Research on Intelligent Service for Smart Museum Users under Artificial Intelligence
- DOI
- 10.2991/978-2-38476-253-8_16How to use a DOI?
- Keywords
- smart museums; perceived affordance; user intelligent services
- Abstract
With the rapid development of artificial intelligence (AI) technology and the rise of the trend of intelligence, smart museums, as an important place for cultural inheritance and educational exchanges, are faced with the challenge and opportunity of how to use AI technology to enhance the user service experience. Starting from user needs, this study constructs a theoretical framework of perceived affordance in the study of intelligent service for users of smart museums through the theory of perceived affordance in the field of human-computer interaction and the method of rooted theory. According to this framework, suggestions for the optimization of smart museum construction and service based on user demand service are proposed, aiming to provide theoretical reference and practical significance for the development of smart museum user intelligent service under artificial intelligence.
- Copyright
- © 2024 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Anqi Zhou AU - Younghwan Pan PY - 2024 DA - 2024/05/28 TI - Research on Intelligent Service for Smart Museum Users under Artificial Intelligence BT - Proceedings of the 2024 3rd International Conference on Humanities, Wisdom Education and Service Management (HWESM 2024) PB - Atlantis Press SP - 128 EP - 135 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-253-8_16 DO - 10.2991/978-2-38476-253-8_16 ID - Zhou2024 ER -