Persistent Link:
http://hdl.handle.net/10150/105791
Title:
Genescene: Biomedical Text And Data Mining
Author:
Leroy, Gondy; Chen, Hsinchun; Martinez, Jesse D.; Eggers, Shauna; Falsey, Ryan R.; Kislin, Kerri L.; Huang, Zan; Li, Jiexun; Xu, Jie; McDonald, Daniel M.; Ng, Gavin
Citation:
Genescene: Biomedical Text And Data Mining 2005, Journal of the American Society for Information Science & Technology
Publisher:
Wiley Periodicals, Inc
Journal:
Journal of the American Society for Information Science & Technology
Issue Date:
2005
Description:
Artificial Intelligence Lab, Department of MIS, University of Arizona
URI:
http://hdl.handle.net/10150/105791
Submitted date:
2004-08-16
Abstract:
To 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.
Type:
Preprint
Language:
en
Keywords:
Data Mining; Medical Libraries; Information Extraction
Local subject classification:
National Science Digital Library; NSDL; Artificial intelligence lab; AI lab; Genescene

Full metadata record

DC FieldValue Language
dc.contributor.authorLeroy, Gondyen_US
dc.contributor.authorChen, Hsinchunen_US
dc.contributor.authorMartinez, Jesse D.en_US
dc.contributor.authorEggers, Shaunaen_US
dc.contributor.authorFalsey, Ryan R.en_US
dc.contributor.authorKislin, Kerri L.en_US
dc.contributor.authorHuang, Zanen_US
dc.contributor.authorLi, Jiexunen_US
dc.contributor.authorXu, Jieen_US
dc.contributor.authorMcDonald, Daniel M.en_US
dc.contributor.authorNg, Gavinen_US
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.en_US
dc.format.mimetypeapplication/pdfen_US
dc.language.isoenen_US
dc.publisherWiley Periodicals, Incen_US
dc.subjectData Miningen_US
dc.subjectMedical Librariesen_US
dc.subjectInformation Extractionen_US
dc.subject.otherNational Science Digital Libraryen_US
dc.subject.otherNSDLen_US
dc.subject.otherArtificial intelligence laben_US
dc.subject.otherAI laben_US
dc.subject.otherGenesceneen_US
dc.titleGenescene: Biomedical Text And Data Miningen_US
dc.typePreprinten_US
dc.identifier.journalJournal of the American Society for Information Science & Technologyen_US
All Items in UA Campus Repository are protected by copyright, with all rights reserved, unless otherwise indicated.