Artificial Intelligence Lab, Department of MIS, University of Arizona / In this paper we describe MedTextus, an online medical search portal with dynamic search and browse tools. To search for information, MedTextus lets users request synonyms and related terms specifically tailored to their query. A mapping algorithm dynamically builds the query context based on the UMLS ontology and then selects thesaurus terms that fit this context. Users can add these terms to their query and meta-search five medical databases. To facilitate browsing, the search results can be reviewed as a list of documents per database, as a set of folders into which all the documents are automatically categorized based on their content, and as a map that is built on the fly. We designed a user study to compare these dynamic support tools with the static query support of NLM Gateway and report on initial results for the search task. The users used NLM Gateway more effectively, but used MedTextus more efficiently and preferred its query formation tools.
| Identifer | oai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/105231 |
| Date | January 2002 |
| Creators | Leroy, Gondy, Chen, Hsinchun |
| Source Sets | University of Arizona |
| Language | English |
| Detected Language | English |
| Type | Conference Paper |
Page generated in 0.0016 seconds