【論文筆記】SEEK: Segmented Embedding of Knowledge Graphs
來自ACL2020 paper：SEEK: Segmented Embedding of Knowledge Graphs code：https://github.com/Wentao-Xu/SEEK 目錄 摘要 1.引言 2.相關工作 3.SEEK的框架 3.1打分函數（四種） 3.2討論 複雜度分析 與其他方法比較 3.3訓練 4.實驗 數據集 對比實驗 參數 鏈接預測 5.總結 三級目錄 6
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相關文章
- 1. 論文筆記008-《A Benchmarking Study of Embedding-based Entity Alignment for Knowledge Graphs》
- 2. 【論文筆記】Representation Learning of Knowledge Graphs with Entity Descriptions
- 3. 論文筆記：Representation Learning of Knowledge Graphs with Entity Descriptions
- 4. 論文筆記003-《Entity Alignment between Knowledge Graphs Using Attribute Embeddings》
- 5. 論文筆記——News Recommendation with Topic-Enriched Knowledge Graphs
- 6. Multi-Label Zero-Shot Learning with Structured Knowledge Graphs 論文筆記
- 7. [論文學習]TDN: An Integrated Representation Learning Model of Knowledge Graphs
- 8. 【論文筆記】Embedding of Embedding (EOE) : Joint Embedding for Coupled Heterogeneous Networks
- 9. 《Multi-Label Zero-Shot Learning With Structured Knowledge Graphs》論文筆記
- 10. Knowledge Base Question Answering via Encodin of Complex Query Graphs