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English(EN) OntoAligner-Ensemble: Voting-Based Fusion across Heterogeneous Ontology Alignment Techniques

新框架融合多种技术以改进本体对齐

作者 PulseAugur 编辑部 · [1 个来源] ·

研究人员开发了OntoAligner-Ensemble，一个旨在通过结合各种技术的预测来改进本体对齐的框架。该集成方法采用两阶段的投票式融合和融合后选择过程来协调不同的对齐器输出。该框架支持集成轻量级字符串对齐器、知识图谱嵌入模型和基于大型语言模型的方法，在多个基准任务中展示了精确率和召回率的一致性提升。 AI

影响 通过集成各种LLM和嵌入技术，增强了本体对齐能力，可能改进知识图谱构建和语义搜索。

排序理由 该条目是一篇研究论文，详细介绍了一种新的本体对齐框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

新框架融合多种技术以改进本体对齐

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该条目是一篇研究论文，详细介绍了一种新的本体对齐框架。[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) · Hamed Babaei Giglou, S\"oren Auer, Peio Popov, Mahsa Sanaei, Jennifer D'Souza ·

    OntoAligner-Ensemble：异构本体对齐技术间的基于投票的融合

    arXiv:2608.31137v1 Announce Type: new Abstract: Ontology alignment (OA) has evolved through several methodological paradigms, ranging from lexical and structural aligners to knowledge graph embedding (KGE) models and, more recently, Large Language Model (LLM)-based approaches. Al…

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