数据挖掘中关联规则在零售业中的应用

Application of Association Rules in Data Mining in the Retail

目前,在需要处理大量数据的科研领域中,数据挖掘受到越来越多的关注。我们可以利用数据挖掘技术从海量数据中发现有用信息,帮助商家了解客户以往的需求趋势,并预测未来,从而给商家带来巨大的利润。在国内很多领域,尤其在银行、零售(如超市)等商业领域,数据挖掘所能解决的典型问题包括:客户群体划分、应用背景分析、销售额分析等市场分析行为,以及客户流失性分析、客户信用积分等。在数据挖掘领域,采用关联规则在大型事务数据库中进行数据挖掘是一个重要的研究内容。

At present, a large amount of data that needed to be processed in the field of scientific research.More and more people pay attentions to data mining.We can use data mining technology to find useful information from the mass data to help businesses understand the needs of customers and predict the future, so as to give business a huge profit.Many areas in China, especially in the banking, retail （eg supermarkets）, such as business, data mining can solve the typical problems including：customer groups divided,the application background analysis ,sales analysis, market analysis, as well as the loss of customers analysis, such as customer credit points.In the field of data mining, using association rules in large transaction database is an important study.