Design of the Higher Education System Based on Parallel Association Rules Algorithm

Abstract

Aiming at improving the quality of online education, a higher education system based on parallel association rules algorithm is designed. In this study, the functional structure module of the system is divided into six modules, namely, the home page module, course module, teacher module, student module, administrator module, and personal center, so as to carry out a comprehensive treatment for students, teaching, and education resources. On the basis of mining the data association rules of the education system, the parallel association rules algorithm is used to identify and analyze the original data of the system, so as to fundamentally improve the ability of the system to process data and complete the personalized recommendation of educational resources and teaching evaluation feedback. Experiments show that the design system has greater information throughput, a short response time, and a resource utilization rate of more than 90%. In addition, the audio teaching resource plays better, which proves that the system effectively achieves the design expectation.