Data mining algorithm of experiential sports marketing based on cloud computing technology

IF 0.5 Q4 ENGINEERING, MULTIDISCIPLINARY Journal of Computational Methods in Sciences and Engineering Pub Date : 2023-06-20 DOI:10.3233/jcm-226908
Mengzhong Chen, Guixian Tian, Y. Tao
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引用次数: 0

Abstract

The internal connection and rule diversification of experience marketing data make it difficult to predict the future trend of data. Therefore, it is necessary to mine sports marketing data to guide future marketing strategies. In order to improve the effect of sports marketing data mining, this paper puts forward the algorithm research of experience sports marketing data mining in the cloud computing environment. In the cloud computing environment, based on the idea of data mining, a sports marketing monitoring system is designed and implemented to obtain a large number of evaluation data. The related data is extracted from the database of sports marketing evaluation system, and the data warehouse is constructed by data preprocessing. Using association rule algorithm to realize the data mining module of sports marketing evaluation system, mining the data in the data warehouse, dividing the data set into various data blocks, and then scanning each data block for association rule mining. The experimental results show that the mining algorithm can effectively mine different factors that affect the marketing status. The customer satisfaction obtained after the practical application of this method reaches more than 90%. Sports marketing enterprises can establish benign interaction between users and enterprises according to the mining results of this method, further meet the personalized and differentiated needs of consumers, thereby expanding the influence of enterprises and promoting the realization of marketing.
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基于云计算技术的体验式体育营销数据挖掘算法
体验营销数据的内在联系和规则多样化,使得数据的未来趋势难以预测。因此,有必要挖掘体育营销数据来指导未来的营销策略。为了提高体育营销数据挖掘的效果,本文提出了云计算环境下体验式体育营销数据的挖掘算法研究。在云计算环境下,基于数据挖掘的思想,设计并实现了一个体育营销监控系统,以获取大量的评价数据。从体育营销评价系统数据库中提取相关数据,通过数据预处理构建数据仓库。利用关联规则算法实现体育营销评价系统的数据挖掘模块,对数据仓库中的数据进行挖掘,将数据集划分为各种数据块,然后扫描每个数据块进行关联规则挖掘。实验结果表明,该挖掘算法能够有效地挖掘出影响营销状况的不同因素。该方法实际应用后,客户满意度达到90%以上。体育营销企业可以根据这种方法的挖掘结果,在用户和企业之间建立良性互动,进一步满足消费者个性化、差异化的需求,从而扩大企业影响力,促进营销的实现。
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来源期刊
CiteScore
0.80
自引率
0.00%
发文量
152
期刊介绍: The major goal of the Journal of Computational Methods in Sciences and Engineering (JCMSE) is the publication of new research results on computational methods in sciences and engineering. Common experience had taught us that computational methods originally developed in a given basic science, e.g. physics, can be of paramount importance to other neighboring sciences, e.g. chemistry, as well as to engineering or technology and, in turn, to society as a whole. This undoubtedly beneficial practice of interdisciplinary interactions will be continuously and systematically encouraged by the JCMSE.
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