AI trends in digital humanities research

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George Pavlidis*

Abstract

Recent advances in specialised equipment and computational methods had a significant impact in the Humanities and, particularly, cultural heritage and archaeology research. Nowadays, digital technology applications contribute in a daily basis to the recording, preservation, research and dissemination of cultural heritage. Digitisation is the defining practice that bridges science and technology with the Humanities, either in the tangible or in the intangible forms. The digital replicas support a wide range of studies and the opening of new horizons in the Humanities research. Furthermore, advances in artificial intelligence methods and their successful application in core technical domains opened up new possibilities to support Humanities research in particularly demanding and challenging tasks. This paper focuses on the forthcoming future of intelligent applications in archaeology and cultural heritage, by reviewing recent developments ranging from deep and reinforcement learning approaches to recommendation technologies in the extended reality domain.

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Pavlidis, G. (2022). AI trends in digital humanities research. Trends in Computer Science and Information Technology, 7(2), 026–034. https://doi.org/10.17352/tcsit.000048
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Copyright (c) 2022 Pavlidis G.

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Nilsson NJ. Artificial intelligence: a new synthesis. Morgan Kaufmann, San Francisco, USA, isbn 1998; 978-1558604674 edition.

Poole D, Mackworth A, Goebel R. Computational Intelligence: A Logical Approach. Oxford University, 4th edition, 2006; isbn 978-0195685725 edition.

Luger GF. Artificial intelligence: structures and strategies for complex problem solving. Pearson Addison-Wesley, USA, 6th edition, isbn 2008; 978-0321545893 edition.

Goodfellow I, Bengio Y, Courville A. Deep learning. MIT press, Massachusetts, USA, isbn 978-0262035613 edition 2016.

Poole DL, Mackworth AK. Artificial Intelligence: Foundations of Computational Agents. Cambridge University Press, Cambridge, United Kingdom, 2nd edition. 2017; isbn 978-1107195394 edition.

Russell S, Norvig P. Artificial Intelligence: A Modern Approach. Pearson, global edition. 2021; 4th edition. isbn 978-1292401133 edition.

Pavlidis G, Koutsoudis A, Arnaoutoglou F, Tsioukas V, Chamzas C. Methods for 3d digitization of cultural heritage. Journal of cultural heritage, 2007; 8(1):93– 98.

Rakitina, E., Rakitin, I., Staleva, V., Arnaoutoglou, F., Koutsoudis, A., and Pavlidis, G. (2008). An overview of 3d laser scanning technology. In proceedings of the international scientific conference, pages 83–92. Citeseer.

Chamzas C, Koutsoudis A, Pavlidis G, Tsiafakis D. Applying 3d digitisation technologies in the cultural heritage domain. In Proceedings: International Symposium on “Information and Communication Technologies in Cultural Heritage”, 2008; 35. Earthlab.

Pavlidis G and Royo S. 3d depth sensing. In Digital Techniques for Documenting and Preserving Cultural Heritage, 2018; 195–198. ARC, Amsterdam University Press.

Hawkins T, Cohen J, Debevec P. A photometric approach to digitizing cultural artifacts. In Proceedings of the 2001 conference on Virtual reality, archeology, and cultural heritage, 2001; 333–342. ACM.

Marbs A. Experiences with laser scanning at i3mainz. In Proceedings of the CIPA WG6 International Workshop on Scanning for Cultural Heritage. 2002.

Vlachos D. Principles and methods of topographic recording. Lecture notes (in Greek). 1998

Patias P. Photogrammetric survey and documentation of architectural monuments and archaeological sites. Lecture notes (in Greek). Lecture notes on the Postgraduate Program of Studies entitled ”Systems of Cultural Goods and Management of the Cultural Heritage” of the University of Crete 1999.

Tziavos I, Spatalas S. Urban design applications and topographic surveys. Lecture notes (in Greek). Aristotle University of Thessaloniki. 2004.

