MusicFX: an arbiter of group preferences for computer supported collaborative workouts
CSCW '98 Proceedings of the 1998 ACM conference on Computer supported cooperative work
Flytrap: intelligent group music recommendation
Proceedings of the 7th international conference on Intelligent user interfaces
Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers
User Modeling and User-Adapted Interaction
An Accurate and Scalable Collaborative Recommender
Artificial Intelligence Review
User Modeling and User-Adapted Interaction
PolyLens: a recommender system for groups of users
ECSCW'01 Proceedings of the seventh conference on European Conference on Computer Supported Cooperative Work
Building CBR systems with jcolibri
Science of Computer Programming
A Case-Based Song Scheduler for Group Customised Radio
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Collaborative filtering adapted to recommender systems of e-learning
Knowledge-Based Systems
Personality aware recommendations to groups
Proceedings of the third ACM conference on Recommender systems
Content-based recommendation systems
The adaptive web
Personality and Social Trust in Group Recommendations
ICTAI '10 Proceedings of the 2010 22nd IEEE International Conference on Tools with Artificial Intelligence - Volume 02
Dynamic adaptation of numerical attributes in a user profile
Applied Intelligence
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In this paper we introduce our application HappyMovie, a Facebook application for movie recommendation to groups. This system takes advantage of social data available in this social network to promote fairness for the provided recommendations. Group recommendations are based in the individual satisfaction of each individual. The (in)satisfaction of users modifies the typical aggregation functions used to estimate the value of an item for the group. This paper proposes a memory of past recommendations to compute the satisfaction of users when similar items (movies, in this case) are recommended several times.