awaida. 2014. ‘KAFD Arabic Font Database’. Pattern Recognition 47 (6): 2231–40. https://doi.org/10.1016/j.patcog.2013.12.012.
Martínek, Jiří, Ladislav Lenc, and Pavel Král. 2020. ‘Building an Efficient OCR System for Historical Documents with Little Training Data’. Neural Computing and Applications 32 (23): 17209–27. https://doi.org/10.1007/s00521-020-04910-x.
Martoglia, Riccardo, Sonia Bergamaschi, Federico Ruozzi, Matteo Vanzini, Luca Sala, and Riccardo Amerigo Vigliermo. 2023. ‘Knowledge Extraction, Management and Long-Term Preservation of Non-Latin Cultural Heritages - Digital Maktaba Project Presentation’. In Proceedings of the 19th Conference on Information and Research Science Connecting to Digital and Library Science, edited by Bardi Alessia, Falcon Alex, Ferilli Stefano, Marchesin Stefano, and Redavid Domenico, 3365:153–61. CEUR Workshop Proceedings. Bari, Italy: CEUR. https://ceur-ws.org/Vol-3365/#short11.
Martoglia, Riccardo, Luca Sala, Matteo Vanzini, and Riccardo Amerigo Vigliermo. 2022a. ‘A Tool for Semiautomatic Cataloguing of an Islamic Digital Library: A Use Case from the Digital Maktaba Project’. In Proceedings of the Third Conference on Digital Curation Technologies (Qurator 2022), Berlin, Germany, Sept. 19th-23rd, 2022, edited by Adrian Paschke, Georg Rehm, Clemens Neudecker, and Lydia Pintscher. Vol. 3234. CEUR Workshop Proceedings. CEUR-WS.org. https://ceur-ws.org/Vol-3234/paper1.pdf.
———. 2022b. ‘A Tool for Semiautomatic Cataloguing of an Islamic Digital Library: A Use Case from the Digital Maktaba Project’. In Proceedings of the Third Conference on Digital Curation Technologies (Qurator 2022), Berlin, Germany, Sept. 19th-23rd, 2022, edited by Adrian Paschke, Georg Rehm, Clemens Neudecker, and Lydia Pintscher. Vol. 3234. CEUR Workshop Proceedings. CEUR-WS.org. https://ceur-ws.org/Vol-3234/paper1.pdf.
Morriello, Rossana. 2020. ‘Birth and Development of Data Librarianship’. Jlis.it 11:1–15. https://doi.org/10.4403/jlis.it-12653.
Naso, Paolo. 2014. ‘Rapporto sull’analfabetismo religioso in Italia’. In I costi sociali dell’analfabetismo religioso, edited by Alberto Melloni, 43–57. Bologna: Il Mulino.
Naz, Saeeda, Arif Iqbal Umar, Syed H. Shirazi, Saeed B. Ahmed, Muhammad I. Razzak, and Imran Siddiqi. 2015. ‘Segmentation Techniques for Recognition of Arabic-like Scripts: A Comprehensive Survey’. Education and Information Technologies, Springer Journal of Education and Information Technologies, 21 (5): 1–20. https://doi.org/10.1007/s10639-015-9377-5.
Nguyen, Kim-Anh Laura. 2024. ‘Document Understanding with Deep Learning Techniques. Document and Text Processing.’ Sorbonne Université, 2024. https://theses.hal.science/tel-04626992/file/140733_NGUYEN_2024_archivage.pdf.
Nguyen, Thi Tuyet Hai, Adam Jatowt, Mickael Coustaty, and Antoine Doucet. 2021. ‘Survey of Post-OCR Processing Approaches’. ACM Computing Surveys 54 (6): 1–37. https://doi.org/10.1145/3453476.
OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, et al. 2024. ‘GPT-4 Technical Report’. arXiv. https://doi.org/10.48550/arXiv.2303.08774.
