TempCaps: A Capsule Network-based Embedding Model for Temporal Knowledge Graph Completion
Guirong Fu, Zhao Meng, Zhen Yu Han, Zifeng Ding, Yunpu Ma, Matthias Schubert, Volker Tresp, Roger P. Wattenhofer · 2022
Temporal knowledge graphs store the dynamics of entities and relations during a time period.However, typical temporal knowledge graphs often suffer from incomplete dynamics with missing facts in real-world scenarios.Hence, modeling temporal knowledge graphs to complete the missing facts is important.In this paper, we tackle the temporal knowledge graph completion task by proposing TempCaps, which is a Capsule networkbased embedding model for Temporal knowledge graph completion.TempCaps models temporal knowledge graphs by introducing a novel dynamic routing aggregator inspired by Capsule Networks.Specifically, TempCaps builds entity embeddings by dynamically routing retrieved temporal relation and neighbor information.Experimental results demonstrate that TempCaps reaches state-of-the-art performance for temporal knowledge graph completion.Additional analysis also shows that TempCaps is efficient 1 .