论文标题
Quatre：知识图嵌入的关系感知的四元素
QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings
论文作者
论文摘要
我们提出了一个简单而有效的嵌入模型，以学习针对实体和知识图中关系的四个嵌入。我们的模型旨在增强跨越汉密尔顿产品之间关系的头部和尾部实体之间的相关性。该模型通过将每个关系与两种关系感知的旋转相关联，可以分别将每个关系旋转旋转，以分别旋转头部和尾部实体的四元素嵌入，从而实现了这一目标。实验结果表明，我们提出的模型在知名基准数据集上产生最新的表演，以完成知识图。我们的代码可在：\ url {https://github.com/daiquocnguyen/quatre}中获得。
We propose a simple yet effective embedding model to learn quaternion embeddings for entities and relations in knowledge graphs. Our model aims to enhance correlations between head and tail entities given a relation within the Quaternion space with Hamilton product. The model achieves this goal by further associating each relation with two relation-aware rotations, which are used to rotate quaternion embeddings of the head and tail entities, respectively. Experimental results show that our proposed model produces state-of-the-art performances on well-known benchmark datasets for knowledge graph completion. Our code is available at: \url{https://github.com/daiquocnguyen/QuatRE}.
