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Lookup NU author(s): Dr Keith Cheverst, Professor Christian Kray
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It is important that systems which exhibit pro-active behaviour (triggered by changes in the user’s environmental context) do so in a way that does not surprise or frustrate the user. Consequently, it is desirable for such systems to be both personalised and designed in such a way as to enable the user to interrogate his or her user model (part of which should hold the rules describing the behaviour of the system). This article describes on-going work to investigate the design of a prototype system that can learn a given user’s behaviour in an office environment in order to use the inferred rules to populate a user model and support appropriate pro-active behaviour, e.g. turning on the user’s fan under appropriate conditions. We explore the tension between user control and proactive services and consider issues related to the design of appropriate transparency with a view to supporting user comprehensibly for system behaviour. To this end, our system enables the user to interrogate and possibly over-ride the ‘IF-THEN’ type rules held in his or her user model. The system infers these rules from the context-history (effectively a data set generated using a variety of sensors) associated with the user by using a fuzzy decision tree based algorithm that can provide a confidence level for each rule in the user model. Currently, a number of users in a university department are running the system and a questionnaire based study has also been completed in order to explore the feasibility of the approach and user acceptance.
Author(s): Cheverst K, Byun HE, Fitton D, Sas C, Kray C, Villar N
Publication type: Article
Publication status: Published
Journal: User Modeling and User-Adapted Interaction
Year: 2005
Volume: 15
Issue: 3-4
Pages: 235-273
ISSN (print): 0924-1868
ISSN (electronic): 1573-1391
Publisher: Springer
URL: http://dx.doi.org/10.1007/s11257-005-1269-8
DOI: 10.1007/s11257-005-1269-8
Notes: Special issue on User Modeling in Ubiquitous Computing.
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