Dietze, Heiko ;
Alexopoulou, Dimitra ;
Alvers, Michael R. ;
Barrio-Alvers, Bill ;
Doms, Andreas ;
Hakenberg, Jörg ;
Mönnich, Jan ;
Plake, Conrad ;
Reischuk, Andreas ;
Royer, Loic ;
Wächter, Thomas ;
Zschunke, Matthias ;
Schroeder, Michael
GoPubMed: Exploring Pubmed with Ontological Background Knowledge
Abstract
With the ever increasing size of scientific literature, finding relevant documents and answering questions has become even more of a challenge. Recently, ontologies  hierarchical, controlled vocabularies  have been introduced to annotate genomic data. They can also improve the question answering and the selection of relevant documents in the literature search. Search engines such as GoPubMed.org use ontological background knowledge to give an overview over large query results and to help answering questions. We review the problems and solutions underlying these next generation intelligent search engines and give examples of the power of this new search paradigm.
BibTeX - Entry
@InProceedings{dietze_et_al:DSP:2008:1520,
author = {Heiko Dietze and Dimitra Alexopoulou and Michael R. Alvers and Bill Barrio-Alvers and Andreas Doms and J{\"o}rg Hakenberg and Jan M{\"o}nnich and Conrad Plake and Andreas Reischuk and Loic Royer and Thomas W{\"a}chter and Matthias Zschunke and Michael Schroeder},
title = {GoPubMed: Exploring Pubmed with Ontological Background Knowledge},
booktitle = {Ontologies and Text Mining for Life Sciences : Current Status and Future Perspectives},
year = {2008},
editor = {Michael Ashburner and Ulf Leser and Dietrich Rebholz-Schuhmann},
number = {08131},
series = {Dagstuhl Seminar Proceedings},
ISSN = {1862-4405},
publisher = {Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik, Germany},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2008/1520},
annote = {Keywords: Text mining, literature search, Gene Ontology, NLP, ontology, thesaurus, PubMed}
}
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Keywords: |
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Text mining, literature search, Gene Ontology, NLP, ontology, thesaurus, PubMed |
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Seminar: |
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08131 - Ontologies and Text Mining for Life Sciences : Current Status and Future Perspectives
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Issue date: |
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2008 |
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Date of publication: |
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03.06.2008 |