論文解讀：Connecting Embeddings for Knowledge Graph Entity Typing
論文解讀：Connecting Embeddings for Knowledge Graph Entity Typing 知識圖譜實體類型推理（KG Entity Typing）致力於預測知識圖譜中可能缺失的實體類型實例，其作爲知識圖譜自動補全的一項子任務，非常重要但仍然缺乏更深入的研究。本文的方法基於聯合學習的思路，從已知實體類型標註集中局部類型標註知識（Local typing knowled
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相關文章
- 1. 論文理解—— DisenE: Disentangling Knowledge Graph Embeddings
- 2. KBGAN: Adversarial Learning for Knowledge Graph Embeddings理解
- 3. PaperReading-TransR,《Learning Entity and Relation Embeddings for Knowledge Graph Completion
- 4. 論文簡讀-MultiKE-《Multi-view Knowledge Graph Embedding for Entity Alignment》
- 5. Learning over Knowledge-Base Embeddings for Recommendation 論文
- 6. 論文筆記：AAAI 2020 Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
- 7. Enriching BERT with Knowledge Graph Embeddings for Document Classification
- 8. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 9. Convolutional 2D Knowledge Graph Embeddings 閱讀筆記
- 10. 論文筆記-Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network