Generating MEDLINE search strategies using a librarian knowledge-based system.
We describe a librarian knowledge-based system that generates a search strategy from a query representation based on a user's information need. Together with the natural language parser AQUA, the system functions as a human/computer interface, which translates a user query from free text into a BRS Onsite search formulation, for searching the MEDLINE bibliographic database. In the system, conceptual graphs are used to represent the user's information need. The UMLS Metathesaurus and Semantic Net are used as the key knowledge sources in building the knowledge base.
Peng
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P
Center for Medical Informatics, Columbia-Presbyterian Medical Center, New York 10032.
Aguirre
A
A
Johnson
S B
SB
Cimino
J J
JJ
D001185:Artificial Intelligence; D003198:Computer Simulation; D006801:Humans; D016247:Information Storage and Retrieval; D016245:Librarians; D016239:MEDLINE; D008962:Models, Theoretical; D009323:Natural Language Processing; D012660:Semantics; D017432:Unified Medical Language System