Design of Repository and Search Platform for Art Painting Teaching Resources in Universities Based on Model of Decision Tree.

Abstract

At present, art education curriculum reform is in full swing. Art education in China started late but as an important element of quality education. Art education is particularly important today with rapid economic development and advanced technology. The art subject is the sum of the teaching content of the art subject and the execution of teaching activities expressed through the network, including two components: the teaching content organized according to specific teaching objectives and teaching strategies and the network teaching support environment. Unlike existing multimedia courseware, several features reflect the advantages of online education, unlike online courseware. Each school generates a large amount of student performance data every year, and existing systems only perform simple backups, queries, and statistics on these data, which do not reflect the weaknesses of education in a centralized and comprehensive manner. Data mining can extract valuable information hidden behind the data from a large amount of data and has been applied in more and more fields with good results, which helps people to make correct decisions. In this study, we propose a decision tree model-based repository and search platform for school art and painting education resources, briefly outline the decision tree model, and analyze the architecture and operation of the school art and painting education resources repository and search platform. The experimental results show that the Virginica accuracy of the decision tree model is 0.42 higher than that of C4.5, which greatly improves the accuracy of the preferred class and ensures the overall accuracy remains unchanged. Therefore, this system realizes the art education resource repository system and realizes the needs of college users to share art professional information and resources.