查看文章

In this study, a new dynamic fuzzy group recommender system (DFGRS) is investigated, which aims to deal with some critical challenges in the group recommender system (GRS), including the user preference uncertainty, item attractiveness tendency, and group members’ interaction and fairness. The proposed approach of the DFGRS applies intuitionistic fuzzy sets (IFSs) to represent user preferences on the considered items by taking into account user hesitancy and inconsistency in ratings. It also incorporates a novel dynamic similarity mechanism for taking into account users’ preference tendency and item attractiveness in predicting unknown user-item preferences. The model’s parameters are optimized using a modified Bayesian method. This combination creates a more realistic and concise prediction of unknown user ratings. Then, to form a balanced solution in the consensus phase of the DFGRS, an …