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统计关系学习模型Markov逻辑网综述 被引量：7

Survey of Markov Logic Networks
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摘要 统计关系学习是人工智能研究的热点,在生物信息学、地理信息系统和自然语言理解等领域有着重要应用,Markov逻辑网是将Markov网与一阶逻辑相结合的一种全新的统计关系学习模型。介绍了Markov逻辑网的理论模型和学习方法,并探讨了目前存在的问题和研究方向。 Statistical Relational Learning（SRL） is a highlight in AI research field, and has important applications on many areas, such as bioinformatics, geography information systems and natural language processing, etc. Markov Logic Networks （MLNs） are a kind of SRL model combining Markov networks and the first-order logic together. In this paper, we introduced the theory and learning methods of MLNs, as well as discussed current problems and directions for future work.
作者 孙舒杨 刘大有 孙成敏 黄冠利
机构地区 吉林大学计算机科学与技术学院 北京电子科技职业学院
出处 《计算机应用研究》 CSCD 北大核心 2007年第2期1-3,共3页 Application Research of Computers
基金 国家自然科学基金资助项目(60496321 60373098 60173006) 国家"863"计划资助项目(2003AA118020) 吉林省科技发展计划重大资助项目(20020303 20030523)
关键词 统计关系学习 一阶逻辑 MARKOV网 机器学习 MARKOV逻辑网 Statistical Relational Learning First-Order Logic Markov Networks Machine Learning Markov Logic Networks
分类号 TP30 [自动化与计算机技术—计算机系统结构]
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参考文献22

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共引文献1

同被引文献101

  • 1肖智,王明恺,谢林林.基于支持向量机的大学生助学贷款个人信用评价[J].清华大学学报（自然科学版）,2006,46(z1):1120-1124. 被引量：20
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  • 3于鹏,刘大有,欧阳丹彤.基于遗传与粒子群算法的Markov逻辑网学习研究[J].电子学报,2006,34(B12):2551-2555. 被引量：1
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引证文献7

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计算机应用研究
2007年 第2期

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