大数据时代精准识别高校贫困生研究  

Study on Precise Identification of Impoverished College Students in Big Data Era

作　　者：孙梦[1] 高峰[1] 

机构地区：[1]北京工商大学,北京100048

出　　处：《北京劳动保障职业学院学报》2017年第2期47-52,共6页Journal of Beijing Vocational College Of Labour And Social Security

摘　　要：近年来,高校贫困生资助成为社会关注的焦点。利用现代信息技术实现高校贫困生识别管理的规范化、信息化和高效化是必要的,也是可行的。统计分析学生以往日常消费数据获得学生在校消费习惯与规律,在统计分析的基础上制定贫困学生的标准,采用支持向量机(SVM)的理论建立数学模型,对当前学生的消费数据分析、分类,鉴别潜在的可能的贫困学生,使高校贫困生资助工作公平、公正、有效。In recent years, college students with financial difficulties have become the concern of the society. It is necessary and also feasible to realize normalization, informatization and high efficiency of poor college students＇ identification management. The students＇ consumption habits and patterns on campus can be obtained from statistical analysis of their previous consumption habits, and criteria of identifying poor students can also be worked out based on the analysis. A mathematical model is to be established based on the theory of support vector machine （SVM） to analyze and classify students＇ consumption data on campus and identify possible poor students, making the work of financial support both fair and effective.

关 键 词：贫困生识别 支持向量机理论 SVM MATLAB 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]