%0 Conference Proceedings %T Map-reduce implementation of belief combination rules %+ Lab-STICC_ENSTAB_CID_SFIIS %+ Pôle STIC_REMS %A Dambreville, Frédéric %< avec comité de lecture %B DATA 2016 %C Lisbonne, Portugal %8 2016-06-24 %D 2016 %K Belief functions %K combination rules %K statistic %K map-reduce %Z Computer Science [cs]/Artificial Intelligence [cs.AI] %Z Computer Science [cs]/Computational Complexity [cs.CC] %Z Computer Science [cs]/Neural and Evolutionary Computing [cs.NE] %Z Computer Science [cs]/Information Theory [cs.IT] %Z Computer Science [cs]/Systems and Control [cs.SY]Conference papers %X This paper presents a generic and versatile approach for implementing combining rules on preprocessed belieffunctions, issuing from a large population of information sources. In this paper, we address two issues, whichare 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. %G English %L hal-01331654 %U https://hal.science/hal-01331654 %~ UNIV-BREST %~ INSTITUT-TELECOM %~ ENSTA-BRETAGNE %~ CNRS %~ UNIV-UBS %~ ENSTA-BRETAGNE-STIC %~ ENIB %~ LAB-STICC_ENIB %~ LAB-STICC %~ INSTITUTS-TELECOM