PROMPT: Algorithm and Tool for Automated Ontology Merging and Alignment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
The Chimaera Ontology Environment
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Adapting a Generic Match Algorithm to Align Ontologies of Human Anatomy
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
SAMBO-A system for aligning and merging biomedical ontologies
Web Semantics: Science, Services and Agents on the World Wide Web
Instance-based matching of large life science ontologies
DILS'07 Proceedings of the 4th international conference on Data integration in the life sciences
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The increasing number of on-line accessible biological data sources has involved a growth of the number and the size of ontologies. This makes it increasingly valuable to map ontologies each other to determine which of their concepts are semantically related. Nowadays, developed tools are often semi-automatic and require the help of experts. Determining semantic relations between concepts is a difficult task, and the problem is still open. Several methods have been proposed in the literature. Existing tools for mapping concepts usually combine several methods, called matchers. In this paper, we propose a tool called OMIE (Ontology Mapping within an Interactive and Extensible environment) which uses and combines several matchers. OMIE is extensible, i.e. matchers could be added or inhibited, and is interactive, i.e. experts could validate or invalidate mappings as well as choose between mapping specific concepts or mapping the entire ontologies.