OM4OV: Leveraging Ontology Matching for Ontology Versioning

Autor:	Qiang, Zhangcheng, Taylor, Kerry
Rok vydání:	2024
Předmět:	Computer Science - Artificial Intelligence Computer Science - Computation and Language Computer Science - Information Retrieval
Druh dokumentu:	Working Paper
Popis:	Due to the dynamic nature of the semantic web, ontology version control is required to capture time-varying information, most importantly for widely-used ontologies. Despite the long-standing recognition of ontology versioning (OV) as a crucial component for efficient ontology management, the growing size of ontologies and accumulating errors caused by manual labour overwhelm current OV approaches. In this paper, we propose yet another approach to performing OV using existing ontology matching (OM) techniques and systems. We introduce a unified OM4OV pipeline. From an OM perspective, we reconstruct a new task formulation, performance measurement, and dataset construction for OV tasks. Reusing the prior alignment(s) from OM, we also propose a cross-reference mechanism to effectively reduce the matching candidature and improve overall OV performance. We experimentally validate the OM4OV pipeline and its cross-reference mechanism using three datasets from the Alignment Evaluation Initiative (OAEI) and exploit insights on OM used for OV tasks. Comment: 7 pages, 7 figures, 1 table
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2409.20302 Zobrazit plný text záznamu View this record from Arxiv