GroupLens: applying collaborative filtering to Usenet news
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
Hybrid Recommender Systems: Survey and Experiments
User Modeling and User-Adapted Interaction
Group Modeling: Selecting a Sequence of Television Items to Suit a Group of Viewers
User Modeling and User-Adapted Interaction
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
TV Program Recommendation for Multiple Viewers Based on user Profile Merging
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
Distributed collaborative filtering with domain specialization
Proceedings of the 2007 ACM conference on Recommender systems
A group recommendation system with consideration of interactions among group members
Expert Systems with Applications: An International Journal
Case-Based Group Recommendation: Compromising for Success
ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
Aggregation Trade Offs in Family Based Recommendations
AI '09 Proceedings of the 22nd Australasian Joint Conference on Advances in Artificial Intelligence
The adaptive web
Cooperating search communities
AH'06 Proceedings of the 4th international conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Group recommendations with rank aggregation and collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
Proceedings of the fifth ACM conference on Recommender systems
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
Generating recommendations for consensus negotiation in group personalization services
Personal and Ubiquitous Computing
Design and evaluation of a group recommender system
Proceedings of the sixth ACM conference on Recommender systems
User requirements and design guidelines for digital restaurant menus
Proceedings of the 7th Nordic Conference on Human-Computer Interaction: Making Sense Through Design
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
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
A food recommender for patients in a care facility
Proceedings of the 7th ACM conference on Recommender systems
Hybreed: A software framework for developing context-aware hybrid recommender systems
User Modeling and User-Adapted Interaction
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Collaborative filtering recommendations were designed primarily for individual user models and recommendations. However, nowadays more and more scenarios evolve, in which the recommended items are consumed by groups of users rather than by individuals. This raises the need to uncover the most appropriate group-based collaborative filtering recommendation strategy. In this work we investigate the use of aggregated group data in collaborative filtering recipe recommendations. We present results of a study that exploits recipe ratings provided by families of users, in order to evaluate the accuracy of several group recommendation strategies and weighting models, and analyze the impact of switching strategies, data aggregation heuristics, and group characteristics on the performance of recommendations.