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
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;
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
DOI :
10.1109/ICONS.2009.19
