UniCast, OutCast & GroupCast: Three Steps Toward Ubiquitous, Peripheral Displays
UbiComp '01 Proceedings of the 3rd international conference on Ubiquitous Computing
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Public Ubiquitous Computing Systems: Lessons from the e-Campus Display Deployments
IEEE Pervasive Computing
A Framework for Context-Aware Adaptation in Public Displays
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Smart Content Selection for Public Displays in Ambient Intelligence Environments
International Journal of Ambient Computing and Intelligence
| Hi-index | 0.00 |
Situated public displays are intended to convey important information to a large and heterogeneous population. Because of the heterogeneity of the population, they may risk providing a lot of irrelevant information. Many such important information items presented on public displays are actionables, items that are intended to trigger specific actions. The expected utility that such actionables have for a user depend on the value of the action for the user. A goal should be to provide for each user the actionables with highest utility. This can be achieved by adapting the information presentation to the users currently in front of the display. Adaptation can take place either by identifying individual users, by using statistics about the user groups usually in front of the display or by a combination of both. We present a formal framework based on decision theory that enables the integration of sensor data and statistics and allows to choose the optimal actionable to present based on this data.