| 贝叶斯网模型的学习、推理和应用 |
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| 引用本文： | 冀俊忠,刘椿年,沙志强.贝叶斯网模型的学习、推理和应用[J].计算机工程与应用,2003,39(5):24-27,47. |
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| 作者姓名： | 冀俊忠 刘椿年 沙志强 |
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| 作者单位： | 北京工业大学计算机学院,北京,100022 |
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| 基金项目： | 国家自然科学基金项目(编号:69883001) |
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| 摘 要： | 近年来在人工智能领域,不确定性问题一直成为人们关注和研究的焦点。贝叶斯网是用来表示不确定变量集合联合概率分布的图形模式,它反映了变量间潜在的依赖关系。使用贝叶斯网建模已成为解决许多不确定性问题的强有力工具。基于国内外最新的研究成果对贝叶斯网模型的学习、推理和应用情况进行了综述,并对未来的发展方向进行了展望。
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| 关 键 词： | 贝叶斯网模型 贝叶斯网学习 概率推理 数据挖掘 智能教学系统 |
| 文章编号： | 1002-8331-(2003)05-0024-04 |
Bayesian Belief Network Model Learning,Inference and Applications |
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| Ji,Junzhong Liu Chunnian Sha Zhiqiang.Bayesian Belief Network Model Learning,Inference and Applications[J].Computer Engineering and Applications,2003,39(5):24-27,47. |
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| Authors: | Ji Junzhong Liu Chunnian Sha Zhiqiang |
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| Abstract: | In recent years,uncertainty reasoning in Artificial Intelligence has been a focus of research.A Bayesian Belief Network(BBN)is a graphic model that encodes joint probability distribution among uncertain variables,it express a potential dependent relationship between variables.Modeling with Bayesian belief network has been a powerful tool to solve many uncertainty problems.Based on the latest researched results at home and abroad,this paper reviews the learning,inference and applications of the Bayesian Belief Network,and presents possible future research orientations. |
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| Keywords: | BBN model BBN learning BBN inference Data mining Intelligence tutor system |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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