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First published February 28, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2233
Journal of the American Medical Informatics Association 2007;14(3):253-263
© 2007 American Medical Informatics Association

A more recent version of this article appeared on May 1, 2007
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Submitted on July 31, 2006
Accepted on January 26, 2007

Essie: A Concept Based Search Engine for Structured Biomedical Text

Nicholas C. Ide1*, Russell F. Loane1, and Dina Demner-Fushman1

Affiliation of the authors: 1 Lister Hill National Center for Biomedical Communications, National Library of Medicine, Bethesda, MD; Thoughtful Solutions, Inc., McLean, VA

* To whom correspondence should be addressed.

This paper 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 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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