Review of Methods for Intelligentization of Tourism Services Empowered by Large language Models (LLMs)
- DOI
- 10.2991/978-2-38476-551-5_63How to use a DOI?
- Keywords
- large model; tourism service; intelligence; natural language processing; speech recognition
- Abstract
In an era of rapid development of artificial intelligence (AI), AI is quietly influencing various industries. The integration of tourism and intelligent technologies has brought new development opportunities to the tourism services industry. The introduction of Large Language Models (LLMs) not only provides a new development direction for intelligent tourism services, but also brings both opportunities and challenges for high-quality innovation to the tourism industry, injecting new forces into smart tourism. To better understand how LLMs can improve tourism services quality and promote the diversified development of the tourism industry, this study systematically reviews, analyzes, and summarizes relevant literature, and analyzes key technologies such as natural language processing and speech recognition. The results show that LLMs have potential applications in tourism planning, intelligent navigation, and data analysis. They have significant advantages in enabling intelligent tourism services industry and provide valuable insights for the development of the tourism industry.
- Copyright
- © 2026 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 - Xue Fu AU - Bingbing Jiang PY - 2026 DA - 2026/03/26 TI - Review of Methods for Intelligentization of Tourism Services Empowered by Large language Models (LLMs) BT - Proceeding of 2025 8th International Conference on Humanities Education and Social Sciences (ICHESS 2025) PB - Atlantis Press SP - 590 EP - 600 SN - 2352-5398 UR - https://doi.org/10.2991/978-2-38476-551-5_63 DO - 10.2991/978-2-38476-551-5_63 ID - Fu2026 ER -