Resource electronic database for measuring regional cultural influence based on machine learning big data

Abstract

With the advent of the information age, the use of various mobile terminal devices has accelerated the integration of local cultures, which has also brought many unstable factors to society while promoting cultural diversification. This article aims to build a resource electronic database to measure regional cultural influence through the current popular big data technology, and to provide some reference suggestions and data resources for the harmonious development of regional culture. Based on the status quo of regional cultural development, this paper determines the key functional requirements for constructing an electronic database of regional cultural influence measurement resources. In the specific process of database design, big data mining algorithms and machine learning classification prediction algorithms are used to collect, classify and process the data resources of the regional cultural influence measurement database. Through case analysis, it is concluded that the electronic database of regional cultural influence measurement resources based on machine learning big data constructed in this paper is rich in data resources, and the relative mean square error of its classification algorithm is only 13.58%.