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基于贝叶斯网络方法的说明者信念度相关性模型——科学说明相关性问题的一个解决方案
The Exponent’s Belief Degree Relevance Model Based on Bayesian Network Approach——A Solution to Relevance Issue in Scientific Explanation
【摘要】 在科学说明中,说明项与被说明项的相关性问题可谓是当代"经典"的热点问题。本文在评析相关性问题以往解决方案遗留难题的基础上,博采以往解决方案之长,探索一条新的解决相关性疑难的路径,提出基于贝叶斯网络方法的说明者信念度相关性模型。
【Abstract】 The relevance issue between explanans and explanandum is a "contemporary classic" and hot issue in scientific explanation.On the basis of critiquing the difficulties of relevance issue left over by the previous solutions,this paper draws the advantages from them,explores a new approach to solve the difficulties,and puts forward the exponent’s belief degree relevance model based on Bayesian network approach.
【关键词】 科学说明;
相关性模型;
贝叶斯网络方法;
【Key words】 Scientific explanation; Relevance model; Bayesian network approach;
【Key words】 Scientific explanation; Relevance model; Bayesian network approach;
- 【文献出处】 自然辩证法通讯 ,Journal of Dialectics of Nature , 编辑部邮箱 ,2010年01期
- 【分类号】N031
- 【被引频次】3
- 【下载频次】340