Persistent Link:
http://hdl.handle.net/10150/105231
Title:
MedTextus: An Ontology-enhanced Medical Portal
Author:
Leroy, Gondy; Chen, Hsinchun
Citation:
MedTextus: An Ontology-enhanced Medical Portal 2002,
Issue Date:
2002
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105231
Submitted date:
2004-08-16
Abstract:
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.
Type:
Conference Paper
Language:
en
Keywords:
Medical Libraries; Digital Libraries
Local subject classification:
National Science Digital Library; NSDL; Artificial Intelligence lab; MedTextus

Full metadata record

DC FieldValue Language
dc.contributor.authorLeroy, Gondyen_US
dc.contributor.authorChen, Hsinchunen_US
dc.date.accessioned2004-08-16T00:00:01Z-
dc.date.available2010-06-18T23:21:52Z-
dc.date.issued2002en_US
dc.date.submitted2004-08-16en_US
dc.identifier.citationMedTextus: An Ontology-enhanced Medical Portal 2002,en_US
dc.identifier.urihttp://hdl.handle.net/10150/105231-
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractIn 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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.subjectMedical Librariesen_US
dc.subjectDigital Librariesen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial Intelligence laben_US
dc.subject.otherMedTextusen_US
dc.titleMedTextus: An Ontology-enhanced Medical Portalen_US
dc.typeConference Paperen_US
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