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Selecting multimedia ontologies to be reused on the basis of the GMAA decision support system

Research Areas
  • Engineering

Reusing knowledge resources has become a popular technique within the ontology engineering field, which allows speeding up the ontology development process, saving time and money, and promoting the application of good practices. Recently, the NeOn methodology has emerged to support this new approach in the development of ontologies. Following NeOn methodology, once the candidate ontologies have been identified, a domain ontology selection is performed to find out which domain ontologies are the most suitable for the development of the ontology network and, finally, the domain ontologies selected are integrated in the ontology network to be developed. The selection of the most appropriate ontologies to be reused in the development of a new ontology is a complex decision-making problem where different conflicting objectives have to be taken into account, like the reuse cost, understandability effort, integration effort and reliability. The Generic Multi-Attribute Analysis System (GMAA) is a decision support system based on an additive multiattribute utility model that is intended to allay many of the operational difficulties involved in the multicriteria decision-making process. The GMAA system accounts for uncertainty about the alternative performances and for incomplete information about the decision-maker?s (DM) preferences, leading to classes of utility functions and weight intervals. This is less demanding for a single DM and also makes the system suitable for group decision support. An application of the GMAA system to select multimedia ontologies to be reused in the development of a new ontology in such a domain (an ontology called M3 that should cover three perspectives: multimedia, multidomain and multilingual) is illustrated throughout the paper.
International Conference on Operations Research 2011
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Book of Abstracts OR 2011

Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Grupo de análisis de decisiones y estadística
  • Grupo de Investigación: Ontology Engineering Group
  • Departamento: Inteligencia Artificial