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Third ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL'03)
Genescene: Biomedical Text And Data Mining
Houston, Texas USA
May 27-May 31
ISBN: 0-7695-1939-3
Gondy Leroy, University of Arizona
Hsinchun Chen, University of Arizona
Jesse D. Martinez, University of Arizona
Shauna Eggers, University of Arizona
Ryan R. Falsey, University of Arizona
Kerri L. Kislin, University of Arizona
Zan Huang, University of Arizona
Jiexun Li, University of Arizona
Jie Xu, University of Arizona
Daniel M. McDonald, University of Arizona
Gavin Ng, University of Arizona
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.
Gondy Leroy, Hsinchun Chen, Jesse D. Martinez, Shauna Eggers, Ryan R. Falsey, Kerri L. Kislin, Zan Huang, Jiexun Li, Jie Xu, Daniel M. McDonald, Gavin Ng, "Genescene: Biomedical Text And Data Mining," jcdl, pp.116, Third ACM/IEEE-CS Joint Conference on Digital Libraries (JCDL'03), 2003
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