Pavlidis G, Tsirliganis N, Tsiafakis D, Arnaoutoglou F, Chamzas C. 3d digitization of monuments: the case of mani. In 3rd International Conference of Museology, Mytilene, Greece. 2006.

Daniil M. Topography topographic mapping of space. Lecture notes (in Greek). Democritus University of Thrace 2009.

Godin G, Rioux M, Beraldin JA, Levoy M, Cournoyer L, Blais F. An assessment of laser range measurement on marble surfaces. In 5th Conference on optical 3D measurement techniques. 2001; 3: 49–56.

Bordoni L, Ardissono L, Barcel´o JA, Chella A, de Gemmis M, Gena C, Iaquinta L, Lops P, Mele F, Musto C, et al. The contribution of ai to enhance understanding of cultural heritage. Intelligenza Artificiale. 2013; 7(2):101–112.

Khalfaoui S, Aigueperse A, Seulin R, Fougerolle Y and Fofi D. Fully automatic 3d digitization of unknown objects using progressive data bounding box. In Three-Dimensional Image Processing (3DIP) and Applications II, 2012; 8290, 829011. International Society for Optics and Photonics.

Khalfaoui S, Seulin R, Fougerolle Y and Fofi D. An efficient method for fully automatic 3d digitization of unknown objects. Computers in Industry. 2013; 64(9):1152– 1160.

Menna F, Nocerino E, Morabito D, Farella E, Perini M, Remondino F. An open source low-cost automatic system for image-based 3d digitization. The International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, 2017; 42:155.

Tausch R, Domajnko M, Ritz M, Knuth M, Santos P, Fellner D. Towards 3d digitization in the glam (galleries, libraries, archives, and museums) sector: Lessons learned and future outlook. IPSI BgD Transactions on Internet Research (TIR). 2020; 16(1):1–9.

González-Merino R, Sánchez-López E, Romero PE, Rodero J, Hidalgo-Fernández RE. Low-Cost Prototype to Automate the 3D Digitization of Pieces: An Application Example and Comparison. Sensors (Basel). 2021 Apr 7;21(8):2580. doi: 10.3390/s21082580. PMID: 33916989; PMCID: PMC8067622.

Tsirliganis N, Pavlidis G, Koutsoudis A, Papadopoulou D, Tsompanopoulos A, Stavroglou K, Loukou Z, Chamzas C. Archiving 3d cultural objects with surface point-wise database information. In Proceedings. First International Symposium on 3D Data Processing Visualization and Transmission. 2002; 766–769. IEEE.

Arnaoutoglou F, Evagelidis V, Pavlidis G, Tsirliganis N, Chamzas C. 3d-gis: New ways in digitization and visualization of cultural objects. In Workshop on the Digitization of Cultural Content. 2003; 27, 28.

Tsirliganis N, Pavlidis G, Koutsoudis A, Papadopoulou D, Tsompanopoulos A, Stavroglou K, Loukou Z, Chamzas C. Archiving cultural objects in the 21st century. Journal of Cultural Heritage. 2014; 5(4):379–384.

Stratis JA, Makarona C, Lazidou D, S´anchez EG, Koutsoudis A, Pamplona M, Pauswein R, Pavlidis G, Simon S, Tsirliganis N. Enhancing the examination workflow for byzantine icons: Implementation of information technology tools in a traditional context. Journal of Cultural Heritage. 2014; 15(1):85–91.

Sabbioni C, Cassar M, Brimblecombe P, Lefevre RA. Vulnerability of cultural heritage to climate change. Technical report, EUR-OPA major hazards agreement, Council of Europe.

Sesana E, Gagnon AS, Bertolin C, Hughes J. Adapting cultural heritage to climate change risks: perspectives of cultural heritage experts in europe. Geosciences. 2018; 8(8):305.

Change C. The future of our pasts: Engaging cultural heritage in climate action outline of climate change and cultural heritage 2019.

Nousias S, Arvanitis G, Lalos AS, Pavlidis G, Koulamas C, Kalogeras A and Moustakas K. A saliency aware cnn-based 3d model simplification and compression framework for remote inspection of heritage sites. IEEE Access, 2020; 8:169982– 170001.

