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  2006, Vol. 19 Issue (1): 31-34    DOI:
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A Method of Bayesian Network Construction Combining Knowledge and Data
YANG ShanLin, HU XiaoXuan, MAO XueMin
Institute of Computer Network Systems, Hefei University of Technology, Hefei 230009

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Abstract  Learning the structure of a Bayesian network from data may be time expensive due to huge search space. Because a Bayesian network contains causal semantics, experts can use their knowledge to confirm cause and effect among variables. In this paper, experts’ opinions are collected and combined using DempsterShafer evidence theory. The network structures without semantics are eliminated, then learning network from data is continued. This method fuses expert knowledge which is used to reduce search space with data to construct a Bayesian network. It avoids the subjective bias of single expert. The experimental results show that this method can improve learning efficiency.
Key wordsBayesian Network      Knowledge      DempsterShafer Evidence Theory      Evidence Combination     
Received: 15 October 2004     
ZTFLH: TP181  
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YANG ShanLin
HU XiaoXuan
MAO XueMin
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YANG ShanLin,HU XiaoXuan,MAO XueMin. A Method of Bayesian Network Construction Combining Knowledge and Data[J]. , 2006, 19(1): 31-34.
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