Virtual user approach for group recommender systems using precedence relations
We describe virtual user strategy and then examine its properties. The experimental results show that virtual strategy achieve better Precision and Recall. We propose incremental algorithms to update virtual user profile. A new measure called monotonicity is introduced to judge the efficiency of a recommender system. Virtual-user profile + Monotonicity yield recommendations having higher accuracy on benchmark datasets.
virtual user recommender system precedence relation