A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system.

Stephen Shaoyi Liao; Huai Qing Wang; Qiu Dan Li; Wei Yi Liu

doi:10.1109/tsmcb.2005.862492

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A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system.

Stephen Shaoyi Liao·Huai Qing Wang·Qiu Dan Li·Wei Yi Liu

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Abstract

This paper presents a new method for learning Bayesian networks from functional dependencies (FD) and third normal form (3NF) tables in relational databases. The method sets up a linkage between the theory of relational databases and probabilistic reasoning models, which is interesting and useful especially when data are incomplete and inaccurate. The effectiveness and practicability of the proposed method is demonstrated by its implementation in a mobile commerce system.

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Algorithms Artificial Intelligence Bayes Theorem Commerce Computer Simulation Decision Support Techniques Food Industry Models, Economic Models, Statistical Motion Pattern Recognition, Automated Journal Article Research Support, Non-U.S. Gov't

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Stephen Shaoyi Liao, Huai Qing Wang, Qiu Dan Li, Wei Yi Liu. 2006. A functional-dependencies-based Bayesian networks learning method and its application in a mobile commerce system.. https://doi.org/10.1109/tsmcb.2005.862492

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