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HSAE: Hierarchical structure augment embedding for various knowledge graph completion
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DOI：10.1016/j.knosys.2025.114320.png)
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Abstract
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• First framework unifying static, temporal, hyper, and few-shot KGC tasks. • Dual-granularity fusion: entity-level and token-level structure augment. • Outperforms competitive baselines on eight benchmarks.
Keywords:
knowledge graph completion
static knowledge graphs
temporal knowledge graphs
hypergraphs
few-shot learning