Resolving knowledge discrepancies in situation‐aware systems

Abstract

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.

Opportunistic spatio-temporal event processing for mobile situation awareness

“…Meissen et al [21] present an approach to predict the future context of a user and efficiently deliver information based on the knowledge discrepancy between the situationawareness system and the user. However, they focus on identifying knowledge discrepancy based on various operations, including set and relational algebra.…”

Basics of Informed Logistics in Just-in-Time Production Sequencing and Supply Chain Systems

“…Many approaches are in existence which consider personalization and adapt information supply to a user context in order to deliver him/her appropriate information. It is a major issue to ensure optimal information supply with respect to the situations and individual demand of a user, and simultaneously prevent an information overload for mobile information services [5].…”