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Link Representation and Discovery

  • Philipp Cimiano
  • Christian Chiarcos
  • John P. McCrae
  • Jorge Gracia
Chapter

Abstract

In this chapter we address the question of how links can be discovered between different datasets published as Linguistic Linked Open Data. We describe common patterns to represent links both between data that are on the same language (monolingual scenario) and between data in different languages (cross-lingual scenario). Further, we describe techniques that can be used to automatically discover links between datasets. As most of these techniques rely on computing similarities between data elements, we briefly review the most common techniques for computing syntactic and semantic similarity. Finally, we provide a brief overview of tools and frameworks that can be used to semi-automatically discover links between language resources.

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Semantic Computing GroupBielefeld UniversityBielefeldGermany
  2. 2.Angewandte ComputerlinguistikGoethe-UniversityFrankfurt am MainGermany
  3. 3.Insight Centre for Data AnalyticsNational University of IrelandGalwayIreland
  4. 4.Aragon Institute of Engineering Research (I3A)University of ZaragozaZaragozaSpain

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