To meet individual needs of home design, a collaborative filtering recommendation
algorithm based on interaction history is presented in this paper. The algorithm has
been introduced into a mobile interactive 3D home design system. In the algorithm, user
historical interaction behavior is analyzed, and a new user interest model built. The model
converts user interaction behavior into a user interest matrix. To improve the recommendation
quality, two furniture item characteristics, i.e., timeliness and resource relevance,
are introduced into the generation process of the collaborative filtering recommendation
algorithm. The recommended items are applied to 3D virtual home design scene. The
home personalized design is completed by scene editing and virtual display. Experimental
results show that the proposed method is feasible. It can effectively improve recommendation
quality with better user experience and visual effects.