Ontology mapping is a task aiming to align semantic resources in order to foster the re-use of information and to enable the knowledge and data expressed in the matched ontologies to interoperate. When ontology mapping algorithms are applied in practice, a manual refinement is furtherly necessary for validating the correctness of the resulted resource, especially, as it happens in real-world cases, when a gold standard cannot be exploited for assessing the generated mappings. In this paper, we present a suggestion-based mapping system, integrated as a component of a knowledge management platform, implementing an information retrieval-based (IR-based) approach for generating and validating, by experts, mappings between ontologies. The proposed platform has been evaluated quantitatively (i.e. effectiveness of suggestions, reduction of the user effort, etc.) and qualitatively (i.e. usability) on two use cases: Organic.Lingua and PRESTO, respectively an EU-funded and regional-funded projects. The results demonstrated the effectiveness and usability of the proposed platform in a real-world environment.
Multilingual Ontology Mapping in Practice: A Support System for Domain Experts
Dragoni, Mauro
2015-01-01
Abstract
Ontology mapping is a task aiming to align semantic resources in order to foster the re-use of information and to enable the knowledge and data expressed in the matched ontologies to interoperate. When ontology mapping algorithms are applied in practice, a manual refinement is furtherly necessary for validating the correctness of the resulted resource, especially, as it happens in real-world cases, when a gold standard cannot be exploited for assessing the generated mappings. In this paper, we present a suggestion-based mapping system, integrated as a component of a knowledge management platform, implementing an information retrieval-based (IR-based) approach for generating and validating, by experts, mappings between ontologies. The proposed platform has been evaluated quantitatively (i.e. effectiveness of suggestions, reduction of the user effort, etc.) and qualitatively (i.e. usability) on two use cases: Organic.Lingua and PRESTO, respectively an EU-funded and regional-funded projects. The results demonstrated the effectiveness and usability of the proposed platform in a real-world environment.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
