A temporal knowledge graph reasoning model based on recurrent encoding and contrastive learning
Temporal knowledge graphs (TKGs) are critical tools for capturing the dynamic nature of facts that evolve over time, making them highly valuable in a broad spectrum of intelligent applications. In the domain of temporal knowledge graph extrapolation reasoning, the prediction of future occurrences is...
| 主要な著者: | , , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
PeerJ Inc.
2025-01-01
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| シリーズ: | PeerJ Computer Science |
| 主題: | |
| オンライン･アクセス: | https://peerj.com/articles/cs-2595.pdf |