Group decision making in ontology matching

  • Authors:

  • Mahdieh Kargar-Ghavi;Mohammad Reza Khayyambashi

  • Affiliations:

  • University of Isfahan, Isfahan, Iran;University of Isfahan, Isfahan, Iran

  • Venue:
  • Proceedings of the International Conference on Web Intelligence, Mining and Semantics
  • Year:
  • 2011

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Abstract

Ontology matching tries to establish semantic relations between similar elements in different ontologies to provide interoperability in the semantic web. Dealing with the problem of semantic heterogeneity is a key point in the semantic web environment. The (semi) automatic generating of mappings with respect to uncertainty is a labor intensive and error prone task. While the confidence values of mappings themselves are uncertain, how can the aggregation method between them be certain? How can we model them in a certain manner? This paper introduces a new approach for modeling uncertainty in ontology matching on the basis of fuzzy set theory and then describes an iterative algorithm that exploits group decision making solutions to aggregate opinions of matchers into a group consensus one. Thus matching systems are combined to overcome contradictory and incomplete alignments, so that the quality and accuracy of final alignment will be improved.