Abstract
The methods and techniques introduced in the previous chapters provide a basic means to aggregate the preferences of individual group members and to determine recommendations suitable for the whole group. However, preference aggregation can go beyond the integration of the preferences of individual group members. In this chapter, we show how to take into account the aspects of personality, emotions, and group dynamics when determining item predictions for groups. We summarize research related to the integration of these aspects into recommender systems, and provide some selected examples.