Prototyping a recommendation system for Ukiyo-e using hybrid recommendation algorithm

This paper introduces a recommendation system for Ukiyo-e prints. Although there are some services available online which recommends Ukiyo-e prints to users, they have not supported a recommendation function, yet. To meet the complex preferences of the users, the hybrid algorithm can fit as a feasible solution to realize the Ukiyo-e recommendation. In this paper, our prototype recommendation system for Ukiyo-e using it is proposed. Our proposed system adapts item-based collaborative filtering, user-based collaborative filtering and popularity-based filtering to predict which Ukiyo-e prints the user may like to view. Also this paper addresses the cold start problem and ways to profile users when limited authentication information is available.