A Bayesian Network Approach to Making Inferences in Causal Maps

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Issue Date
2001-02-01Author
Nadkarni, Sucheta
Shenoy, Prakash P.
Publisher
Elsevier Science Publishers B. V.
Format
353110 bytes
Type
Article
Metadata
Show full item recordAbstract
The main goal of this paper is to describe a new graphical structure called "Bayesian causal maps" to represent and analyze domain knowledge of experts. A Bayesian causal map is a causal map, i.e., a network-based representation of an expert's cognition. It is also a Bayesian network, i.e., a graphical representation of an expert's knowledge based on probability theory. Bayesian causal maps enhance the capabilities of causal maps in many ways. We describe how the textual analysis procedure for constructing causal maps can be modi®ed to construct Bayesian causal maps, and we illustrate it using a causal map of a marketing expert in the context of a product development decision.
ISSN
0377-2217Collections
Citation
Nadkarni, S. and P. P. Shenoy, "A Bayesian Network Approach to Making Inferences in Causal Maps," European Journal of Operational Research, Vol. 128, No. 3, 2001, 479--498.
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