An approach for automated matching of Linked Open Data at the schema level with very high scoring evaluation results, based on comparison with manually mapped schemata of major LOD datasets to PROTON upper level ontology.

1. Contextual Ontology Alignment of LOD with an Upper Ontology: A Case Study with PROTON Prateek Jain, Peter Z. Yeh, Kumal Verma, Reymond Vasques, Mariana Damova, Pascal Hitzler and Amit Sheth ESWC’2011

28. Experimental Results Linked Open Data and Proton Schema Ontology Alignment DB-PRO GEO-PRO FB-PRO Overall System Rec Prec F Rec Prec F Rec Prec F Rec Prec F AROMA 0.19 0.59 0.28 0.04 8/1000 0.01 0.31 0.49 0.38 0.22 0.37 0.28 S-Match-M 0.26 0.05 0.08 0.04 6/1000 0.01 0.2 0.05 0.08 0.23 0.05 0.08 S-Match-C 0.33 3/1000 6/1000 0.04 0.009 0.01 0.3 0.4 0.34 0.31 4/1000 0.007 BLOOMS 0.48 0.19 0.27 0.04 6/1000 0.01 0.28 0.32 0.3 0.42 0.19 0.26 BLOOMS+ no context 0.77 0.59 0.67 0.04 5/1000 0.01 0.48 0.65 0.55 0.66 0.45 0.54 BLOOMS+ 0.73 0.90 0.81 0.04 5/1000 0.01 0.49 0.59 0.54 0.63 0.55 0.59

30. Related Work Euzenat, J. & al. Matching ontologies for context, a Tech Report of NEON project from 2007 - rely on background knowledge from online ontologies - their process relies on identification of contextual relationship using the relationships encoded in the ontologies Ontology matching surveys (Euzenat and Shvaiko, 2007) emphasize that systems typically utilize a structured source of information (dictionaries or upper level ontologies) Wikipedia categorization has been utilized for creating and restructuring taxonomies Identification and creation of links between LOD cloud datasets ontology schema matching used to improve instance coreference resolution UMBEL – a unified reference point to LOD schemas