Semantic annotation of biomedical literature using google

  • Authors:

  • Rune Sætre;Amund Tveit;Tonje S. Steigedal;Astrid Lægreid

  • Affiliations:

  • Department of Computer and Information Science, Norwegian University of Science, and Technology, Trondheim, Norway;Department of Computer and Information Science, Norwegian University of Science, and Technology, Trondheim, Norway;Department of Cancer Research and Molecular Medicine, Norwegian University of Science, and Technology, Trondheim, Norway;Department of Cancer Research and Molecular Medicine, Norwegian University of Science, and Technology, Trondheim, Norway

  • Venue:
  • ICCSA'05 Proceedings of the 2005 international conference on Computational Science and Its Applications - Volume Part III
  • Year:
  • 2005

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Abstract

With the increasing amount of biomedical literature, there is a need for automatic extraction of information to support biomedical researchers. Due to incomplete biomedical information databases, the extraction is not straightforward using dictionaries, and several approaches using contextual rules and machine learning have previously been proposed. Our work is inspired by the previous approaches, but is novel in the sense that it is using Google for semantic annotation of the biomedical words. The semantic annotation accuracy obtained – 52% on words not found in the Brown Corpus, Swiss-Prot or LocusLink (accessed using Gsearch.org) – is justifying further work in this direction.