Presented at: 10th International Semantic Web Conference (ISWC2011)
by Carina Haupt, Paul Groth, Marc Zimmermann
Several approaches integrating life science data using Semantic Web technologies have been described in the literature . However, these approaches have largely ignored the vast amount of content only available within the scientific literature. In this article, we present an RDF schema for text mining results that enables queries in SPARQL over textual and database data together. We show how real pharmacological queries can be answered over 4 billion text mined triples.
Representing Text Mining Results for Structured Pharmacological Queries was presented at this event.
Resource URI on the dog food server: http://data.semanticweb.org/conference/iswc/2011/paper/poster-demo/19
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