MetaTKG: Learning Evolutionary Meta-Knowledge for Temporal Knowledge Graph Reasoning

Understand

Reasoning over Temporal Knowledge Graphs (TKGs) aims to predict future facts based on given history.

• One of the key challenges for prediction is to learn the evolution of facts.
• Most existing works focus on exploring evolutionary information in history to obtain effective temporal embeddings for entities and relations, but they ignore the variation in evolution patterns of facts, which makes them struggle to adapt to future data with different evolution patterns.
• Moreover, new entities continue to emerge along with the evolution of facts over time.