Data mining applications in university information management system development

IF 2.1 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Journal of Intelligent Systems Pub Date : 2022-01-01 DOI:10.1515/jisys-2022-0006
Minshun Zhang, Jun-Chen Fan, A. Sharma, Ashima Kukkar
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引用次数: 14

Abstract

Abstract Nowadays, the modern management is promoted to resolve the issue of unreliable information transmission and to provide work efficiency. The basic aim of the modern management is to be more effective in the role of the school to train talents and serve the society. This article focuses on the application of data mining (DM) in the development of information management system (IMS) in universities and colleges. DM provides powerful approaches for a variety of educational areas. Due to the large amount of student information that can be used to design valuable patterns relevant to student learning behavior, research in the field of education is continuously expanding. Educational data mining can be used by educational institutions to assess student performance, assisting the institution in recognizing the student’s accomplishments. In DM, classification is a well-known technique that has been regularly used to determine student achievement. In this study, the process of DM and the application research of association rules is introduced in the development of IMS in universities and colleges. The results show that the curriculum covers the whole field and the minimum transaction support count be 2, minconf = 70%. The results also suggested that students who choose one course also tend to choose the other course. The application of DM theory in university information will greatly upsurge the data analysis capability of administrators and improve the management level.
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数据挖掘在高校信息管理系统开发中的应用
摘要为了解决信息传输不可靠的问题,提高工作效率,现代管理被大力提倡。现代管理的基本目标是更有效地发挥学校培养人才和服务社会的作用。本文主要研究了数据挖掘技术在高校信息管理系统开发中的应用。DM为各种教育领域提供了强大的方法。由于大量的学生信息可用于设计与学生学习行为相关的有价值的模式,因此教育领域的研究不断扩大。教育数据挖掘可以被教育机构用来评估学生的表现,帮助机构认识到学生的成就。在DM中,分类是一种众所周知的技术,经常用于确定学生的成绩。本文介绍了信息管理在高校IMS开发中的过程和关联规则的应用研究。结果表明,该课程覆盖了整个领域,最小事务支持数为2,minconf = 70%。结果还表明,选择一门课程的学生也倾向于选择另一门课程。数据决策理论在高校信息管理中的应用,将极大地提高管理人员的数据分析能力,提高管理水平。
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来源期刊
Journal of Intelligent Systems
Journal of Intelligent Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-
CiteScore
5.90
自引率
3.30%
发文量
77
审稿时长
51 weeks
期刊介绍: The Journal of Intelligent Systems aims to provide research and review papers, as well as Brief Communications at an interdisciplinary level, with the field of intelligent systems providing the focal point. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. It covers contributions from the social, human and computer sciences to the analysis and application of information technology.
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