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| Title: | A Bayesian Network Approach to Making Inferences in Causal Maps |
| Authors: | Nadkarni, Sucheta
Shenoy, Prakash P. |
| Keywords: | Causal maps
Cognitive Maps
Bayesian networks
Bayesian causal maps |
| Issue Date: | 1-Feb-2001 |
| Publisher: | Elsevier Science Publishers B. V. |
| Extent: | 353110 bytes |
| Type: | Article |
| 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. |
| Abstract: | 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. |
| URI: | http://hdl.handle.net/1808/164 |
| ISSN: | 0377-2217 |
| Appears in Collections: | School of Business Articles
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