Interpreting natural language queries using the UMLS

This paper describes AQUA (A QUery Analyzer), the natural language front end of a prototype information retrieval system. AQUA translates a user's natural language query into a representation in the Conceptual Graph formalism. The graph is then used by subsequent components to search various resources such as databases of the medical literature. The focus of the parsing method is on semantics rather than syntax, with semantic restrictions being provided by the UMLS Semantic Net. The intent of the approach is to provide a method that can be emulated easily in applications that require simple natural language interfaces.

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.