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Semantic Metrics

  • Bo Hu
  • Yannis Kalfoglou
  • Harith Alani
  • David Dupplaw
  • Paul Lewis
  • Nigel Shadbolt
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4248)

Abstract

In the context of the Semantic Web, many ontology-related operations, e.g. ontology ranking, segmentation, alignment, articulation, reuse, evaluation, can reduced to one fundamental operation: computing the similarity and/or dissimilarity among ontological entities, and in some cases among ontologies themselves. In this paper, we review standard metrics for computing distance measures and we propose a series of semantic metrics. We give a formal account of semantic metrics drawn from a variety of research disciplines, and enrich them with semantics based on standard Description Logic constructs. We argue that concept-based metrics can be aggregated to produce numeric distances at ontology-level and we speculate on the usability of our ideas in potential areas.

Keywords

Resource Description Framework Description Logic Vector Space Model Conditional Entropy Numeric Distance 
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 2006

Authors and Affiliations

  • Bo Hu
    • 1
  • Yannis Kalfoglou
    • 1
  • Harith Alani
    • 1
  • David Dupplaw
    • 1
  • Paul Lewis
    • 1
  • Nigel Shadbolt
    • 1
  1. 1.IAM Group, ECSUniversity of SouthamptonUK

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