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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.
Semantic query expansion improves PubMed searches. Evaluating three strategies, UMLS and CISMeF showed similar precision, but results varied by descriptor, suggesting tailored approaches for medical literature retrieval.
Area of Science:
- Medical Informatics
- Information Retrieval
- Biomedical Literature Search
Background:
- PubMed is a critical resource for accessing medical literature.
- Semantic query expansion, utilizing synonyms, can enhance search effectiveness.
Purpose of the Study:
- To evaluate the performance of three distinct semantic query expansion strategies.
- Assessing the impact of MeSH synonyms, UMLS mappings, and CISMeF mappings on PubMed search results.
Main Methods:
- Developed queries for 40 MeSH descriptors using three semantic expansion techniques.
- Sent queries to PubMed and evaluated the relevance of the top 20 retrieved citations by three independent judges.
Main Results:
- UMLS expansion yielded slightly higher mean precision (74.19%) than CISMeF (70.28%), though not statistically significant.
- Significant variation in retrieval performance was observed across different descriptors.
- Low inter-rater agreement (0.28) indicated subjectivity in relevance judgments.
Conclusions:
- The effectiveness and precision of semantic expansion strategies differ significantly based on the chosen descriptor, likely due to synonym quality.
- Combining UMLS and CISMeF expansions may offer optimal results.
- Information retrieval systems should offer adaptable semantic expansion options tailored to specific descriptors and user search goals.
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