Related Experiment Video
Updated: Jul 17, 2026
Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
Published on: February 23, 2019
A day in the life of PubMed: analysis of a typical day's query log
Jorge R Herskovic1, Len Y Tanaka, William Hersh
1University of Texas School of Health Information Sciences at Houston, 7000 Fannin St. Suite 600, Houston, TX 77030, USA.
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 should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.