Levy TE, Smith NG, Najjar M, DeFanti TA, Kuester F, Lin AYM. Cyber-archaeology in the holy land. California Institute for Telecommunications and Information Technology (Calit2), UC San Diego: La Jolla, CA, USA. 2012.

Terras, M. and Robertson, P. (2005). Image and interpretation using artificial intelligence to read ancient roman texts. Human IT, 7(3):1–56.

Hamdany AHS, Al-Nima RRO, Albak LH. Translating cuneiform symbols using artificial neural network. Telkomnika, 2021; 19(2):438–443.

Assael Y, Sommerschield T, Prag J. Restoring ancient text using deep learning: a case study on greek epigraphy. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019; 6368–6375. Association for Computational Linguistics.

Fetaya E, Lifshitz Y, Aaron E, Gordin S. Restoration of fragmentary Babylonian texts using recurrent neural networks. Proc Natl Acad Sci U S A. 2020 Sep 15;117(37):22743-22751. doi: 10.1073/pnas.2003794117. Epub 2020 Sep 1. PMID: 32873650; PMCID: PMC7502733.

Balla A, Pavlogeorgatos G, Tsiafakis D, Pavlidis G. Predicting macedonian tombs’ locations using gis, predictive modeling and fuzzy logic. In 40th Annual Conference of Computer Applications and Quantitative Methods in Archaeology (CAA) 2012. University of Southampton, CAA International.

Balla A, Pavlogeorgatos G, Tsiafakis D, Pavlidis G. Modelling archaeological and geospatial information for burial site prediction, identification and management. International journal of heritage in the digital era, 2013; 2(4):585–609.

Balla A, Pavlogeorgatos G, Tsiafakis D, Pavlidis G. Locating macedonian tombs using predictive modelling. Journal of cultural heritage. 2013a; 14(5):403–410.

Koutsoudis A, Pavlidis G, Arnaoutoglou F, Tsiafakis D and Chamzas C. A 3d pottery database for benchmarking content based retrieval mechanisms. In Eurographics 2008 Workshop on 3D Object Retrieval (Chersonesos, Crete 2008.

Koutsoudis A, Pavlidis G, Arnaoutoglou F, Tsiafakis D, Chamzas C. Qp: A tool for generating 3d models of ancient greek pottery. Journal of Cultural Heritage, 2009; 10(2):281–295.

Koutsoudis A, Pavlidis G and Chamzas C. Detecting shape similarities in 3d pottery repositories. In 2010 IEEE Fourth International Conference on Semantic Computing. 2010; 548–552. IEEE.

Koutsoudis A, Pavlidis G, Liami V, Tsiafakis D and Chamzas C. 3d pottery content-based retrieval based on pose normalisation and segmentation. Journal of Cultural Heritage. 2010b; 11(3):329–338.

Bogacz B and Mara H. From extraction to spotting for cuneiform script analysis. In 2018 13th IAPR International Workshop on Document Analysis Systems (DAS). 2018; 199–204. IEEE.

Sevetlidis V, Pavlidis G. Hierarchical classification for improved compound identification in raman spectroscopy. In 3rd Computer Applications and Quantitative Methods in Archaeology (CAA-GR) Conference, 2018.

Sevetlidis, V. and Pavlidis, G. Effective raman spectra identification with treebased methods. Journal of Cultural Heritage. 2019; 37:121–128.

Ioannakis G, Arnaoutoglou F, Koutsoudis A, Pavlidis G, Chamzas C. Curvmaps: A novel feature for 3d model classification. In 2018 International Conference on Intelligent Systems (IS), 2018; 242–248. IEEE.

Davoudi H, Fiorucci M and Traviglia A. Ancient document layout analysis: Autoencoders meet sparse coding. In 2020 25th International Conference on Pattern Recognition (ICPR). 2021; 5936–5942. IEEE.

