Sciweavers

Share
PERCOM
2010
ACM

Faster Bayesian context inference by using dynamic value ranges

8 years 6 months ago
Faster Bayesian context inference by using dynamic value ranges
—This paper shows how to reduce evaluation time for context inference. Probabilistic Context Inference has proven to be a good representation of the physical reality with uncertain or missing information, giving with the probability also a measure of the quality of information. As the inference complexity is very high, the complexity of the to be evaluated rule (representing a share of the real world) should be reduced as far as possible. Therefore we present an approach to select only relevant values of context types and to adapt this selection during its usage time. A short proof of concept indicates that both targets, reducing inference time and maintaining quality of information, can be reached with the proposed approach. Keywords-Context Inference, Bayesian Inference, Dynamic Value Ranges, Bayeslets
Korbinian Frank, Patrick Robertson, Sergio Fortes
Added 29 Jan 2011
Updated 29 Jan 2011
Type Journal
Year 2010
Where PERCOM
Authors Korbinian Frank, Patrick Robertson, Sergio Fortes Rodriguez, Raquel Barco Moreno
Comments (0)
books