让知识图谱符合本体规范，提升可解释性与跨系统兼容性。
Ontology-Compliant Knowledge Graphs
- 基于模式匹配实现知识图谱与本体的内外一致性对齐
- 提出新型术语匹配算法与合规度量指标，支持跨源图谱整合
- 在建筑领域验证可行性，适合需标准化数据的工程场景
本体可作为构建知识图谱（KG）的模式，提供可解释性、互操作性和可重用性。本文探讨了‘本体合规’知识图谱，旨在实现内部与外部的本体一致性。我们分析了本体合规的关键任务，提出了新的术语匹配算法和基于模式的合规方法，以及全新的合规度量标准。以建筑行业为案例研究，验证了本体合规知识图谱的有效性。建议使用本体合规知识图谱来实现异构知识图谱的自动匹配、对齐与调和。
原文摘要 · Abstract (English)
Ontologies can act as a schema for constructing knowledge graphs (KGs), offering explainability, interoperability, and reusability. We explore \emph{ontology-compliant} KGs, aiming to build both internal and external ontology compliance. We discuss key tasks in ontology compliance and introduce our novel term-matching algorithms. We also propose a \emph{pattern-based compliance} approach and novel compliance metrics. The building sector is a case study to test the validity of ontology-compliant KGs. We recommend using ontology-compliant KGs to pursue automatic matching, alignment, and harmonisation of heterogeneous KGs.
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