The Path of Meishan Cultural Renewal and Expansion Based on Data Association Rules

Abstract

Abstract Metadata and data association rules are combined in this paper to create an aggregation framework for Meishan cultural digital resources. Meishan cultural digital resources are standardized through the use of metadata standards. The accuracy of metadata is evaluated in conjunction with trustworthiness. Metadata association rules are employed to evaluate the degree of association in Meishan cultural data. Enhance the efficiency of data association analysis by enhancing the Apriori algorithm. The algorithm is applied to the association analysis of Meishan culture data, and the degree of association between different digital resources and Meishan culture is determined by combining the data. The results show that the highest correlation with Meishan culture is the digital resources of documentaries and skills, with a correlation degree of 0.9, and the lowest correlation is the book resources, with a correlation degree of 0.65. The number of nodes in the period of 1-6 and the time consumed by each dataset is in the interval of (7000,1100).