Generating Personalized Destination Suggestions for Automotive Navigation Systems under Uncertainty

Michael Feld, Martin Theobald, Christoph Stahl, Timm Meiser, Christian Müller

In: Proceedings of the 19th International Conference on User Modeling, Adaptation, and Personalization. International Conference on User Modeling, Adaptation, and Personalization (UMAP-2011) 19th July 11-15 Girona Spain Lecture Notes in Computer Science (LNCS) Springer 2011.


Programming a car's navigation system manually takes time and is error-prone. When the address is not handy, a cumbersome search may start. Changing the destination while driving is even more problematic. Given a modern car's role as an information hub, we argue that an intelligent system could in many cases infer the right destination or have it among the top N suggestions. In this work, we propose a personalized navigation system that is built from three main ingredients: strong user models, knowledge source fusion, and reasoning under uncertainty. We focus on emails as one particular knowledge source, exploring the uncertainties involved when extracting empirical data of email appointments.


uncertainties_posterpaper_submitted.pdf (pdf, 171 KB )

German Research Center for Artificial Intelligence
Deutsches Forschungszentrum für Künstliche Intelligenz