Research on Explanation Function for Reason Conclusions with Bayesian Network

Wang Ronggui, Zhang Yousheng, Gao Jun, and Peng Qingsong

Journal of Computer Research and Development > 2005 > 42(9): 1527-1532.

Wang Ronggui, Zhang Yousheng, Gao Jun, and Peng Qingsong. Research on Explanation Function for Reason Conclusions with Bayesian Network[J]. Journal of Computer Research and Development, 2005, 42(9): 1527-1532.

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Research on Explanation Function for Reason Conclusions with Bayesian Network

Wang Ronggui, Zhang Yousheng, Gao Jun, and Peng Qingsong

(College of Computer and Information, Hefei University of Technology, Hefei 230009)

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Published Date: September 14, 2005

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Abstract

Abstract

In this paper, an explanation function about Bayesian network is presented. With it, evidences' effect degree, direction and paths on reason conclusion can be explained. Necessity factor and sufficiency factor are designed as a measure approach, to valuate evidences' effect degree on posteriori distributions. By the way of qualitatively analysis the character of network structure, notes relative to reason conclusion are find out. Based on those notes, and combined with the quantitatively analysis, sub chains which consist of effect paths are found out, too. Those sub chains are valuated to create and explain the effect paths. Experiment results show the effectiveness of the explain function.
- Bayesian network,
- posteriori distribution,
- 1-normal,
- effect degree,
- effect direction,
- effect path

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