• DocumentCode
    1591309
  • Title

    Implicit Adaptation of User Preferences in Pervasive Systems

  • Author

    McBurney, Sarah ; Papadopoulou, Elizabeth ; Taylor, Nick ; Williams, Howard M.

  • Author_Institution
    Sch. of Math & Comput. Sci., Heriot-Watt Univ., Edinburgh
  • fYear
    2009
  • Firstpage
    56
  • Lastpage
    62
  • Abstract
    User preferences have an essential role to play in decision making in pervasive systems. However, building up and maintaining a set of user preferences for an individual user is a nontrivial exercise. Relying on the user to input preferences has been found not to work and the use of different forms of machine learning are being investigated. This paper is concerned with the problem of updating a set of preferences when a new aspect of an existing preference is discovered. A basic algorithm (with variants) is given for handling this situation. This has been developed for the Daidalos and Persist pervasive systems. Some research issues are also discussed.
  • Keywords
    learning (artificial intelligence); ubiquitous computing; machine learning; pervasive systems; user preferences; Availability; Decision making; Graphical user interfaces; Information management; Learning systems; Machine learning; Machine learning algorithms; Monitoring; Pervasive computing; Technological innovation; machine learning; pervasive systems; user preferences;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Systems, 2009. ICONS '09. Fourth International Conference on
  • Conference_Location
    Gosier, Guadeloupe
  • Print_ISBN
    978-1-4244-3469-5
  • Electronic_ISBN
    978-0-7695-3551-7
  • Type

    conf

  • DOI
    10.1109/ICONS.2009.19
  • Filename
    4976318
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1591309