Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings

时间 2021-01-02

标签论文阅读笔记 paper 繁體版

原文原文链接

Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings 0.Summary 1.Reseach Objective this research on multi-hop KGQA( Question Answering over Knowledge Graphs)

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1. 论文解读：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
2. Knowledge Base Question Answering via Encodin of Complex Query Graphs
3. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. 论文总结之问答生成《Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering》
6. # Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Netwo
7. Improved Neural Relation Detection for Knowledge Base Question Answering
8. Learning over Knowledge-Base Embeddings for Recommendation 论文
9. 论文略读 | Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base
10. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global
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1. 论文解读：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
2. Knowledge Base Question Answering via Encodin of Complex Query Graphs
3. 论文解读：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. 论文总结之问答生成《Improving Knowledge-aware Dialogue Generation via Knowledge Base Question Answering》
6. # Strong Baselines for Simple Question Answering over Knowledge Graphs with and without Neural Netwo
7. Improved Neural Relation Detection for Knowledge Base Question Answering
8. Learning over Knowledge-Base Embeddings for Recommendation 论文
9. 论文略读 | Dialog-to-Action: Conversational Question Answering Over a Large-Scale Knowledge Base
10. An End-to-End Model for Question Answering over Knowledge Base with Cross-Attention Combining Global

>>更多相关文章<<