Semantic Parsing via Staged Query Graph Generation: Question Answering with Knowledge Base（笔记）

时间 2020-12-29

标签知识图谱繁體版

原文原文链接

introduction 组织世界上的事实并且把它们存储成结构化的数据逐渐变成开源域问答的重要资源，例如：DBPedia (Auer et al., 2007) and Freebase (Bollacker et al., 2008)，大部分的KBQA都是基于语义解析。把问题转化为语义表示，然后转化为KB查询。答案能够简单地通过查询得到，同时，语义解析能够提供一个深度理解问题的方法，不仅能够提供

>>阅读原文<<

1. Knowledge Base Question Answering via Encodin of Complex Query Graphs
2. Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering笔记
3. Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering读书笔记
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. Improved Neural Relation Detection for Knowledge Base Question Answering
6. 论文总结之问答生成《Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering》
7. Constraint-Based Question Answering with Knowledge Graph 论文笔记
8. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
9. Neural Generative Question Answering笔记
10. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global
更多相关文章...
• PDO::query - PHP参考手册
• ASP.NET Razor - 标记 - ASP.NET 教程
• Tomcat学习笔记（史上最全tomcat学习笔记）
• Composer 安装与使用

最新文章

1. Window下Ribbit MQ安装
2. Linux下Redis安装及集群搭建
3. shiny搭建网站填坑战略
4. Mysql8.0.22安装与配置详细教程
5. Hadoop安装及配置
6. Python爬虫初学笔记
7. 部署LVS-Keepalived高可用集群
8. keepalived+mysql高可用集群
9. jenkins 公钥配置
10. HA实用详解

本站公众号

欢迎关注本站公众号,获取更多信息

1. Knowledge Base Question Answering via Encodin of Complex Query Graphs
2. Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering笔记
3. Modeling Semantics with Gated Graph Neural Networks for Knowledge Base Question Answering读书笔记
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. Improved Neural Relation Detection for Knowledge Base Question Answering
6. 论文总结之问答生成《Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering》
7. Constraint-Based Question Answering with Knowledge Graph 论文笔记
8. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
9. Neural Generative Question Answering笔记
10. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global

>>更多相关文章<<