Digitisation, Big Data, and the Future of the Medical Humanities/Text-Mining and the History of Medicine: Big Data, Big Questions?
The article presents the authors' views on their experience of embarking on a collaborative project to develop a search engine for medical history. The project involves the use of text mining tools to search for high quality data by analyzing patterns and trends. The project was sponsored by British...
| Publicado en: | Medical History Vol. 60; no. 2; pp. 294 - 297 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Cambridge University Press
Apr2016
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=115449828&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 115449828 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 00257273 7JL jtl: Medical History issn: 00257273 maglogo: N pubinfo: dt: Apr2016 vid: 60 iid: 2 pid: 15979 pub: Cambridge University Press artinfo: ui: 115449828 10.1017/mdh.2016.18 ppf: 294 ppct: 3 formats: tig: atl: Digitisation, Big Data, and the Future of the Medical Humanities/Text-Mining and the History of Medicine: Big Data, Big Questions? aug: au: Toon, Elizabeth Timmermann, Carsten Worboys, Michael affil: University of Manchester, UK su: History of medicine Search engines Computer software development Text mining Data mining Electronic information resource searching sug: subj: History of medicine Search engines Computer software development Text mining Data mining Electronic information resource searching ab: The article presents the authors' views on their experience of embarking on a collaborative project to develop a search engine for medical history. The project involves the use of text mining tools to search for high quality data by analyzing patterns and trends. The project was sponsored by British nonprofit UK Arts and Humanities Research Council and conducted in partnership with the National Centre for Text Mining. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2016 holdings: @attributes: islocal: N |
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