DMCA
A unifying model for representing and reasoning about context under uncertainty (2006)
| Venue: | In Proceedings of the 11th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU |
| Citations: | 5 - 2 self |
BibTeX
@INPROCEEDINGS{Padovitz06aunifying,
author = {Amir Padovitz and Arkady Zaslavsky and Seng W. Loke},
title = {A unifying model for representing and reasoning about context under uncertainty},
booktitle = {In Proceedings of the 11th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU},
year = {2006}
}
Share
 |
 |
 |
 |
||
OpenURL
Abstract
Modeling and reasoning about context under uncertainty is a major challenge in context-aware computing. This paper proposes a novel approach to represent context in a unifying way and to perform reasoning about context represented with that model, under uncertainty. We develop a novel reasoning approach based on Multi-Attribute Utility Theory as the means to integrate heuristics about the relative importance, inaccuracy and characteristics of sensory information. Our approach allows applying different reasoning approaches, and in this paper we qualitatively and quantitatively compare between our proposed reasoning approach and Dempster-Shafer sensor data fusion technique.