Qalqašandī, Abu al-ʿAbbās ’Aḥmad al-. 1913. Ṣubḥ al-’aʿšà. Vol. 3. 15 vols. al-Qāhira: al-Maṭbaʿa al-’amīriyya.
Radford, Alec, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, et al. 2021. ‘Learning Transferable Visual Models From Natural Language Supervision’. arXiv. https://doi.org/10.48550/arXiv.2103.00020.
Roncaglia, Gino. 2023. L’architetto e l’oracolo: Forme Digitali Del Sapere Da Wikipedia a ChatGPT. Bari, Italy: Editori Laterza.
Russell, John E., and Merinda Kaye Hensley. 2017. ‘Beyond Buttonology: Digital Humanities, Digital Pedagogy, and the ACRL Framework’. College & Research Libraries News 78 (11). https://doi.org/10.5860/crln.78.11.588.
Saddami, Khairun, Khairul Munadi, and Fitri Arnia. 2015. ‘A Database of Printed Jawi Character Image’. 2015 Third International Conference on Image Information Processing (ICIIP), December, 56–59. https://doi.org/10.1109/ICIIP.2015.7414740.
Safadi, Yasin Hamid. 1978. Islamic Calligraphy. Thames and Hudson.
Schimmel, Annemarie, and Barbara Rivolta. 1992. Islamic Calligraphy. Brill Archive.
Schwartz, Christine. 2022. ‘Using XQuery and XSLT to Build an Aggregation of Metadata Records for Religious Texts and Non-Print Items’. In Digital Humanities and Libraries and Archives in Religious Studies: An Introduction, edited by Clifford B. Anderson, 95–108. De Gruyter. https://doi.org/10.1515/9783110536539-007.
Slimane, Fouad, Rolf Ingold, Slim Kanoun, Adel Alimi, and Jean Hennebert. 2009. ‘A New Arabic Printed Text Image Database and Evaluation Protocols’. In 10th International Conference on Document Analysis and Recognition, 946–50. Barcelona, Spain. https://doi.org/10.1109/ICDAR.2009.155.
Smith, David A., Jacob Murel, Jonathan Parkes Allen, and Matthew Thomas Miller. 2023. ‘Automatic Collation for Diversifying Corpora: Commonly Copied Texts as Distant Supervision for Handwritten Text Recognition’. In Proceedings of the Computational Humanities Research Conference 2023, edited by Artjoms Šeļa, Fotis Jannidis, and Iza Romanowska, 3558:206–21. CEUR Workshop Proceedings. Paris, France: CEUR. https://ceur-ws.org/Vol-3558/#paper1708.
Smith, David, and Ryan Cordell. 2018. ‘A Research Agenda for Historical and Multilingual Optical Character Recognition - DRS’. 2018. https://repository.library.northeastern.edu/files/neu:f1881m035.
Stokes, Peter, Benjamin Kiessling, Daniel Stökl Ben Ezra, R. Tissot, and E.H. Gargem. 2021. ‘The EScriptorium VRE for Manuscript Cultures’. Edited by Claire Clivaz and Garrick V. Allen. Classics@ Journal, Ancient Manuscripts and Virtual Research Environments 18.
Sturgeon, Donald. 2021. ‘Chinese Text Project: A Dynamic Digital Library of Premodern Chinese’. Digital Scholarship in the Humanities 36 (Supplement_1): 101–12. https://doi.org/10.1093/llc/fqz046.
Ṣubḥī Murād, Ḥassān. 2003. Tārīḫ al-ḫaṭṭ al-ʿarabī: bayna al-māḍī wa-l-ḥāḍir. Benghazi, Libia: al-dār al-ǧamāhīriyya li-l-na wa al-tawzīʿwa al-’iʿlān.
Sullutrone, Giovanni, Riccardo Amerigo Vigliermo, Luca Sala, and Sonia Bergamaschi. 2024. ‘Sensitive Topics Retrieval in Digital Libraries: A Case Study of Ḥadīṯ Collections’. In Linking Theory and Practice of Digital Libraries, edited by Apostolos Antonacopoulos, Annika Hinze, Benjamin Piwowarski, Mickaël Coustaty, Giorgio Maria Di Nunzio, Francesco Gelati, and Nicholas Vanderschantz, 51–62. Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-72440-4_5.
