摘要
知识推理是知识图谱补全的重要手段,一直以来都是知识图谱领域的研究热点之一。随着神经网络不断取得新的发展,其在知识推理中的应用在近几年逐渐得到广泛重视。基于神经网络的知识推理方法具备更强的推理能力和泛化能力,对知识库中实体、属性、关系和文本信息的利用率更高,推理效果更好。简要介绍知识图谱及知识图谱补全的相关概念,阐述知识推理的概念及基本原理,从语义、结构和辅助存储三个维度展开,综述当下基于神经网络的知识推理最新研究进展,总结了基于神经网络的知识推理在理论、算法和应用方面存在的问题和发展方向。
Knowledge reasoning is an important means of knowledge graph completion and has always been one of the research hotspots in the field of knowledge graph. With the development of neural network, its applications in knowledge reasoning have been paid more and more attention in recent years. The knowledge reasoning methods based on neural network have not only stronger reasoning and generalization abilities, but also higher utilization rates of entities, attributes, relations and text information in the knowledge base. These methods are more effective in reasoning. The relevant concepts of knowledge graph and knowledge graph completion are introduced, the concepts and basic principles of knowledge reasoning are indicated, and then the latest research progresses of the technology of knowledge reasoning based on neural network are reviewed. The existing problems and development directions of knowledge reasoning in the aspect of theory, algorithm and application are summarized.
作者
张仲伟
曹雷
陈希亮
寇大磊
宋天挺
ZHANG Zhongwei;CAO Lei;CHEN Xiliang;KOU Dalei;SONG Tianting(College of Command & Control Engineering,Army Engineering University of PLA,Nanjing 210000,China;Unit 73671 of PLA,China;Unit 68023 of PLA,China)
出处
《计算机工程与应用》
CSCD
北大核心
2019年第12期8-19,36,共13页
Computer Engineering and Applications
基金
国防科技重点实验室基金(No.61421010318)
国家自然科学基金(No.61806221)
关键词
知识图谱
知识推理
神经网络
knowledge graph
knowledge reasoning
neural network