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Essie: a concept-based search engine for structured biomedical text.
Full Abstract
This article describes the algorithms implemented in the Essie search engine that is currently serving several Web sites at the National Library of Medicine. Essie is a phrase-based search engine with term and concept query expansion and probabilistic relevancy ranking. Essie's design is motivated by an observation that query terms are often conceptually related to terms in a document, without actually occurring in the document text. Essie's performance was evaluated using data and standard evaluation methods from the 2003 and 2006 Text REtrieval Conference (TREC) Genomics track. Essie was the best-performing search engine in the 2003 TREC Genomics track and achieved results comparable to those of the highest-ranking systems on the 2006 TREC Genomics track task. Essie shows that a judicious combination of exploiting document structure, phrase searching, and concept based query expansion is a useful approach for information retrieval in the biomedical domain.
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Author information
Author/s: Ide, Nicholas C (NC); Loane, Russell F (RF); Demner-Fushman, Dina (D);
Affiliation: Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD 20894, USA. ide(-atsign-)nlm.nih.gov
Journal and publication information
Publication Type: Evaluation Studies; Journal Article
Journal: Journal of the American Medical Informatics Association : JAMIA (J Am Med Inform Assoc), published in United States. (Language: eng)
Reference: -2007 May-Jun; vol 14 (issue 3) : pp 253-63
Dates: Created 2007/05/04; Completed 2007/06/12; Revised 2008/11/20;
PMID: 17329729, status: MEDLINE (last retrieval date: 12/26/2008)
Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.
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