Fab: content-based, collaborative recommendation
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
An algorithmic framework for performing collaborative filtering
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Analysis of recommendation algorithms for e-commerce
Proceedings of the 2nd ACM conference on Electronic commerce
Flytrap: intelligent group music recommendation
Proceedings of the 7th international conference on Intelligent user interfaces
E-Commerce Recommendation Applications
Data Mining and Knowledge Discovery
Tailoring the Recommendation of Tourist Information to Heterogeneous User Groups
Revised Papers from the nternational Workshops OHS-7, SC-3, and AH-3 on Hypermedia: Openness, Structural Awareness, and Adaptivity
Sparsity, scalability, and distribution in recommender systems
Sparsity, scalability, and distribution in recommender systems
Evaluating collaborative filtering recommender systems
ACM Transactions on Information Systems (TOIS)
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
IEEE Transactions on Knowledge and Data Engineering
Talk to me: foundations for successful individual-group interactions in online communities
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
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
Web Personalization as a Persuasion Strategy: An Elaboration Likelihood Model Perspective
Information Systems Research
Design science in information systems research
MIS Quarterly
Empirical analysis of predictive algorithms for collaborative filtering
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
Evaluation of a personalized digital library based on cognitive styles: Adaptivity vs. adaptability
International Journal of Information Management: The Journal for Information Professionals
New learning network paradigms: Communities of objectives, crowdsourcing, wikis and open source
International Journal of Information Management: The Journal for Information Professionals
Automated user modeling for personalized digital libraries
International Journal of Information Management: The Journal for Information Professionals
Online business: tailoring your business environment in order to compete
International Journal of Information Management: The Journal for Information Professionals
Space efficiency in group recommendation
The VLDB Journal — The International Journal on Very Large Data Bases
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
A literature review and classification of recommender systems research
Expert Systems with Applications: An International Journal
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
Recommending QA documents for communities of question-answering websites
ACIIDS'13 Proceedings of the 5th Asian conference on Intelligent Information and Database Systems - Volume Part II
Recommendation in Online Health Communities
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
QA document recommendations for communities of question-answering websites
Knowledge-Based Systems
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Online communities are virtual spaces over the Internet in which a group of people with similar interests or purposes interact with others and share information. To support group activities in online communities, a group recommendation procedure is needed. Though there have been attempts to establish group recommendation, they focus on off-line environments. Further, aggregating individuals' preferences into a group preference or merging individual recommendations into group recommendations-an essential component of group recommendation-often results in dissatisfaction of a small number of group members while satisfying the majority. To support group activities in online communities, this paper proposes an improved group recommendation procedure that improves not only the group recommendation effectiveness but also the satisfaction of individual group members. It consists of two phases. The first phase was to generate a recommendation set for a group using the typical collaborative filtering method that most existing group recommendation systems utilize. The second phase was to remove irrelevant items from the recommendation set in order to improve satisfaction of individual members' preferences. We built a prototype system and performed experiments. Our experiment results showed that the proposed system has consistently higher precision and individual members are more satisfied.