【论文笔记】Information Extraction over Structured Data: Question Answering with Freebase

时间 2020-12-23

标签 KBQA 信息抽取问答系统繁體版

原文原文链接

一、概要该文章发于ACL 2014，作者提出了一个基于Freebase knowledge base，结合web-scale语料，通过信息抽取的方法进行KBQA，并在当时取得了比前人方法都要好的效果。二、模型方法 2.1 任务简介假设给一个问题中含有一个或几个主题（topics），那么我们就会基于这些主题在知识库中寻找答案，主题在知识库中的主题节点（topic node），以及与其相

>>阅读原文<<

1. Information Extraction over Structured Data: Question Answering with Freebase【论文笔记】
2. 【论文笔记】Question Answering over Freebase with Multi-Column Convolutional Neural Networks
3. 论文浅尝 | Question Answering over Freebase
4. 【论文笔记】Question Answering with Subgraph Embeddings
5. Question Answering with Subgraph Embeddings笔记
6. Question Answering with Subgraph Embeddings【论文笔记】
7. Question Answering over Freebase via Attentive RNN with Similarity Matrix based CNN
8. Character-Level Question Answering with Attention 论文笔记
9. More Accurate Question Answering on Freebase阅读笔记
10. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
更多相关文章...
• CAP理论是什么？ - NoSQL教程
• ASP.NET Razor - 标记 - ASP.NET 教程
• Tomcat学习笔记（史上最全tomcat学习笔记）
• Scala 中文乱码解决

最新文章

1. 融合阿里云，牛客助您找到心仪好工作
2. 解决jdbc(jdbctemplate)在测试类时不报错在TomCatb部署后报错
3. 解决PyCharm GoLand IntelliJ 等 JetBrains 系列 IDE无法输入中文
4. vue+ant design中关于图片请求不显示的问题。
5. insufficient memory && Native memory allocation (malloc) failed
6. 解决IDEA用Maven创建的Web工程不能创建Java Class文件的问题
7. [已解决] Error: Cannot download ‘https://start.spring.io/starter.zip?
8. 在idea让java文件夹正常使用
9. Eclipse启动提示“subversive connector discovery”
10. 帅某-技巧-快速转帖博主文章（article_content）

本站公众号

欢迎关注本站公众号,获取更多信息

1. Information Extraction over Structured Data: Question Answering with Freebase【论文笔记】
2. 【论文笔记】Question Answering over Freebase with Multi-Column Convolutional Neural Networks
3. 论文浅尝 | Question Answering over Freebase
4. 【论文笔记】Question Answering with Subgraph Embeddings
5. Question Answering with Subgraph Embeddings笔记
6. Question Answering with Subgraph Embeddings【论文笔记】
7. Question Answering over Freebase via Attentive RNN with Similarity Matrix based CNN
8. Character-Level Question Answering with Attention 论文笔记
9. More Accurate Question Answering on Freebase阅读笔记
10. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...

>>更多相关文章<<