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A Bayesian belief network for IT implementation decision support
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DOI：10.1016/j.dss.2006.01.003.png)
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摘要
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Bayesian Belief Networks (BBNs) are graphical models that provide a compact and simple representation of probabilistic data. BBNs depict the relationships among several variables and include conditional probability distributions that make probabilistic statements about those variables. This paper demonstrates how to create a BBN from real-world data on Information Technology implementations. The paper also displays the resulting BBN and describes how it can be incorporated into a DSS to support what-if' analyses about Information Technology implementations. The paper combines techniques originating from artificial intelligence, statistics, and computer-based decision making. (c) 2006 Elsevier B.V. All rights reserved.
Keyword:
Information Technology (IT) implementation
Bayesian Belief Networks (BBNs)
Decision Support Systems (DSSs)
期刊
IF:
6.8
论文数:
3.8K
被引数:
1.5W
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