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Efficient cluster-guided key timestamp discovery for temporal knowledge graph completion
DOI:10.1016/j.knosys.2025.114537.png)
Abstract
En 中文
• Effectively addresses the “time lag” problem in temporal KG completion. • Instruction-tuned language models guide relation clustering in temporal KGs. • Discovers key timestamps via temporal analysis using relation clustering. • Historical view contrastive learning enhances relevant entity representations.
Journal
K
IF:
7.6
Papers:
1.2W
Citations:
4.5W

