Interaction analysis for adaptive user interfaces

Adaptive User Interfaces are able to facilitate the handling of computer systems through the automatic adaptation to users' needs and preferences. For the realization of these systems, information about the individual user is needed. This user information can be extracted from user events by applying analytical methods without the active information input by the user. In this paper we introduce a reusable interaction analysis system based on probabilistic methods that predicts user interactions, recognizes user activities and detects user preferences on different levels of abstraction. The evaluation reveals that the prediction quality of the developed algorithm outperforms the quality of other established prediction methods