Analysis on Merchandise Hierarchy via Clustering Retail Records
Merchandise hierarchy plays an important role in modern retail business.In this paper,we suggest a quantitative consumer-related evaluation method of merchandise hierarchy via clustering the retail records.The retail records contains much information reflecting the consumer buying behavior,and it should be effectively utilized to judge whether a predefined merchandise hierarchy is appropriate for a specific retailers business.Here,we mainly mine the complementary information between products from the retail records,that reflect some crucial consumer buying habits and can be used to evaluate predefined merchandise hierarchy.Concretely,the spectral clustering algorithm is adopted to obtain the cluster assignments of items on each level of merchandise hierarchy and Normalized Mutual Information is used to compare the cluster results and the corresponding merchandise hierarchy.We conduct some experiments on a real supermarket retail records and get some interesting and valuable consumer insights.Besides the merchandise hierarchy evaluation work,we further provide a preliminary scheme that can refine the merchandise hierarchy by clustering the retail records.
merchandise hierarchy clustering consumer buying behavior
Xinxin Bai Hairong Lv Wenjun Yin Jin Dong Gang Chen
IBM China Research LaboratoryBeijing,China IBM China Research Laboratory Tsinghua University Beijing,China
国际会议
北京
英文
2008-10-12（万方平台首次上网日期，不代表论文的发表时间）