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GoPubMed: Exploring Pubmed with Ontological Background Knowledge Dietze, Heiko Alexopoulou, Dimitra Alvers, Michael R. Barrio-Alvers, Bill Doms, Andreas Hakenberg, Jörg Mönnich, Jan Plake, Conrad Reischuck, Andreas Royer, Loic Wächter, Thomas Zschunke, Matthias Schroeder, Michael Text mining literature search Gene Ontology NLP ontology thesaurus PubMed 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. Schloss Dagstuhl – Leibniz-Zentrum für Informatik Heiko Dietze and Dimitra Alexopoulou and Michael R. Alvers and Bill Barrio-Alvers and Andreas Doms and Jörg Hakenberg and Jan Mönnich and Conrad Plake and Andreas Reischuck and Loic Royer and Thomas Wächter and Matthias Zschunke and Michael Schroeder 2008 Is Part Of Dagstuhl Seminar Proceedings, Volume 8131, Ontologies and Text Mining for Life Sciences : Current Status and Future Perspectives (2008) InProceedings Text doc-type:ResearchArticle publishedVersion application/pdf doi:10.4230/DagSemProc.08131.6 urn:nbn:de:0030-drops-15204 https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.08131.6 eng https://creativecommons.org/licenses/by/4.0/legalcode