QuatRE: Relation-Aware Quaternions for Knowledge Graph Embeddings

作者：D. Q. Nguyen, Thanh Vu, T. Nguyen, Dinh Q. Phung · 发表于：The Web Conference · 年份：2020 · DOI：10.1145/3487553.3524251 · 被引用次数：45 · 研究领域：Computer Science

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: https://github.com/daiquocnguyen/QuatRE.