Information Extraction over Structured Data: Question Answering with Freebase【論文筆記】
Information Extraction over Structured Data:Question Answering with Freebase 一、摘要 最近，人們一直在探索使用Freebase知識庫來回答自然語言問題，作爲在開放域語義分析中推進最新技術發展的平臺。 這些努力將問題映射到複雜的意義表示，然後嘗試將其與知識庫中的可行答案候選者進行匹配。 在這裏，我們
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相關文章
- 1. 【論文筆記】Information Extraction over Structured Data: Question Answering with Freebase
- 2. 【論文筆記】Question Answering over Freebase with Multi-Column Convolutional Neural Networks
- 3. 論文淺嘗 | Question Answering over Freebase
- 4. More Accurate Question Answering on Freebase閱讀筆記
- 5. Question Answering with Subgraph Embeddings筆記
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- 7. Character-Level Question Answering with Attention 論文筆記
- 8. 【論文筆記】Question Answering with Subgraph Embeddings
- 9. Question Answering over Freebase via Attentive RNN with Similarity Matrix based CNN
- 10. 論文解讀：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...