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.
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.
Authors: William R Hersh; M Katherine Crabtree; David H Hickam; Lynetta Sacherek; Charles P Friedman; Patricia Tidmarsh; Craig Mosbaek; Dale Kraemer Journal: J Am Med Inform Assoc Date: 2002 May-Jun Impact factor: 4.497
Authors: Elmer V Bernstam; Jorge R Herskovic; Yindalon Aphinyanaphongs; Constantin F Aliferis; Madurai G Sriram; William R Hersh Journal: J Am Med Inform Assoc Date: 2005-10-12 Impact factor: 4.497
Authors: David A Hanauer; Danny T Y Wu; Lei Yang; Qiaozhu Mei; Katherine B Murkowski-Steffy; V G Vinod Vydiswaran; Kai Zheng Journal: J Biomed Inform Date: 2017-01-25 Impact factor: 6.317