Data Correlation Analysis Algorithm of University-enterprise Cooperation and Cultivation Quality

Abstract

Enterprise cooperation mechanisms play an important role in the cultivation of college students, but a scientific method is needed to evaluate the potential relationship between the university-enterprise cooperation and the quality of student cultivation. This paper proposes a data correlation analysis algorithm between university-enterprise cooperation and college students' training quality, in order to scientifically evaluate the impact of university-enterprise cooperation mechanisms on college students' training quality. The transaction data set and item set reflecting the relationship between university-enterprise cooperation mechanisms and training quality are established. The association rules for the influence of university-enterprise cooperation mechanism on the cultivation quality of college students are designed. The computation method of the item set support degree for student training affairs is defined, and the computation method of the confidence degree of the association rules for the influence of university-enterprise cooperation mechanisms on training quality is defined. The strongest association rules between the university-enterprise cooperation mechanisms and the quality of student training are confirmed by the support degree and the confidence degree. At the same time, the corresponding correlation analysis algorithm is designed, and the effectiveness of the proposed algorithm is verified by experiments.