A Bayesian network approach to making inferences in causal maps

@article{Nadkarni2001ABN,
  title={A Bayesian network approach to making inferences in causal maps},
  author={S. Nadkarni and P. P. Shenoy},
  journal={Eur. J. Oper. Res.},
  year={2001},
  volume={128},
  pages={479-498}
}
  • S. Nadkarni, P. P. Shenoy
  • Published 2001
  • Computer Science
  • Eur. J. Oper. Res.
  • 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… CONTINUE READING
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