Incorporating Affectivity into Preference Elicitation for Personalizesd Recommendation via Spreading Activation
Personalized recommender system is an indispensable application and re-shaping the world in e-commerce scopes. Following a brief review of approaches to elucidate personalized recommendation, our research work focuses on exploring a new approach of semantically associated extension by integrating the Spreading Activation model with the knowledge of chromatology to dynamically acquire the information of user preference. We attempt to apply a characteristic sequence consisted of color nodes mapping the relationships between user mood preference and item feature and illustrated the proposed approach through an instantiation of movie recommendation. This paper presents a novel insight into exploitation of rich repository of the domainspecific knowledge to elicit optimum recommendation for user.
cognitive psychology color sequence personalized recommendation spreading activation
Xiaohui Li Tomohiro Murata
Graduate School of Information,Production and System,Waseda University,808-0135,Japan
国际会议
上海
英文
268-273
2011-03-11（万方平台首次上网日期，不代表论文的发表时间）