摘 要:学生在校期间产生的数据,可用以分析和挖掘与学风建设有关的因素,并有针对性地对学生加以引导,从而提升高校在学风建设和管理方面的成效。在高校智慧校园建设的基础上,通过基于关联分析模型的数据挖掘方法,对高校一卡通、教务信息系统、学生工作数据等多个源渠道的数据信息进行分析,为高校的学风建设提供精准的技术支撑和决策辅助。
关键词:数据挖掘;关联分析;学风建设
DOI:10.19850/j.cnki.2096-4706.2021.14.033
中图分类号:TP311.13 文献标识码:A 文章编号:2096-4706(2021)14-0127-03
Research on the Construction of Study Style Model in College Based on Association Analysis Algorithm
YANG Zitian, WEN Shanghai
(Jiangsu University of Science & Technology (Zhangjiagang), Suzhou 215600, China)
Abstract: The data generated by students in school can be used to analyze and mine the factors related to the construction of study style, and give targeted guidance to students, so as to improve the effectiveness of the construction of study style and management in colleges and universities. Based on the construction of wisdom campus in Colleges and universities, through the data mining method based on association analysis model, this paper analyzes the data information of multiple source channels such as college all-in-one card, educational administration information system and student work data, so as to provide accurate technical support and decision-making assistance for the construction of study style in colleges and universities.
Keywords: data mining; association analysis; the construction of study style
参考文献:
[1] 白娟 . 基于大数据分析的学风建设以及学生管理工作探析 [J]. 无线互联科技,2020,17(9):74-76.
[2] 曹阳,张小恒 . 数据挖掘在学风量化评价中的应用 [J]. 科学咨询(科技·管理),2018(8):85.
[3] 王宁,孟倩玉 . 基于学风数据分析的高校学生学风建设对策研究 [J]. 同行,2016(5):136.
[4] SRIDHAR R S,PRASAD M V N K,BALAKRISHNAN R. Spatio-Temporal association rule based deep annotation-free clustering (STAR-DAC)for unsupervised person re-identification [J].Pattern Recognition,2021,122:1082-1087.
[5] 王晓翠,高雅奇,苏亚萍 . 大数据助力高校学风建设研究——以北京第二外国语学院为例 [J].信息技术与信息化,2021(2): 205-207+212.
作者简介:杨子天(1984.07—),男,汉族,江苏连云港人,实验师,硕士,研究方向:计算机技术、信息系统;温上海(1991.02—),男, 汉族,江苏徐州人,工程师,硕士,研究方向:数据挖掘、信息系统。