This thesis focusses on the study of AI techniques which improve the performance of recommender systems. Initially, a detailed analysis of the current state- of-the-art in this field has been carried out. This work has been organised as a taxonomy where existing recommender systems on the Internet are classified. Secondly, this thesis proposes a new CBR approach to recommendation. CBR is suitable for recommender systems due to its being based on experience and human reasoning. A forgetting mechanism is also proposed for case-based profiles that controls the relevance and age of...
This thesis focusses on the study of AI techniques which improve the performance of recommender systems. Initially, a detailed analysis of the curre...