Group recommender systems (GRSs) identify items to recommend to a group of people by aggregating group members’ individual preferences into a group profile and selecting the items that have the largest score in the group profile. The GRS predicts that ...

Recommender Systems (RecSys) provide suggestions in many decision-making processes. Given that groups of people can perform many real-world activities (e.g., a group of people attending a conference looking for a place to dine), the need for ...

In many settings, it is required that items are recommended to a group of users instead of a single user. Most often, when the decision criteria and preferences of the group as a whole are not known, the gold standard is to aggregate individual member ...

In many settings it is required that items are recommended to a group of users instead of a single user. Conventionally, the objective is to maximize the overall satisfaction among group members. Recently, however, attention has shifted to ensuring that ...

Today most of existing personalization systems (e.g content recommenders, or targeted ad) focus on individual users and ignore the social situation in which the services are consumed However, many human activities are social and involve several ...

We model the aggregation process used by individual decision makers (DMs) who obtain probabilistic information from multiple, possibly nonindependent, sources. We distinguish between two qualitatively different aggregation approaches: compromising, by ...