Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
這是一篇將GNN運用在預測知識圖譜(Knowledge Graph)節點重要性的文章，被KDD2019接收。文中提出了GENI模型，在GNN聚合信息的過程中只聚合一個標量（score）而不是聚合節點的embedding。 Introduction 知識圖譜可以看做是一個有向多關係圖，並且節點之間可能存在不止一條邊。 Given a KG, estimating the importance of
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相關文章
- 1. 論文閱讀 Estimating Node Importance in Knowledge Graphs Using Graph Neural Networks
- 2. Applications of Graph Neural Networks
- 3. Emotion Recognition Using Graph Convolutional Networks
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- 5. Learning Convolutional Neural Networks for Graphs
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- 10. STRATEGIES FOR PRE-TRAINING GRAPH NEURAL NETWORKS