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Evaluation of Document Retrieval Systems on a Medical Corpus in French: Indexation vs. Feature Learning.
Robert, Arnaud; Damachi, Francis; Bjelogrlic, Mina; Goldman, Jean-Philippe; Lovis, Christian.
Afiliación
  • Robert A; Division of Medical Information Sciences, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
  • Damachi F; Division of Medical Information Sciences, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
  • Bjelogrlic M; Division of Medical Information Sciences, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
  • Goldman JP; Division of Medical Information Sciences, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
  • Lovis C; Division of Medical Information Sciences, University Hospitals of Geneva and University of Geneva, Geneva, Switzerland.
Stud Health Technol Inform ; 270: 208-212, 2020 Jun 16.
Article en En | MEDLINE | ID: mdl-32570376
This paper presents five document retrieval systems for a small (few thousands) and domain specific corpora (weekly peer-reviewed medical journals published in French) as well as an evaluation methodology to quantify the models performance. The proposed methodology does not rely on external annotations and therefore can be used as an ad hoc evaluation procedure for most document retrieval tasks. Statistical models and vector space models are empirically compared on a synthetic document retrieval task. For our dataset size and specificities the statistical approaches consistently performed better than its vector space counterparts.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Lenguaje Natural / Modelos Estadísticos / Almacenamiento y Recuperación de la Información / Medical Subject Headings / Lenguaje Tipo de estudio: Evaluation_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2020 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Países Bajos
Texto completo
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Procesamiento de Lenguaje Natural / Modelos Estadísticos / Almacenamiento y Recuperación de la Información / Medical Subject Headings / Lenguaje Tipo de estudio: Evaluation_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Stud Health Technol Inform Asunto de la revista: INFORMATICA MEDICA / PESQUISA EM SERVICOS DE SAUDE Año: 2020 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Países Bajos