Bohnert, Fabian, Ingrid Zukerman, Shlomo Berkovsky, Timothy Baldwin and Elizabeth Sonenberg (2008) Using Collaborative Models to Adaptively Predict Visitor Locations in Museums, In Proceedings of the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems, Hanover, Germany, pp. 42-51

The vast amounts of information presented in museums can be overwhelming to a visitor, whose receptivity and time are typically limited. Hence, s/he might have difficulties selecting interesting exhibits to view within the available time. Mobile, context-aware guides offer the opportunity to improve a visitor’s experience by recommending exhibits of interest, and personalising the delivered content. The first step in this recommendation process is the accurate prediction of a visitor’s activities and preferences. In this paper, we present two adaptive collaborative models for predicting a visitor’s next locations in a museum, and an ensemble model that combines their predictions. Our experimental results from a study using a small dataset of museum visits are encouraging, with the ensemble model yielding the best performance overall.