Item-based collaborative filtering recommendation algorithms
Proceedings of the 10th international conference on World Wide Web
More than the sum of its members: challenges for group recommender systems
Proceedings of the working conference on Advanced visual interfaces
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Group recommender systems: a critiquing based approach
Proceedings of the 11th international conference on Intelligent user interfaces
A music recommendation system based on music and user grouping
Journal of Intelligent Information Systems - Special issue: Intelligent multimedia applications
Efficient bayesian hierarchical user modeling for recommendation system
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A group recommendation system with consideration of interactions among group members
Expert Systems with Applications: An International Journal
Applications of web mining for marketing of online bookstores
Expert Systems with Applications: An International Journal
A Group Recommender System for Tourist Activities
EC-Web 2009 Proceedings of the 10th International Conference on E-Commerce and Web Technologies
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Today, due to their flexibility and ease of use, social networks have fallen in the center of attention for users. The variety of social network groups has made users uncertain. This diversity has also made it difficult for them to find a group that well suits their preferences and personality. Therefore, to overcome this problem, we introduce the group recommendation system. This system offers customized recommendations based on each user's preferences. It is created by selecting related features based on supervised entropy as well as using association rules and D-Tree classification method. Assuming that members in each group share similar characteristics, heterogeneous members are identified and removed. Unlike other methods, this method is also applicable for users who have just been joined to the social network while they do not have friendship relationships with others or do not yet have memberships in any groups.