Intelligent Campus Resource Sharing System Based on Data Fusion Sensor

Abstract

In order to make full use of the large amount of teaching data existing in the data center, the author proposes a mining algorithm using classification technology and association rules in data mining technology; the teaching quality evaluation data and student achievement data were mined. By constructing the C4.5 decision tree algorithm, this method taps the potential links between teachers’ professional titles, degrees, ages, and teaching quality evaluation results, through correlation analysis theory; the correlation between professional courses was mined from the student’s course achievement database, and some reasonable and reliable course association rules were obtained. Experimental results show that the correct rate of C4.5 decision tree algorithm under different sampling times is above 80%. The conclusions drawn have certain guiding significance for college teaching and personnel training.