基于人群队列模型的高校毕业生趋向大数据分析方法研究

Research on the Graduates Engagement Trend Big Data Analysis Method Based on APC Model

近年来国内高校毕业生数量呈日益增长趋势,不仅将导致人才供需问题,而且对高等院校教学辅助资源的合理化分配提出了挑战。为准确判断高校毕业生趋向及其对应的教学辅助资源,提出基于人群队列模型的高校毕业生趋向大数据分析模型。在提出的模型中,毕业趋向可分为深造、就业和其它。选取毕业趋向的影响因子时,根据收集的数据分别选择性别和政策。最后利用人群队列模型对年龄、时期、队列相关大数据进行毕业趋向分析。实验收集了山东科技大学2011-2018年毕业生基本信息,并建立人群队列模型进行毕业趋向分析。实验结果表明,基于人群队列模型的分析模型不仅能更准确地预测高校毕业生毕业趋向,而且能更科学、准确、及时地提供教学辅助资源的合理化分配依据。

Recently,the increasing trend of domestic university graduates not only leads the problem of talent supply and demand,but also challenges the rational allocation of teaching auxiliary resources in universities.In order to accurately judge the employment trend of university graduates and the corresponding teaching auxiliary resources needed for employment,that Age Period Cohort model based graduates engagement trend big data analysis model is proposed in this research.In this proposed big data analysis model,the employment is divided into further study,job selection and others.Among the selecting of influencing factors that affect employment trends,which the gender and policy were selected from the collected graduation data.Finally,using the age period cohort model analyzed the employment trend based on age,period and cohort related big data.In this employment trend big data analysis experiment,the basic information and employment results of graduates of Shandong University of Science and Technology from 2011 to 2018 were collected and using the big data established age period cohort model sample data modeling.Through the comparative analysis of experimental results,that the proposed analysis model based on age period cohort model not only more accurately predicts the university graduates employment trend but also provides a rational allocation basis in terms of the demand for teaching auxiliary resources more scientifically,accurately,timely.