系统分为三个模块:知识图谱,节点的graph embedding和对话生成器,下面分模块介绍。 1. Knowledge Graph 我们知道,知识图谱里一般用节点表示实体,边表示关系。本文的知识图谱里包含三类节点: 项目节点(item ID),属性节点,实体节点,组合成三元组,如(item-1, hasSchool, columbia)。(Gt)t=1T表示T轮对话的图谱,Gt的...
However, these methods mostly assume a static knowledge graph, so subsequent updates inevitably require a re-run of the embedding process. In this work the Navi Approach is introduced which aims to maintain advantages of established embedding methods while making them accessible to dynamic domains. ...
因此,作者希望提出一个考虑到实体和关系的不同类型带来的影响的模型,通过投影向量产生的动态映射矩阵去学习编码知识图谱为embedding。 TransD 如前文所述,每个命名符号对象(实体和关系)都由两个向量表示。第一个向量负责捕获实体(关系)的意义,另一个用于构建映射矩阵。例如,对于给定的三元组(h,r,t),它的向量是(h...
论文解读:(TransD)Knowledge Graph Embedding via Dynamic Mapping Matrix 知识图谱作为人工智能应用的重要资源,表示学习对知识图谱的完善和应用至关重要。先前提出的TransE、TransH、TransR模型对表示学习提升不少,表示学习对关系抽取、三元组分类以及链接预测等方面具有作用。TransD模型改进TransR,认为不同的实体应...
Fast pathfinding in knowledge graphs using word embeddings Proceedings of the Deutsche Jahrestagung für Künstliche Intelligenz (2020) Google Scholar [57] Q. Wang, Z. Mao, B. Wang, L. Guo Knowledge graph embedding: a survey of approaches and applications IEEE Trans. Knowl. Data Eng., 29 (...
Knowledge Graph Embedding Static Graph Embedding Survey Others Useful Libararies Temporal Knowledge Graph Completion / Reasoning Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs Woojeong Jin, Meng Qu, Xisen Jin, Xiang Ren. EMNLP 2020. ...
In this paper, we propose a novel DRL-based end-to-end dynamic knowledge graph reasoning framework for the KGQA task to address the above problems. First, we use a pre-trained model to initialize the embedding layers of entities and corresponding relations. Then, we take full advantage of th...
Knowledge graph embedding aims to embed both entities and relations into a low-dimensional space. Most existing methods of representation learning consider direct relations and some of them consider multiple-step relation paths. Although those methods ac
概述:作者认为现有的knowledge graph embedding方法忽略了时态一致性;时态一致性能够建模事实与事实所在上下文(上下文是指包含参与该事实的所有实体)的关系。为了验证时态知识图谱中事实的有效性,作者提出了上下文选择的双重策略:1、验证组成该事实的三元组是否可信;2、验证这个事实的时态区间是否与其上下文冲突。作者在实体预...
先前的工作如TransE,TransH,TransR/CTransR将关系作为头实体到尾实体的位移,CTransR达到了SOTA性能。在本文中,我们提出了一个更细粒度的模型TransD,其是TransR/CTransR的一个改进。在TransD中,我们使用两个向量表示一个命名符号对象(实体和关系)。第一个向量表示实体(关系)的意义,另一个则用来动态构造映射矩阵...