Abstract
Building a probabilistic network for a real-life application is a difficult and time-consuming task. Methodologies for building such a network, however, are still lacking. Also, literature on network-specific modelling issues is quite scarce. As we have developed a large probabilistic network for a complex medical domain, we have encountered and resolved numerous non-trivial modelling issues. Since many of these issues pertain not only to our application but are likely to emerge for other applications as well, we feel that sharing them will contribute to engineering probabilistic networks in general.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
G. Schreiber, H. Akkermans, A. Anjewierden, R. de Hoog, N. Shadbolt, W. Van de Velde, B. Wielinga, Knowledge Engineering and Management: The CommonKADS Methodology, MIT Press, Cambridge, Massachusetts, 2000.
M.J. Druzdzel, L.C. van derGaag,’ Building Bayesian networks: ”Where do the numbers come from?” Guest editors’ introduction’, IEEE Transactions on Knowledge and Data Engineering, 12, 481–486, 2000.
F.V. Jensen, Bayesian Networks and Decision Graphs, Statistics for Engineering and Information Science, Springer-Verlag, New York, 2001.
L.C. van der Gaag, S. Renooij, C.L.M. Witteman, B.M.P. Aleman, B.G. Taal,’ Probabilities for a probabilistic network: a case study in oesophageal cancer’, Artificial Intelligence in Medicine, 25, 123–148, 2002.
A.C. Scott, J.E. Clayton, E.L. Gibson, A Practical Guide to Knowledge Acquisition, Addison-Wesley, Reading, Massachusetts, 1991.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2002 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
van der Gaag, L.C., Helsper, E.M. (2002). Experiences with Modelling Issues in Building Probabilistic Networks. In: Gómez-Pérez, A., Benjamins, V.R. (eds) Knowledge Engineering and Knowledge Management: Ontologies and the Semantic Web. EKAW 2002. Lecture Notes in Computer Science(), vol 2473. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45810-7_4
Download citation
DOI: https://doi.org/10.1007/3-540-45810-7_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-44268-4
Online ISBN: 978-3-540-45810-4
eBook Packages: Springer Book Archive