Multi-database mining.
Biomedical data useful for data mining are often distributed across multiple databases. These databases may be aggregated using several techniques to create single data sets that may be mined using standard approaches; however, separate databases may, in their design or data representation, capture...
| Publicado en: | Clinics in Laboratory Medicine Vol. 28; no. 1; pp. 73 - 83 |
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| Autores principales: | , |
| Formato: | tables/charts Journal Article |
| Publicado: |
W B Saunders
2008 Mar
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105904751&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105904751 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 02722712 23R jtl: Clinics in Laboratory Medicine issn: 02722712 maglogo: N pubinfo: dt: 2008 Mar vid: 28 iid: 1 pid: 1351 pub: W B Saunders place: Philadelphia, Pennsylvania artinfo: ui: 105904751 105904751 2009807250 NLM18194719 105904751 ppf: 73 ppct: 10 formats: tig: atl: Multi-database mining. aug: au: Siadaty MS Harrison JH Jr. affil: Division of Clinical Informatics, Department of Public Health Sciences, University of Virginia, Suite 3181 West Complex, 1335 Hospital Drive Charlottesville, VA 22908, USA. sug: subj: Data Mining Methods Medical Informatics Data Warehouse Resource Databases ab: Biomedical data useful for data mining are often distributed across multiple databases. These databases may be aggregated using several techniques to create single data sets that may be mined using standard approaches; however, separate databases may, in their design or data representation, capture information that is analytically useful and that is lost on integration. Recent techniques for mining multiple databases simultaneously but separately may preserve and leverage the unique perspectives within each database. This article presents an example, 'dual mining,' in which concurrent analysis of a target database with a related knowledge base can improve the identification of association patterns in the target most likely to be of interest for further analysis. Copyright © 2008 by Elsevier Inc. pubtype: Periodical doctype: tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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