Research on Markov Logic Networks
Research on Markov Logic Networks
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DOI：
10.3724/sp.j.1001.2011.04053
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发表时间：
2011
期刊：
影响因子：
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通讯作者：
Cong-Fu Xu;Chunhe Hao;Baoxia Su;Jun-Jie Lou
中科院分区：
文献类型：
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作者：
Cong-Fu Xu;Chunhe Hao;Baoxia Su;Jun-Jie Lou
马尔可夫逻辑网络(MLN)是一种将马尔可夫网络和一阶逻辑相结合的统计关系学习(SRL)模型。马尔可夫逻辑网络在自然语言处理、复杂网络、信息抽取等领域有着广泛的应用。本文综述了马尔可夫逻辑网络的理论模型、权值和结构学习，并对未来的工作进行了展望。
Markov logic networks (MLNs) is a statistical relational learning (SRL) model, which combines Markov network and first order logic. It has been applied widely in nature language processing, complex networks, information extraction, etc. This paper addresses the theoretical model of Markov logic networks (MLNs), weight and structure learning of MLNs comprehensively, and finally presents future works of MLNs.