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English(EN) SLogic: Subgraph-Informed Logical Rule Learning for Knowledge Graph Completion

SLogic框架学习查询相关的逻辑规则以进行知识图谱补全

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了SLogic，一个用于知识图谱补全（KGC）的新框架，该框架为逻辑规则分配与查询相关的分数。与使用统一规则权重的先前方法不同，SLogic分析查询头实体局部子图以确定规则的重要性。这种方法允许根据其查询上下文区分规则的权重，这与常识推理中的特异性原则一致。实验表明，SLogic取得了有竞争力的性能，并生成了可读的逻辑规则来解释其推理。 AI

影响 该框架通过提供上下文感知的逻辑规则，有望提高知识图谱补全系统的可解释性和准确性。

排序理由 这是一篇详细介绍知识图谱补全新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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SLogic框架学习查询相关的逻辑规则以进行知识图谱补全

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这是一篇详细介绍知识图谱补全新框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.AI TIER_1 English(EN) · Trung Hoang Le, Tran Cao Son, Ishtiaq Ahmed, Huiping Cao ·

    SLogic：基于子图感知的逻辑规则学习用于知识图谱补全

    arXiv:2510.00279v3 Announce Type: replace-cross Abstract: Logical rule-based methods offer an interpretable approach to knowledge graph completion (KGC) by capturing compositional relationships in the form of human-readable inference rules. While existing logical rule-based metho…

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