基于Apriori算法的购物篮关联规则分析

数据挖掘是适应信息社会从海量的数据库中提取信息的需要而产生的新学科。它是统计学、机器学习、数据库、模式识别、人工智能等学科的交叉。IT就业市场竞争已经相当激烈,而数据处理的核心技术——数据挖掘更是得到了前所未有的重视。关联规则一般用以发现交易数据库中不同商品(项)之间的联系,用这些规则找出顾客的购买行为模式,比如购买了某一种商品对购买其他商品的影响,这种规则可以应用于超市商品货架设计、货物摆放以及根据购买模式对用户进行分类等。通过发现这个关联的规则,可以更好地了解和掌握事物的发展、动向等。在市场营销、企业投资中具有重要的作用。

Apriori Algorithm Based on Association Rules Analysis of the Shopping Basket

Data mining is the new discipline evolved due to the need of information retrieval from immense amount of data in databases.It relates to subjects in statistics,machine learning,database technique,pattern recognition,artificial intelligence,etc.The competition in IT jobs market is enormous,and data mining-the core technique in data processingis gaining more and more attention.Association rules are commonly used to figure out what relations exist between different data sets in transactional databases and to find out further the customers′purchasing behavior pattern,for example,the influence on customers′buying other products after having bought some kind of products.These rules can be applied in supermarkets to product shelf design,goods deposit and classification of customers according to customers′purchasing pattern.Through discovering of the association rules the development and trend of the underlying objects can be better realized and mastered.In marketing and business investment data mining plays an important role.