发明名称 Analysis of clustering solutions
摘要 A computing system determines incremental values associated with a plurality of clustering solutions. Each of the clustering solutions groups stores of a retailer into clusters in a different way. For each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution. The computing system then determines, based on the incremental values associated with the plurality of clustering solutions, the appropriate number of clusters. The clustering solutions that group the stores into more or fewer clusters than the appropriate number of clusters tend to be associated with incremental values that are the same or lower than the clustering solutions that group the stores into the appropriate number of clusters.
申请公布号 US9412109(B2) 申请公布日期 2016.08.09
申请号 US201213677996 申请日期 2012.11.15
申请人 Target Brands, Inc. 发明人 Nelson James Carl;Ranganathan Raja;Sharma Abhijit;Sands Zachary George
分类号 G06F7/00;G06F17/30;G06Q30/00;G06Q10/06 主分类号 G06F7/00
代理机构 Shumaker & Sieffert, P.A. 代理人 Shumaker & Sieffert, P.A.
主权项 1. A method comprising: determining, by a computing system, incremental values associated with a plurality of clustering solutions, wherein each of the clustering solutions groups stores of a retailer into clusters in a different way, wherein for each clustering solution in the plurality of clustering solutions, the incremental value associated with the clustering solution indicates a difference between an estimated revenue associated with the clustering solution and revenue associated with a baseline clustering solution, wherein determining the incremental values associated with the plurality of clustering solutions comprises, for each respective clustering solution from the plurality of clustering solutions: determining, by the computing system, incremental values associated with each of the clusters into which the respective clustering solution groups the stores, wherein the incremental value associated with each of the clusters into which the respective clustering solution groups the stores is an aggregation of incremental values associated with the stores in the cluster, and the incremental value associated with each store in the cluster is an estimated change in a revenue of the store if a current assortment of items in the store is swapped with another assortment of items; and determining, by the computing system, the incremental value associated with the respective clustering solution based on a sum of the incremental values associated with each of the clusters into which the respective clustering solution groups the stores; determining, by the computing system and based on the incremental values associated with the plurality of clustering solutions, an appropriate number of clusters into which to group the stores of the retailer, wherein the appropriate number of clusters corresponds to a turning point of a best fit curve through a plurality of points, each respective point of the plurality of points corresponding to a respective clustering solution of the plurality of clustering solutions, the respective point having a first coordinate corresponding to a number of clusters associated with the respective clustering solution and a second coordinate corresponding to the incremental value associated with the respective clustering solution; selecting, based at least on part on the appropriate number of clusters, a particular clustering solution in the plurality of clustering solutions; and distributing, based at least in part on the particular clustering solution, merchandise to the stores.
地址 Minneapolis MN US