论文解读：Connecting Embeddings for Knowledge Graph Entity Typing
论文解读：Connecting Embeddings for Knowledge Graph Entity Typing 知识图谱实体类型推理（KG Entity Typing）致力于预测知识图谱中可能缺失的实体类型实例，其作为知识图谱自动补全的一项子任务，非常重要但仍然缺乏更深入的研究。本文的方法基于联合学习的思路，从已知实体类型标注集中局部类型标注知识（Local typing knowled
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相关文章
- 1. 论文理解—— 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. 论文简读-MultiKE-《Multi-view Knowledge Graph Embedding for Entity Alignment》
- 5. Learning over Knowledge-Base Embeddings for Recommendation 论文
- 6. 论文笔记：AAAI 2020 Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction
- 7. Enriching BERT with Knowledge Graph Embeddings for Document Classification
- 8. 论文解读：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 9. Convolutional 2D Knowledge Graph Embeddings 阅读笔记
- 10. 论文笔记-Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network