Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains
Abstract
When constructing a Bayesian network, it can be advantageous to employ structural learning algorithms to combine knowledge captured in databases with prior information provided by domain experts. Unfortunately, conventional learning algorithms do not easily incorporate prior information, if this information is too vague to be encoded as properties that are local to families of variables. For instance, conventional algorithms do not exploit prior information about repetitive structures, which are often found in object oriented domains such as computer networks, large pedigrees and genetic analysis.
Cite
Text
Langseth and Nielsen. "Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains." Journal of Machine Learning Research, 2003.Markdown
[Langseth and Nielsen. "Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains." Journal of Machine Learning Research, 2003.](https://mlanthology.org/jmlr/2003/langseth2003jmlr-fusion/)BibTeX
@article{langseth2003jmlr-fusion,
title = {{Fusion of Domain Knowledge with Data for Structural Learning in Object Oriented Domains}},
author = {Langseth, Helge and Nielsen, Thomas D.},
journal = {Journal of Machine Learning Research},
year = {2003},
pages = {339-368},
volume = {4},
url = {https://mlanthology.org/jmlr/2003/langseth2003jmlr-fusion/}
}