主管单位:中国科学技术协会
主办单位:中国地理学会
承办单位:华东师范大学

World Regional Studies ›› 2025, Vol. 34 ›› Issue (12): 188-200.DOI: 10.3969/j.issn.1004-9479.2025.12.20240841

Previous Articles    

Deep learning in tourism study: A systematic review and prospects

Jiaqi LUO1(), Xianzhu JIN1(), Songshan HUANG2, Lawrence Hoc Nang FONG3   

  1. 1.School of Economic and Management, East China Normal University, Shanghai 200062, China
    2.School of Business and Law, Edith Cowan University, Joondalup, WA 6027, Australia
    3.Faculty of Business Administration, University of Macau, Macau SAR 999087, China
  • Received:2024-09-30 Revised:2025-01-08 Online:2025-12-15 Published:2025-12-23
  • Contact: Xianzhu JIN

深度学习技术在旅游研究中应用的发展与展望

罗佳琦1(), 金贤珠1(), 黄松山2, 冯学能3   

  1. 1.华东师范大学经济与管理学院,上海 200062
    2.埃迪斯科文大学法律与商务学院,澳大利亚 珀斯 6027
    3.澳门大学工商管理学院,澳门 999087
  • 通讯作者: 金贤珠
  • 作者简介:罗佳琦(1986—),女,博士,副教授,研究方向为旅游营销和旅游人工智能,E-mail:jqluo@tour.ecnu.edu.cn
  • 基金资助:
    国家自然科学基金青年项目(72402069);教育部人文社科基金青年项目(23YJCZH156)

Abstract:

The use of Deep Learning (DL) in tourism research has produced a considerable body of literature. This study discusses a literature evolution on DL in tourism research using systematic review and computational methods. Adopting Leiper's framework for the tourism system, we discovered that studies employing the DL technique in tourism fit into five groups and 10 themes. Each theme's topics were recognised. From the perspectives of study emphasis, data sources, specific DL models, and future goals, a comprehensive analysis was undertaken. This study presents a historical perspective and summarises the current understanding of DL used in tourism and combines China's market and social characteristics to look forward to the future application of DL in tourism research and practice. Additionally, it assists governments and practitioners in identifying new ways to derive value from DL and tourism big data.

Key words: deep learning, Leiper's tourism system model, tourism geography, systematic review, LDA model

摘要:

近年来,深度学习技术在旅游领域的应用日益增多,已积累了丰富的研究成果。鉴于此,本文通过系统性文献综述和运用LDA主题模型总结了旅游研究中深度学习相关文献的演变过程和发展轨迹。基于Leiper的旅游地理系统框架,本文将深度学习在旅游领域应用的相关文献归纳为5个重要领域和10个具体主题,对每个主题进行了深入分析,并总结其核心议题。文章从研究重点、数据来源、具体模型等多个维度对现有研究进行了全面回顾和评述,梳理了未来研究方向,结合中国国情,对深度学习技术未来在旅游研究和实践中的应用进行了展望。本综述有利于研究者加深对旅游业中深度学习技术应用的理解,并为政策制定者和旅游从业者提供深度学习技术和旅游大数据挖掘价值的新思路。

关键词: 深度学习, Leiper旅游系统模型, 旅游地理, LDA模型, 综述