支持模糊量化查询的通用框架，可处理标准与模糊本体及知识图谱。
Fuzzy Quantification over OWL Ontologies and Knowledge Graphs
- 统一框架支持类型I和类型II模糊量化表达式查询
- 无需指定量词类型或评估方法，适配多种数据源
- 开源实现Q2S2助力后续研究，提升可复现性
本文提出一个通用框架，用于在标准本体、模糊本体以及知识图谱上评估模糊量化查询。主要目标是检索满足类型I或类型II模糊量化表达式的个体。该方法的核心优势在于其固有的灵活性：完全不依赖于量词类型、底层评估方式以及本体的数据源（即OWL本体或RDFS知识图谱）。此外，我们开发了公开可用的系统Q2S2，以支持未来的研究工作。
原文摘要 · Abstract (English)
This paper presents a versatile framework for evaluating fuzzy quantification queries over both standard and fuzzy ontologies as well as knowledge graphs. The primary objective is the retrieval of individuals that satisfy queries articulated via Type I or Type II fuzzy quantified expressions. A key advantage of the proposed approach is its inherent adaptability: it remains entirely agnostic to the quantifier type, the underlying evaluation method, and the specific data source of the ontology (i.e., OWL ontologies or RDFS knowledge graphs). Furthermore, we present Q2S2, a publicly accessible implementation of this system developed to support future research.
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