大数据分析下的助学金发放判断辅助模型

Grants Issue Judgment Auxiliary Model in the Case of Big Data Analysis

大学生助学金资助精准识别与认定是实际操作中的难题,无法实现资助定量分析,而定性分析目前又较模糊,缺乏科学性。鉴于此,对大学资助对象进行建模,实现定量和定性分析相结合,以达到精准识别目的。创造性地利用校园网已建的“互联网+”、“大数据”平台收集学生日常消费习惯、日常行动轨迹等数据,通过建立精确预测模型对学生在校生活水平进行定量和定性分析。实际操作效果表明,该分析模型实操性强,能够实现精准资助。

Accurate identification of college student grants is a difficult problem in reality.Quantitative analysis of funding cannot be done,and qualitative analysis is currently relatively vague.In view of this,the university funding objects are modeled,and quantita⁃tive and qualitative analysis are combined to achieve the purpose of accurate identification.This article creatively uses the“Internet+”and“big data”platforms that have been built on the campus network to collect data on students’daily consumption habits,daily action trajectories,etc.,and establishes a precise prediction model to quantitatively and qualitatively analyze the quality of students’school life.From the actual operation effect analysis,the proposed model is practical and can be accurately funded.