Computing and Informatics

The popularity of group recommender systems has increased in the last years. Ever more social activity is generated by users over the web and thus not only domains such as TV, music or holiday resorts are used and researched for group recommendations, but also collaborative learning support, digital libraries and other domains seem to be promising for group recommendations. Moreover, principles of group recommenders can be used to overcome some single-user recommendation shortcomings, such as cold start problem. Numerous group recommenders have been proposed; they differ in application domains (which in the group recommender context are specific in various group characteristics). Today's group recommenders do not include and use the power of social aspects (a group structure, social status etc.), which can be extracted and derived from the group. We provide a survey of group recommendation principles for the Web domain and discuss trends and perspectives for further research.