摘要
购物篮分析是数据挖掘技术在零售业的典型应用之一,旨在从零售记录中分析出顾客经常同时购买商品的组合,挖掘出购物篮中有价值的信息。如今购物篮分析在零售业已经有了广泛的应用,包括商品的促销、摆架、物流等。通过与零售客户的详细沟通与调研,发现传统购物篮分析并不考虑商品之间的层次关系,并且将支持度作为评估购物篮的唯一指标,在实际应用中存在缺陷。针对传统购物篮分析的不足,文中提出一种带有约束条件的购物篮分析,定义了一种新的购物篮评估方法。通过对真实数据进行一系列实验研究与分析,得到了更有实际意义的购物篮,并且在算法复杂度与运行时间方面比传统购物篮分析算法有了很大提升。
Basket analysis is a typical application of data mining technology in retail industry. It aims to analyze customers＇ purchase pat- terns of goods from sales transactions and digs out the valuable information in the basket. Nowadays,basket analysis has been widely used in retail business, including sales promotion, pendulum shelf and logistics for goods. Through communication with retail customers, it is found that traditional basket analysis, which doesn＇ t consider the hierarchical relation between goods and takes the support degree as the unique index of evaluating basket, has some defects in real applications. In view of the deficiencies, a new basket analysis method with constraints is proposed and a new basket evaluation method is defined. Through a series of experiment research and analysis of real data, the basket with more practical significance is obtained, and the complexity and mn time of proposed algorithm is better than the traditional one.
出处
《计算机技术与发展》
2016年第8期69-74,共6页
Computer Technology and Development
基金
国家自然科学基金资助项目(61305059)
深圳大学青年教师科研启动项目(201432)
