【論文筆記】Representation Learning of Knowledge Graphs with Entity Descriptions
中文標題：融入實體描述的知識圖譜表示學習 發表會議：AAAI-2016 文章鏈接：Representation Learning of Knowledge Graphs with Entity Descriptions 源碼鏈接：DKRL 1 Introduction 1.1 問題陳述： 知識圖譜嵌入將知識圖譜中的實體和關係表示爲低維的連續向量，從而使知識圖譜可以適用於機器學習模型。 大多數知識圖
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相關文章
- 1. 論文筆記：Representation Learning of Knowledge Graphs with Entity Descriptions
- 2. [論文學習]TDN: An Integrated Representation Learning Model of Knowledge Graphs
- 3. 論文筆記008-《A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs》
- 4. 論文筆記: Inductive Representation Learning on Large Graphs
- 5. Inductive Representation Learning on Large Graphs論文筆記
- 6. 論文筆記：Inductive Representation Learning on Large Graphs
- 7. 【論文筆記】SEEK: Segmented Embedding of Knowledge Graphs
- 8. 《Multi-Label Zero-Shot Learning With Structured Knowledge Graphs》論文筆記
- 9. 讀書筆記3：Representation Learning on Graphs with Jumping Knowledge Networks
- 10. Multi-Label Zero-Shot Learning with Structured Knowledge Graphs 論文筆記