云模型数据挖掘算法的高校教育信息化效益评估模型构建  

Construction of university education informatization benefit evaluation model using cloud model data mining algorithm

作　　者：唐菡悄 沈磊 TANG Hanqiao;SHEN Lei(School of Educational Science,Anhui Normal University,Wuhu 241000,China;School of Finance and Mathematics,Huainan Normal University,Huainan 232038,China)

机构地区：[1]安徽师范大学教育科学学院,安徽芜湖241000 [2]淮南师范学院金融与数学学院,安徽淮南232038

出　　处：《现代电子技术》2020年第13期25-27,31,共4页Modern Electronics Technique

摘　　要：传统高校教育信息化效益评估模型的数据处理量少,因此构建一个云模型数据挖掘算法的高校教育信息化效益评估模型。建立评估指标体系,融合全局评估视角,得到了评估指标的三维结构,通过计算数据的后挖掘概率计算出判决准则,利用该准则对评估体系中的各个指标进行评分,最后计算原始的指标数据矩阵,确定指标隶属度向量,完成教育信息化效益的评估流程。实验结果表明,设计的评估模型在完成评估时的数据处理量比传统模型高出51%,说明设计的评估模型在处理海量数据时的性能比传统模型更加优越。The traditional informatization benefit evaluation model for university education has a poor data processing capacity,so a university education informatization benefit evaluation model using cloud model data mining algorithm is constructed.An evaluation indicator system is set up and a global evaluation perspective is fused with it to get a 3D structure of evaluation indicator.By calculating the post⁃mining probability of the data,the judgment criterion is worked out,which is used to score each indicator in the evaluation system.Then,the original indicator data matrix is calculated to determine the indicator membership vector and complete the evaluation process of educational informatization benefit.The experimental results show that the data processing capacity of the designed evaluation model is 51%higher than that of the traditional model in the whole evaluation,which indicates that the performance of the model when processing the massive data is better than that of the traditional model.

关 键 词：效益评估模型 数据挖掘算法 高校教育信息化 评估指标三维结构 判决准则 评估流程 

分 类 号：TN911.1-34[电子电信—通信与信息系统] G434[电子电信—信息与通信工程]