Abstract
This study combined VOSviewer and CiteSpace to conduct a knowledge mapping analysis of the Web of Science research record on artificial intelligence exhibition design from 1991–2022. The results show that: (1) international research is more influential in western developed countries; (2) higher education institutions are the main research institutions; (3) international research focuses on environments, augmented reality and virtual-reality; (4) social robotics, deep learning, emotional computing, cultural display and cultural heritage have become international research hotspots in recent years; (5) RAI-ED can be divided into four main categories: #1 Theoretical framework, #2 Optimization design, #3 Application themes and #4 Scientific analysis. In this paper, Citespace and VOSviewer are combined in the research of artificial intelligence exhibition design, which can effectively visualize the existing data and provide reference meaning and research path for similar themes.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Magistretti, S., Dell'Era, C., Messeni Petruzzelli, A.: How intelligent is Watson? enabling digital transformation through artifificial intelligence. Bus. Horizons 62(6), 819–829 (2019)
Goodfellow, I., Bengio, Y., Courville, A.: Deep Learning. MIT Press, Cambridge (2016)
Bishop, C.M. (ed.): Pattern Recognition and Machine Learning. ISS, Springer, New York (2006). https://doi.org/10.1007/978-0-387-45528-0
Kopp, S., Gesellensetter, L., Kramer, N.C., Wachsmuth, I.: A conversational agent as museum guide-Design and evaluation of a real-world application. In: International Workshop on Intelligent Virtual Agents, pp. 329–343. Springer, Berlin (2005). https://doi.org/10.1007/11550617_28
Tu, S.: Analysis on the development trend and application technology of digital museum. In: 1st International Symposium on Innovation and Education, Law and Social Sciences (IELSS 2019), pp. 138–141. Atlantis Press (2019)
Li, H.: Evolutionary features of academic articles co-keyword network and keywords co-occurrence network: based on two-mode affiliation network. Physica A 450, 657–669 (2016)
Sanchez-Lengeling, B., Aspuru-Guzik, A.: Inverse molecular design using machine learning: generative models for matter engineering. Science 361(6400), 360–365 (2018)
Abualigah, L., et al.: The arithmetic optimization algorithm. Comput. Meth. Appl. Mech. Eng. 376, 113609 (2021)
Duffy, B.R.: Anthropomorphism and the social robot. Robot. Auton. Syst. 42(3–4), 177–190 (2003)
Belpaeme, T., et al.: Social robots for education: a review. Sci. Robot. 3(21), eaat5954 (2018)
Hancke, G.P., de Carvalho e Silva, B., Hancke Jr., G.P.: The role of advanced sensing in smart cities. Sensors 13(1), 393–425 (2012)
You, X., Wang, C.X., Huang, J., et al.: Towards 6G wireless communication networks: vision, enabling technologies, and new paradigm shifts. Sci. China Inf. Sci. 64(1), 1–74 (2021)
Coley, C.W., Green, W.H., Jensen, K.F.: Machine learning in computer-aided synthesis planning. Acc. Chem. Res. 51(5), 1281–1289 (2018)
Sadri, F.: Ambient intelligence: a survey. ACM Comput. Surv. (CSUR) 43(4), 1–66 (2011)
Zawacki-Richter, O., Marín, V.I., Bond, M., et al.: Systematic review of research on artificial intelligence applications in higher education- where are the educators? Where are the educators? Int. J. Educ. Technol. High. Educ. 16(1), 1–27 (2019)
Kibria, M.G., Nguyen, K., Villardi, G.P., et al.: Big data analytics, machine learning, and artificial intelligence in next-generation wireless networks. IEEE Access 6, 32328–32338 (2018)
Shiomi, M., Kanda, T., Ishiguro, H., et al.: Interactive humanoid robots for a science museum. In: Proceedings of the 1st ACM SIGCHI/SIGART Conference on Human- Robot Interaction, pp. 305–312 (2006)
Zhang, T., Wang, X., Xu, X., et al.: GCB-Net: graph convolutional broad network and its application in emotion recognition. IEEE Trans. Affect. Comput. 13(1), 379–388 (2019)
Magnisalis, I., Demetriadis, S., Karakostas, A.: Adaptive and intelligent systems for collaborative learning support: a review of the field. IEEE Trans. Learn. Technol. 4(1), 5–20 (2011)
Sharp, M., Ak, R., Hedberg, T., Jr.: A survey of the advancing use and development of machine learning in smart manufacturing. J. Manuf. Syst. 48, 170–179 (2018)
Gao, Z., Zhang, D., Ge, Y.: Design optimization of a spatial six-degree-of-freedom parallel manipulator based on artificial intelligence approaches. Robot. Comput.-Integr. Manuf. 26(2), 180–189 (2010)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Yi, X., Liu, Z. (2023). Research on the Current Situation and Trends of Artificial Intelligence in Exhibition Design. In: Rauterberg, M. (eds) Culture and Computing. HCII 2023. Lecture Notes in Computer Science, vol 14035. Springer, Cham. https://doi.org/10.1007/978-3-031-34732-0_14
Download citation
DOI: https://doi.org/10.1007/978-3-031-34732-0_14
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-34731-3
Online ISBN: 978-3-031-34732-0
eBook Packages: Computer ScienceComputer Science (R0)