A microeconomic data mining problem: customer-oriented catalog segmentation

The microeconomic framework for data mining [7] assumes that an enterprise chooses a decision maximizing the overall utility over all customers where the contribution of a customer is a function of the data available on that customer. In Catalog Segmentation, the enterprise wants to design k product catalogs of size r that maximize the overall number of catalog products purchased. However, there are many applications where a customer, once attracted to an enterprise, would purchase more products beyond the ones contained in the catalog. Therefore, in this paper, we investigate an alternative problem formulation, that we call Customer-Oriented Catalog Segmentation, where the overall utility is measured by the number of customers that have at least a specified minimum interest t in the catalogs. We formally introduce the Customer-Oriented Catalog Segmentation problem and discuss its complexity. Then we investigate two different paradigms to design efficient, approximate algorithms for t...

• Type: Conference
• Year: 2004
• Where: KDD
• Authors: Martin Ester, Rong Ge, Wen Jin, Zengjian Hu
• Keywords: Catalog Segmentation Algorithms, Catalog Segmentation Problem, Customer-Oriented Catalog Segmentation, Data Mining, KDD 2004