基于数据挖掘的就业困难学生认定研究

Research on the Identification of Students with Employment Difficulty Based on Data Mining

政府一直高度重视高校毕业生的就业工作,并出台大量有关就业困难学生的扶持政策。然而在高校就业困难学生认定工作中,如何界定就业困难学生还没有统一的标准。本文构建高校学生就业困难程度评分指标体系,运用层次分析法(AHP)确定就业困难程度指标权重,运用聚类评级法构建就业困难程度评级模型,最终开发系统实现对就业困难学生的预测及认定。

The government has attached great importance to the employment of College graduates and releases a large number of supporting policies for the students who have employment difficulties. However, during the mission of identifying college students＇ employment difficulties, there is no uniform standard about how to define the students who have employment difficulties. This paper uses the Analytic Hierarchy Process （AHP） to determine the weight of the index of the employment difficulty degree, which constructs the evaluation index system of College Students＇ employment difficulty degree and the model of difficulty degree in employment by clustering rating method to achieve the final goal of predicting and identifying the students with difficulties in employment.