A Collaborative Filtering Recommender Algorithm Based On the User Interest Model

To cope with the transfer of user interest and improve the accurate of prediction in recommender system, this paper proposes a Dynamic User-Interest-Model (DUIM). The model adopts the memory curve equation to address the influence of time factor. Users' long term interest and short term interest can be embodied clearly in this model. Based on the model, the paper presents a novel collaborative filtering recommender algorithm (Model-based Collaborative Filtering Recommender Algorithm, MCF). Experiments prove that MCF gets better prediction and higher time efficiency compared with other similar algorithms.