The Needs of the Many: A Case-Based Group Recommender System

While much of the research in the area of recommender systems has focused on making recommendations to the individual, many recommendation scenarios involve groups of inter-related users. In this paper we consider the challenges presented by the latter scenario. We introduce a (case-based) group recommender designed to meet these challenges through a variety of recommendation features, including the generation of reactive and proactive suggestions based on user feedback in the form of critiques, and demonstrate its effectiveness through a live-user case-study.

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