Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks2
ACL 2017年論文 Abs: 核心思想是對KB和text的集合，對知識庫的一種擴展，甚至再細一點，應該算是對text三元組的提取，使用universal schema將KB和text得到的知識映射到同一個embedding space中，然後就是key-value MemoryNetwork的事了。 1. universal schema是什麼？ 一般用於處理知識庫文本中的關係抽取問題，通過e
相關文章
- 1. Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
- 2. 【PaperReading】Knowledge Graph Embedding Based Question Answering
- 3. Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 4. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 5. 論文略讀 | Pattern-revising Enhanced Simple Question Answering over Knowledge Bases
- 6. # Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Netwo
- 7. 【論文解讀 AAAI 2020 | GNTP】Differentiable Reasoning on Large Knowledge Bases and Natural Language
- 8. 論文筆記 Dynamic Memory Networks for Visual and Textual Question Answering（ICML2016)
- 9. (Paper Reading)Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
- 10. Neural Generative Question Answering筆記
- 更多相關文章...
- • W3C RDF and OWL 活動 - W3C 教程
- • XSL-FO table-and-caption 對象 - XSL-FO 教程
- • RxJava操作符（七）Conditional and Boolean
- • 三篇文章瞭解 TiDB 技術內幕 —— 說計算
相關標籤/搜索
每日一句
-
每一个你不满意的现在，都有一个你没有努力的曾经。
歡迎關注本站公眾號,獲取更多信息
相關文章
- 1. Question Answering on Knowledge Bases and Text using Universal Schema and Memory Networks
- 2. 【PaperReading】Knowledge Graph Embedding Based Question Answering
- 3. Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 4. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 5. 論文略讀 | Pattern-revising Enhanced Simple Question Answering over Knowledge Bases
- 6. # Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Netwo
- 7. 【論文解讀 AAAI 2020 | GNTP】Differentiable Reasoning on Large Knowledge Bases and Natural Language
- 8. 論文筆記 Dynamic Memory Networks for Visual and Textual Question Answering（ICML2016)
- 9. (Paper Reading)Bottom-Up and Top-Down Attention for Image Captioning and Visual Question Answering
- 10. Neural Generative Question Answering筆記