STOC '98 Proceedings of the thirtieth annual ACM symposium on Theory of computing
Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
A Microeconomic View of Data Mining
Data Mining and Knowledge Discovery
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
IEEE Transactions on Knowledge and Data Engineering
Journal of the ACM (JACM)
A microeconomic data mining problem: customer-oriented catalog segmentation
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Decision support system induced guidance for model formulation and solution
Decision Support Systems
Mining typical patterns from databases
Information Sciences: an International Journal
Catalog segmentation with double constraints in business
Pattern Recognition Letters
Evolutionary approach to the development of decision support systems in the movie industry
Decision Support Systems
Spatially enabled customer segmentation using a data classification method with uncertain predicates
Decision Support Systems
An effective customer oriented E-catalog method in OKP
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Designing customer-oriented catalogs in e-CRM using an effective self-adaptive genetic algorithm
Expert Systems with Applications: An International Journal
A semantic query approach to personalized e-catalogs service system
Journal of Theoretical and Applied Electronic Commerce Research
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We consider in this paper the customer-oriented catalog segmentation problem that consists of designing K catalogs, each of size r products that maximize the number of covered customers. A customer is covered if he/she has interest in at least the specified minimum number of products in one of the catalogs. The problem addresses the crucial issue of the design of the actual contents of the catalogs that serves as a back-end to catalog production for the purpose of more focused design of catalogs as a targeted marketing tool. We developed two algorithms to solve the problem. Results of an extensive computational study using real and synthetic data sets show that one of the proposed algorithms outperforms the state-of-the-art algorithm found in the literature in terms of customer coverage, resulting potentially in significant increase in organization profit. In the spirit of the guidance role that a Decision Support System (DSS) should play by recommending alternative, satisfactory solutions to the decision maker, the prototype of a DSS integrating all three algorithms is presented to provide the decision maker with an easy-to-use, yet powerful tool to examine various catalog design options and their implications on the contents of the catalogs and the clusters of covered customers.