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.

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