One of the main current applications of intelligent systems is recommender systems (RS).
RS can help users to find relevant items in huge information spaces in a personalized way …

Recommender systems aim at filtering large amounts of information for users, providing
them with those pieces of information which better meet their preferences or needs. Such …

The focus of this work is on the problem of team recommendations, in which teams have
multidisciplinary requirements and team members' selection is based on the match of their …

Recommender systems have focused on algorithms for a recommendation for individuals.
However, in many domains, it may be recommending an item, for example, movies …

Recommender systems (RSs) have emerged as a solution to the information overload
problem by filtering and presenting the users with information, services etc. according to …

Existing group recommender systems utilize attention mechanisms to identify critical users
who influence group decisions the most. We analyzed user attention scores from a widely …

Many recommender systems frequently make suggestions for group consumable items to
the individual users. There has been much work done in group recommender systems …

In this paper, we deal with group recommendations where the task is to choose a sequence
of natural attractions that better matches the expectation of a group of tourists. We show in …

This paper focuses on the recommendation problem from the perspective of hierarchical
heterogeneous portfolios. These portfolios consist of several base recommenders. Each of …

This paper focuses on recommending items to group of users rather than individual users.
To model group profile, existing researches almost aggregate preferences of members into …