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Updated: Jul 18, 2026
05:02
Comparing Bibliometric Analysis Using PubMed, Scopus, and Web of Science Databases
Published on: October 24, 2019
Specific classification of elibrary resources says more about users' preferences
Judas Robinson1, Simon de Lusignan, Patty Kostkova
1St. George's, University of London, Cranmer Terrace, London, SW17 0RE. jsrobins@sgul.ac.uk
Studies in Health Technology and Informatics
|November 17, 2006
Summary
Specific Medical Subject Headings (MeSH) terms accurately predict user preferences in digital libraries, unlike generic terms. Analyzing specific MeSH classifications reveals user interests that generic terms obscure.
Area of Science:
- Information Science
- Medical Informatics
- Library Science
Background:
- Medical Subject Headings (MeSH) is a hierarchical taxonomy of over 42,000 descriptors used to classify scientific literature.
- The Primary Care Electronic Library (PCEL) utilized MeSH to classify over 1,000 resources.
Purpose of the Study:
- To determine if generic or specific MeSH terms best predict user preferences for resources in a digital library.
- To evaluate the effectiveness of MeSH term specificity in understanding user behavior.
Main Methods:
- Each resource in the PCEL was assigned up to five MeSH terms.
- A comparative analysis was conducted to assess whether specific or generic MeSH terms better predicted user preferences.
Main Results:
- Statistically significant differences in user preferences were observed for resources classified by specific MeSH terms over a four-month period.
- This significant predictive power was not found when analyzing generic MeSH terms.
Conclusions:
- Specific MeSH terms effectively reveal user preferences within digital libraries that generic terms do not capture.
- Utilizing specific MeSH classifications enhances the understanding of user interests and information-seeking behavior.
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