高校智慧校园学生综合测评系统数据挖掘模型研究  

Research on Data Mining Model of Comprehensive Evaluation System for Students in the Smart Campus of Colleges & Universities

作　　者：茆灵铖 谢桂芳 邵周伟 凡玲 蒋秀莲[1] MAO Lingcheng;XIE Guifang;SHAO Zhouwei;FAN Ling;JIANG Xiulian(Xuzhou University of Technology,Xuzhou,221008)

机构地区：[1]徐州工程学院

出　　处：《办公自动化》2020年第1期15-17,共3页Office Informatization

基　　金：江苏省大学生创新创业训练计划项目（项目编号：XCX2019056）

摘　　要：当前,信息化正面临着一个全新的阶段,即以数据的深度挖掘和整合应用为核心的智慧化阶段,智慧校园已成为当前高校信息化建设的重要内容。分析高校信息化建设现状和常用数据挖掘模型的原理及应用,并重点根据FP-growth算法、K-means聚类、真实爛、分类和回归等模型对智慧校园学生综合测评系统的数据挖掘进行综述,旨在为数据挖掘技术与智慧校园的深度融合提供方案。At present,informatization is facing a brand-new stage,namely,the intelligent stage with the core of deep data mining and integrated application.Smart campus has become an important part of university informatization construction.This article analyzes the current status of university information construction and the principles and applications of commonly used data mining models,and focuses on data mining of smart campus student comprehensive evaluation systems based on FP-growth algorithm,K-means clustering,real entropy,classification and regression models etc.,aiming to provide solutions for the deep integration of data mining technology and smart campus.

关 键 词：智慧校园 数据挖掘 Hadoop和Spark 

分 类 号：TP274.2[自动化与计算机技术—检测技术与自动化装置] TP391[自动化与计算机技术—控制科学与工程]