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Towards a framework for approximate ontologies
2003 (English)In: Fundamenta Informaticae, ISSN 0169-2968, Vol. 57, no 2-4, 147-165Artikel i tidskrift (Refereed) Published
Abstract [en]

Currently, there is a great deal of interest in developing tools for the generation and use of ontologies on the WWW. These knowledge structures are considered essential to the success of the semantic web, the next phase in the evolution of the WWW. Much recent work with ontologies assumes that the concepts used as building blocks are crisp as opposed to approximate. It is a premise of this paper that approximate concepts and ontologies will become increasingly more important as the semantic web becomes a reality. We propose a framework for specifying, generating and using approximate ontologies. More specifically, (1) a formal framework for defining approximate concepts, ontologies and operations on approximate concepts and ontologies is presented. The framework is based on intuitions from rough set theory, (2) algorithms for automatically generating approximate ontologies from traditional crisp ontologies or from large data sets together with additional knowledge are presented. The knowledge will generally be related to similarity measurements between individual objects in the data sets, or constraints of a logical nature which rule out particular constellations of concepts and dependencies in generated ontologies. The techniques for generating approximate ontologies are parameterizable. The paper provides specific instantiations and examples.

Keyword [en]
approximate concept, approximate reasoning, approximation space, category, concept, approximate concept, approximate ontology, ontology, tolerance space, tolerance-based ontology
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-48415 (URN)oai:DiVA.org:liu-48415 (OAI)
Available from2009-10-11 Created:2009-10-11 Last updated:2011-02-27

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Doherty, PatrickGrabowski, MLukaszewicz, WitoldSzalas, Andrzej
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The Institute of TechnologyKPLAB - Knowledge Processing Lab
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