Markov逻辑网研究综述
Survey of Markov Logic Networks
DOI: 10.12677/SEA.2015.43010, PDF, HTML, XML, 下载: 3,125  浏览: 19,691 
作者: 徐元子, 刘登第：空军指挥学院，北京 ；张迎新：中国人民解放军71375部队，山东 潍坊
关键词: Markov逻辑网；一阶谓词逻辑；统计关系学习；推理；参数学习；Markov Logic Network； First-Order Logic； Statistical Relational Learning； Inference； Parametric Learning Algorithms
摘要: Markov逻辑网是将Markov网络与一阶谓词逻辑相结合的统计关系学习模型。Markov逻辑网在实体识别、数据融合、信息抽取等领域都有重要研究价值，具有广泛的应用。本文较为全面的介绍了Markov逻辑网的理论模型、推理、参数学习、与其他算法的比较，最后探讨Markov逻辑网未来的研究方向。
Abstract: Markov logic networks (MLNs) is a kind of statistical relational learning model which combines Markov network and first-order logic together. MLNs has the significant research value and in many areas it has widely applications, such as entity recognition, data integration and information extrac-tion. In this paper, we introduced the theoretical model of Markov logic networks, inference and pa-rametric learning of it and compared it with other. In the end, we discussed future works of MLNs.
文章引用：徐元子, 张迎新, 刘登第. Markov逻辑网研究综述[J]. 软件工程与应用, 2015, 4(3): 73-80. http://dx.doi.org/10.12677/SEA.2015.43010

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