Papers with static knowledge graph embedding methods

1 papers
Learning Joint Structural and Temporal Contextualized Knowledge Embeddings for Temporal Knowledge Graph Completion (2023.findings-acl)

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Challenge: Existing methods that incorporate time information into static knowledge graph embedding ignore the contextual nature of the TKG structure.
Approach: They propose a method that employs pre-trained language models to learn joint Structural and Temporal Contextualized Knowledge Embeddings.
Outcome: The proposed method is superior to existing methods that ignore the contextual nature of the TKG structure.

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