Adaptive information systems typically exploit knowledge about the user’s interests, preferences, goals etc. to determine what should be presented to the user and how this presentation should take place. When dealing with mobile users, however, information about their motions—the places visited, the duration of stays, average velocity etc.—can be additionally exploited to enrich the user model and better adapt the system behavior to the user’s needs. This paper discusses what type of positioning data and background knowledge is required to achieve such a motion-based adaptation of information provision and how it can be implemented using a variety of mostly standard machine-learning techniques.