Career Decision Making Based on Graduate's Information Analysis Model

In recent years, the number of Chinese university graduates is increasing, which not only leads to the problem of supply and demand of talents, but also make it difficult for graduates to make future career decision. In the prior study, experts use Goal Programming, Intrinsic Estimator and other models to analyze the engagement of graduates, but these models have the problems of time consuming and low accuracy and so on. In order to solve the problems mentioned above, that a proposed graduate's information analysis model based on Age Period Cohort algorithm was proposed. It is found that the traditional Age Period Cohort algorithm very suitable for graduate's engagement trend analysis. For the test, sample data model used graduate's information of Shan Dong University of Science and Technology from 2011 to 2019. In order to improve the timeliness and prediction accuracy, the influence factors such as policy and gender are added in Age Period Cohort algorithm and modified algorithm applied to proposed analysis model. As the test results show, that the proposed model can analyze the graduate's engagement trend more timely and accurately than traditional data analysis model, and provide reliable data analysis basis for predicting future engagement trend of graduates.