On the soundness of altering granular information

  • Authors:
  • Ronald R. Yager

  • Affiliations:
  • Machine Intelligence Institute, Iona College, New Rochelle, NY 10801, United States

  • Venue:
  • International Journal of Approximate Reasoning
  • Year:
  • 2007

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Abstract

Computer based multi-source and information fusion is often an intermediate step in the deduction of decision-relevant information. Fuzzy sets provide a useful formalism for the representation of the types of uncertain granular information that appear as inputs and outputs of these fusion systems. When our ultimate goal is the derivation of human oriented decision-relevant information we must often alter the output of these fusion systems to provide information in a form more readily accessible to the human recipient. In this work we introduce and investigate a measure of soundness which can be used to calculate the validity of various alterations of fuzzy granular information in the course of transforming outputs of fusion systems into forms more useful for human comprehension and manipulation. An important role in this work is played by the idea of similarity.