Coastal tourism resource development based on big data mining and environmental sustainability

This paper puts forward a research system for the development of coastal tourism resources and the sustainable development of environment. This paper discusses and classifies the concept, index system, calculation model, island tourism, and other related literature about the development of coastal tourism resources and the sustainable development of environment. In addition, according to the characteristics of the island’s ecological environment, the components of ecological capacity are determined. The system determines the first level of four indicators, namely, the capacity of ecological environment, the capacity of resource space environment, the capacity of tourism facilities, and the capacity of tourists’ psychological environment. Using simulation analysis, the obtained indicators are compared with the traditional data mining algorithms (such as Apriori and Eclat). The simulation results show that the proposed method has excellent performance, and the final average accuracy of recommendation can reach about 80%. This paper discusses the evolution of coastal tourism resources and the sustainable development of environment in data mining and puts forward the suggestions of using multimedia technology, data mining, and geographic information technology to realize the coastal tourism resource development system and the sustainable development consistent with the space-time environment. In addition, this paper proposes a method to filter the tourism destinations according to the current situation of users and then classifies the tourism destinations by collaborative filtering to study the environmental impact. Big data mining technology will provide new ideas for developing coastal tourism resources and ensuring environmental sustainability.