• DocumentCode
    2096663
  • Title

    Crowd-voting-based group recommender systems

  • Author

    Boulkrinat, Samia ; Hadjali, Allel ; Mokhtari, Aicha

  • Author_Institution
    USTHB, FEI/LRIA Algiers, Algeria
  • fYear
    2015
  • fDate
    28-30 April 2015
  • Firstpage
    1
  • Lastpage
    9
  • Abstract
    In this paper, we deal with group recommendations where the task is to choose a sequence of natural attractions that better matches the expectation of a group of tourists. We show in this setting, that the crowd support in selecting potential alternatives, may help members to preserve the harmony of their group and not deviating too much from each other as well. Taking into consideration each member preferences, we tackle the consensus joint decision as a voting process that builds a majority opinion about a sequence of the most interesting natural attractions to visit by the group. Beyond consensus joint decision, it´s possible afterwards to perform better group satisfaction by improving the collective gain based on a likewise genetic mutation operation. Preliminary experimental results show that the proposed approach may outperform better when there is a higher heterogeneity between group members voting.
  • Keywords
    Context; Decision making; Electronic mail; Genetic mutations; Joints; Pragmatics; Recommender systems;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Programming and Systems (ISPS), 2015 12th International Symposium on
  • Conference_Location
    Algiers, Algeria
  • Type

    conf

  • DOI
    10.1109/ISPS.2015.7244973
  • Filename
    7244973