論文解讀：Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question
論文解讀：Multi-Task Learning with Multi-View Attention for Answer Selection and Knowledge Base Question 知識圖譜問答的任務目標是在給定一個自然問句以及對應的知識庫下，找到正確的答案（實體）。本文則通過多任務學習的框架，利用多視角注意力機制完成知識圖譜問答任務。 1、什麼是知識圖譜？ 知識圖譜是近
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相關文章
- 1. 論文解讀：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
- 2. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 3. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global
- 4. 論文解讀：Improved Neural Relation Detection for Knowledge Base Question Answering
- 5. embedding entities and relations for learning and inference knowledge base
- 6. Learning over Knowledge-Base Embeddings for Recommendation 論文
- 7. [論文解讀]Test Selection for Deep Learning Systems
- 8. 論文筆記：Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answer
- 9. Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering筆記
- 10. 論文閱讀 decaNLP -- The Natural Language Decathlon: Multitask Leaning as Question Answering