An Architecture for Semi-Automatic Ontology Merging System
Siham Amrouch, Sihem Mostefai
Journal of Data Processing, Vol. 2, No. 2, 2012.
DOI: 
Link: http://www.dline.info/jdp/fulltext/v1n2/5.pdf
Abstract:
In recent years, ontologies have played a key technology role for information sharing and agents interoperabilityin different information systems. But, it seems that there is always more than one conceptualization for the same domain oreven for similar domains. In other words, it emerges every day, new different ontology to model the same domain. Therefore,to answer queries on the modeled domain, bridge the gaps between different ontologies is a key challenge for the researchersin the AI community by using ontology merging. In this paper, we propose an architecture for a semi-automatic ontologymerging process. The semi-automatic character is handled by the human intervention where the knowledge engineer inter-venes to validate the results provided by the similarity computation module. This later is based on a lexicosemantic algo-rithm that combines lexical and semantic measures to identify the similar concepts that have to be merged into a single onein the merged ontology, after human validation. The judged different concepts are directly copied to the merged ontology.