Tang, Jingqun, Chunhui Lin, Zhen Zhao, Shu Wei, Binghong Wu, Qi Liu, Hao Feng, et al. 2024. ‘TextSquare: Scaling up Text-Centric Visual Instruction Tuning’. arXiv. https://doi.org/10.48550/arXiv.2404.12803.
Thaller, Manfred. 1989. ‘The Need for a Theory of Historical Computing’. In History and Computing II, edited by P. Denley, S. Folgevik, and C. Harvey, 2–11. Manchester.
Vigliermo, Riccardo Amerigo, Giovanni Sullutrone, Sonia Bergamaschi, and Luca Sala. 2025. ‘Proposing a Comprehensive Dataset for Arabic Script OCR in the Context of Digital Libraries and Religious Archives (Extended Abstract)’. In Proceedings of the 21st Conference on Information and Research Science Connecting to Digital and Library Science, edited by Marcella Cornia, Giorgio Maria Di Nunzio, Donatella Firmani, Stefano Mizzaro, Giuseppe Serra, Sara Tonelli, and Alessandro Tremamunno. Vol. 3937. CEUR Workshop Proceedings. Udine, Italy: CEUR. https://ceur-ws.org/Vol-3937/#short5.
Wang, Hao, Qingxuan Wang, Yue Li, Changqing Wang, Chenhui Chu, and Rui Wang. 2023. ‘DocTrack: A Visually-Rich Document Dataset Really Aligned with Human Eye Movement for Machine Reading’. arXiv. https://doi.org/10.48550/arXiv.2310.14802.
Wang, Peng, Shuai Bai, Sinan Tan, Shijie Wang, Zhihao Fan, Jinze Bai, Keqin Chen, et al. 2024. ‘Qwen2-VL: Enhancing Vision-Language Model’s Perception of the World at Any Resolution’. arXiv. https://doi.org/10.48550/arXiv.2409.12191.
Xu, Derong, Wei Chen, Wenjun Peng, Chao Zhang, Tong Xu, Xiangyu Zhao, Xian Wu, Yefeng Zheng, and Enhong Chen. 2023. ‘Large Language Models for Generative Information Extraction: A Survey’. arXiv. https://doi.org/10.48550/arXiv.2312.17617.
Yousfi, Sonia, Sid-Ahmed Berrani, and Christophe Garcia. 2015. ‘ALIF: A Dataset for Arabic Embedded Text Recognition in TV Broadcast’. In , 1221–25. IEEE Computer Society. https://doi.org/10.1109/ICDAR.2015.7333958.
Zayene, Oussama, Jean Hennebert, Sameh Masmoudi Touj, Rolf Ingold, and Najoua Essoukri Ben Amara. 2015. ‘A Dataset for Arabic Text Detection, Tracking and Recognition in News Videos- AcTiV’. In 2015 13th International Conference on Document Analysis and Recognition (ICDAR), 996–1000. https://doi.org/10.1109/ICDAR.2015.7333911.
Zayene, Oussama, Sameh Masmoudi Touj, Jean Hennebert, Rolf Ingold, and Najoua Essoukri Ben Amara. 2018. ‘Open Datasets and Tools for Arabic Text Detection and Recognition in News Video Frames’. Journal of Imaging 4 (2): 32. https://doi.org/10.3390/jimaging4020032.
ʿAfīfī, F.S. 1980. Našāt wa taṭawwur al-kitāba al-ḫaṭṭiyya al-ʿarabiyya wa dawri-ha al-ṯaqāfī wa al-iǧtimāʿī. al-Kuwayt: Wikāla al-maṭbūʿāt.
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Copyright (c) 2026 Riccardo Amerigo Vigliermo, Giovanni Sullutrone, Sonia Bergamaschi, Luca Sala
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