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1. 7 Related Work The Lumiere project [9] realized pro-active assistance for computer software users. A bayesian user model was employed to infer a user’s information needs. While Lumiere mainly focussed on enhancing the usage of some software, EPOS pursues assisting the users’ work in general. That means, first, not only one application is observed and enhanced with some (closed) assistance, and second, not only the user’s information need is elicited, but his context. Watson [3] observes user interaction with everyday applications and attempts to automatically fulfil a user’s information need by querying common Internet information sources automatically.

However, most currently implemented human computer interaction systems that employ a user model or context model work with isolated models. The main challenge in our opinion is to let different systems that are interconnected or even organized in intelligent environments, communicate about their context models and user models. This challenge has been motivated by the expected result that permanent evaluation of user behavior with different systems and devices will lead to better models and thus allow better functions of adaptation like adaptive web-sites, recommended products, adaptive route planning or better speech interaction.

For example, the user will model a new project and its project members in the organizational repository freely if the context elicitation is then able to proposes the new project together with related information like the project homepage for example. 32 S. Schwarz The set of supported applications and, accordingly, the set of observable user actions is limited by the set of available user observation plugins. Implementing new plugins for yet unsupported applications is merely a question of how to integrate plugins into that application and how to recognize the the user’s actions therein.

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