The creation of links between schemas of published datasets is a key part of the Linked Open Data (LOD) paradigm. The ability to discover these links "on the go" requires that ontology matching techniques achieve good precision and recall within acceptable execution times. In this paper, we add similarity-based and mediator-based ontology matching methods to the Agreementmaker ontology matching system, which aim to efficiently discover high precision subclass mappings between LOD ontologies. Similarity-based matching methods discover subclass mappings by extrapolating them from a set of high quality equivalence mappings and from the interpretation of compound concept names. Mediator-based matching methods discover subclass mappings by comparing polysemic lexical annotations of ontology concepts and by considering external web ontologies. Experiments show that when compared with a leading LOD approach, Agreementmaker achieves considerably higher precision and F-measure, at the cost of a slight decrease in recall. © 2012 Springer Science+Business Media Dordrecht.

Cruz, I., Palmonari, M., Caimi, F., Stroe, C. (2013). Building linked ontologies with high precision using subclass mapping discovery. ARTIFICIAL INTELLIGENCE REVIEW, 40(2), 127-145 [10.1007/s10462-012-9363-x].

Building linked ontologies with high precision using subclass mapping discovery

PALMONARI, MATTEO LUIGI;
2013

Abstract

The creation of links between schemas of published datasets is a key part of the Linked Open Data (LOD) paradigm. The ability to discover these links "on the go" requires that ontology matching techniques achieve good precision and recall within acceptable execution times. In this paper, we add similarity-based and mediator-based ontology matching methods to the Agreementmaker ontology matching system, which aim to efficiently discover high precision subclass mappings between LOD ontologies. Similarity-based matching methods discover subclass mappings by extrapolating them from a set of high quality equivalence mappings and from the interpretation of compound concept names. Mediator-based matching methods discover subclass mappings by comparing polysemic lexical annotations of ontology concepts and by considering external web ontologies. Experiments show that when compared with a leading LOD approach, Agreementmaker achieves considerably higher precision and F-measure, at the cost of a slight decrease in recall. © 2012 Springer Science+Business Media Dordrecht.
Articolo in rivista - Articolo scientifico
semantic web, data integration, ontology matching, linked data
English
2013
40
2
127
145
none
Cruz, I., Palmonari, M., Caimi, F., Stroe, C. (2013). Building linked ontologies with high precision using subclass mapping discovery. ARTIFICIAL INTELLIGENCE REVIEW, 40(2), 127-145 [10.1007/s10462-012-9363-x].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/49299
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