WCONS: An Ontology Mapping Approach Based on Word and Context Similarity
Zhen Zhen, Junyi Shen, Shengjun Lu · 2008
This paper introduces an ontology mapping approach based on word and context similarity (WCONS) to find equivalence relation between concepts from two different ontologies, using Levenshtein distance and Tverskypsilas similarity model. The context of each concept is expanded to four kinds of facet contexts for context similarity computing, which are structure facet context, relation facet context, attribute facet context and instance facet context. A preliminary experiment is then conducted using ontologies #101, #301, #302, #303 and #304 in benchmark suite of OAEI 2007, indicating that WCONS can be evidently helpful to discovering semantic mappings for ontology integration.