一种改进的量化关联规则算法在零售业中的应用  

An Improved Algorithm of Quantitative Association Rule with Application in Retail

作　　者：陈思敏[1] 邢延[1] 

机构地区：[1]广东工业大学自动化学院,广州510006

出　　处：《电脑编程技巧与维护》2011年第6期24-25,34,共3页Computer Programming Skills & Maintenance

摘　　要：以超市的量化属性为研究对象,提出一种基于模糊聚类和减类聚类的量化关联规则算法。该算法基本思想是把模糊聚类技术融入到离散化过程中,使数据离散到合理的区间,再利用经典的布尔关联规则挖掘算法Apriori进行挖掘。实验证明,这种方法能够有效挖掘量化关联规则,提高交叉销售的可能性。An improved algorithm of mining quantitative association rule based on quantitative attributes in supermarket is used in this paper.By combining with fuzzy C-means cluster method,a available discrete algorithm can be finished and Apriori algotithm is used to data mining associations.Empirical results show that this method can make Mining association rule and improves the probability of cross-selling success.

关 键 词：零售业 交叉销售 量化关联规则 模糊聚类 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]