The Development of Search Filters for One Health Articles Using CAB Abstracts Descriptors


Journal article


Jeanine M. Williamson, Maggie Albro, Steven D. Milewski, Brianne Dosch, Niki Cobb, Melanie A. Dixson
Journal of Agricultural & Food Information, vol. 24(1-4), 2023, pp. 29-39


Cite

Cite

APA   Click to copy
Williamson, J. M., Albro, M., Milewski, S. D., Dosch, B., Cobb, N., & Dixson, M. A. (2023). The Development of Search Filters for One Health Articles Using CAB Abstracts Descriptors. Journal of Agricultural &Amp; Food Information, 24(1-4), 29–39. https://doi.org/10.1080/10496505.2023.2275059


Chicago/Turabian   Click to copy
Williamson, Jeanine M., Maggie Albro, Steven D. Milewski, Brianne Dosch, Niki Cobb, and Melanie A. Dixson. “The Development of Search Filters for One Health Articles Using CAB Abstracts Descriptors.” Journal of Agricultural & Food Information 24, no. 1-4 (2023): 29–39.


MLA   Click to copy
Williamson, Jeanine M., et al. “The Development of Search Filters for One Health Articles Using CAB Abstracts Descriptors.” Journal of Agricultural &Amp; Food Information, vol. 24, no. 1-4, 2023, pp. 29–39, doi:10.1080/10496505.2023.2275059.


BibTeX   Click to copy

@article{williamson2023a,
  title = {The Development of Search Filters for One Health Articles Using CAB Abstracts Descriptors},
  year = {2023},
  issue = {1-4},
  journal = {Journal of Agricultural & Food Information},
  pages = {29-39},
  volume = {24},
  doi = {10.1080/10496505.2023.2275059},
  author = {Williamson, Jeanine M. and Albro, Maggie and Milewski, Steven D. and Dosch, Brianne and Cobb, Niki and Dixson, Melanie A.}
}

Abstract

This study seeks to develop and test the recall of two search hedges for One Health articles. CAB Abstracts was searched, and the first 100 relevance-ranked results were downloaded. The most frequent co-occurrences of CAB descriptors were used to develop a hedge. A second hedge was developed using the descriptors and related natural language keywords. The natural language hedge had better recall (100% and 95%, respectively) than the co-occurrence hedge (24% and 86%, respectively). When searching a broad-based topic area like One Health, there is a need for expansive language to incorporate multiple expressions of a concept.
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Recipient of the 2024 Medical Library Association Animal and Veterinary Information Specialist Research Award 


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