AI-powered Tourism Recommendation System Leveraging GPT-3.5 for Real-time and Comprehensive Travel Itineraries

DOI

10.2991/978-94-6463-866-0_19How to use a DOI?

Keywords

AI-powered travel; GPT-3.5 for travel planning; Real-time travel itineraries; Kernel API; Machine learning

Abstract

This research intends to improve the user experience and simplify travel planning by creating an AI-driven Tourism Recommendation System with GPT-3.5 technology, acting as a standalone travel guide. In contrast to conventional NLP-based systems, this solution includes Kernel APIs to provide real-time, customized itineraries depending on the user’s budget, interests, and timeline. The system dynamically recommends accommodations, transportation, activities, and destinations, providing a more interactive and adaptive experience. Existing tourism recommendation systems are typically constrained by static user profiles, pre-calculated itineraries, and limited real-time information, which renders them less sensitive to dynamic conditions such as traffic, weather, and spontaneous user interests. AI powered tourism recommendation system overcomes these constraints by incorporating live data streams to generate adaptive travel plans that can adapt recommendations according to evolving conditions, spontaneous feedback, and even user mood. Utilizing distil BERT based GPT-3.5’s sophisticated natural language processing (NLP) technology, the system comprehensively grasps user intentions and limitations, providing accurate, context-specific recommendations. Contextual understanding increases precision, relevance, and adaptability, leading to greater user satisfaction. In contrast to traditional systems, which provide generic recommendations, our product offers dynamic, tailored plans that adjust in real-time. In addition, it surpasses current best tourism models, such as CV-DCN, CRISP-DM, SMTM-LDA, and the AI-Hybrid Model, with a 91% increase in recommendation accuracy and user satisfaction. Finally, this AI-driven method transforms tourism planning by making travel easier, more personalized, dynamic, and responsive to real-time user requirements.

Copyright

© 2025 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.

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TY  - CONF
AU  - Karthik Elangovan
AU  - Banaganipalli Saidavali
AU  - Yadavalli Pavan
PY  - 2025
DA  - 2025/10/31
TI  - AI-powered Tourism Recommendation System Leveraging GPT-3.5 for Real-time and Comprehensive Travel Itineraries
BT  - Proceedings of the International Conference on Intelligent Systems and Digital Transformation (ICISD 2025)
PB  - Atlantis Press
SP  - 207
EP  - 219
SN  - 2589-4919
UR  - https://doi.org/10.2991/978-94-6463-866-0_19
DO  - 10.2991/978-94-6463-866-0_19
ID  - Elangovan2025
ER  -