论文标题
NAGE：非亚伯群体嵌入知识图
NagE: Non-Abelian Group Embedding for Knowledge Graphs
论文作者
论文摘要
我们证明了隐藏在关系知识嵌入问题中的组代数结构的存在，这表明基于组的嵌入框架对于设计嵌入模型至关重要。我们的理论分析仅探讨了嵌入问题本身的内在特性，因此是独立的。在理论分析的激励下，我们提出了一个基于群体理论的知识图嵌入框架，其中关系嵌入为群体元素，实体由群体行动空间中的向量表示。我们提供了一个通用配方，以构建与两个实例化示例相关的嵌入模型：SO3E和SU2E，两者都将连续的非亚伯群群应用于关系嵌入。使用这两个检查模型的经验实验显示了基准数据集上的最新结果。
We demonstrated the existence of a group algebraic structure hidden in relational knowledge embedding problems, which suggests that a group-based embedding framework is essential for designing embedding models. Our theoretical analysis explores merely the intrinsic property of the embedding problem itself hence is model-independent. Motivated by the theoretical analysis, we have proposed a group theory-based knowledge graph embedding framework, in which relations are embedded as group elements, and entities are represented by vectors in group action spaces. We provide a generic recipe to construct embedding models associated with two instantiating examples: SO3E and SU2E, both of which apply a continuous non-Abelian group as the relation embedding. Empirical experiments using these two exampling models have shown state-of-the-art results on benchmark datasets.
