Discovery knowledge of user preferences: Ontologies in fashion design recommender agent system

Solutions for filtering the WWW exist, but they are hampered by the difficulty of discovery knowledge of user preferences in such a dynamic environment. We explore an ontological approach to discovery knowledge of user preference in fashion design recommender agent system. Information filtering can be used for the discovery knowledge of user preference and is therefore a key-technology for the construction of personalized recommeder system. In this paper, we focus in the application of hybrid collaborative filtering and content-based filtering to improve the performance. And we validate our web based fashion design recommender agent system according to discovery knowledge of user preference in on-line experiments. Design merchandizing may meet the consumer's needs more exactly and easily.