摘要
针对高校就业质量评价错误大,可靠性低等不足,为了获得理想的高校就业质量评价效果,设计了基于大数据挖掘技术的高校就业质量评价模型。首先,研究当前高校就业质量评价相关文献,选择一些影响因素构建高校就业质量评价指标体系,并通过专家确定高校就业质量等级;然后,引入大数据挖掘技术拟合高校就业质量变化特点,建立高校就业质量评价模型;最后,采用具体数据对高校就业质量评价模型性能进行分析。文中所提模型较好地解决了当前高校就业质量评价模型的弊端,评价结果更加科学,高校就业质量评价偏差小于当前典型模型,具有广泛的实际应用价值。
In view of big errors and low reliability of the employment quality evaluation of universities,an employment quality evaluation model based on big data mining technology is designed to obtain an ideal evaluation effect. The related literatures on the current employment quality evaluation of universities are studied. Some influencing factors are selected to construct an index system for employment quality evaluation of universities,and the employment quality stages of universities are determined by experts. The big data mining technology is introduced to fit the changing characteristics of employment quality evaluation and establish the evaluation model. Finally,the specific data is used to analyze the performance of the evaluation model. It shows that the proposed model can eliminate the drawbacks existing in the current evaluation models,and the evaluation results are more scientific. The evaluation deviation of the proposed model is smaller than that of the current typical models. Therefore,the proposed model has a wide range of application.
作者
魏玉曦
WEI Yuxi(Hetao College,Bayannur 015000,China)
出处
《现代电子技术》
北大核心
2020年第7期103-106,共4页
Modern Electronics Technique
基金
河套学院一般课题:基于应用型人才培养背景下就业指导课程建设研究。
关键词
高校就业
质量评价
大数据挖掘技术
仿真实验
评价指标
模型建立
university employment
quality evaluation
big data mining technology
simulation experiment
evaluation index
model building
