Design of Knowledge Based System for Direct Marketing

Since recommendation systems have been increasing gradually, it is difficult for decision makers to find the customers which interest them as well as representative lists. How to utilize meaningful information effectively to improve the service quality of recommendation system appears to be very important. The purpose of this paper is to provide recommendation system architecture to promote direct marketing services in electronic commerce. In the proposed architecture, a two-phase data mining process used by association rule and clustering methods is designed to generate a recommendation system. The process considers not only the relationship of a cluster of customers but also the associations among the information accessed. The recommendation supported by the proposed system architecture would be closely served to meet customers’ needs. This paper not only constructs a recommendation system for decision makers to search customers but takes the initiative in finding the most suitable customers for them as well. Furthermore, managers are expected to contact with core customers from a limited budget to maintain and satisfy the requirements along with promoting direct marketing. KeywordsDirect Marketing; Data Mining; Framework.