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Fuzzy functional dependencies and Bayesian networks

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Abstract

Bayesian networks have become a popular technique for representing and reasoning with probabilistic information. The fuzzy functional dependency is an important kind of data dependencies in relational databases with fuzzy values. The purpose of this paper is to set up a connection between these data dependencies and Bayesian networks. The connection is done through a set of methods that enable people to obtain the most information of independent conditions from fuzzy functional dependencies.

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Correspondence to Liu WeiYi.

Additional information

This work is supported by the National. Natural Science Foundation of China (Grant No.60263006), and the Foundation of the Key Laboratory of Intelligent Information Processing Institute of Computing Technology, Chinese Academy of Sciences (Grant No. IIP2002-2).

LIU WeiYi graduated from Huazhong University of Science and Technology in 1976. He has been a research fellow at Hong Kong City University. Currently, he is a professor of the Department of Computer Science of Yunnan University. His research interests include fuzzy systems, data and knowledge engineering. He is a member of IEEE Computer Society.

SONG Ning received the M.S. degree from Kunming University of Science and Technology in 1993. She is an associate professor of the Department of Metallurgical Engineering. Her current research interests are data and knowledge engineering.

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Liu, W., Song, N. Fuzzy functional dependencies and Bayesian networks. J. Comput. Sci. & Technol. 18, 56–66 (2003). https://doi.org/10.1007/BF02946651

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