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Genescene: Biomedical Text And Data Mining

dc.contributor.authorLeroy, Gondy
dc.contributor.authorChen, Hsinchun
dc.contributor.authorMartinez, Jesse D.
dc.contributor.authorEggers, Shauna
dc.contributor.authorFalsey, Ryan R.
dc.contributor.authorKislin, Kerri L.
dc.contributor.authorHuang, Zan
dc.contributor.authorLi, Jiexun
dc.contributor.authorXu, Jie
dc.contributor.authorMcDonald, Daniel M.
dc.contributor.authorNg, Gavin
dc.date.accessioned2004-08-16T00:00:01Z
dc.date.available2010-06-18T23:34:31Z
dc.date.issued2005en_US
dc.date.submitted2004-08-16en_US
dc.identifier.citationGenescene: Biomedical Text And Data Mining 2005, Journal of the American Society for Information Science & Technologyen_US
dc.identifier.urihttp://hdl.handle.net/10150/105791
dc.descriptionArtificial Intelligence Lab, Department of MIS, University of Arizonaen_US
dc.description.abstractTo access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. Genescene provides biomedical researchers with research findings and background relations automatically extracted from text and experimental data. These provide a more detailed overview of the information available. The extracted relations were evaluated by qualified researchers and are precise. A qualitative ongoing evaluation of the current online interface indicates that this method to search the literature is more useful and efficient than keyword based searching.
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherWiley Periodicals, Incen_US
dc.subjectNational Science Digital Libraryen_US
dc.subjectNSDLen_US
dc.subjectArtificial intelligence laben_US
dc.subjectAI laben_US
dc.subjectGenesceneen_US
dc.subjectData Miningen_US
dc.subjectMedical Librariesen_US
dc.subjectInformation Extractionen_US
dc.titleGenescene: Biomedical Text And Data Miningen_US
dc.typePreprinten_US
dc.identifier.journalJournal of the American Society for Information Science & Technologyen_US
refterms.dateFOA2018-08-16T12:03:41Z
html.description.abstractTo access the content of digital texts efficiently, it is necessary to provide more sophisticated access than keyword based searching. Genescene provides biomedical researchers with research findings and background relations automatically extracted from text and experimental data. These provide a more detailed overview of the information available. The extracted relations were evaluated by qualified researchers and are precise. A qualitative ongoing evaluation of the current online interface indicates that this method to search the literature is more useful and efficient than keyword based searching.


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