二Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network
二、Cross-lingual Knowledge Graph Alignment via Graph Matching Neural Network 摘要：先前的跨語言的知識圖譜對齊研究依賴於實體嵌入的思想，，其不能夠在兩個知識圖譜上；此文介紹一種方法，表示其上下文信息的特徵實體，主體實體圖（局部實體子圖），從這個角度來看，知識庫的對齊工作可以看做圖匹配問題，進一步提出 注意力機制的解決方案 代
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相關文章
- 1. Cross-lingual Knowledge Graph Alignment viaGraph Matching Neural Network
- 2. Graph Neural Network Review
- 3. Graph Few-shot learning via Knowledge Transfer
- 4. Contextualized Graph Attention Network for Recommendation with Item Knowledge Graph
- 5. Cs224W 8.1-Graph Neural Network
- 6. CS224W 8.2-Graph Neural Network
- 7. 20200427 Knowledge Graph Attention Network for Recommendation
- 8. 實體對齊4.EMNLP2018：（GCN-Align）Cross-lingual Knowledge Graph Alignment via Graph Convolutional Networks
- 9. EMNLP2019 | Knowledge-Aware Graph Networks
- 10. Knowledge Graph Attention Network for Recommendation