Demand-orientation is of crucial importance in mobile and pervasive information services in order to ensure the delivery of the right information at the right time and at the right place. In the past years, increasing attention has been devoted to the notion of personalized services that take the situation of the user into account. The trade-off is to ensure appropriate information supply while preventing information overload. Comparing situations predicted by the system with the expectations of a user yields information about "so-farunexpected" changes the user should be informed about. This paper describes an approach to identify and to resolve these knowledge discrepancies by informing the user about them in order to support his or her situation-awareness. Our approach is illustrated in two applications.
Demand-orientation is of crucial importance in mobile and pervasive information services in right place. Increasing attention has been devoted to the notion of personalized services that take the situation of the user into account. The trade-off is to ensure appropriate information supply while preventing information overload. Comparing situations predicted by the system with the expectations of a user yields information about "so-far unexpected" changes the user should be informed about. This paper describes an approach to support situation-awareness and introduces an underlying model that additionally handles information from various sources. Our approach is illustrated in a driving assistance application
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