Personalized Recommendation System for E-Commerce Based on Psychological Community

This paper attempts to do a research on personalized recommendation in a completely original way-a recommendation based on psychological community. On the basis of concept of psychology and theory of artificial psychology, we provide two methods to quantify personal psychological properties: client remark and Quantity I Theory. The system transforms a direct link between client and recommendable object into an indirect form, building psychological community between them. That is to say, no more do we seek to directly match clients with the objects they might be interested in, instead, the system sets up psychological community containing two attributes - client and recommendable object as a bridge to match the two together.