Digital Management and Optimization of Tourism Information Resources Based on Machine Learning

Author:

Zhuang Xueqiu1,Jiao Huihua2ORCID,Kang Li3

Affiliation:

1. College of Finance and Economics, Hainan Vocational University of Science and Technology, Haikou 571126, Hainan, China

2. Network and Educational Technology Center, Qiongtai Normal University, Haikou 571127, Hainan, China

3. Office of Academic Research, Hainan Vocational College of Political Science and Law, Haikou 570100, Hainan, China

Abstract

With the gradual growth of economy, tourism has become a pillar industry in many countries and plays an important role in promoting national development. The individualization and diversification of tourism resources must be supported by a powerful information resource management system. However, the traditional tourism information resource management system has some problems, such as scattered sources of tourism information, low interactivity, and slow update of information resources. Tourists cannot get detailed information of scenic spots and make detailed plans for tourism which hinder the further development of the tourism industry. In order to solve these problems and promote the development of the tourism industry, this paper carried out digital management of tourism information based on machine learning and digital management of information resources of different tourist attractions and surveyed and tested the number of tourists, expenditure of scenic spots, income of scenic spots, and satisfaction of tourists. The total result showed that the digital management of tourism information resources in scenic spots can increase the passenger flow, increase the income of scenic spots, reduce the expenditure of scenic spots by 6.7%, and increase the satisfaction of tourists by 4.1%. The digital management of tourism information resources based on machine learning can optimize the tourism industry and promote its development.

Funder

Natural Science Foundation of Hainan Province

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Unveiling trends in digital tourism research: A bibliometric analysis of co-citation and co-word analysis;Environmental and Sustainability Indicators;2023-12

2. Retracted: Digital Management and Optimization of Tourism Information Resources Based on Machine Learning;International Transactions on Electrical Energy Systems;2023-08-16

3. Sustainable Intelligent Information System for Tourism Industry;2023 IEEE 8th International Conference for Convergence in Technology (I2CT);2023-04-07

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