Class structures and lexical similarities of class names for ontology matching

Abstract

Semantic Interoperability is a major issue for National Spatial data Infrastructures (NSDIs) and mapping across heterogeneous databases is essential for such interoperability. Mapping of schemas based on ontology mapping provides opportunities for semantic translation of schemas elements and hence for database queries across heterogeneous sources. Such semantics based mappings are usually human centered processes. This paper demonstrates semi-automatic mapping using semantic similarity values from an electronic lexicon. Lexical similarity of class names and class structures constitute knowledge base for mapping between two schemas. We employ semantic mapping based on synonym similarity matches from WordNet. We use heuristics based propagation of similarities using attribute mapping and superclass-subclass relations. The machine based similarity values are seen to be comparable to human generated values of mapping. © 2007 Springer-Verlag Berlin Heidelberg.