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Performance evaluation of three semantic expansions to query PubMed.
Massonnaud, Clément; Lelong, Romain; Kerdelhué, Gaétan; Lejeune, Emeline; Grosjean, Julien; Griffon, Nicolas; Darmoni, Stefan J.
Afiliação
  • Massonnaud C; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France.
  • Lelong R; LIMICS U1142, Sorbonne Université, Paris, France.
  • Kerdelhué G; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France.
  • Lejeune E; LIMICS U1142, Sorbonne Université, Paris, France.
  • Grosjean J; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France.
  • Griffon N; LIMICS U1142, Sorbonne Université, Paris, France.
  • Darmoni SJ; Department of Biomedical Informatics, Rouen University Hospital, Normandy, France.
Health Info Libr J ; 38(2): 113-124, 2021 Jun.
Article em En | MEDLINE | ID: mdl-31837099
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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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Comportamento Apetitivo / PubMed Idioma: En Ano de publicação: 2021 Tipo de documento: Article País de afiliação: França

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Comportamento Apetitivo / PubMed Idioma: En Ano de publicação: 2021 Tipo de documento: Article País de afiliação: França