Representing biomedical knowledge in the UMLS semantic network
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WordNet: a lexical database for English
Communications of the ACM
Issues and approaches of database integration
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SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
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Communications of the ACM - Ontology: different ways of representing the same concept
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CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
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ER '02 Proceedings of the 21st International Conference on Conceptual Modeling
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Data & Knowledge Engineering
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SSDBM '00 Proceedings of the 12th International Conference on Scientific and Statistical Database Management
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ICDE '02 Proceedings of the 18th International Conference on Data Engineering
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VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
FCA-MERGE: bottom-up merging of ontologies
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
Logical Analysis of Mappings between Medical Classification Systems
AIMSA '08 Proceedings of the 13th international conference on Artificial Intelligence: Methodology, Systems, and Applications
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The Unified Medical Language System (UMLS) contains two separate but interconnected knowledge structures, the Semantic Network (upper level) and the Metathesaurus (lower level). In this paper, we have attempted to work out better how the use of such a two-level structure in the medical field has led to notable advances in terminologies and ontologies. However, most ontologies and terminologies do not have such a two-level structure. Therefore, we present a method, called semantic enrichment, which generates a two-level ontology from a given one-level terminology and an auxiliary two-level ontology. During semantic enrichment, concepts of the one-level terminology are assigned to semantic types, which are the building blocks of the upper level of the auxiliary two-level ontology. The result of this process is the desired new two-level ontology. We discuss semantic enrichment of two example terminologies and how we approach the implementation of semantic enrichment in the medical domain. This implementation performs a major part of the semantic enrichment process with the medical terminologies, with difficult cases left to a human expert.