Joint entity structural and attribute information for knowledge graph completion

Yuanbo Zhang; Wanbo Zheng; Hong Wang; Yongjian Yang; Xingliang Zhang; Huiming Ren; Yuanbo Xu

doi:10.1117/12.2628049

18 February 2022 Joint entity structural and attribute information for knowledge graph completion

Yuanbo Zhang, Wanbo Zheng, Hong Wang, Yongjian Yang, Xingliang Zhang, Huiming Ren, Yuanbo Xu

Proceedings Volume 12162, International Conference on High Performance Computing and Communication (HPCCE 2021); 1216215 (2022) https://doi.org/10.1117/12.2628049
Event: 2021 International Conference on High Performance Computing and Communication, 2021, Guangzhou, China

Abstract

Knowledge Graph Completion (KGC) aims at predicting missing information for knowledge graphs. Most methods concentrate on learning entities’ representations with structural information indicating the relations between entities, while the utilization of entity attribute information is not sufficient for KGC. How to use the complex and diverse entity attribute information for KGC is still a challenging problem. In this paper, we propose a novel joint model Entity Structural and Attribute Embedding (ESAE) for KGC, which takes advantage of the entity structural and attribute information. Specifically, we first design a novel encoder Attribute Encoder (AE), which encodes both entity attribute types and values to generate the entities’ attribute-based representations. Based on AE, we use the structure-based and attribute-based representations in ESAE. We evaluate our method on the KGC task. Experimental results on real-world datasets show that our method outperforms other baselines on KGC.

Citation Download Citation

Yuanbo Zhang, Wanbo Zheng, Hong Wang, Yongjian Yang, Xingliang Zhang, Huiming Ren, and Yuanbo Xu "Joint entity structural and attribute information for knowledge graph completion", Proc. SPIE 12162, International Conference on High Performance Computing and Communication (HPCCE 2021), 1216215 (18 February 2022); https://doi.org/10.1117/12.2628049

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Computer programming

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Data modeling

Information visualization

Matrices

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