Elgammal A, Kang Y, Den Leeuw M Picasso, matisse, or a fake? automated analysis of drawings at the stroke level for attribution and authentication. In Thirty-second AAAI conference on artificial intelligence 2018.

Mai CH, Nakatsu R, Tosa N, Kusumi T, Koyamada K. Learning of art style using ai and its evaluation based on psychological experiments. In International Conference on Entertainment Computing, 2020; 308–316. Springer.

Arampatzakis V, Sevetlidis V, Arnaoutoglou F, Kalogeras A, Koulamas C, Lalos A, Kiourt, C, Ioannakis G, Koutsoudis A, Pavlidis G. Art3mis: Raybased textual annotation on 3d cultural objects. In CAA 2021, Limassol, Cyprus. Cyprus University of Technology.

Koutsoudis A, Makarona C, Pavlidis G. Content-based navigation within virtual museums. Journal of Advanced Computer Science and Technology. 2012; 1(2):73–81.

Knabb KA, Schulze JP, Kuester F, DeFanti TA, Levy TE. Scientific visualization, 3d immersive virtual reality environments, and archaeology in jordan and the near east. Near Eastern Archaeology. 2014; 77(3):228–232.

Levy TE, Smith C, Agcaoili K, Kannan A, Goren A, Schulze JP, Yago G. At-risk world heritage and virtual reality visualization for cyber-archaeology: The mar saba test case. In Forte, M. and Murteira, H., editors, Digital Cities: Between History and Archaeology, chapter 7, 2020; 151–171. Oxford University Press.

Kiourt C, Koutsoudis A and Pavlidis G. Dynamus: A fully dynamic 3d virtual museum framework. Journal of Cultural Heritage, 2016; 22: 984-991.

Kiourt C, Pavlidis G, Koutsoudis A and Kalles D. Realistic simulation of cultural heritage. International Journal of Computational Methods in Heritage Science (IJCMHS). 2017b; 1(1):10–40.

Kiourt C, Pavlidis G, Koutsoudis A, Kalles D. Multi-agents based virtual environments for cultural heritage. In 2017 XXVI International Conference on Information. Communication and Automation Technologies (ICAT). 2017; 1–6. IEEE.

Pavlidis G. Recommender systems, cultural heritage applications, and the way forward. Journal of Cultural Heritage. 2019; 35:183–196.

Kiourt C, Koutsoudis A and Kalles D. Enhanced virtual reality experience in personalised virtual museums. International Journal of Computational Methods in Heritage Science (IJCMHS), 2018; 2(1):23–39.

Pavlidis G, Markantonatou S, Donig S and Koumpis A. Ten challenges for digital humanities and the way forward. International Journal of Computational Methods in Heritage Science (IJCMHS), 2018; 2(1):1–7.

Pavlidis G. Apollo-a hybrid recommender for museums and cultural tourism. In 2018 International Conference on Intelligent Systems (IS), 2018a; 94–101. IEEE.

Pavlidis G. Towards a novel user satisfaction modelling for museum visit recommender systems. In International Conference on VR Technologies in Cultural Heritage, 2018b; 60–75. Springer.

Pavlidis GP. On the end-to-end development of a cultural tourism recommender. International Journal of Computational Methods in Heritage Science (IJCMHS). 2019; 3(2):73–90.

Sidiropoulos G, Kiourt C, Sevetlidis V, Pavlidis G. Shaping the behavior of reinforcement learning agents. In 25th Pan-Hellenic Conference on Informatics, Volos, Greece. 2021

Pistofidis P, Ioannakis G, Arnaoutoglou F, Michailidou N, Karta M, Kiourt C, Pavlidis G, Mouroutsos SG, Tsiafaki D, Koutsoudis A. Composing smart museum exhibit specifications for the visually impaired. Journal of Cultural Heritage. 2021; 52:1–10.

Markantonatou S, Donig S, Pavlidis G, Gees T and Koumpis A. Ten challenges for digital humanities and the way forward: Revisited from the social context. In Applying Innovative Technologies in Heritage Science. 2020; 297–305. IGI Global.