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Exploring semantic dependency for reasoning over temporal knowledge graph
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AI
DOI：10.1016/j.engappai.2026.114845.png)
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Abstract
En 中文
• A temporal knowledge graph reasoning method proposed for scenarios with insufficient historical information. • To exploit potential semantic dependencies based on k-hop rule path beyond the direct interactions. • A theoretical analysis is conducted on the rationality of potential semantic dependency. • A negative-free contrastive learning is employed to enhance the semantic dependency.
Keywords:
temporal knowledge graph
semantic dependency
rule path
contrastive learning
reasoning
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