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rdf:type |
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lifeskim:mentions |
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pubmed:dateCreated |
2006-9-5
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pubmed:abstractText |
Document classification is a wide-spread problem with many applications, from organizing search engine snippets to spam filtering. We previously described Textpresso, a text-mining system for biological literature, which marks up full text according to a shallow ontology that includes terms of biological interest. This project investigates document classification in the context of biological literature, making use of the Textpresso markup of a corpus of Caenorhabditis elegans literature.
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pubmed:grant |
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pubmed:commentsCorrections |
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pubmed:language |
eng
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pubmed:journal |
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pubmed:citationSubset |
IM
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pubmed:status |
MEDLINE
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pubmed:issn |
1471-2105
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pubmed:author |
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pubmed:issnType |
Electronic
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pubmed:volume |
7
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pubmed:owner |
NLM
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pubmed:authorsComplete |
Y
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pubmed:pagination |
370
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pubmed:dateRevised |
2009-11-18
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pubmed:meshHeading |
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pubmed:year |
2006
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pubmed:articleTitle |
Automatic document classification of biological literature.
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pubmed:affiliation |
Division of Biology and Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California, USA. davidc@caltech.edu
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pubmed:publicationType |
Journal Article,
Research Support, Non-U.S. Gov't,
Research Support, N.I.H., Extramural
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