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Combining Evidence in the Extended Dempster-Shafer Theory

  • Jiwen Guan
  • Jasmina Pavlin
  • Victor R. Lesser
Conference paper
Part of the Workshops in Computing book series (WORKSHOPS COMP.)

Abstract

The Dempster-Shafer (D-S) theory of evidence generalizes Bayesian probability theory, by providing a coherent representation for ignorance (lack of evidence). However, uncertain relationships between evidence and hypotheses bearing on this evidence are difficult to represent in applications of the theory. Yen [1] extended the theory by introducing a probabilistic mapping that uses conditional probabilities to express these uncertain relationships, and developed a three-step method for combining evidence from different evidential sources. We present a simpler, one-step method for combining evidence based on the extended D-S theory, and prove that it gives the same results.

Keywords

Belief Function Hypothesis Space Focal Element Basic Probability Assignment Evidential Source 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

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Copyright information

© British Computer Society 1990

Authors and Affiliations

  • Jiwen Guan
    • 1
  • Jasmina Pavlin
    • 2
  • Victor R. Lesser
    • 2
  1. 1.Department of Information SystemsUniversity of Ulster at JordanstownNewtownabbeyUK
  2. 2.Department of Computer and Information ScienceUniversity of MassachusettsAmherstUSA

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