Application of Association Rule Mining Algorithm based on 5G Technology in Information Management System

IF 0.9 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Juan Gao, Zidi Chen
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引用次数: 0

Abstract

In this paper, an application method of association rule mining algorithm based on 5G technology in information management system is proposed to solve the problems of long running time and low processing efficiency in traditional financial information processing system. The association rule mining algorithm's employment in information management systems is the main topic of this research study, which is based on 5G technology. The efficiency and efficacy of information management systems have a lot of room to grow with the introduction of 5G. Large datasets may be mined for patterns and associations using the potent approach known as association rule mining. We want to improve the performance of information management systems by fusing association rule mining with the capabilities of 5G technology. The experimental findings indicate that in the first group of trials, the traditional system’s time for information mining is identical to that of the developed system, which is around one minute. The typical system's time to mine financial information, however, steadily grows with the amount of experimental data. The difference between the two is most obvious in the sixth experiment. Because the design system can delve deeply into the financial information, the overall information mining time of the financial information management system based on the association rule mining algorithm of the design is shorter. It is confirmed that the system for automatically processing financial information described in this study has a high level of processing accuracy and a positive processing outcome.
基于5G技术的关联规则挖掘算法在信息管理系统中的应用
本文针对传统财务信息处理系统运行时间长、处理效率低的问题,提出了一种基于5G技术的关联规则挖掘算法在信息管理系统中的应用方法。基于5G技术的关联规则挖掘算法在信息管理系统中的应用是本研究的主要课题。随着5G的引入,信息管理系统的效率和功效有很大的增长空间。可以使用称为关联规则挖掘的有效方法来挖掘大型数据集的模式和关联。我们希望通过融合关联规则挖掘和5G技术的能力来提高信息管理系统的性能。实验结果表明,在第一组试验中,传统系统的信息挖掘时间与开发的系统相同,都在1分钟左右。然而,典型的系统挖掘金融信息的时间随着实验数据的数量而稳步增长。这两者的区别在第六个实验中最为明显。由于设计的系统能够深入挖掘财务信息,因此设计的基于关联规则挖掘算法的财务信息管理系统的整体信息挖掘时间较短。验证了本研究描述的财务信息自动处理系统具有较高的处理精度和良好的处理效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Scalable Computing-Practice and Experience
Scalable Computing-Practice and Experience COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.00
自引率
0.00%
发文量
10
期刊介绍: The area of scalable computing has matured and reached a point where new issues and trends require a professional forum. SCPE will provide this avenue by publishing original refereed papers that address the present as well as the future of parallel and distributed computing. The journal will focus on algorithm development, implementation and execution on real-world parallel architectures, and application of parallel and distributed computing to the solution of real-life problems.
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