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BioNav: An Ontology-Based Framework to Discover Semantic Links in the Cloud of Linked Data

  • María-Esther Vidal
  • Louiqa Raschid
  • Natalia Márquez
  • Jean Carlo Rivera
  • Edna Ruckhaus
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6089)

Abstract

We demonstrate BioNav, a system to efficiently discover potential novel associations between drugs and diseases by implementing Literature-Based Discovery techniques. BioNav exploits the wealth of the Cloud of Linked Data and combines the power of ontologies and existing ranking techniques, to support discovery requests. We discuss the formalization of a discovery request as a link-analysis and authority-based problem, and show that the top ranked target objects are in correspondence with the potential novel discoveries identified by existing approaches. We demonstrate how by exploiting properties of the ranking metrics, BioNav provides an efficient solution to the link discovery problem.

Keywords

Link Data MeSH Term Query Optimizer Ranking Technique Nerve Growth Factor Protein 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • María-Esther Vidal
    • 1
  • Louiqa Raschid
    • 2
  • Natalia Márquez
    • 1
  • Jean Carlo Rivera
    • 1
  • Edna Ruckhaus
    • 1
  1. 1.Universidad Simón BolívarCaracasVenezuela
  2. 2.University of Maryland 

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