A Hybrid Recommender Combining User, Item and Interaction Data

  • Autors
  • Grivolla J, Badia T, Campo D, Sonsona M, Pulido JM
  • Autors UPF
  • GRIVOLLA ., JENS; BADIA CARDUS, ANTONI;
  • Autors del llibre
  • VV.AA.
  • Titol del llibre
  • Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014
  • Editorial
  • IEEE Computer Society
  • Data publicació del Llibre
  • 2014
  • Pàgines
  • -
  • ISBN del libre
  • 9781479930098
  • Resum
  • While collaborative filtering often yields very good recommendation results, in many real-world recommendation scenarios cold-start and data sparseness remain important problems. This paper presents a hybrid recommender system that integrates user demographics and item characteristics, around a collaborative filtering core based on user-item interactions. The recommender system is evaluated on Movie lens data (including genre information and user data) as well as real-world data from a discount coupon provider. We show that the inclusion of additional item and user information can have great impact on recommendation quality, especially in settings where little interaction data is available.
  • Citació completa
  • Grivolla J, Badia T, Campo D, Sonsona M, Pulido JM. A Hybrid Recommender Combining User, Item and Interaction Data. Dins: VV.AA.. Proceedings - 2014 International Conference on Computational Science and Computational Intelligence, CSCI 2014. 1 ed. IEEE Computer Society; 2014.
Indicadors bibliomètrics
  • 8 Cites a Scopus
  • 5 Cites a WOS
  • Índex Scimago de 0