论文标题
用语义嵌入和基于逻辑的模块将本体学对齐任务划分
Dividing the Ontology Alignment Task with Semantic Embeddings and Logic-based Modules
论文作者
论文摘要
大型本体论仍然对最新的本体一致性系统构成严重挑战。在本文中，我们提出了一种结合神经嵌入模型和基于逻辑的模块的方法，以将输入本体匹配任务准确分为较小且更可拖动的匹配（子）任务。我们使用本体一致评估计划的数据集进行了全面的评估。结果令人鼓舞，并表明所提出的方法在实践中足够，并且可以集成到无法应对大本体论的系统的工作流程中。
Large ontologies still pose serious challenges to state-of-the-art ontology alignment systems. In this paper we present an approach that combines a neural embedding model and logic-based modules to accurately divide an input ontology matching task into smaller and more tractable matching (sub)tasks. We have conducted a comprehensive evaluation using the datasets of the Ontology Alignment Evaluation Initiative. The results are encouraging and suggest that the proposed method is adequate in practice and can be integrated within the workflow of systems unable to cope with very large ontologies.
