关联和聚类分析在数据挖掘中应用

发布时间：2018-08-03 20:37

【摘要】：随着互联网技术的快速发展,各行业竞争也日趋激烈,客户已成为关系企业成败的最重要资源,理解不同消费群体的购物习惯、价格观念是市场营销成功的关键,聪明的商家会根据不同的消费者群体来制定有效的市场营销策略,包括优化商品布局、设计促销方案,使商场布局更加符合消费者购物习惯,从而提高商家业绩和利润,也为消费者带来更多的方便。本文以零售业为例,探讨了关联规则和聚类分析在数据挖掘中的应用。首先,介绍了数据挖掘概况及其特点；其次,给出了关联规则的相关理论,重点介绍了Aprior算法；再次,给出了聚类分析相关知识和主要算法,重点介绍了系统聚类法和快速聚类法；最后,为了更好地理解关联和聚类分析在数据挖掘中应用,本文选取了某商业区10家之佳便利店一个月的顾客购物记录数据作为研究对象,利用SQL对数据进行预处理,使用SPSS软件对数据进行关联规则和聚类分析,通过聚类分析,本文把客户分成四类,并对相应结果进行合理解释。数据挖掘是一个反复尝试以便找出规则解释现象的过程,它需要熟练掌握挖掘算法和了解具体的行业背景。本文挖掘的规则对超市实施正确的营销方案起了很大的现实指导意义。
[Abstract]:With the rapid development of Internet technology, the competition in various industries is becoming more and more fierce. Customers have become the most important resource related to the success or failure of enterprises. To understand the shopping habits of different consumer groups, the price concept is the key to the success of marketing. Smart businesses make effective marketing strategies based on different consumer groups, including optimizing product layout, designing promotional programs, making store layout more in line with consumer shopping habits, and thus improving business performance and profits. It also brings more convenience to consumers. This paper discusses the application of association rules and clustering analysis in data mining. Firstly, the general situation and characteristics of data mining are introduced. Secondly, the related theory of association rules is given, and the Aprior algorithm is emphasized. Thirdly, the related knowledge and main algorithms of clustering analysis are given. Finally, in order to better understand the application of association and cluster analysis in data mining, the system clustering method and fast clustering method are introduced. In this paper, the customer shopping record data of 10 best convenience stores in a commercial district are selected as the research object. The data are preprocessed by SQL, association rules and clustering analysis are carried out by SPSS software, and the data are analyzed by clustering analysis. This article divides the customer into four categories, and carries on the reasonable explanation to the corresponding result. Data mining is a process of repeatedly trying to find out the phenomenon of rule interpretation. It requires mastering the mining algorithm and understanding the specific background of the industry. This article excavates the rule to the supermarket to carry out the correct marketing plan to play the very big realistic guiding significance.
【学位授予单位】：云南大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：TP311.13

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