Learning to map between ontologies on the semantic web
Proceedings of the 11th international conference on World Wide Web
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
A survey of approaches to automatic schema matching
The VLDB Journal — The International Journal on Very Large Data Bases
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Standardized medical terminologies are often used for the registration of patient data. In several situations there is a need to align these terminologies to other terminologies. Even when the terminologies cover the same domain, this is often a non-trivial task. The task is even more complicated when the terminology does not contain much structure. In this paper we describe the initial results of a procedure for mapping a terminology with little or no structure to a structure-rich terminology. This procedure uses the knowledge of the structure-rich terminology and a method for semantic explicitation of concept descriptions. The first results shows that, when compared to approaches based on syntactic analysis only, the recall can be greatly improved without sacrificing much of the precision.