Open Relation Extraction: Relational Knowledge Transfer論文解析
Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised Data Abstract 多數的OpenRE問題都限定在了unsupervised的模式中，沒有利用Knowledge Base中的知識和標註數據。 所以提出RSN，學習預定義relation中的相似metric
相關文章
- 1. 【論文讀後感】Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised
- 2. Open Relation Extraction- Relational Knowledge Transfer from Supervised Data to Unsupervised Data
- 3. 論文淺嘗 | Global Relation Embedding for Relation Extraction
- 4. 論文Relational Knowledge Distillation
- 5. Context-Aware Representations for Knowledge Base Relation Extraction論文筆記
- 6. EMNLP2020 | 近期必讀Relation Extraction精選論文
- 7. 【論文筆記】SelfORE: Self-supervised Relational Feature Learning for Open Relation
- 8. 【論文讀後感】Dialogue-Based Relation Extraction
- 9. 論文淺嘗 | Distant Supervision for Relation Extraction
- 10. 論文淺嘗 | Learning with Noise: Supervised Relation Extraction
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相關文章
- 1. 【論文讀後感】Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised
- 2. Open Relation Extraction- Relational Knowledge Transfer from Supervised Data to Unsupervised Data
- 3. 論文淺嘗 | Global Relation Embedding for Relation Extraction
- 4. 論文Relational Knowledge Distillation
- 5. Context-Aware Representations for Knowledge Base Relation Extraction論文筆記
- 6. EMNLP2020 | 近期必讀Relation Extraction精選論文
- 7. 【論文筆記】SelfORE: Self-supervised Relational Feature Learning for Open Relation
- 8. 【論文讀後感】Dialogue-Based Relation Extraction
- 9. 論文淺嘗 | Distant Supervision for Relation Extraction
- 10. 論文淺嘗 | Learning with Noise: Supervised Relation Extraction