Header And Logo
Site Navigation
Dipl.-Inf Thorsten Bohnenberger
|
|
|
Contact:
Contact information is not available.
|
Projects |
Back to Top |
Publications |
Back to Top |
2005
User Experience Design for a Decision-Theoretic Shopping Guide
Oliver Jacobs, Anthony Jameson,Thorsten Bohnenberger and Ilhan Aslan
Workshop on User Experience Design for Pervasive Computing, 2005
[ DOWNLOAD NOTE ]
Decision-Theoretic Planning Meets User Requirements
Thorsten Bohnenberger, Oliver Jacobs, Anthony Jameson, Ilhan Aslan
Enhancements and Studies of an Intelligent Shopping Guide. Proc. of the 3rd International Conference on Pervasive Computing, 2005 (In Press).
[ DOWNLOAD NOTE ]
show abstract
This paper reports on extensions to a decision-theoretic location-aware
shopping guide and on the results of user studies that have accompanied its development. On the basis of the results of an earlier user study in a mock-up of
a shopping mall, we implemented an improved version of the shopping guide.
A new user study with the improved system in a real shopping mall conrms in
a much more realistic setting the generally positive user attitudes found in the
earlier study. The new study also sheds further light on the usability issues raised
by the system, some of which can also arise with other mobile guides and recommenders. One such issue concerns desire of users to be able to understand and second-guess the system's recommendations. This requirement led to the development of an explanation component for the decision-theoretic guide, which was evaluated in a smaller follow-up study in the shopping mall.
2002
Empirically Grounded Decision-Theoretic Adaptation to Situation-Dependent Resource Limitations
Thorsten Bohnenberger, Boris Brandherm, Barbara Großmann-Hutter, Dominik Heckmann, Frank Wittig
Special Issue "Adaptivity and User Modeling", KI-Journal, Vol.3, 2002, pages 10-16
[ DOWNLOAD NOTE ]
[BibTeX]
show abstract
This article summarizes research on several interrelated general issues that can arise in the design and development of user modeling systems: the learning and subsequent adaptation of general user models on the basis of empirical data; the modeling of temporally variable properties of users, in particular time pressure and cognitive load; and the user-adaptive planning of interactions under uncertainty. The methods and results are integrated and illustrated with a prototype of a mobile assistance system for travelers in an airport.