• DocumentCode
    2626909
  • Title

    Preference learning for affective modeling

  • Author

    Yannakakis, Georgios N.

  • Author_Institution
    Center for Comput. Games Res., IT Univ. of Copenhagen, Copenhagen, Denmark
  • fYear
    2009
  • fDate
    10-12 Sept. 2009
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    There is an increasing trend towards personalization of services and interaction. The use of computational models for learning to predict user emotional preferences is of significant importance towards system personalization. Preference learning is a machine learning research area that aids in the process of exploiting a set of specific features of an individual in an attempt to predict her preferences. This paper outlines the use of preference learning for modeling emotional preferences and shows the methodology´s promise for constructing accurate computational models of affect.
  • Keywords
    behavioural sciences computing; learning (artificial intelligence); affective modeling; computational models; interaction personalization; machine learning; preference learning; service personalization; user emotional preference prediction; Computational modeling; Control systems; Gaussian processes; Humans; Instruments; Interactive systems; Machine learning; Neural networks; Predictive models; Protocols;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Affective Computing and Intelligent Interaction and Workshops, 2009. ACII 2009. 3rd International Conference on
  • Conference_Location
    Amsterdam
  • Print_ISBN
    978-1-4244-4800-5
  • Electronic_ISBN
    978-1-4244-4799-2
  • Type

    conf

  • DOI
    10.1109/ACII.2009.5349491
  • Filename
    5349491