Title: Application of scenic spot recommendation model combined with TDRA in tourism service management under the background of big data

Authors: Xiao Hu

Addresses: The College of Tourism and Aviation, Jiangxi Modern Polytechnic College, Nanchang, 330095, China

Abstract: To improve the search efficiency of group travellers for travel information and optimise user experience, a model combining tourist attractions and travel route planning, namely the algorithm based on time, region, and popularity (TRPA), is proposed. The model first analyses the group travel recommendation algorithm that combines spatiotemporal factors and the popularity of travel attractions. Then it is introduced into the route algorithm based on time division (TDRA) model to further plan group travel routes, fully considering factors such as geography, time, and tourist attraction flow that affect people's travel decisions. The validation results on the dataset showed that the highest rating rate of TRPA-TDRA model reached 38%, which was about 30% higher than other models. This study fills the research gap in group travel attraction recommendation algorithms, providing new theoretical and methodological support for tourism management practices.

Keywords: big data; internet; time, region, and popularity; TRPA; TDRA; tourist attraction recommendation; travel route planning; group travel.

DOI: 10.1504/IJTIP.2024.145510

International Journal of Technology Intelligence and Planning, 2024 Vol.13 No.4, pp.345 - 363

Received: 11 Sep 2023
Accepted: 22 Jul 2024
Published online: 02 Apr 2025 *

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