Communications of the ACM
MusicFX: an arbiter of group preferences for computer supported collaborative workouts
CSCW '98 Proceedings of the 1998 ACM conference on Computer supported cooperative work
Rank aggregation methods for the Web
Proceedings of the 10th international conference on World Wide Web
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
IEEE Transactions on Knowledge and Data Engineering
Ordering by weighted number of wins gives a good ranking for weighted tournaments
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
TV Program Recommendation for Multiple Viewers Based on user Profile Merging
User Modeling and User-Adapted Interaction
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
Group modeling in a public space: methods, techniques, experiences
AIC'05 Proceedings of the 5th WSEAS International Conference on Applied Informatics and Communications
Introduction to Information Retrieval
Introduction to Information Retrieval
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Hybrid web recommender systems
The adaptive web
The adaptive web
Group-based recipe recommendations: analysis of data aggregation strategies
Proceedings of the fourth ACM conference on Recommender systems
Informative household recommendation with feature-based matrix factorization
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
SVD-based group recommendation approaches: an experimental study of Moviepilot
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
Mining relational context-aware graph for rater identification
Proceedings of the 2nd Challenge on Context-Aware Movie Recommendation
Towards effective group recommendations for microblogging users
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Generating recommendations for consensus negotiation in group personalization services
Personal and Ubiquitous Computing
Exploring social influence for recommendation: a generative model approach
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Design and evaluation of a group recommender system
Proceedings of the sixth ACM conference on Recommender systems
Exploring personal impact for group recommendation
Proceedings of the 21st ACM international conference on Information and knowledge management
Social factors in group recommender systems
ACM Transactions on Intelligent Systems and Technology (TIST) - Special section on twitter and microblogging services, social recommender systems, and CAMRa2010: Movie recommendation in context
Contextual recommendations for groups
ER'12 Proceedings of the 2012 international conference on Advances in Conceptual Modeling
Fast group recommendations by applying user clustering
ER'12 Proceedings of the 31st international conference on Conceptual Modeling
A group recommendation approach for service selection
Proceedings of the Fourth Asia-Pacific Symposium on Internetware
A group recommender for movies based on content similarity and popularity
Information Processing and Management: an International Journal
Tailoring recommendations to groups of users: a graph walk-based approach
Proceedings of the 2013 international conference on Intelligent user interfaces
Knowledge-Based Systems
Incorporating group recommendations to recommender systems: Alternatives and performance
Information Processing and Management: an International Journal
Probabilistic group recommendation via information matching
Proceedings of the 22nd international conference on World Wide Web
Location-aware music recommendation using auto-tagging and hybrid matching
Proceedings of the 7th ACM conference on Recommender systems
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The majority of recommender systems are designed to make recommendations for individual users. However, in some circumstances the items to be selected are not intended for personal usage but for a group; e.g., a DVD could be watched by a group of friends. In order to generate effective recommendations for a group the system must satisfy, as much as possible, the individual preferences of the group's members. This paper analyzes the effectiveness of group recommendations obtained aggregating the individual lists of recommendations produced by a collaborative filtering system. We compare the effectiveness of individual and group recommendation lists using normalized discounted cumulative gain. It is observed that the effectiveness of a group recommendation does not necessarily decrease when the group size grows. Moreover, when individual recommendations are not effective a user could obtain better suggestions looking at the group recommendations. Finally, it is shown that the more alike the users in the group are, the more effective the group recommendations are.