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IF Cruz, W Sunna (2008)
Structural alignment methods with applications to geospatial ontologiesTrans GIS Special Issue Semant Similarity Meas Geosp Appl, 12
J Li, J Tang, Y Li, Q Luo (2009)
RiMOM: a dynamic multistrategy ontology alignment frameworkIEEE Trans Data Knowl Eng, 21
S Sorrentino, S Bergamaschi, M Gawinecki, L Po (2010)
Schema label normalization for improving schema matchingData Knowl Eng, 69
C Bizer, T Heath, T Berners-Lee (2009)
Linked data—the story so farInt J Semant Web Inf Sys (IJSWIS), 5
IF Cruz, F Palandri Antonelli, C Stroe (2009)
AgreementMaker: efficient matching for large real-world schemas and ontologiesPVLDB, 2
AJG Gray, J Sadler, O Kit, K Kyzirakos, M Karpathiotakis, JP Calbimonte, K Page, R Garca-Castro, A Frazer, I Galpin, AAA Fernandes, NW Paton, O Corcho, M Koubarakis, DD Roure, K Martinez, A Gmez-Prez (2011)
A semantic sensor web for environmental decision support applicationsSensors, 11
E Rahm, PA Bernstein (2001)
A survey of approaches to automatic schema matchingVLDB J, 10
E Williams (1981)
On the notions “Lexically Related” and “Head of a Word”Linguist Inq, 12
L Po, S Sorrentino (2011)
Automatic generation of probabilistic relationships for improving schema matchingInf Syst, 36
J Euzenat, P Shvaiko (2007)
Ontology Matching
ED Valle, I Celino, D Dell’Aglio, R Grothmann, F Steinke, V Tresp (2011)
Semantic traffic-aware routing using the larkc platformIEEE Internet Comput, 15
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.
Artificial Intelligence Review – Springer Journals
Published: Nov 9, 2012
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