STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
The 2-catalog segmentation problem
Proceedings of the tenth annual ACM-SIAM symposium on Discrete algorithms
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
A Microeconomic View of Data Mining
Data Mining and Knowledge Discovery
Item selection by "hub-authority" profit ranking
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining customer product ratings for personalized marketing
Decision Support Systems - Special issue: Web data mining
A microeconomic data mining problem: customer-oriented catalog segmentation
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Customer-oriented catalog segmentation: effective solution approaches
Decision Support Systems
| Hi-index | 0.10 |
Catalog segmentation is an important issue in data mining in business from the microeconomic point of view. In catalog segmentation, an enterprise tries to develop k catalogs with r products that are sent to corresponding customers in order to maximize the overall number of catalog products purchased. In this paper, a novel model called catalog segmentation problem with double constraints (DCCSP) is presented. In this model, the interest constraint is minimized and the profit constraint is maximized so that the profit of products purchased by customers who have at least t interesting products in receiving catalogs is maximized. The complexity of the DCCSP is analyzed, and a DCCS algorithm to solve the optimization is proposed. The experimental results show that the proposed algorithm is efficient and can be used to solve the DCCSP effectively.