Artificial Intelligence Lab, Department of MIS, University of Arizona / This paper describes the development and testing of the Medical Concept Mapper as an aid to providing
synonyms and semantically related concepts to improve searching. All terms are related to the userquery
and fit into the query context. The system is unique because its five components combine humancreated
and computer-generated elements. The Arizona Noun Phraser extracts phrases from natural
language user queries. WordNet and the UMLS Metathesaurus provide synonyms. The Arizona Concept
Space generates conceptually related terms. Semantic relationships between queries and concepts are
established using the UMLS Semantic Net. Two user studies conducted to evaluate the system are
described.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105149 |
| Date | January 1999 |
| Creators | Leroy, Gondy, Tolle, Kristin M., Chen, Hsinchun |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Conference Paper |
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