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References
Ohsawa Y, McBurney P (2003) Chance Discovery. Springer, Berlin Heidelberg New York
Ohsawa Y (2002) Chance discoveries for making decisions in complex real world. New Generation Computing 20(2): 143-164
Ohsawa Y, Yachida M (1999) Discover risky active faults by indexing an earth-quake sequence. Proceedings of the Second International Conference on Dis-covery Science 208-219
Onisko A, Lucas P J F, Druzdzel M J (2001) Comparison of rule-based and Bayesian network approaches in medical diagnostic systems. Lecture Notes in Computer Science 2101: 283-292
Gibbs W W (2004) Considerate computing. Scientific American January 54-61
Kim K J, Cho S B (2005) Construction of Bayesian networks for context-aware service robot. The 2nd International Conference on Ubiquituos Robots and Ambient Intelligence 69
Song Y S, Cho S B, Suh I H (2005) Activity-oriented Bayesian networks for detecting occluded objects in uncertain indoor environment. Lecture Notes in Artificial Intelligence 3683: 937-944
Charniak E (1991) Bayesian network without tears. AI Magazine 12(4): 50-63
Stephenson T (2000) An introduction to Bayesian network theory and usage IDLAP-PR00-03
Kim Z, Nevatia R (2003) Expandable Bayesian networks for 3D object de-scription from multiple views and multiple mode inputs. IEEE Transactions on Pattern Analysis and Machine Intelligence 25(6): 769-774
Lam W (1998) Bayesian network refinement via machine learning approach. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(3): 240-251
Zadeh L A (1965) Fuzzy sets. Information and Control 8:338-353
Pawlak Z (1991) Rough Sets: Theoretical Aspects of Reasoning about Data. Kluwer Academic Publishers, Dordrecht, The Netherlands
Pearl J (1988) Probabilistic Reasoning in Intelligent Systems: Networks of Plau-sible Inference. Morgan Kaufmann
Engestrom Y (1999) Activity theory and individual and social transformation. Perspectives on Activity Theory, Cambridge University Press
Horvitz E, Dumais S, Koch P (2004) Learning predictive models of memory landmarks. CogSci 2004: 26th Annual Meeting of the Cognitive Science Society
1st Annual Workshop on Rougth Sets and Chance Discovery (2005) http://www.jcis.org/pages/subconference/rscd/rscd.aspx
Chen X (2005) Cognitive relevance and chance discovery. Readings in Chance Discovery (Abe A, Ohsawa Y eds.)
Ogata N (2005) Towards dynamic probabilistic logic: A survey and a proposal. Readings in Chance Discovery (Abe A, Ohsawa Y eds.)
Tung W L, Quek C, Cheng P Y K (2005) A neuro-fuzzy perspective to chance discovery and its application to the study of banking failures. Readings in Chance Discovery (Abe A, Ohsawa Y eds.)
Horvitz E, Kadie C M, Paek T, Hovel D (2003) Models of attention in com-puting and communications: From principles to applications. Communications of the ACM 46(3):52-59
Yang S, Chang K C (2002) Comparison of score metrics for Bayesian network learning. IEEE Transactions on Systems, Man and Cybernetics-Part A 32(3): 419-428
Cooper G F, Herskovits E (1992) A Bayesian method for the induction of probabilistic networks from data. Machine Learning 7: 299-347
Heckerman D, Geiger D, Chickering D M (1995) Learning Bayesian net-works: The combination of knowledge and statistical data. Machine Learning 20(3):197-243
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Kim, KJ., Cho, SB. (2006). Uncertainty Reasoning and Chance Discovery. In: Ohsawa, Y., Tsumoto, S. (eds) Chance Discoveries in Real World Decision Making. Studies in Computational Intelligence, vol 30. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-34353-0_6
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