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A Bayesian Network Approach to Making Inferences in Causal Maps
Nadkarni, Sucheta Shenoy, Prakash P.
Nadkarni, Sucheta
Shenoy, Prakash P.
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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 modiĀ®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.
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Date
2001-02-01
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Elsevier Science Publishers B. V.
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Keywords
Causal maps, Cognitive maps, Bayesian networks, Bayesian causal maps
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.