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Conference Papers Year : 2002

A new definition of qualified gain in a data fusion

Anne Boyer

Abstract

A formal framework is proposed for defining data fusion processes and particularly a notion of qualified gain in a data fusion process is proposed: gain in representation, completeness, accuracy and certainty. These notions are applied to a medical monitoring and diagnosis problem where a dynamic Bayesian network (DBN) is used to modelize time series of observations and evolving states. The model aims at giving a daily diagnosis. Our experiments are under way by using data of an already existing system collected on kidney disease patients. Results will be characterized using our notion of qualified gains.
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Dates and versions

inria-00100825 , version 1 (26-09-2006)

Identifiers

  • HAL Id : inria-00100825 , version 1

Cite

David Bellot, Anne Boyer, François Charpillet. A new definition of qualified gain in a data fusion. The Fifth International Conference on Information Fusion - FUSION'2002, 2002, Annapolis, Maryland, USA, 8 p. ⟨inria-00100825⟩
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