Applying Expert Knowledge and Social Imformation to Product Recommendations in E-Commerce

The advance of Internet and Web technologies has boosted the development of electronic commerce. More and more people have changed their traditional trading behaviors and conducted Internet shopping. However, the exponentially increasing product information provided by Internet enterprises causes the problem of information overload, and this inevitably reduces the customer's satisfaction and loyalty. To over come this problem, in this paper we proposed an intelligent agent-based system that is capable of recommending optimal products based on the built-in knowledge and the customer's preferences obtained from the system-consumer interactions. In addition, the system also uses social information collected from previous consumers to predict what the current consumer may expect. Experiments have been conducted and the results show that our system can give sensible recommendations, and it is able to adapt to the most up-to-date preferences for the customers.