Task Oriented Evaluation of Module Extraction Techniques

  • Authors:
  • Ignazio Palmisano;Valentina Tamma;Terry Payne;Paul Doran

  • Affiliations:
  • Department of Computer Science, University of Liverpool, Liverpool, United Kingdom L69 3BX;Department of Computer Science, University of Liverpool, Liverpool, United Kingdom L69 3BX;Department of Computer Science, University of Liverpool, Liverpool, United Kingdom L69 3BX;Department of Computer Science, University of Liverpool, Liverpool, United Kingdom L69 3BX

  • Venue:
  • ISWC '09 Proceedings of the 8th International Semantic Web Conference
  • Year:
  • 2009

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Abstract

Ontology Modularization techniques identify coherent and often reusable regions within an ontology. The ability to identify such modules, thus potentially reducing the size or complexity of an ontology for a given task or set of concepts is increasingly important in the Semantic Web as domain ontologies increase in terms of size, complexity and expressivity. To date, many techniques have been developed, but evaluation of the results of these techniques is sketchy and somewhat ad hoc. Theoretical properties of modularization algorithms have only been studied in a small number of cases. This paper presents an empirical analysis of a number of modularization techniques, and the modules they identify over a number of diverse ontologies, by utilizing objective, task-oriented measures to evaluate the fitness of the modules for a number of statistical classification problems.