Abstract
In response to the personalized needs of the tourism industry, intelligent tourism planning services should be adopted. Through artificial intelligence and Big data technology, users' travel preferences, time, budget and other information are analyzed and mined in depth to provide users with more suitable travel routes and services. Therefore, according to the demand of tourist path recommendation in cultural scenic spots, this paper proposes a light sensor positioning method based on deep learning algorithm. This paper expounds the advantages of using optical sensor positioning for path recommendation, and describes the specific steps and processes of the optical sensor positioning method based on deep learning algorithm in detail. Finally, the feasibility and effect of this method are verified by experiments and data analysis. The results show that the localization of light sensor based on deep learning algorithm has high accuracy and practicability in the travel path recommendation of cultural scenic spots. Therefore, this method can provide accurate and reasonable path recommendation for tourists in cultural scenic spots and improve tourism experience and benefits. With the continuous development of the tourism market and the changing needs of users, this personalized tourism route planning and recommendation system will be increasingly widely applied and promoted.
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Wei He has contributed to the paper’s analysis, discussion, writing, and revision.
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He, W. Application of light sensor localization based on deep learning algorithm in tourist path recommendation in cultural scenic spots. Opt Quant Electron 56, 238 (2024). https://doi.org/10.1007/s11082-023-05876-5
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DOI: https://doi.org/10.1007/s11082-023-05876-5