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Ontology Adaptation upon Updates

  • Alessandro Solimando
  • Giovanna Guerrini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7955)

Abstract

Ontologies, like any other model, change over time due to modifications in the modeled domain, deeper understanding of the domain by the modeler, error corrections, simple refactoring or shift of modeling granularity level. Local changes usually impact the remainder of the ontology as well as any other data and metadata defined over it. The massive size of ontologies and their possible fast update rate requires automatic adaptation methods for relieving ontology engineers from a manual intervention, in order to allow them to focus mainly on high-level inspection. This paper, in spirit of the Principle of minimal change, proposes a fully automatic ontology adaptation approach that reacts to ontology updates and computes sound reformulations of ontological axioms triggered by the presence of certain preconditions. The rule-based adaptation algorithm covers up to \(\mathcal{SROIQ}\) DL.

Keywords

Description Logic Belief Revision Adaptation Algorithm Ontology Evolution Adaptation Rule 
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 2013

Authors and Affiliations

  • Alessandro Solimando
    • 1
  • Giovanna Guerrini
    • 1
  1. 1.Dipartimento di Informatica, Bioingegneria, Robotica e Ingegneria dei SistemiUniversità di GenovaItaly

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