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oai:docta.ucm.es:20.500.14352/454032024-08-23T12:26:58Zcom_20.500.14352_14col_20.500.14352_21

00925njm 22002777a 4500 dc Quijano Sánchez, Lara author Recio García, Juan Antonio author Díaz Agudo, María Belén author 2011 In this paper we introduce our application HappyMovie, a Facebook application for movie recommendation to groups. This system takes advantage of social data available in this social network to promote fairness for the provided recommendations. Group recommendations are based in the individual satisfaction of each individual. The(in)satisfaction of users modifies the typical aggregation functions used to estimate the value of an item for the group. This paper proposes a memory of past recommendations to compute the satisfaction of users when similar items (movies, in this case) are recommended several times. 978-3-642-23290-9 https://hdl.handle.net/20.500.14352/45403 http://link.springer.com/content/pdf/10.1007%2F978-3-642-23291-6_17 http://link.springer.com/ User satisfaction in long term group recommendations