A fuzzy approach to fulfilling personalized service through association rules derived from large databases

A fuzzy inference model is generated to fulfill the personalized service through mining the association rules from a large database in this paper. Instead of just considering whether interesting items have appeared in the same transaction, we also investigate other aspects, such as the purchased quantity, associated with the items. Based on the proposed model, our system can predict which items should be recommended to the prospective customers to realize the personalized service. How to derive the association rules from large database and how to apply the derived rules to establishing a fuzzy inference model are illustrated by simple examples.