贝叶斯网络是在不确定性环境下有效的知识表示方式和概率推理模型，是一种流行的图形决策化分析工具。
Bayesian Networks is a model that efficiently represents knowledge and probabilistic inference and is a popular graphics decision-making analysis tool.
贝叶斯网络是数据采掘的一个非常有效的工具，它能够定性和定量地分析属性之间的依赖关系，进行概率推理。
Bayesian network as, a very useful tool in data mining, can provide qualitative and quantitative relationship between attributes and probability inference.
所提出计算模型为贝叶斯网的概率推理提供了一种新的局部计算方法。
The proposed computation models will supply new local computation methods for Bayesian network probabilistic inferences.
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