Abstract
This paper proposes a personalised frequency-based model for predicting a user’s pathway through a physical space, based on non-intrusive observations of users’ previous movements. Specifically, our approach estimates a user’s transition probabilities between discrete locations utilising personalised transition frequency counts, which in turn are estimated from the movements of other similar users. Our evaluation with a real-world dataset from the museum domain shows that our approach performs at least as well as a non-personalised frequency-based baseline, while attaining a higher predictive accuracy than a model based on the spatial layout of the physical museum space.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Bohnert, F., Zukerman, I.: Non-intrusive personalisation of the museum experience. In: Houben, G.-J., McCalla, G., Pianesi, F., Zancanaro, M. (eds.) UMAP 2009. LNCS, vol. 5535, pp. 197–209. Springer, Heidelberg (2009)
Bohnert, F., Zukerman, I., Berkovsky, S., Baldwin, T., Sonenberg, L.: Using interest and transition models to predict visitor locations in museums. AI Communications 21(2-3), 195–202 (2008)
Stock, O., Zancanaro, M., Busetta, P., Callaway, C., Krüger, A., Kruppa, M., Kuflik, T., Not, E., Rocchi, C.: Adaptive, intelligent presentation of information for the museum visitor in PEACH. User Modeling and User-Adapted Interaction 18(3), 257–304 (2007)
Wang, Y., Aroyo, L., Stash, N., Sambeek, R., Schuurmans, Y., Schreiber, G., Gorgels, P.: Cultivating personalized museum tours online and on-site. Interdisciplinary Science Reviews 34(2), 141–156 (2009)
Cantino, A.S., Roberts, D.L., Isbell, C.L.: Autonomous nondeterministic tour guides: Improving quality of experience with TTD-MDPs. In: Proc. of the 6th Intl. Joint Conf. on Autonomous Agents and Multi-Agent Systems (AAMAS-07), pp. 91–93 (2007)
Han, S.J., Cho, S.B.: Predicting user’s movement with a combination of self-organizing map and Markov model. In: Kollias, S.D., Stafylopatis, A., Duch, W., Oja, E. (eds.) ICANN 2006. LNCS, vol. 4132, pp. 884–893. Springer, Heidelberg (2006)
Krumm, J.: A Markov model for driver turn prediction. In: Proc. of the Society of Automotive Engineers (SAE) 2008 World Congress (2008) Paper 2008-01-0195
Krumm, J., Horvitz, E.: Predestination: Inferring destinations from partial trajectories. In: Dourish, P., Friday, A. (eds.) UbiComp 2006. LNCS, vol. 4206, pp. 243–260. Springer, Heidelberg (2006)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Bohnert, F., Zukerman, I. (2010). Personalised Pathway Prediction. In: De Bra, P., Kobsa, A., Chin, D. (eds) User Modeling, Adaptation, and Personalization. UMAP 2010. Lecture Notes in Computer Science, vol 6075. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13470-8_33
Download citation
DOI: https://doi.org/10.1007/978-3-642-13470-8_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13469-2
Online ISBN: 978-3-642-13470-8
eBook Packages: Computer ScienceComputer Science (R0)