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Enhancing Personalized Services in Tianfu Cultural Tourism: Pathways and Strategies Based on User Profiling

Author(s)

Zhengrong Luo1,2,3,*, Jinyang Jiang1,3, Huajie Zhou1,3, Jian Wu1

Affiliation(s)

1Guang’an Vocational & Technical College, Guangan, Sichuan, China 2Key Laboratory of Digital Innovation of Tianfu Culture, Sichuan Provincial Department of Culture and Tourism, Chengdu University, Chengdu, Sichuan, China 3Guang’an City Artificial Intelligence Technology Innovation Center, Guangan, Sichuan, China *Corresponding Author.

Abstract

Against the backdrop of a burgeoning global cultural tourism industry, Tianfu cultural tourism has emerged as a vital driver of economic growth in Sichuan, owing to its unique natural and cultural resources. To address the growing demand for personalized experiences among tourists, this study explores the application of user profiling technologies to enhance the delivery of personalized services in Tianfu cultural tourism. Leveraging big data and artificial intelligence, the study proposes a service optimization framework centered on data collection, profile analysis, and precise content delivery. By examining domestic and international case studies, the research underscores the importance of policy support, industry collaboration, and service innovation. Personalized services significantly enhance tourist experiences and loyalty, fostering the digital transformation and sustainable development of the cultural tourism industry.

Keywords

Tianfu Cultural Tourism; User Profiling; Personalized Services; Big Data Technologies

References

[1] Yao, W., Hou, Q., Wang, J., Lin, H., Li, X., & Wang, X. (2019, July). A personalized recommendation system based on user portrait. In Proceedings of the 2019 international conference on artificial intelligence and computer science, 341-347. [2] Hong, J., Suh, E. H., Kim, J., & Kim, S. (2009). Context-aware system for proactive personalized service based on context history. Expert Systems with Applications, 36(4), 7448-7457. [3] Zhou, E. (2021, June). The Influence of Chengdu Universiade on Tianfu Culture. In 2nd International Conference on Language, Art and Cultural Exchange (ICLACE 2021), 395-398. [4] Fan, Y., Song, X., & Wang, R. (2024). The role of big data in the integrated development of culture and tourism public services. Journal of Computational Methods in Sciences and Engineering, 24(1), 445-462. [5] Gan, X. (2024, October). Cultural Heritage of Ancient Shu’s Wangcong Culture Driven by Dual Wheels: Cultural Creative Industries and Digital Technologies. In 4th International Conference on Public Administration, Health and Humanity Development (PAHHD 2024), 177-186. [6] Xiang, M., & Xu, Y. (2021). Path Analysis of Rural Landscape Protection and Creation under the Guidance of High-Quality Development of Rural Tourism—A case study on Tianfu Red Valley in Chengdu. In E3S Web of Conferences 251(1), 002-003. [7] Chen, Y., He, J., Wei, W., Zhu, N., & Yu, C. (2021). A multi-model approach for user portrait. Future Internet, 13(6), 147-149. [8] Rane, J., Kaya, O., Mallick, S. K., & Rane, N. L. (2024). Influence of digitalization on business and management: A review on artificial intelligence, blockchain, big data analytics, cloud computing, and internet of things. Generative Artificial Intelligence in Agriculture, Education, and Business, 1-26. [9] E Silva, F. B., Herrera, M. A. M., Rosina, K., Barranco, R. R., Freire, S., & Schiavina, M. (2018). Analysing spatiotemporal patterns of tourism in Europe at high-resolution with conventional and big data sources. Tourism Management, 68, 101-115. [10] Granier, B., & Kudo, H. (2016). How are citizens involved in smart cities? Analysing citizen participation in Japanese'' Smart Communities''. Information Polity, 21(1), 61-76.