AHCI RESEARCH GROUP

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OUR RESEARCH

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2025

Guo, H.; Liu, Z.; Tang, C.; Zhang, X.

An Interactive Framework for Personalized Navigation Based on Metacosmic Cultural Tourism and Large Model Fine-Tuning Journal Article

In: IEEE Access, vol. 13, pp. 81450–81461, 2025, ISSN: 21693536 (ISSN).

Abstract | Links | BibTeX | Tags: Cultural informations, Digital Cultural Heritage, Digital cultural heritages, Digital guide, Fine tuning, fine-tuning, Historical monuments, Language Model, Large language model, Leisure, Metacosmic cultural tourism, Multimodal Interaction, Tourism, Virtual tour

@article{guo_interactive_2025,

title = {An Interactive Framework for Personalized Navigation Based on Metacosmic Cultural Tourism and Large Model Fine-Tuning},

author = {H. Guo and Z. Liu and C. Tang and X. Zhang},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004059236&doi=10.1109%2fACCESS.2025.3565359&partnerID=40&md5=45d328831c5795fa31e7e033299912b5},

doi = {10.1109/ACCESS.2025.3565359},

issn = {21693536 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {IEEE Access},

volume = {13},

pages = {81450–81461},

abstract = {With the wide application of large language models (LLMs) and the rapid growth of metaverse tourism demand, the digital tour and personalized interaction of historical sites have become the key to improving users’ digital travel experience. Creating an environment where users can access rich cultural information and enjoy personalized, immersive experiences is a crucial issue in the field of digital cultural travel. To this end, we propose a tourism information multimodal generation personalized question-answering interactive framework TIGMI (Tourism Information Generation and Multimodal Interaction) based on LLM fine-tuning, which aims to provide a richer and more in-depth experience for virtual tours of historical monuments. Taking Qutan Temple as an example, the framework combines LLM, retrieval augmented generation (RAG), and auto-prompting engineering techniques to retrieve accurate information related to the historical monument from external knowledge bases and seamlessly integrates it into the generated content. This integration mechanism ensures the accuracy and relevance of the generated answers. Through TIGMI’s LLM-driven command interaction mechanism in the 3D digital scene of Qutan Temple, users are able to interact with the building and scene environment in a personalized and real-time manner, successfully integrating historical and cultural information with modern digital technology. This integration significantly enhances the naturalness of interaction and personalizes the user experience, thereby improving user immersion and information acquisition efficiency. Evaluation results show that TIGMI excels in question-answering and multimodal interactions, significantly enhancing the depth and breadth of services provided by the personalized virtual tour. We conclude by addressing the limitations of TIGMI and briefly discuss how future research will focus on further improving the accuracy and user satisfaction of the generated content to adapt to the dynamically changing tourism environment. © 2013 IEEE.},

keywords = {Cultural informations, Digital Cultural Heritage, Digital cultural heritages, Digital guide, Fine tuning, fine-tuning, Historical monuments, Language Model, Large language model, Leisure, Metacosmic cultural tourism, Multimodal Interaction, Tourism, Virtual tour},

pubstate = {published},

tppubtype = {article}

}

With the wide application of large language models (LLMs) and the rapid growth of metaverse tourism demand, the digital tour and personalized interaction of historical sites have become the key to improving users’ digital travel experience. Creating an environment where users can access rich cultural information and enjoy personalized, immersive experiences is a crucial issue in the field of digital cultural travel. To this end, we propose a tourism information multimodal generation personalized question-answering interactive framework TIGMI (Tourism Information Generation and Multimodal Interaction) based on LLM fine-tuning, which aims to provide a richer and more in-depth experience for virtual tours of historical monuments. Taking Qutan Temple as an example, the framework combines LLM, retrieval augmented generation (RAG), and auto-prompting engineering techniques to retrieve accurate information related to the historical monument from external knowledge bases and seamlessly integrates it into the generated content. This integration mechanism ensures the accuracy and relevance of the generated answers. Through TIGMI’s LLM-driven command interaction mechanism in the 3D digital scene of Qutan Temple, users are able to interact with the building and scene environment in a personalized and real-time manner, successfully integrating historical and cultural information with modern digital technology. This integration significantly enhances the naturalness of interaction and personalizes the user experience, thereby improving user immersion and information acquisition efficiency. Evaluation results show that TIGMI excels in question-answering and multimodal interactions, significantly enhancing the depth and breadth of services provided by the personalized virtual tour. We conclude by addressing the limitations of TIGMI and briefly discuss how future research will focus on further improving the accuracy and user satisfaction of the generated content to adapt to the dynamically changing tourism environment. © 2013 IEEE.