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Discounting and Combination Scheme in Evidence Theory for Dealing with Conflict in Information Fusion

  • Van-Nam Huynh
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5861)

Abstract

Recently combination rules as well as the issue of conflict management in Dempster-Shafer theory have received considerable attention in information fusion research. Mostly these studies considered the combined mass assigned to the empty set as the conflict and have tried to provide alternatives to Dempster’s rule of combination, which mainly differ in the way of how to manage the conflict. In this paper, we introduce a hybrid measure to judge the difference between two bodies of evidence as a basis for conflict analysis, and argue that using the combined mass assigned to the empty set as a whole to quantify conflict seems inappropriate. We then propose to use the discounting operator in association with the combination operator to resolve conflict when combining evidence, in which the discount rate of a basic probability assignment is defined using the entropy of its corresponding pignistic probability function. Finally, an application of this discounting and combination scheme to fusion of decisions in classifier combination is demonstrated.

Keywords

Support Vector Machine Discount Rate Combination Scheme Combination Rule Belief Function 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Van-Nam Huynh
    • 1
  1. 1.School of Knowledge ScienceJapan Advanced Institute of Science and TechnologyIshikawaJapan

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