RT Journal Article
T1 An Architecture and Functional Description to IntegrateSocial Behaviour Knowledge Into Group Recommender Systems
A1 Quijano Sánchez, Lara
A1 Recio García, Juan Antonio
A1 Díaz Agudo, Mª Belen
AB 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 diferent ways of combining the preferences of diferent 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 diferent recommenders that use increasing levels of social behaviour knowledge.
PB Springer Verlag
SN 1573-7497
YR 2014
FD 2014-06
LK https://hdl.handle.net/20.500.14352/34761
UL https://hdl.handle.net/20.500.14352/34761
LA spa
NO Ministerio de Educación, Cultura y Deporte
NO Madrid Educational Council
NO Ministerio de Economía y Competitividad
DS Docta Complutense
RD 2 may 2024