A probabilistic evaluation function for relaxed unification

  • Authors:

  • Tony Abou-Assaleh;Nick Cercone;Vlado Kešelj

  • Affiliations:

  • Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada;Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada;Faculty of Computer Science, Dalhousie University, Halifax, Nova Scotia, Canada

  • Venue:
  • COMPSAC-W'05 Proceedings of the 29th annual international conference on Computer software and applications conference
  • Year:
  • 2005

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Abstract

Classical unification is strict in the sense that it requires a perfect agreement between the terms being unified. In practise, data are seldom error-free and can contain incorrect information. Classical unification fails when the data are imperfect. Relaxed unification is a new formalism that relaxes the rigid constraints of classical unification and enables reasoning under uncertainty and in the presence of inconsistent data. We propose a probabilistic evaluation function to evaluate the degree of mismatches in relaxed terms and illustrate its use with an example.