Papers with cross-lingual AI
Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks (D18-1)
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| Challenge: | Existing approaches to align multilingual knowledge graphs with counterparts in different languages are not effective. |
| Approach: | They propose a novel approach for cross-lingual KG alignment via graph convolutional networks . they train GCNs to embed entities of each language into a unified vector space . |
| Outcome: | The proposed approach gets the best performance on real multilingual KGs compared with other embedding-based approaches. |
Modeling Multi-mapping Relations for Precise Cross-lingual Entity Alignment (D19-1)
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| Challenge: | Entity alignment aims to find entities in different knowledge graphs (KGs) that refer to the same real-world object. |
| Approach: | They propose to use dot product-based functions to define dot products over embeddings to better capture semantics of 1-N, N-1 and N-N relations. |
| Outcome: | The proposed framework outperforms existing methods on multilingual datasets. |