D-CIS Publication Database

Publication

Type of publication:Inproceedings
Entered by:PdO
Title
Bibtex cite ID
Booktitle The 11th International Conference on Information Fusion
Year published 2008
Keywords Bayesian networks,distributed fusion,structure learning
Abstract
This paper introduces an information theoretic approach to verification of causal models in modular Bayesian fusion systems. We assume distributed fusion systems which are gradually extended by adding new modules, each having a limited domain knowledge captured in local Bayesian networks. However, since di erent modules originate from different, independent design processes important dependencies between the variables in diff erent modules might not correctly be captured in the distributed fusion system. This could have a significant impact on the fusion quality. The introduced method supports discovery of significant dependencies which are ignored in the distributed fusion system.
Authors
de Oude, Patrick
Pavlin, Gregor
Topics
=SEE CLASSIFICATION DIFFERENCE FROM OTHERS=
BibTeXBibTeX
RISRIS
Attachments
oude08icif.pdf (main file)
 
Total mark: 5