Markov逻辑网研究综述
Survey of Markov Logic Networks

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 (2015) Markov逻辑网研究综述。 软件工程与应用, 4, 73-80. doi: 10.12677/SEA.2015.43010

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