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2017-10-06 - Colloque/Article dans les actes avec comité de lecture - Anglais - 4 page(s)

Rafailidis Dimitrios , Crestani Fabio, "A Collaborative Ranking Model for Cross-Domain Recommendations" in International Conference on Information and Knowledge Management, Pan Pacific Singapore, Singapore, 2017

  • Codes CREF : Informatique générale (DI1162)
  • Unités de recherche UMONS : Systèmes d'information (S832)
  • Instituts UMONS : Institut de Recherche en Technologies de l’Information et Sciences de l’Informatique (InforTech), Institut de Recherche sur les Systèmes Complexes (Complexys)
  • Centres UMONS : Modélisation mathématique et informatique (CREMMI)

Abstract(s) :

(Anglais) With the advent of social media, generating high quality cross-domain recommendations has become more and more important for users of heterogeneous domains. In this study, we propose a collaborative ranking model to generate cross-domain recommendations. Given a target domain, we design an objective function aimed at performing push of relevant items at the top of a recommendation list. Also, as users may have different behaviours in multiple domains in our collaborative ranking model we propose a weighting strategy to control the influence of user preferences from auxiliary domains when producing the recommendation lists. Our experiments on ten cross-domain recommendation tasks show that the proposed approach achieves higher recommendation accuracy than other state-of-the-art methods.