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Map-reduce Implementation of Belief Combination Rules

This paper presents a generic and versatile approach for implementing combining rules on preprocessed belief 
 
functions, issuing from a large population of information sources. In this paper, we address two issues, which 
 
are the intrinsic complexity of the rules processing, and the possible large amount of requested combinations. 
 
We present a fully distributed approach, based on a map-reduce (Spark) implementation.