Papers with relation approximation

1 papers
Jointly Learning Entity and Relation Representations for Entity Alignment (D19-1)

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Challenge: Entity alignment is a viable method for integrating heterogeneous knowledge among different knowledge graphs (KGs).
Approach: They propose a Graph Convolutional Network-based framework for learning relation representations by embedding relation seeds into entities and incorporating relation approximation into entities to iteratively improve alignment.
Outcome: The proposed approach outperforms state-of-the-art methods on three real-world cross-lingual datasets.

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