Memorias de investigación
Book chapters:
A Hybrid Collaborative Filtering System for Contextual Recommendations in Social Networks
Year:2009

Research Areas
  • Telematics

Information
Abstract
Recommender systems are based mainly on collaborative filtering algorithms, which only use the ratings given by the users to the products. When context is taken into account, there might be difficulties when it comes to making recommendations to users who are placed in a context other than the usual one, since their preferences will not correlate with the preferences of those in the new context. In this paper, a hybrid collaborative filtering model is proposed, which provides recommendations based on the context of the travelling users. A combination of a user-based collaborative filtering method and a semantic-based one has been used. Contextual recommendation may be applied in multiple social networks that are spreading world-wide. The resulting system has been tested over 11870.com, a good example of a social network where context is a primary concern.
International
Si
10.1007/978-3-642-04747-3
Book Edition
0
Book Publishing
Springer Berlin / Heidelberg
ISBN
978-3-642-04746-6
Series
Book title
Discovery Science
From page
393
To page
400
Participants
  • Participante: Elena García Hortelano GSI-UPM
  • Participante: Jorge Gonzalo Alonso GSI-UPM
  • Autor: Carlos Angel Iglesias Fernandez UPM
  • Participante: Paloma de Juan GSI-UPM

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de Sistemas Inteligentes
  • Departamento: Ingeniería de Sistemas Telemáticos