基于大数据分析下的高校信用评估体系的构建研究  

Research on the Construction of College Credit Evaluation System Based on Big Data Analysis

作　　者：李京瞳 LI Jing-tong(Harbin University of Commerce,150028,Harbin,Heilongjiang,China)

机构地区：[1]哈尔滨商业大学,黑龙江哈尔滨150028

出　　处：《特区经济》2022年第2期108-111,共4页Special Zone Economy

基　　金：2020年全国大学生创新创业训练计划省级项目“基于大数据分析下的大学生信用体系构建研究”(项目编号:202010240051),该论文所属基金项目为作者主持研究。

摘　　要：本文立足于各大高校,以大学生为研究对象,以构建信用评估体系为研究目的,以大数据、人工智能等信息技术为研究工具,以分析大学生消费心理、消费观念、信用意识以及信用教育等方面存在的问题为出发点,从大学生特征、经济实力、消费能力、信用记录、学术态度、考试纪律和风险信息七个指标来构建基于大数据分析下的高校信用评估体系,这七个指标已经涵盖了大部分影响大学生信用行为的主要因素,通过使用层次法、熵权法和汇总评估法作为量化评估模型的基础,在方法上尽可能消除主观数据和客观数据带来的误差影响,充分发挥信息数据的动态性和体系的联动性优势,构建综合性的信用评价体系,以保证信用评估体系的高效性和准确性。Based on colleges and universities, college students as the research object, to build a credit evaluation system for research purposes, with large data, such as artificial intelligence information technology as a research tool, to analyze college students’ consumption psychology, consumption concept, credit consciousness and credit education problems as a starting point, from the college students’ characteristics,economic strength, consumption ability, credit record, academic attitude, exam discipline and risk information seven indicators to build based on the credit evaluation system in colleges and universities under the big data analysis, the seven indicators have covered most of the main factors affecting college students’ credit behavior, By using the AHP method and entropy weight method and summary evaluation method as the basis of quantitative evaluation model, on the way to eliminate error influence of subjective and objective data,give full play to the information system of dynamic and correlation advantage, build a comprehensive credit evaluation system, to ensure the efficiency and accuracy of credit evaluation system.

关 键 词：信用评估体系 大数据 构建 大学生 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] F832.4[自动化与计算机技术—控制科学与工程]