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Updated: Jan 1, 2026
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Performance evaluation of three semantic expansions to query PubMed
Clément Massonnaud1,2, Romain Lelong1,2, Gaétan Kerdelhué1,2
1Department of Biomedical Informatics, Rouen University Hospital, Normandy, France.
Background:
PubMed is one of the most important basic tools to access medical literature. Semantic query expansion using synonyms can improve retrieval efficacy.
Objective:
The objective was to evaluate the performance of three semantic query expansion strategies.
Methods:
Queries were built for forty MeSH descriptors using three semantic expansion strategies (MeSH synonyms, UMLS mappings, and mappings created by the CISMeF team), then sent to PubMed. To evaluate expansion performances for each query, the first twenty citations were selected, and their relevance were judged by three independent evaluators based on the title and abstract.
Results:
Queries built with the UMLS expansion provided new citations with a slightly higher mean precision (74.19%) than with the CISMeF expansion (70.28%), although the difference was not significant. Inter-rater agreement was 0.28. Results varied greatly depending on the descriptor selected.
Discussion:
The number of citations retrieved by the three strategies and their precision varied greatly according to the descriptor. This heterogeneity could be explained by the quality of the synonyms. Optimal use of these different expansions would be through various combinations of UMLS and CISMeF intersections or unions.
Conclusion:
Information retrieval tools should propose different semantic expansions depending on the descriptor and the search objectives.
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