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First published January 9, 2007 as JAMIA PrePrint; doi:10.1197/jamia.M2191
Journal of the American Medical Informatics Association 2007;14(2):212-220
© 2007 American Medical Informatics Association

A more recent version of this article appeared on March 1, 2007
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Submitted on July 1, 2006
Accepted on December 6, 2006

A Day in the Life of PubMed: Analysis of a Typical Day's Query Log

Jorge R. Herskovic MD, MS1*, Len Y. Tanaka MD2, William Hersh MD3, and Elmer V. Bernstam MD, MS, MSE4

Affiliation of the authors: 1 The University of Texas School of Health Information Sciences at Houston, Houston, TX ; 2 The University of Texas School of Health Information Sciences at Houston, Houston, TX; Department of Pediatrics, Division of Pediatric Critical Care, The University of Texas School of Medicine at Houston, Houston, TX ; 3 Department of Medical Informatics and Clinical Epidemiology, Oregon Health & Science University, Portland, OR ; 4 The University of Texas School of Health Information Sciences at Houston, Houston, TX; Department of Internal Medicine, Division of General Internal Medicine, The University of Texas School of Medicine at Houston, Houston, TX

* To whom correspondence should be addressed.

Objective To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines.

Design We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day.

Measurements We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies.

Results The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms.

Conclusion PubMed's usage profile must be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.






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