| Título: | An Architecture and Functional Description to IntegrateSocial Behaviour Knowledge Into Group Recommender Systems |
| Autores: | Quijano Sánchez, Lara ; Recio García, Juan Antonio ; Díaz Agudo, Mª Belen |
| Tipo de documento: | texto impreso |
| Editorial: | Springer Verlag, 2014-06 |
| Dimensiones: | application/pdf |
| Nota general: | info:eu-repo/semantics/openAccess |
| Idiomas: | |
| Palabras clave: | Estado = Publicado , Materia = Ciencias: Informática , Materia = Ciencias: Informática: Inteligencia artificial , Tipo = Artículo |
| Resumen: |
In this paper we consider the research challenges of generating a set of recommendations that will satisfy a group of users, with potentially competing interests. We review di?erent ways of combining the preferences of di?erent users and propose an approach that takes into account the social behaviour within a group. Our method, named delegation-based prediction method, includes an analysis of the group characteristics, such as size, structure, personality of its members in conict situations, and trust between group members. A key element in this paper is the use of social information available in the Web to make enhanced recommendations to groups. We propose a generic architecture named arise (Architecture for Recommendations Including Social Elements) and describe, as a case study, our Facebook application HappyMovie: a group recommender system that is designed to provide assistance to a group of friends that might be selecting which movie to watch on a cinema outing. We evaluate the performance (compared with the real group decision) of di?erent recommenders that use increasing levels of social behaviour knowledge. |
| En línea: | https://eprints.ucm.es/id/eprint/31221/1/QuijanoAppInt_RevisedVersion.pdf |
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