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Group Recommendation Systems (GRS) aim at recommending items that are relevant for the joint interest of a group of users. Voting mechanisms assume that users rate all items in order to identify an item that suits the preferences of all group members. This assumption is not feasible in sparse rating scenarios which are common in the recommender systems domain. In this paper we examine an application of voting theory to GRS. We propose a method to accurately determine the winning item whiledoi:10.1145/1864708.1864763 dblp:conf/recsys/DeryKRS10 fatcat:cufhreheljggtgfthz7jcrh3ai