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More Than the Sum of Its Parts – Holistic Ontology Alignment by Population-Based Optimisation

  • Jürgen Bock
  • Sebastian Rudolph
  • Michael Mutter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7153)

Abstract

Ontology alignment is a key challenge to allow for interoperability between heterogeneous semantic data sources. Today, most algorithms extract an alignment from a matrix of the pairwise similarities of ontological entities of two ontologies. However, this standard approach has severe disadvantages regarding scalability and is incapable of accounting for global alignment quality criteria that go beyond the aggregation of independent pairwise correspondence evaluations. This paper considers the ontology alignment problem as an optimisation problem that can be addressed using nature-inspired population-based optimisation heuristics. This allows for the deployment of an objective function which can be freely defined to take into account individual correspondence evaluations as well as global alignment constraints. Moreover, such algorithms can easily be parallelised and show anytime behaviour due to their iterative nature. The paper generalises an existing approach to the alignment problem based on discrete particle swarm optimisation, and presents a novel implementation based on evolutionary programming. First experimental results demonstrate feasibility and scalability of the presented approaches.

Keywords

Global Alignment Reference Alignment Discrete Particle Swarm Optimisation Alignment System Ontology Match 
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 2012

Authors and Affiliations

  • Jürgen Bock
    • 1
  • Sebastian Rudolph
    • 2
  • Michael Mutter
    • 1
  1. 1.FZI Research Center for Information TechnologyKarlsruheGermany
  2. 2.Karlsruhe Institue of TechnologyKarlsruheGermany

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