Research On The Application Of Big Data Technology In The Digital Integration Of Intangible Cultural Heritage Tourism Resources In The Context Of Cultural Tourism Integration

Abstract

In order to enhance the value of intangible cultural heritage tourism resources data and better develop intangible cultural heritage tourism, the application method of big data technology in the digital integration of intangible cultural heritage tourism resources under the background of cultural tourism integration is studied. The functions of digital integration of intangible cultural heritage tourism resources based on big data technology under the background of cultural tourism integration are analyzed, and a digital integration platform of intangible cultural heritage tourism resources that includes data layer integration, platform layer integration and service layer integration is built. In data layer integration, considering the multi-source heterogeneity of intangible cultural heritage tourism resource data, the federal learning algorithm is adopted to integrate intangible cultural heritage tourism resource data through feature extraction, feature integration and feature decision-making. In the platform level integration, based on the integration results of intangible cultural heritage tourism resources data, the initial clustering center is determined according to the distribution density of intangible cultural heritage tourism resources data by using the k-clustering algorithm based on density and object direction, and the intangible cultural heritage tourism resources data is clustered according to the clustering direction of intangible cultural heritage tourism resources data. In the service level integration, based on the clustered intangible cultural heritage tourism resource data and the theory of Resource-Market-Product, an evaluation index system is constructed to evaluate the tourism utilization potential of intangible cultural heritage resources, providing reference for the development of intangible cultural heritage tourism. The experimental results show that the data correlation after data integration of this method is above 0.943, which can accurately evaluate the development potential of intangible cultural heritage tourism resources and significantly improve the regional tourist flow.