Abstract
This paper studies the comprehensive quality evaluation system of college students, and puts forward a design idea based on the comprehensive quality evaluation data warehouse system of college students. Through questionnaire surveys, enterprise surveys, and investigations on students, the comprehensive quality of college students is evaluated. Analytic hierarchy process (AHP) is used to calculate the index weight, which can reflect the importance of scientific and reasonable indexes in comprehensive quality evaluation. Based on the evaluation of students' comprehensive qualities, data mining technology is introduced. This paper describes the system design of the data mining model for the evaluation of university students' comprehensive qualities and the realization process of the data mining system. It mainly uses frequent itemset mining methods, namely association rules and Apriori algorithm to generate association rules and frequent itemsets that affect the relationship between the factors of comprehensive quality. Based on the generated rule set, the relationship between the comprehensive quality assessment of college students and the employment situation of students is predicted, analyzed and mastered. Mastering this relationship is conducive to further training useful talents to meet the needs of the society, and it is beneficial for the employer to conduct targeted selection of talents
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