Visitors to physical educational environments, such as museums, galleries or zoos, are often overwhelmed by the information available in the space they are exploring. Typically being limited in receptivity and time, they are confronted with the challenge of finding and selecting the personally interesting items to view within the available time. A personal human guide could support a visitor in this selection process, but the provision of personal guides is generally not possible. Advances in mobile technologies and user modelling point towards an alternative solution: personalised electronic handheld guides.
Personalised electronic handheld guides can provide guidance and support a visitor in the process of selecting suitable items by identifying and recommending items that match his/her interests. Additionally, they have the potential to infer these interests by tracking a visitor's behaviour within the environment. However, recommendation generation from non-intrusive observations of a visitor's behaviour in a physical space has challenges of its own. For example, as items have informational dependencies suggesting a certain order of access, careful thought is usually put into placing the items into the physical space to enable a coherent experience. Hence, a visitor's behaviour is influenced by both the suggested order of item access and the spatial layout of the environment, and consequently, these factors must be considered when modelling a visitor's interests from non-intrusive observations of his/her movements through the space. They must also be taken into account when generating and delivering recommendations. Therefore, the overall personalisation process is constrained by such factors. This research investigates adaptive user modelling and recommendation approaches that consider such and other constraints.
Authors: Fabian Bohnert
Event: SF08: Embodied Interaction in Mobile, Physical and Virtual Environments Workshop