Linked Life Data

11079965

Source:http://linkedlifedata.com/resource/pubmed/id/11079965

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:dateCreated
2001-1-10
pubmed:abstractText
A searcher's inability to formulate an appropriate query can result in an overwhelming number of retrieved documents. Our approach to this problem is to use information about common types or categories of queries to (1) reformulate the user's initial query and (2) create an informative organization of the retrieved documents from the reformulated query. To achieve these goals, we first must identify which common categories or types of queries are the best abstraction of the user's specific query. In this paper, we describe a system that performs this first step of categorizing the user's query. Our system uses a two-phased approach: a lexical analysis phase, and a semantic analysis phase. An evaluation of our system demonstrates that its query categorization corresponds reasonably well to the query categorizations by medical librarians and physicians.
pubmed:commentsCorrections
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:issn
1531-605X
pubmed:author
pubmed:issnType
Print
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
655-9
pubmed:dateRevised
2009-11-18
pubmed:meshHeading
pubmed:year
2000
pubmed:articleTitle
QueryCat: automatic categorization of MEDLINE queries.
pubmed:affiliation
Information and Computer Science Department, University of California, Irvine, USA. pratt@ics.uci.edu
pubmed:publicationType
Journal Article, Evaluation Studies