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

時間 2021-01-02

標籤論文閱讀筆記 paper 简体版

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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. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
2. Knowledge Base Question Answering via Encodin of Complex Query Graphs
3. 論文解讀：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. 論文總結之問答生成《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 論文
9. 論文略讀 | 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. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
2. Knowledge Base Question Answering via Encodin of Complex Query Graphs
3. 論文解讀：Question Answering over Knowledge Base with Neural Attention Combining Global Knowledge Info...
4. 【PaperReading】Knowledge Graph Embedding Based Question Answering
5. 論文總結之問答生成《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 論文
9. 論文略讀 | 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

>>更多相關文章<<