論文閱讀 Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
論文閱讀 Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks 摘要 如何評估知識圖（KG）中節點的重要性？KG是一個多關係圖，已被證明在許多任務上都有價值，包括問答和語義搜索。本文提出了一種解決KGs中節點重要性評估問題的GENI方法，該方法可以用於項目推薦和資源分配等下游應用。雖然已經有了一些方法來
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相關文章
- 1. Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
- 2. Applications of Graph Neural Networks
- 3. Learning Convolutional Neural Networks for Graphs論文筆記
- 4. 論文解讀：Improving Multi-hop Question Answering over Knowledge Graphs using Knowledge Base Embeddings
- 5. Inductive Representation Learning on Large Graphs 論文閱讀
- 6. 論文閱讀：Extending Neural Generative Conversational Model using External Knowledge Sources
- 7. 論文閱讀：Learning Human-Object Interactions by Graph Parsing Neural Networks
- 8. 【論文解讀 ICLR 2020 | LambdaNet】Probabilistic Type Inference using Graph Neural Networks
- 9. 論文閱讀：Knowledge Graph Convolutional Networks for Recommender Systems
- 10. Emotion Recognition Using Graph Convolutional Networks