Abstract
When a complex information system is modelled by a Bayesian network the backward inference is normal requirement in system management. This paper proposes one inference algorithm in Bayesian networks, which can track the strongest causes and trace the strongest routes between particular effects and their causes. This proposed algorithm will become the foundation for further intelligent decision in management of information systems.
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References
Pearl, J.: Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo, CA (1988)
Cowell, R.G., Dawid, A.P., Lauritzen, S.L., Spiegelhalter, D.J.: Probabilistic Networks and Expert Systems. Springer, New York (1999)
Nikovski, D.: Constructing Bayesian networks for medical diagnosis from incomplete and partially correct statistics. IEEE Transactions on Knowledge and Data Engineering 12(4), 509–516 (2000)
Basye, K., Dean, T., Vitter, J.S.: Coping with Uncertainty in Map Learning. Machine Learning 29(1), 65–88 (1997)
Charniak, E., Goldman, R.P.: A Semantics for Probabilistic Quantifier-Free First-Order Languages, with Particular Application to Story Understanding. In: Proceedings of IJCAI 1989, pp. 1074–1079. Morgan-Kaufmann, San Francisco (1989)
Pearl, J.: Causality: Models, Reasoning, and Inference. Cambridge University Press, Cambridge (2000) ISBN: 0-521-77362-8
Wiegerinck, W., Kappen, H.J., ter Braak, E.W.M.T., ter Burg, W.J.P.P., Nijman, M.J., Neijt, Y.L.O.: Approximate inference for medical diagnosis. Pattern Recognition Letters 20, 1231–1239 (1999)
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© 2004 Springer-Verlag Berlin Heidelberg
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Ding, J., Zhang, J., Bai, Y., Chen, H. (2004). One Backward Inference Algorithm in Bayesian Networks. In: Liew, KM., Shen, H., See, S., Cai, W., Fan, P., Horiguchi, S. (eds) Parallel and Distributed Computing: Applications and Technologies. PDCAT 2004. Lecture Notes in Computer Science, vol 3320. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30501-9_18
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DOI: https://doi.org/10.1007/978-3-540-30501-9_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-24013-6
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