On saying “Enough already!” in SQL
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Optimal aggregation algorithms for middleware
PODS '01 Proceedings of the twentieth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Combining fuzzy information: an overview
ACM SIGMOD Record
Cumulated gain-based evaluation of IR techniques
ACM Transactions on Information Systems (TOIS)
Adaptive Processing of Top-k Queries in XML
ICDE '05 Proceedings of the 21st International Conference on Data Engineering
IEEE Transactions on Knowledge and Data Engineering
PolyLens: a recommender system for groups of users
ECSCW'01 Proceedings of the seventh conference on European Conference on Computer Supported Cooperative Work
The adaptive web
Crowds, clouds, and algorithms: exploring the human side of "big data" applications
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Evaluating, combining and generalizing recommendations with prerequisites
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
Enhancing group recommendation by incorporating social relationship interactions
Proceedings of the 16th ACM international conference on Supporting group work
Space efficiency in group recommendation
The VLDB Journal — The International Journal on Very Large Data Bases
TopRecs: Top-k algorithms for item-based collaborative filtering
Proceedings of the 14th International Conference on Extending Database Technology
A survey on representation, composition and application of preferences in database systems
ACM Transactions on Database Systems (TODS)
Information seeking: convergence of search, recommendations, and advertising
Communications of the ACM
Double-sided recommendations: a novel framework for recommender systems
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
Proceedings of the fifth ACM conference on Recommender systems
Design guidelines for mobile group recommender systems to handle inaccurate or missing location data
Proceedings of the fifth ACM conference on Recommender systems
PICASSO: automated soundtrack suggestion for multi-modal data
Proceedings of the 20th ACM international conference on Information and knowledge management
On the complexity of package recommendation problems
PODS '12 Proceedings of the 31st symposium on Principles of Database Systems
gRecs: a group recommendation system based on user clustering
DASFAA'12 Proceedings of the 17th international conference on Database Systems for Advanced Applications - Volume Part II
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 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
In the Mood4: recommendation by examples
Proceedings of the 16th International Conference on Extending Database Technology
Probabilistic group recommendation via information matching
Proceedings of the 22nd international conference on World Wide Web
Question routing to user communities
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
GBPR: group preference based Bayesian personalized ranking for one-class collaborative filtering
IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence
Modeling and exploiting collaborative traces in web-based collaborative working environment
Computers in Human Behavior
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We study the problem of group recommendation. Recommendation is an important information exploration paradigm that retrieves interesting items for users based on their profiles and past activities. Single user recommendation has received significant attention in the past due to its extensive use in Amazon and Netflix. How to recommend to a group of users who may or may not share similar tastes, however, is still an open problem. The need for group recommendation arises in many scenarios: a movie for friends to watch together, a travel destination for a family to spend a holiday break, and a good restaurant for colleagues to have a working lunch. Intuitively, items that are ideal for recommendation to a group may be quite different from those for individual members. In this paper, we analyze the desiderata of group recommendation and propose a formal semantics that accounts for both item relevance to a group and disagreements among group members. We design and implement algorithms for efficiently computing group recommendations. We evaluate our group recommendation method through a comprehensive user study conducted on Amazon Mechanical Turk and demonstrate that incorporating disagreements is critical to the effectiveness of group recommendation. We further evaluate the efficiency and scalability of our algorithms on the MovieLens data set with 10M ratings.