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Title: A method for knowledge integration (English)
Author: Janžura, Martin
Author: Boček, Pavel
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 34
Issue: 1
Year: 1998
Pages: [41]-55
Summary lang: English
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Category: math
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Summary: With the aid of Markov Chain Monte Carlo methods we can sample even from complex multi-dimensional distributions which cannot be exactly calculated. Thus, an application to the problem of knowledge integration (e. g. in expert systems) is straightforward. (English)
Keyword: Markov chain Monte Carlo
Keyword: multi-dimensional distribution
Keyword: Gibbs distribution
Keyword: sampled data
Keyword: knowledge integration
Keyword: expert systems
MSC: 60J10
MSC: 60J22
MSC: 62H99
MSC: 65C05
MSC: 65C40
MSC: 68T30
MSC: 68T35
idZBL: Zbl 1274.65004
idMR: MR1619054
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Date available: 2009-09-24T19:13:32Z
Last updated: 2015-03-27
Stable URL: http://hdl.handle.net/10338.dmlcz/135184
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Reference: [1] Besag J.: On the statistical analysis of dirty pictures (with discussion).J. Roy. Statist. Soc. Ser. B 48 (1986), 259–302 Zbl 0609.62150, MR 0876840
Reference: [2] Gallager R.: Information Theory and Reliable Communication.J. Wiley, New York 1968 Zbl 0295.94001
Reference: [3] Gelfand A. E., Smith A. F. M.: Sampling–based approaches to calculating marginal densities.J. Amer. Statist. Assoc. 85 (1990), 398–409 Zbl 0702.62020, MR 1141740, 10.1080/01621459.1990.10476213
Reference: [4] Geman D., Geman S.: Stochastic relaxation, Gibbs distributions, and the Bayesian restoration of images.IEEE Trans. Pattern Anal. Mach. Intell. 6 (1984), 721–741 Zbl 0573.62030, 10.1109/TPAMI.1984.4767596
Reference: [5] Gilks W. R., Richardson S., (eds.) D. J. Spiegelhalter: Markov Chain Monte Carlo in Practice.Chapman and Hall, London 1996 Zbl 0832.00018, MR 1397966
Reference: [6] Hadley G.: Linear Programming.Addison Wesley, Reading 1962 Zbl 0102.36304, MR 0135622
Reference: [7] Janžura M., Přeučil S.: An expert system based on the simulated annealing algorithm.In: WUPES 91, Prague 1991
Reference: [8] Lauritzen S. L.: Graphical Models.University Press, Oxford 1996 Zbl 1055.62126, MR 1419991
Reference: [9] Matúš F.: On iterations of average of $I$-projections.In: Highly Structured Stochastic Systems. Rebild, Denmark 1996
Reference: [11] Moussouris J.: Gibbs and Markov random systems with constraints.J. Statist. Phys. 10 (1974), 1, 11–33 MR 0432132, 10.1007/BF01011714
Reference: [12] Perez A.: Barycenter of a set of probability measures and its application in statistical decision.In: Proceedings COMPSTAT 1984, Physica–Verlag, Wien 1984, pp. 154–159 Zbl 0577.62011, MR 0806993
Reference: [13] Winkler G.: Image Analysis, Random Fields and Dynamic Monte Carlo Methods.Springer–Verlag, Berlin 1995 Zbl 0821.68125, MR 1316400
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