Publication:
An Architecture and Functional Description to Integrate Social Behaviour Knowledge Into Group Recommender Systems

Loading...
Thumbnail Image
Full text at PDC
Publication Date
2014-06
Authors
Quijano Sánchez, Lara
Díaz Agudo, Mª Belen
Advisors (or tutors)
Editors
Journal Title
Journal ISSN
Volume Title
Publisher
Springer Verlag
Citations
Google Scholar
Research Projects
Organizational Units
Journal Issue
Abstract
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.
Description
Keywords
Citation
Collections