A strategy-oriented operation module for recommender systems in E-commerce

Electronic commerce (EC) has become an important support for business and is regarded as an efficient system that connects suppliers with online users. Among the applications of EC, a recommender system (RS) is undoubtedly a popular issue to make the best recommendation to the users. Even if many approaches have been proposed to perfect the recommendation, a comprehensive module comprising of essential sub-modules of input profiles, a recommendation scheme, and an output interface of recommendations in the RS is still lacking. Besides, the fundamental issue of profit consideration for an EC company is not stressed in general terms. Therefore, this study aims to construct an RS with a strategy-oriented operation module regarding the above aspects; and with this module, an approach named clique-effects collaborative filtering (CECF) for predicting the consumer's purchase behavior was proposed. Finally, we applied our proposed module to a 3C retailer in Taiwan, and promising results were obtained.Scope and PurposeThis study aims to construct a comprehensive module for the recommender systems. The proposed strategy-oriented operation module comprises the essential parts of a recommender system. By utilizing the proposed module with marketing strategies and an effective on-line interface scheme, the recommender system could emphasize not only the customer's satisfaction as conventional recommender system suggested, but also the supplier's profit which shall be an important issue to an E-commerce company. Thus, a better recommendation environment could be displayed.